Posted By Dana L Gardner,
Wednesday, September 10, 2014
| Comments (0)
It's only been a few years since Waste Management's IT organization began rebuilding their quality assurance processes from the ground up.
"Our availability scorecard was pretty bad. Our services were down. At times, we didn’t know that our services were down. Our first indication of a problem was from customers calling us," remembers Gautam Roy, Vice President of Infrastructure, Operations and Technical Services at Waste Management in Houston, Texas.
"Now, fast-forward a few years -- with making the appropriate choices and investments in technology, such as in people and processes -- and our scorecard is very good. We know of the problems rapidly. We proactively detect problems and fix the problems before they impact our customers," he says.
To learn how Waste Management came to deliver 4 9s availability for its critical applications, BriefingsDirect sat down with Roy at the recent HP Discover conference in Las Vegas. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Roy: Water Management is an environmental services company. We have primarily three lines of business. First is waste service. This is our traditional waste pickup, transfer, and disposal. Our second line of business is renewable energy or green energy, and our third is recycling.
What makes Waste Management different from others in the waste industry is that we also invest quite a lot of effort in next-generation waste technology. We invest in companies like Agilyx, which converts very hard-to-recycle waste, such as plastic, into crude oil. We convert organic food waste into natural gas. We pressurize, scrub, and dry municipal solid waste into solid fuel, which burns cleaner than coal.
And we're quite diverse, a global company. We have operations in the US and Canada, Asia, and Europe. We have our renewable energy plants. There is quite a large array of technology and IT to support these business processes to ensure consistent business-services availability.
Gardner: As with many organizations, gaining greater visibility into operations -- having earlier detection of problems, and therefore earlier remediation -- means better performance. What were some of the drivers for your organization specifically to mature your IT operations?
Roy: I'll give a few business reasons, and a couple of technology reasons. From the business side, we began business transformation a couple of years ago. We wanted to ensure that we unlocked the value for our customers and for us, and to institutionalize the benefits for Waste Management.
Customer care, providing outstanding, world-class customer service is aligned completely with our business strategy. Business services availability is crucial, it's in our DNA. Our IT business service availability scorecard a few years ago wasn't too good. So we had to put the focus on people, process, and technology to ensure that we provide a very consistent service set to our customers.
Gardner: Moving across the spectrum of development, test, and operations can be challenging for many organizations. You have put in place standardized processes to measure, organize, and perform better across the DevOps spectrum. Tell us how you accomplished that. How did you get there?
Roy: That's a very good question. For us, IT business-service availability is really not about having a great monitoring solution. It starts even before the services are in production. It starts with partnership with our business and business requirements. It starts with having a great development methodology and a robust testing program. It starts with architecture processes, standardization, and communication. All those things have to be in place. And you have to have security services and a monitoring solution to wrap it up.
We try to approach it from the front end, instead of chasing it from the back end.
What we are trying to do is to not fight the issue at the back-end. If a service is down, our monitoring software picks it up, our operational team and engineering team jumps on it, we are able to fix the problem ASAP before it impacts the customer. Great. But, boy, wouldn’t it be nice if those services aren't going down in the first place? So we try to approach it from the front-end, instead of just chasing it from the back-end.
Gardner: So it’s Application Lifecycle Management (ALM) and Business Service Management (BSM), not one or the other, but really both -- and simultaneously?
Roy: Exactly, ALM, BSM, testing, and security products. We also want to make sure that the services are not down from intentional disruption. We want to make sure that we produce code with quality and velocity, and code that is consistent with the experience of our customer.
With our operational processes, ITIL and Lean IT, we want to make sure that the change management and incident management are followed to our prescription. We want to make sure that the disaster-recovery (DR) program, the high-availability (HA) program, the security operation center (SOC), the network operation center (NOC), and the command centers are all working together to ensure that the services are up 24/7, 365.
Gardner: And when you do this well, when you have put in place many of the capabilities that we have been describing, do you have any sense of payback? Do you keep score?
Roy: A few years ago, when we were not as good at it, we started rebuilding this all from the ground up, and our availability scorecard was pretty bad. Our services were down. At times, we didn’t know that our services were down. Our first indication of a problem was from customers calling us.
Now, fast-forward a few years, with making the appropriate choices and investments in technology -- such as in people and processes -- and our scorecard is very good. We know of the problems rapidly. We proactively detect problems and fix the problems before they impact our customers.
We have 4 9s availability for our critical applications. We're able to provide services to our customers via wm.com, our digital channel, and it has been quite a success story. We still have work to cover, but it has been following the right trajectory.
Gardner: Here at HP Discover, are there any developments that you're monitoring closely? Are there some things that you're particularly interested in that might help you continue to close the gap on quality?
We want to provide optimal solutions at a right price point for our customers and our business.
Roy: Sure. Things like understanding what's happening in the world of big data and HP’s views and position on that. I want to understand and learn about testing, software testing, how to test faster and produce better code, and to ensure, on a continuous basis that we're reducing the cost of running the business. We want to provide optimal solutions at a right price point for our customers and our business.
Gardner: On that topic of big data, are you referring to the data generated within IT, in your systems, to be able to better analyze and react to that? Or perhaps also the data from your marketplace, things that your customers might be saying in social media, for example? Or is it all of the above?
Roy: It’s all of the above. We have internal data that we're harvesting. We want to understand what it’s telling us. And we'd like to predict certain trends of our system, across the use of our applications.
Externally, we have 18 call centers. We get user calls. We also want to know our customer better and serve them the best. So we want to move into a situation where we can take their issues, frame them into solutions, and proactively service them the best in our industry.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
You may also be interested in:
Posted By Dana L Gardner,
Monday, September 08, 2014
| Comments (0)
It's a shame when the data analysis providers inside a company get the cold shoulder from the business leaders because the data keeps proving the status quo wrong, or contradicts the conventional corporate wisdom.
Fortunately for GSN Games in San Francisco, there's no such culture clash there. "The real thing that's helped us get to the point we are is a culture where everybody is open to being wrong -- and open to being proven wrong by the data," says Portman Wills, Vice President of Data at GSN Games.
"One of the things we use data for is to challenge all of our assumptions about our own products and our own businesses, says Wills. "It's really gotten to a point where it's almost religious in our company. The moment two people start debating what should or shouldn't happen, they say, 'Well let's just let the data decide.' That's been a core change not just for us, but for the game industry as a whole."
How did GSN Games get to the point where the data usually wins? It took a blazing fast data warehouse of 1.3 trillion rows that consumes, stores and produces analysis from some 110 million registered game-players in near real time. The next BriefingsDirect podcast focuses on just how GSN Games exploits such big data to effectively uncover game-changing entertainment trends for their audience. Oh, and it changes corporate cultures, too.
The discussion, at the recent HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Wills: GSN started as a cable network in the U.S. We’re distributed in 80 million households as the Game Show Network, and then we also have a digital wing that produces casual and social games on Facebook, web, tablets, and mobile. That division has 110 million registered game-players. My team takes data from all over those worlds, throws them into a big data warehouse, and starts trying to find trends and insights for both our TV audience and our online game-players.
In terms of the games, which is really where the growth is, our core demographic is older females, believe it or not, who love playing casual games. We skew more in the 55-plus age range, and we have players from all over the world.
Gardner: The word “games” means a lot of different things to a lot of people. We’re talking about a heritage of network television games back in the ’60s and ’70s that have led us to what is now your organization. But what sort of newer games are we talking about, and what proportion of them are online games, versus more of the passive watching like that on a cable or other media outlets?
Wills: Originally, when our games division started as a branch of GSN, it was companion games to Wheel of Fortune, Minute to Win It, whatever the hot game show was. That's still a part of it, but the growth in the last few years has been in social games on Facebook, where a lot of our games are more casual titles and have nothing to do with the game shows -- tile-matching games or solitaire games, for example.
In the last year or year-and-a-half for us, like everyone else, there’s been this explosion in mobile.
Then, in the last year or year-and-a-half for us, like everyone else, there’s been this explosion in mobile. So it’s iPad, Android, and iPhone games, and there we have the solitaires and the tile matching, too.
Increasingly, a lot of our success and growth has come from virtual casino games. People are playing Bingo, video poker, even slots, virtual slots. We have this title called GSN Casino. That’s an umbrella app with a lot of mini games that are casino-themed, and that one has really just exploded really in the last six months. It's a long way from the Point A of Family Feud reruns to the Point Z of virtual slot machines, but hopefully you can see how we got there.
Gardner: It seems like a long distance, but it’s been also a fairly short amount of time. It wasn't that long ago that the information you might have in your audience came through Nielsen for passive audiences, and you had basically a one- or two-dimension view of that individual, based on the estimate of what time was devoted to a show. But now, with the mobile devices in particular, you have a plethora of data.
Tell us about the types of data that you can get, and what volumes are we talking about.
Wills: Let’s take mobile, because I think it's easy to grok. Everything about the device is exposed to us. The fact that you’re playing on an iPad Mini Retina versus an iPad 1 tells us a lot about you, whether you know it or not.
Then, a lot of our users sign-in via Facebook, which is another vector for information. If you sign-in via Facebook, Facebook provides us your age range, gender, some granular location information. For every player, we get between 40 and 50 dimensions of data about that player or about that device.
That’s one bucket. But the actual gameplay is another whole bucket. What games do you choose to play in our catalog? How long do you play them? What time of day do you play them? Those start to classify users into various buckets -- from the casual commute player, who plays for 15 minutes every morning and afternoon, to the hard-core player who spends 8 to 10 hours a day, believe it or not, playing our games on their mobile devices.
Mobile doesn’t necessarily mean mobile, like out and about. A lot of our players are on their iPad, sitting on the couch in their home.
At that point, and this is a little bit of a pet peeve of mine, mobile doesn’t necessarily mean mobile, like out and about. A lot of our players are on their iPad, sitting on the couch in their home.
It’s not mobility. They’re not using 3G. They’re not using augmented reality. It’s just a device that happens to be a very convenient device for playing games. So it’s much more of a laptop replacement than any sort of mobile thing. That’s sort of a side track.
We collect all of this data, and it’s a fair amount. Right now, we’re generating about 900 million events per day across all of our players. That’s all streamed into our HP Vertica data warehouse, and there are a few tables, event time series tables, that we put the stuff into. A small table for us would be a few hundred billion records, and a large table, as I said, is 1.3 trillion records right now.
So the scale is big for us. I know that for other companies that seems like peanuts. It’s funny how big data is so broad. What’s big to one person is tiny to someone else, but this is the world that we’re dealing in right now.
We have 110 million players. Thankfully, not all of them are active at one time. That would be really big data. But we will have about 20 million at any given time in peak time playing concurrently. That’s a little bit about the numbers in our data warehouse.
Gardner: Understanding your audience through this data is something fairly new. Before, you couldn’t get this amount of data. Now that you have it, what is it able to do for you? Are you crafting new games based on your findings? Are you finding information that you can deliver back to a marketer or advertiser that links them to the audience better? There must be many things you can do.
Wills: First of all, we don’t do any advertising in our mobile games. So that’s one piece that we’re not doing, although I know others are. But there are two broad buckets in which we use data. The first is that we run a lot of the A/B tests, experiments. All of our games are constantly being multivariate tested with different versions of that same game in the field.
We run 20 to 40 tests per week. As an example, we have a Wheel of Fortune game that we recently released, and there was all this debate about the difficulty of the puzzles. How hard should the puzzles be? Should they be very obscure pieces of Eastern literature, mainstream pop culture, or even easier?
So, we tested different levels of difficulty. Some players got the easy, some players got the medium, and some players got the hard ones. We can measure the return rate, the session duration, and the monetization for people who buy power-ups, and we see which level of difficulty performs the best. In the first test of easy, medium, hard, easy overwhelmingly did the best.
So we generated a whole bunch of new puzzles that were even easier than were the previous easy ones and tested that against what was now the control level. The easier puzzles won again. So we generated a whole new set of puzzles that were absurdly easy. We were trying to prove the point that if we gave Wheel of Fortune puzzles that are four-letter words like “bird” and “cups,” nobody would enjoy playing something that simplistic.
Well it turns that they do -- surprise, surprise -- and so that’s how we evolved into a version of Wheel of Fortune that, compared to the game show, looks very different, but it’s actually what customers want. It’s what players want. They want to relax and solve simple puzzles like “door.”
Hopefully faster than overnight. Overnight is a little too slow these days.
Gardner: So Vertica analysis determined that everyone is a winner on GSN, but you’re able to do real-time focus-group types of activities. The data -- because it's so fast, because there is so much information available and you can deal with it so quickly -- means that you’re able to tune your games to the audience virtually overnight.
Wills: Hopefully faster than overnight. Overnight is a little too slow these days. We push twice a day both to our platform code and updates to all of our games in the morning around 11 a.m and in the afternoon around 3:30. Each one of those releases is based on the data that came from the prior release.
So we're constantly evolving these games. I want to go back to your previous question, because I only got to talk about one bucket, which is this experimentation. The other bucket is using the usage patterns that customers have to evolve our product in ways that aren’t necessarily structured around an A/B test.
We thought when we launched our iPhone app that there would be a lot of commuting usage. We had in our head this hypothetical bus player, who plays on the bus in the morning. And so we thought we would build all the stuff around daily patterns. We built this daily return bonus that you can do in the morning and then again in the evening.
The data showed us that that really was only a tiny fraction of our players. There were, in fact, very few players who had this bimodal, morning and evening usage pattern. Most people didn't play at all until after dinner and then they would play a lot, sometimes even binge from 7 p.m. until 2 a.m. on games.
That was an area where we didn't even set up an experiment. We just had false assumptions about our player base. And that happens a surprising amount of the time. We all -- especially the game-design team and people who spent their careers designing video games -- have assumptions about their audience that half the time are just wrong. One of the things we use data for is to challenge all of our assumptions about our own products and our own businesses.
It's really gotten to a point where it's almost religious in our company. The moment two people start debating what should or shouldn't happen, they say, “Well let's just let the data decide.” That's been a core change not just for us, but for the game industry as a whole.
Because we’re here in Spain, a quick tidbit that we uncovered recently is that our main time-frame in every country on Earth, when people play games, is 7 p.m. to 11 p.m., except in Spain where it’s 1 p.m. to 3 p.m. -- siesta time. That’s just one of the examples of how we use big data to use discover insights about our players and our audiences worldwide.
Understanding the audience
Gardner: I have to imagine that the data that led you to that inference in Spain was something other than what we might consider typical structured data. How did the different data brought together allow you to understand your audience better?
Wills: We use this product from HP called Vertica, which is just a tremendous data warehouse, that lets us throw every single click, touch, or swipe in all of our games into a big table. By big, I mean right now it’s I think 1.3 trillion rows. We keep saying that we should really archive this thing. Then, we say we’ll archive it when it slows down, and then it just never slows down, so we have yet to archive it.
We put all of the click stream data in there. The traditional joins, schemas, and all of that don’t really have to happen because we have one table with all of the interactions. You have the device, the country, the player, all these attributes. It’s a very wide table. So if you want to do things like ask what is the usage in five-minute slices by country, it’s a simple SQL query, and you get your results.
Gardner: What you’re describing is very much desired by a lot of types of businesses through understanding a massive amount of data from their audience, to be able to react quickly to that, and then to stop guessing about products and pricing and distribution and logistics and supply chain and be driven purely by the data. You’re a really interesting harbinger of things to come.
One of the things we use data for is to challenge all of our assumptions about our own products and our own businesses.
Portman, tell me little bit about the process by which you were able to do this. Did you have an older data warehouse? What did you use before, and how did you make a transition to HP Vertica?
Wills: When we started the social mobile business three years ago, we were on MySQL, which we are still on for our transactional load. We have three data centers around the world. When people are playing our games, it’s recording, reading, and writing 125,000 transactions per second, and that MySQL, sharded out, works great for that.
When you want to look at your entire player base and do a cross-shard query, we found that MySQL really fell down. Our original Vertica proof of concept (POC) was just to replace these A/B test queries, which have to look across the entire population.
So in comes Vertica. We set up a single node, a Vertica data warehouse. We pull in a year's worth of data, and the same query to synthesize these sessions ran in 800 milliseconds.
So the thing that took 24 hours, which is 86,400 seconds, ran in less than one second. By the way, that 24-hour query was running across dozens of machines, and this Vertica query was running on a single server of commodity hardware.
That's when we really became believers in the power of the column store and column-oriented data warehouses. From the small beginning of just one simple query, it’s now expanded -- and pretty much our whole business runs on top of HP Vertica on the data warehouse side.
Gardner: As I said, I think GSN Games is a really harbinger of what a lot of other companies in many different vertical industries will be seeking. Looking back, if you had to do it again, what might you have done differently or what suggestions might you have for others who would like to be able to do what you are doing?
Wills: I definitely wish that we had switched to a column store sooner. I think the reason that we've been so successful at this is because of our game design team, which was so open to using data.
I definitely wish that we had switched to a column store sooner.
I’ve heard hard stories from other companies where they want to use a data-driven approach, and there's just a lot of cultural inertia and push back against doing that. It's hard to be consistently proven wrong in your job, which is always what happens when you rely on data.
The real thing that's helped us get to the point we are in is a culture and a company where everybody is open to being wrong -- and open to being proven wrong by the data, which I am very thankful for.
Gardner: Well, it's good to be data-driven, and I think you should feel good being responsible for making 110 million people feel good about themselves every day.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
You may also be interested in:
Posted By Dana L Gardner,
Friday, August 22, 2014
| Comments (0)
The old model of just being an outsourcer or on-premises service provider is dead for many IT solutions providers. Instead, we’re all now in a hybrid world where will have some private-cloud solutions and multiple public clouds. The challenge is to have the right level of governance, and to be in a position to move the workloads, and adjust the workloads with the needs.
These words of wisdom come from European IT services provider Steria, which along with hundreds of its customers are charting a journey to hybrid cloud while maintaining control, automation, and reporting across all IT infrastructure.
To learn more about how services standardization leads to improved hybrid cloud automation, BriefingsDirect spoke to Eric Fradet, Industrialization Director at Steria in Paris. The discussion, at the recent HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Fradet: Steria is a 40-year-old service provider company, mainly based in Europe, with a huge location in India and also Singapore. We provide all types of services related to IT, starting from infrastructure management to application management. We help to develop and deploy new IT services for all our customers.
Gardner: How are your activities at Steria helping you better deliver the choice of cloud and software-as-a-service (SaaS) to your customers?
Fradet: That change may be quicker than expected. So, we must be in a position to manage the services wherever they’re from. The old model of saying that we’re an outsourcer or on-premises service provider is dead. Today, we’re in a hybrid world and we must manage that type of world. That must be done in collaboration with partners, and we share the same target, the same ambition, and the same vision.
Benefit, not a pain
The cloud must not be seen as disruptive by our customers. Cloud is here to accompany your transformation. It must be a benefit for them, and not a pain.
A private solution should be the best as a starting point for some customers. The full public solution should be a target. We’re here to manage their journey and to define with the customer what is the best solution for the best need.
Gardner: And in order for that transition from private to public or multiple public or sourced-infrastructure support, a degree of standardization is required. Otherwise, it's not possible. Do you have a preferred approach to standardization?
Fradet: The choice of HP as a partner was based on two main criteria. First of all, the quality of the solution, obviously, but there are multiple good solutions on the market. The second one is the capacity with HP to have a smooth transition, and that means getting to the industrialization benefits and the economic benefits while also being open and interconnected with existing IT systems.
That's why the future model is quite simple. Our work is to know we have on-premises and physical remaining infrastructure. We will have some private-cloud solutions and multiple public clouds, as you mentioned. The challenge is to have the right level of governance, and to be in a position to move the workload and adjust the workloads with the needs.
We continue to invest deeply in ITSM because ITSM is service management.
Gardner: Of course, once you've been able to implement across a spectrum of hosting possibilities, then there is the task of managing that over time, being able to govern and have control.
Fradet: With HP, we have a layer approach which is quite simple. First of all, if you want to manage, you must control, as you mentioned. We continue to invest deeply in IT Service Management (ITSM) because ITSM is service governance. In addition, we have some more innovative solutions based on the last version of Cloud Services Automation (CSA). Control, automate, and report remain as key whatever the cloud or non-cloud infrastructure.
Gardner: Of course, another big topic these days is big data. I would think that a part of the management capability would be the ability to track all the data from all the systems, regardless of where they’re physically hosted. Do you have a preference or have you embarked on a big-data platform that would allow you to manage and monitor IT systems regardless of the volume, and the location?
Fradet: Yes, we have some very interesting initiatives with HP around HAVEn, which is obviously one of the most mature big-data platforms. The challenge for us is to transform a technologically wonderful solution into a business solution. We’re working with our business units to define use-cases that are totally tailored and adjusted for the business, but big data is one of our big challenges.
Gardner: Have you been using a more traditional data-warehouse approach, or are you not yet architecting the capability? Are you still in a proof-of-concept stage?
Fradet: Unfortunately, we have hundreds of data-warehouse solutions, which are customer-dedicated, starting from very old-fashioned level to operational key performance indicators (KPI) to advanced business intelligence (BI).
The challenge now is really to design for what will be top requirements for the data warehouse, and you know that there is a mix of needs in terms of data warehouses. Some are pure operational KPIs, some are analytics, and some are really big data needs. To design the right solution for the customer remains a challenge. But, we’re very confident that with HAVEn, sometime in 2014, we will have the right solution for those issues.
Gardner: Lastly, Eric, the movement toward cloud models for a lot of organizations is still in the planning stages. They are mindful of the vision, but they have also IT housecleaning to do internally. Do you have any suggestions as to how to properly modernize, or move toward a certain architecture that would then give them a better approach to cloud and set them up for less risk and less disruption? What are some observations that you have had for how to prepare for moving toward a cloud model?
Cloud can offer many combinations or many benefits, but you have to define as a first step your preferred benefits.
Fradet: As with any transformation program, the cloud’s eligibility program remains key. That means we have to define the policy with the customer. What is their expectation -- time to market, cost saving, to be more efficient in terms of management?
Cloud can offer many combinations or many benefits, but you have to define as a first step your preferred benefits. Then, when the methodology is clearly defined, the journey to the cloud is not very different than from any other program. It must not be seen as disruptive, keeping in mind that you do it for benefits and not only for technical reasons or whatever.
So don't jump to the cloud without having strong resources below the cloud.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
You may also be interested in:
Posted By Dana L Gardner,
Monday, August 11, 2014
| Comments (0)
It’s no secret that communication service providers (CSPs) are under a lot of pressure as they make massive investments in upgraded networks while facing shrinking margins and revenues from their eroding traditional voice or broadcasting businesses.
Traditional operators understand that they must go beyond what they did before. They need to offer more compelling services to reduce churn and acquire new customers. But how to know what services customers want most, and how much to charge for them?
A key asset CSPs have is the huge amount of information that they generate and maintain. And so it's the analytics from their massive data sets that becomes the go-to knowledge resource as CSPs re-invent themselves.
Our next Big Data innovation discussion therefore explores how the telecommunication service-provider industry is gaining new business analytic value and strategic return through the better use and refinement of their Big Data assets.
To learn more about how analytics has become a business imperative for service providers, peruse this interview with Oded Ringer, Worldwide Solution Enablement Lead for HP Communication and Media Solutions. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: What are the major trends leading CSPs to view themselves as being more data-driven organizations?
Ringer: CSPs are under a lot of pressure. On one hand, this industry has never been more central. Everybody is connected, spending so much more time online than ever before, and carrying with them small devices through which they connect to the network. So CSPs are central to our work and personal lives – as a result, they’re under lot of pressure.
They’re under a lot of pressure, because they’re required to make massive investments in the networks, but they also need to deal with shrinking margins and revenues to subsidize these investments. So, at the end of the day, they’re squeezed between these two motions.
One approach many CSPs have adopted in the last year was to reduce cost and to cut operations. But this is pretty much a trip to nowhere. Going into most basic services and commodity services is no way for these kinds of things to survive.
In the last two to three years, more and more traditional operators understand that they must go beyond what they did before. They need to offer more compelling services to reduce churn and acquire new customers. They need to leverage their position as a central place between consumers and what they are looking for to become some kind of brokers of information.
The key asset they have in their hand to become such brokers is the huge amount of information that they maintain. It’s exactly where analytics comes into play.
Gardner: When we say CSP and telecommunication companies these days, we’re more and more talking about mobile, right? How big a shift has mobile been in terms of the need to analyze use patterns and get to know what's really happening out in the mobile network?
Ringer: Mobile services are certainly the leading tool in most operator’s arsenals. Operators that have the subscriber “connected” with them wherever they go, around the clock, have an advantage over those that are more dependent upon or only provide tethered services.
But we need to keep in mind that there’s also a whole space for analytics solutions that are related to fixed-line services, like cable, satellite, broadband, and other, landline services. CSPs are investing a lot in becoming more predictive, finding out what the subscriber really wants, what the quality of those services are at any given time, and how we can reduce churn in their customer base.
Another kind of analytics practices that operators take is trying to be predictive in their investments in the network, understanding which network segments are used by more high-worth individuals, those that they do want to improve service to, beefing up those networks and not the other networks.
Again, it’s these mobile operators who are on the front lines of doing more with subscriber data and information in general, but it is also true for cable operators and pay-TV operators, and landline CSPs.
CSPs, unlike most enterprises, need to handle not only the structured data that’s coming from databases and so on, but also unstructured data.
Gardner: Oded, what are some of the data challenges specific to CSPs?
Ringer: In the CSP industry, Big Data is bigger than in any other industry. Bigger, first of all, in volume. There is no other industry that runs this amount of data – if you take into consideration they’re carrying everybody’s data, consumer and enterprise. But that’s one aspect and is not even the most complicated one.
The more complicated thing is the fact that CSPs, unlike most enterprises, need to handle not only the structured data that’s coming from databases and so on, but also unstructured data, such as web communication, voice communication, and video content. They want to analyze all those things, and this requires analyzing unstructured data.
So that’s a significant change in that type of process flow. They are also facing the need to look at new sets of structured data, data from IT management and security log files, from sensors and end-point mobile device telematics, cable set-top boxes, etc.
And two, in the CSP industry, because everything is coming from the wire, there’s no such thing as off-line analytics or batch analytics. Everything needs to be real-time analytics. Of course, this doesn’t mean that there will not be off-line or batch analytics, but even these are becoming more complex and span many more data sets across multiple enterprise silos.
If you analyze subscriber behavior right now and you want to make an offer to improve the experience that he’s having in real time, you need to capture the degradation of service right now and correlate it with what you know about the subscriber right now. So it's so much more real time than in any other industry.
The market is still young. So it's very hard to say which one will be more dominant.
We’re not talking here about projects of data consolidation. It may be necessary in some cases, but that’s not really the practice that we’re talking about here. We’re talking about federating, referring to external information, analyzing in the context of the logic that we want to apply, and making real-time decisions.
In short, CSP Big Data analytics is Big Data analytics on steroids.
Gardner: What does a long-term solution look like, rather than cherry picking against some of these analytics requirements? Is there a more strategic overview approach that would pay off longer term and put these organizations in a better position as they know more and more requirements will be coming their way?
Ringer: Actually we see two kinds of behaviors. The market is still young. So it's very hard to say which one will be more dominant. We see some CSPs that are coming to us with a very clear idea on what business process they want to implement and how they believe a data-driven approach can be applied to it.
They have clear model, a clear return on investment (ROI) and they want to go for it and implement it. Of course, they need the technology, the processes, and the business projects, but their focus is pretty much on a single use case or a variety of use cases that are interrelated. That’s one trend.
There’s another trend in which operators say they need to start looking at their data as an asset, as an area that they want to centralize. They want to control it in a productive manner, both for security, for privacy, and for the ability to leverage it to different purposes.
Those will typically come with a roadmap of different implementations that they would like to do via this Big Data facility that they have in mind and want to implement. But what’s more important for them is not the quickest time to launch specific processes, but to start treating the data as a central asset and to start building a business plan around it.
I guess both trends will continue for quite some while, but we see them both in the market sometimes even in the same company in different organizations.
Gardner: How does a CSP can really change their identity from being a pipe, a conduit, to being more of a rich services provider on top of communications?
And what is it that HP is bringing to the table? What is it about HP HAVEn, in particular, that is well suited to where the telecommunications industry is going and what the requirements are?
Ringer: HP has made huge investments in the space of Big Data in general and analytics in particular, both in-house developments, multiple products, as well as acquisitions of external assets.
HAVEn is now the complete platform that includes multiple best-in-class product elements based multiple, cutting edge yet proven technologies, for exploiting Big Data and analytics. Our solution for the space is pretty much based on HAVEn and expanded with specific solutions for CSP needs, with a wide gallery of connectors for external data sources that exist within the CSP space.
In short, we’re taking HAVEn and using it for the CSP industry with lots of knowledge about what traditional CSP operators need to become next-generation CSPs. Why?
Because we have a very large group within HP of telecom experts who interact with and leverage what we’re doing in other industries and with many of the new age service providers like the Amazons, Googles, Facebook and Twitters of the world. We go a long way back in expertise in telecom -- but combine this with forward thinking customers and our internal visionaries in HP Labs and across our business units.
Gardner: Just to be clear for our audience, HAVEn translates to Hadoop, Autonomy, Vertica, and Enterprise Security, along with a whole suite of horizontally and vertically integrated set of applications that are vertical industry specific. Is that right?
It’s coming from the business people that understand that they need to do something with the data and monetize it.
Gardner: Tell me what you do in terms of how you reach out to communications organizations. Is there something about meeting them at the hardware level and then alerting them to what these other Big Data capabilities are? Is this a cross-discipline type of approach? How do you actually integrate HP services and then take that and engage with these CSPs?
Ringer: Those things exist, like engaging at a hardware level, but those are the less common go-to-market motions that we see. The more popular ones are more top-down, in the sense that we are meeting with business stakeholders who wants to know how to leverage Big Data and analytics to improve their business.
They don’t care about the data other than how it’s going to be result in actionable intelligence. So, at the CSP level, it can be with marketing officers within the CSP who are looking to create more personalized services or more sticky services to increase the attention of their subscribers. They’re looking to analytics for that.
It can be with business-development managers within the CSP organization that are looking to create models of collaboration with the Yahoos and Facebooks of the world, with retailers, or with any kind of other participants of their ecosystem where they can bring the ability to provide the pipe, back-end hosting of services and intelligence about how the pipe is providing the services and the sentiment of the customers on the other end of the pipe.
They want to share information of value to their customers, making them dependent on them in new ways that aren’t just about the pipe thereby gaining new revenue streams. That’s the kind of motivation they have. It can be with IT folks as well, but at the end of the day the discussion about CSP Big Data isn’t coming from the technology. It’s coming from the business people that understand that they need to do something with the data and monetize it.
Then, of course, it becomes pretty quickly a technical discussion that the motion is business to technology, rather than infrastructure to technology.
We also developed the support practice within our organization that does exactly that, business advisory workshops. It’s for stakeholders of different roles to realize what the priorities are in using Big Data. What is the roadmap that they want to implement?
The purpose of this exercise is to quickly bring everybody to the same room, sit together for a day or two, and come out with an agreement on how to turn themselves from conventional services to more personalized services and diversify the business channels via using information data.
For several years now, we have one large customer, Telefónica a Latin American conglomerate, has been working with us on analytics projects to improve the quality of experience of their subscribers.
In Latin America, most people are interested in football, and many of them want to watch it on their mobile device. The challenge is that they all want to watch it during the same 90 minutes. That’s a challenge for any mobile operator, and that’s exactly where we started a critical project with Telefónica.
We’re helping them analyze the quality of experience. Realizing the quality of the experience isn’t a very complicated thing. There are probes in the network to do that. We can pretty accurately get the quality of experience for every single video streaming session. It’s no big deal.
Analytics kicks in when you want to correlate this aggregation of quality with who the subscriber is, how the subscriber is expected to behave, and what he’s interested in. We know that the quality isn’t good enough for many subscribers during the football game, but we need to differentiate and know to which one of them we want to make an offer to upgrade his package. What’s the right offer? When’s the right time to make the offer? How many different offers do we test to zero in on the best set of offers?
We want to know which one of them we don’t want to promote anything to, but just want to make him happy. We want to give him a better quality experience for free, because he is a good customer and we don’t want to lose him. And we want to know which customer we want to come back to later, apologize, and offer him a better deal.
Based on real-time triggering of events from the network, degradation of quality with information that is ongoing about the subscriber, who the subscriber is, what marketing segment he belongs to, what package is he subscribed to and so on, we do the analytics in real time, and decide what the right action is and what the right move is, in order for us to give the best experience for the individual subscriber.
It’s working very nicely for them. I like this example, first of all, because it’s real, but also because it shows the variety of processes we have here with correlation of real-time information with ongoing information for the subscribers. We have contextual action that is taken to monetize and to improve quality and to improve satisfaction.
This example touches so many needs of an operator and is all done in a pretty straightforward manner. The implementation is rather simple. It’s all based on running the right processes and putting the right business process in place. But this isn’t always straightforward for enterprise customers, particularly those in the small to medium enterprise segment so imagine what CSPs could do for their customers once they’ve gotten a handle on this for their own businesses.
We have contextual action that is taken to monetize and to improve quality and to improve satisfaction.
Gardner: It seems to me that that helps reduce the risk of a provider or their customers coming out with new services. If they know that they can adjust rapidly and can make good on services, perhaps this gives them more runway to take off with new services, knowing that they can adjust and be more agile. It seems like it really fundamentally changes how well they can do their business.
Ringer: Absolutely. It also reduces quite a lot the risk of investment. If you launch a new service and you find out that you need to beef up your entire network, that is a major hit for your investment strategy. At the same time, if you realize that you can be very granular and very selective in your investment, you can do it much more easily and justify subsequent investments more clearly.
Gardner: Are there any other examples of how this is manifesting itself in the market -- the use of Big Data in the telecommunication’s industry?
Ringer: Let me give another example in North America. This is an implementation that we did for a large mobile operator in North America, in collaboration with a chain of retail malls.
What we did there is combine their ongoing information that the mobile operator has about its subscribers -- he knows what the subscriber is interested in, what they’re prior buying pattern and transactions were and so on -- with the location information of where the individual person is at the mall.
The mall operator runs a private wi-fi network there, so he has his own system of being able to track where the individual is exactly within the mall. He knows within two meters where a person is in the mall but with the map overlay of the physical mall and all product and service offerings to the same grid.
When we know a person is in the mall, we can correlate it with what the CSP knows about this person already. He knows that the specific person has high probability of looking for a specific running shoe. The mobile operator knows it because he tracks the web behavior of the specific individual. He tracks the profile of the specific individual and he can have pretty good accuracy in telling that this guy, for the right offer, will say yes for running shoes.
So combining these two things, the ongoing analytics of the preferences, together with real-time location information, give us the ability to push out targeted and timely promotions and coupons.
Imagine that you go in the mall and suddenly you pass next to the shoe store. Here, your device pops up a message and that says right now, Nike shoes are 50 percent off for the next 15 minutes. You know that you’re looking for Nike shoes. So the chance that you’ll go into the store is very good, and the results are very good because you create a “buy-now or you’ll miss-out” feeling in the prospect. Many subscribers take the coupons that are pushed to them in this way.
Of course, it’s all based on opt-in, and of course, it’s very granular in the sense that there are analytics that we do on subscriber information that is opted in at the level of what they allow us to look at. For instance, a specific person may allow us to look at his behavior on retail sites, but not on financial sites.
Gardner: Again, this shows a fundamental shift that the communications provider is not just a conduit for information, but can also offer value-added services to both the seller and the buyer -- radically changing their position in their markets.
If I am an organization in the CSP industry and I listen to you and I have some interest in pursuing better Big Data analytics, how do I get started? Where can I go for more information? What is it that you’ve put together that allows me to work on this rather quickly?
Ringer: As I mentioned before, we typically recommend engaging in a two-day workshop with our business consultants. We have a large team of Big Data advisory consultants, and that’s exactly what they do. They understand the priorities and work together with the telecom organizations to come up with some kind of a roadmap -- what they want to do, what they can do, what they are going to do first, and what they are going to do later.
They all look to become more proactive, they all realize that data is an asset and is something that you need to keep handy, keep private, and keep secured.
That’s our preferred way of approaching this discipline. Overall, there are so many kinds of use cases, and we need to decide where to start. So that’s how we start. To engage, the best place is to go to our website. We have lots of information there. The URL is hp.com/go/telcoBigData, that’s one word, and from there you just click Contact Us, and we’ll get back to you. We’ll take you from there. There are no commitments, but chances are very good.
Gardner: Before we sign off, I just wanted to look into the future. As you pointed out, more and more entertainment and media services are being delivered through communication providers. The mobile aspect of our lives continues to grow rapidly. And, of course, now that cloud computing has become more prominent, we can expect that more data will be available across cloud infrastructures, which can be daunting, but also very powerful. Where do you see the future challenges, and what are some of the opportunities?
Ringer: We can summarize four main trends that we’re seeing increasing and accelerating. One is that CSPs are becoming more active in enabling new business models with partnerships, collaborations, internet players, and so on. This is a major trend.
The second trend that we see increasing quite intensively is operators becoming like marketing organizations, promoting services for their own or for others.
The third one is more related to the operation of the CSP itself. They need to be more aware of where they invest, what’s their risk and probability of seeing an specific ROI and when will that occur. In short, Big Data and Analytics will make them smarter and more proactive in making the investments. That’s another driver that increases their interest in using the data.
Overall they all look to become more proactive, they all realize that data is an asset and is something that you need to keep handy, keep private, and keep secured, but be able to use it for variety of use cases and processes to be ready for the next move.
Posted By Dana L Gardner,
Monday, August 04, 2014
| Comments (0)
The next BriefingsDirect deep-dive discussion explores how one of the most costly and complex parts of any enterprises IT infrastructure -- storage -- is being dramatically improved by the accelerating adoption of software-defined storage (SDS).
The ability to choose low-cost hardware, to manage across different types of storage, and radically simplify data storage via intelligent automation means a virtual rewriting of the economics of data.
But just as IT leaders seek to simultaneously tackle storage pain points of scalability, availability, agility, and cost -- software-defined storage is also providing significant strategic- and architectural-level benefits.
We're joined by two executives from VMware to unpack these efficiencies and examine the broad innovation behind the rush to exploit software-defined storage, Alberto Farronato, Director of Product Marketing for Cloud Infrastructure Storage and Availability at VMware, and Christos Karamanolis, Chief Architect and a Principal Engineer in the Storage and Availability Engineering Organization at VMware. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Software-defined storage is changing something more fundamental than just data and economics of data. How do you see the wider implications of what’s happening now that software-defined storage is becoming more common?
Farronato: Software-defined storage is certainly about addressing the cost issue of storage, but more importantly, as you said, it’s also about operations. In fact, the overarching goal that VMware has is to bring to storage the efficient operational model that we brought to compute with server virtualization. So we have a set of initiatives around improving storage on all levels, and building a parallel evolution of storage to what we did with compute. We're very excited about what’s coming.
Gardner: Christos, one of my favorite sayings is that "architecture is IT destiny." How you see software-defined storage at that architectural level? How does it change the game?
Concept of flexibility
Karamanolis: The fundamental architectural principle behind software-defined storage is the concept of flexibility. It's the idea of being able to adapt to different hardware resources, whether those are magnetic disks, flash storage, or other types of non-volatile memories in the future.
How does the end user adapt their storage platform to the needs they have in terms of the capabilities of the hardware, the ratios of the different types of storage, the networking, the CPU resources, and the memory resources needed for executing and providing their service to what's ahead?
That’s one part of flexibility, but there is another very interesting part, which is a very acute problem for VMware customers today. Their operational complexity of provisioning storage for applications and virtual machines (VMs) has been one way of packaging applications.
Today, customers virtualize environments, but also in general have to provision physical storage containers. They have to anticipate their uses over time and have make an investment up front in resources that they'll need over a long period of time. So they create those logical unit number (LUN) file services, or whatever that is needed, for a period of time that spans anything from weeks to years.
Software-defined storage advocates a new model, where applications and VMs are provisioned at the time that the user needs them. The storage resources that they need are provisioned on-demand, exactly for what the application and the user needs -- nothing more or less.
The idea is that you do this in a way that is really intuitive to the end-user, in a way that reflects the abstractions that user understands -- applications, the data containers that the applications need, and the characteristics of the application workloads.
So those two aspects of flexibility are the two fundamental aspects of any software-defined storage.
Gardner: As we see this increased agility, flexibility, the on-demand nature of virtualization now coupled with software-defined storage, how are organizations benefiting at a business level?
Farronato: There are several benefits and several outcomes of adopting software-defined storage. The first that I would call out is the ability to be much more responsive to the business needs -- and the changing business needs -- in the form of what your application needs faster.
As Christos was saying, in the old model, you had to guess ahead of time what the applications will need, spend a lot of time trying to preconfigure and predetermine the various services levels, performance, availability and other things that our storage really would be required by your application, and so spend a lot of time setting things up, and then hopefully, down the line, consume it the way you thought you would.
Difficult change management
In many cases, this causes long provisioning cycles. It causes difficult change management after you provision the application. You find that you need to change things around, because either the business needs have changed or what you guessed was wrong. For example, customers have to face constant data migration.
With the policy-driven approach that Christos has just described -- with the ability to create these storage services on-the-fly for a policy approach -- you don’t have to do all that pre-provisioning and preconfiguring. As you create the VMs and specify the requirements, the system responds accordingly. When you have to change things, you just modify the policy and everything in the underlying infrastructure changes accordingly.
Responsiveness, in my opinion, is the one biggest benefit that IT will deliver to the business by shifting to software-defined storage. There are many others, but I want to focus on the most important one.
When you have to change things, you just modify the policy and everything in the underlying infrastructure will change accordingly.
Gardner: Can you explain what happens when software-defined storage becomes strategic at the applications level, perhaps with implications across the entire data lifecycle?
Karamanolis: One thing we already see, not only among VMware customers, but as a more generic trend, is that infrastructure administrators -- the guys who do the heavy-lifting in the data centers day in and day out, who manage much more beyond what is traditionally servers and applications -- are getting more and more into managing networks and data storage.
Talking about changing models here, what we see is that tools have to be developed and software-defined storage is a key technology evolution behind that. These are tools for those administrators to manage all those resources that they need to make their day-to-day jobs happen.
Here, software-defined storage is playing a key role. With technology like Virtual SAN, we make the management of storage visible for people who are not necessarily experts in the esoterics of a certain vendor's hardware. It allows more IT professionals to specify the requirements of their applications.
Then, the software storage platform can apply those requirements on the fly to provision, configure, and dynamically monitor and enforce compliance for the policy and requirements that are specified for the applications. This is a major shift we see in the IT industry today, and it’s going to be accelerated by technologies like Virtual SAN.
Gardner: When you go to software-defined storage, you can get to policy level, automation, and intelligence when it comes to how you're executing on storage. How does software-defined storage simplify storage overall?
Karamanolis: That's an interesting point, because if you think about this superficially, we’ll now go from a single, monolithic storage entity to a storage platform that is distributed, controlled by software, and can span tens or sometimes hundreds of physical nodes and/or entities. Isn’t complexity harder in the latter case?
The reality is that whether it's because of necessity or because we've learned a lot over the last 10 to 15 years about how to manage and control large distributed systems, that there is a parallel evolution of these ideas of how you manage your infrastructure, including the management of storage.
The user has to be exposed to the consequences of the policy they choose. There is a cost there for every one of those services.
As we alluded to already, the fundamental model here is that the end user, the IT professional that manages this infrastructure, expresses in a descriptive way, what they need for their applications in terms of CPU, memory, networking, and, in our case, storage.
What do I mean by descriptive? The IT professional does not need to understand all the internal details of the technologies or the hardware used at any point in time, and which may evolve over a period of time.
Instead, they express at a high level a set of requirements -- we call them policies -- that capture the requirements of the application. For example, in the case of storage, they specify the level of availability that is required for certain applications and performance goals, and they can also specify things like the data protection policies for certain data sets.
Of course, for all those things, nothing comes for free. So the user has to be exposed to the consequences of the policy that they choose. There is a cost there for every one of those services.
But the key point is that the software platform automatically configures the appropriate resources, whether they're arrayed across multiple physical devices, arrayed across the network, or whether they get asynchronous data as specified in a remote location in order to comply with certain disaster recovery (DR) policies.
All those things are done by the software, without the user having to worry about whether the storage underneath is highly available storage, in which case they need to be able to create only two copies of the data, or whether it is of some low-end hardware for which that would require three or four copies of the data. All those things are determined automatically by the platform.
This is the new mode. Perhaps I'm oversimplifying some of these problems, but the idea is that the user should really not have to know the specific hardware configurations of a disk array. If the requirements can not be met, it is because these new technologies are not incorporated into the storage platform.
Farronato: Virtual SAN is a completely policy-driven product, and we call it VM-centric or application-centric. The whole management paradigm for storage, when you use Virtual SAN, is predicated around the VM and the policies that you create and you assign to the VMs as you create your VMs, as you scale your environment.
One of the great things that you can achieve with Virtual SAN is providing differentiated service levels to individual VMs from a single data store. In the past, you had to create individual LUNs or volumes, assign data services like replication or RAID levels to each individual volume, and then map the application to them.
With Virtual SAN, you're simply going to have a capacity container that happens to be distributed across a number of nodes in your cluster -- and everything that happens from that point on is just dropping your VMs into this container. It automatically instantiates all the data services by virtue of having built-in intelligence that interprets the requirements of the policy.
One of the great things that you can achieve with Virtual SAN is providing differentiated service levels to individual VMs from a single data store.
That makes this system extremely simple and intuitive to use. In fact, one of the core design objectives of Virtual SAN is simplicity. If you look at a short description of the system, the radically simple hypervisor-converged storage means bringing that idea of eliminating the complexity of storage to the next level.
Gardner: We've talked about simplicity, policy driven, automation, and optimization. It seems to me that those add up very quickly to a fit-for-purpose approach to storage, so that we are not under-provisioning or over-provisioning, and that can lead to significant cost-savings.
So let’s translate this back to economics. Alberto, do you have any thoughts on how we lower total cost of ownership (TCO) through these SDS approaches of simplicity, optimization, policy driven, and intelligence?
Farronato: There are always two sides of the equation. There is a CAPEX and an OPEX component. Looking at how a product like Virtual SAN reduces CAPEX, there are several ways, but I can mention a couple of key components or drivers.
First, I'd call out the fact that it is an x86 server-based storage area network (SAN). So it leverages server-side components to deliver shared storage. By virtue of using server-side resources right off the bat there are significant savings that you can achieve through lower-cost hardware components. So the same hard drive or solid-state drive (SSD) that you deploy on a shared external storage array could be on the order of 80 percent cheaper.
The other aspect that I would call out that reduces the overall CAPEX cost is more along the lines of this, as you said, consume on-demand approach or, as we put it in many other terms, grow-as-you-go. With a scale-out model, you can start with a small deployment and a small upfront investment.
You can then progressively scale out as your environment grows by the much finer granularity that you would with a monolithic array. And as you scale, you scale both compute, but also IOPs and that goes hand in hand with often the number of VMs that you are running out of your cluster.
So the system grows with the size of your environment, rather than requiring you to buy a lot of resources upfront that many times remain under-utilized for a long time.
On the OPEX side, when things become simpler, it means that overall administration productivity increases. So we expect a trend where individual administrators will be able to manage a greater amount of capacity, and to do so in conjunction with management of the virtual infrastructure to achieve additional benefits.
Gardner: Virtual SAN has been in general availability now for several months, since March 2014, after being announced last year at VMworld 2013. Now that it’s in place and growing in the market, are there any unintended benefits or unintended consequences from that total-cost perspective in real-world day-in, day-out operations?
The system grows with the size of your environment, rather than require you to buy a lot of resources upfront that many times remain under-utilized for a long time.
I'm looking for ways in which a typical organization is seeing software-defined storage benefiting them culturally and organizationally in terms of skills, labor, and that sort of softer metric.
Karamanolis: That’s a very interesting point. Our technologists sometimes tend to overlook the cultural shifts that technology causes in the field. In the case of Virtual SAN, we see a lot of, as one customer put it, being empowered to manage their own storage, in the vertical that we are controlling in their IT organization, without having to depend on the centralized storage organization in this company.
What we really see here is a shift in paradigm about how our customers use Virtual SAN today to enable them to have a much faster turnaround for trying new applications, new workloads, and getting them from test and dev into production without having to be constrained by the processes and the timelines that are imposed by a central storage IT organization.
This is a major achievement, and the major tool for VMware administrators in the field, which we believe is going to lead the way to a much wider adoption of Virtual SAN and software-defined storage in general.
Gardner: How does this simplification and automation have a governance, risk, and compliance (GRC) benefit?
Farronato: With this approach you have a more granular way to control the service levels that you deliver to your customers, to your internal customers, and a more efficient way to do it by standardizing through polices rather than trying to standardize service levels over a category of hardware.
You can more easily keep track of what each individual application is receiving, whether it’s in compliance to that particular policy that you specified. You can also now enable self-service consumption more easily and effectively.
We have, as part of our Policy-Based Management Engine, APIs that will allow for integration with cloud automation frameworks, such as vCloud Automation Center for OpenStack, where end users will be able to consume a predefined category of service.
It will speed up the provisioning process, while at the same time, enabling IT to maintain that control and visibility that all the admins want to maintain over how the resources are consumed and allocated.
You can also now enable self-service consumption more easily and effectively.
Gardner: I suppose there are as many on-ramps to software-defined data center as there are enterprises. So it's interesting that it can be done at that custom level, based on actual implementation, but also have a strategic vision or a strategic architectural direction. So, it's future-proof as well as supporting legacy.
How about some examples? Do we have either use-case scenarios or an actual organization that we can look to and say that they have deployed these VSAN and they have benefited in certain ways and they are indicative of what others should expect?
Farronato: Let me give you some statistics and some interesting facts. We can look at some of the early examples where, in the last three months since the product has become available, we've found a significant success already in the marketplace, with a great start in terms of adoption from our customers.
We already have more than 300 paying customers in just one quarter. That follows the great success of the public beta that ran through the fall and the early winter with several thousand customers testing and taking a look at the product.
We are finding that virtual desktop infrastructure (VDI) is the most popular use case for Virtual SAN right now. There are a number of reasons why Virtual SAN fits this model from the scale out, as well as the fact that the hyper-converged storage architecture is particularly suitable to address the storage issues of a VDI deployment.
DevOps, or if you want, preproduction environments, loosely defined as test dev, is another area. There are disaster recovery targets in combination with vSphere Replication and Site Recovery Manager. And some of the more aggressive customers are also starting to deploy it in production use cases.
In the last three months since the product has become available, we've found a significant success already in the marketplace.
As I said, the 300 customers that we already have span the gamut in terms of size and names. We have large enterprises, banking, down to the smaller accounts and companies, including education or smaller SMBs.
There are a couple of interesting cases that we'll be showcasing at VMworld 2014 in late-August. If you look at the session list, they're already available as actual use cases presented by our customers themselves.
Adobe will be talking about their massive implementation of Virtual SAN. And for their our production environment, on their data analytics platform, there will be another interesting use case with TeleTech talking about how they have leveraged Cisco UCS to progress VDI deployments.
Gardner: I'd like to revisit the VDI equation for a moment, because one of the things that’s held people up is the impact on storage, and the costs associated with the storage to support VDI. But if you're able to bring down costs by 50 percent, in some cases, using software-defined storage. That radically changes the VDI equation. Isn’t that the case, Christos, where you can now say that you can do VDI cheaper than almost any other approach to a virtualized desktop?
Karamanolis: Absolutely, and the cost of storage is the main impediment in organizations to implement a VDI strategy. With Virtual SAN, as Alberto mentioned earlier, we provide a very compelling cost proposition, both in terms of the capacity of the storage, as well as the performance you gain out of the storage.
You get the needs, both capacity and performance of your VDI workloads for a fraction of the cost you would pay for with a traditional disk array storage.
Alberto already touched on the cost of the capacity, referring to the difference in prices one can get from server vendors and from the market, as opposed to single hardware being procured as part of a traditional disk array.
I'd like to touch on something that is an unsung hero of Virtual SAN and of VDI deployment especially, and that's performance. Virtual SAN, as should be clear by now, is a storage platform that is strongly integrated with our hypervisor. Specifically, the data path implementation and the distributed protocols that are implemented in Virtual SAN are part of the ESXi kernel.
That means that, because of that, we can actually achieve very high performance goals, while we minimize the CPU cycles that are consumed to serve those high I/Os per second. What that means, especially for VDI, is that we use a small slice of the CPU and memory of every single ESXi host to implement this distributed software-driven storage controller.
It doesn't affect all the VMs that run on the same ESXi host, who have already published extensive and detailed performance evaluations, where we compare VDI deployments only on Virtual SAN versus using an external disk array.
And even though Virtual SAN use percentage is cut to be 10 percent of local CPU and memory on those hosts, the consolidation ratio, the number of virtual desktops we run on those clusters, is virtually unaffected, while we get the full performance that is realized with an external, all-flash disk array. So this is the value of Virtual SAN in those environments.
Essentially, you get the needs, both capacity and performance of your VDI workloads, for a fraction of the cost you would pay for with a traditional disk array storage.
Gardner: We're only a few weeks from VMworld 2014 in San Francisco, and I know there's going to be a lot of interest in mobile and in desktop infrastructure for virtualized desktops and applications.
Do you think that we can make some sort of a determination about 2014? Maybe this is the year that we turn the corner on VDI, and that that is a bigger driver to some of these higher efficiencies. Any closing thoughts on the vision for software-defined data center and VDI and the timing with VMworld. Alberto?
Farronato: Certainly, one of the goals that we set ourselves for this Virtual SAN release, solving the VDI use case, eliminating probably the last barrier, and enabling a broader adoption of VDI across the enterprise, and we hope that will materialize. We're very excited about what the early findings show.
With respect to VMworld and some of the other things that we'll be talking about at the conference with respect to storage, we'll continue to explain our vision of software-defined storage, talk about the Virtual SAN momentum, some of the key initiatives that we are rolling out with our OEM partners around things such as Virtual SAN Ready Nodes.
We're going to talk about how we will extend the concept of policy management and dynamic composition of storage services to external storage, with a technology called Virtual Volumes.
There are many other things, and it's gearing up to be a very exciting VMworld Conference for storage-related issues.
Gardner: Last word to you, Christos. Do you have any thoughts about why 2014 is such a pivotal time in the software-defined storage evolution?
Karamanolis: I think that this is the year where the vision that we've been talking about, us and the industry at large, is going to become real in the eyes of some of the bigger, more conservative enterprise IT organizations.
With Virtual SAN from VMware, we're going to make a very strong case at VMworld that this is a real enterprise-class storage system that's applicable across a very wide range of use cases and customers.
With actual customers using the product in the field, I believe that it is going to be a strong evidence for the rest of the industry that software-defined storage is real, it is solving real world problems, and it is here to stay.
Together with opening up some of the management APIs that Virtual SAN uses in VMware products to third parties through this Virtual Volumes technology that Alberto mentioned, we'll also be initiating an industry-wide initiative of making, providing, and offering software-defined storage solutions beyond just VMware and the early companies, mostly startups so far, that have been adopting this model. It’s going to become a key industry direction.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: VMware.
You may also be interested in:
Posted By Dana L Gardner,
Thursday, July 31, 2014
| Comments (0)
As a provider of both application development management and infrastructure outsourcing, Denmark-based NNIT needed a better way to track, manage and govern the more than 10,000 services across its global data centers.
Beginning in 2010, the journey to better overall services automation paved the way to far stronger cloud services delivery, too. NNIT uses HP Cloud Service Automation (CSA) to improve their deployment of IT applications and data, and to provide higher overall service delivery speed and efficiency.
To learn more about how services standardization leads to improved cloud automation, BriefingsDirect spoke with Jesper Bagh, IT Architect and cloud expert at NNIT, based in Copenhagen. The discussion, at the HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Tell us about your company and what you do. Then, we’ll get into some of the services delivery problems and solutions that you've been tasked with resolving.
Bagh: NNIT is a service provider located in Denmark. We have offices around the world, China, Philippines, Czech Republic, and the United States. We’re 2,200 employees globally and we're a subsidiary of Novo Nordisk, the pharmaceutical company.
My responsibility is to ensure for the company that business goals can be delivered through functional requirements, and in turning the functional requirements into projects that can be delivered by the organization.
We’re a wall-to-wall, full-service provider. So we provide both application development management and infrastructure outsourcing. Cloud is just one aspect that we’re delivering services on. We started off by doing service-portfolio management and cataloging of our services, trying to standardize the services that we have on the shelf ready for our customers.
That allowed us to then put offerings into a cloud, and to show the process benefits of standardizing of services, doing cloud well, and of focusing on the dedicated customers. We still have customers using our facility management who are not able to leverage cloud services because of compliance or regulatory demands.
We have roughly over 10,000 services in our data centers. We’re trying now to broaden the capabilities of cloud delivery to the rest of the infrastructure so that we get a more competitive edge. We’re able to deliver better quality, and the end users -- at the end of the day -- get their services faster.
Back in the good old days, developers were in one silo and operations were in another silo. Now, we see a mix of resources, both in operations and in development.
We embarked on CSA together with HP back in 2010. Back then, CSA consisted of many different software applications. It wasn't really complete software back then. Now, it’s a full suite of software.
It has helped us to show to our internal groups -- and our customers -- that we have services in the cloud. For us it has been a tremendous journey to show that you can deliver these services fully automatically, and by running them well, we can gain great efficiency.
Gardner: How has this benefited your speed-to-value when it comes to new applications?
Bagh: The adoption of automation is an ongoing journey. I imagine other companies have also had the opportunity of adopting a new breed of software, and a new life in automation and orchestration. What we see is that the traditional operations divisions now suddenly get developers trying to comprehend what they mean, and trying to have them work together to deliver operations automatically.
Back in the good old days, developers were in one silo, and operations were in another silo. Now, we see a mix of resources -- both in operations and in development. So the organizational change management derived from automation projects is key. We started up, when we did service cataloging and service portfolio management, by doing organizational change to see if this could fit into our vision.
Gardner: Now, a lot of people these days like to measure things. It’s a very data-driven era. Have you been able to develop any metrics of how your service automation and cloud-infrastructure developments have shown results, whether it’s productivity benefits or speeds and feeds? Have you measured this as a time-to-value or a time-to-delivery benefit? What have you come up with?
Bagh: As part of the cloud project, we did two things. We did infrastructure as a service (IaaS), but we also did a value add on IaaS. We were able to deliver qualified IaaS to the life science industry fully compliant. That alone, in the traditional infrastructure, would have taken us weeks or months to deliver servers because of all the process work involved. When we did the CSA and the GxP Cloud, we were able to deliver the same server within a matter of hours. So that’s a measurable efficiency that is highly recognized.
Gardner: For other organizations that are also grappling with these issues and trying to go over organization and silo boundaries for improvement in collaboration, do you have any words of advice? Now that you've been doing this for some time and at that key architect level, which I think is really important, what thoughts do you have that you could share with others, lessons learned perhaps?
Bagh: The lesson learned is that having senior management focus on the entire process is key. Having the organization recognized is a matter of change management. So communication is key. Standardization before automation is key.
You need to start out by doing your standardization of your services, doing the real architectural work, identifying which components you have and which components you don't have, and matching them up. It’s trying to do all the Lego blocks in order to build the house. That’s key. The parallel that I always use is there is nothing different for me as an architect than there is for an architect building a house.
The next step for us is to be more proactive than reactive in our monitoring and reporting capabilities, because we want to be more transparent to our customers.
Gardner: Looking to the future, are there other aspects of service delivery, perhaps ways in which you could gather insights into what's happening across your infrastructure and the results, that end users are seeing through the applications? Do you have any thoughts about where the next steps might be?
Bagh: The next step for us is to be more transparent to our customers. So the vision is now we can deliver services fully automatically. We can run them semi-automatically. We will still do funny stuff from time to time that you need to keep your eyes on. But in order for us to show the value, we need to report on it.
The next step for us is to be more proactive than reactive in our monitoring and reporting capabilities, because we want to be more transparent to our customers. We have a policy called Open and Honest Value-Adding. From that, we want to show our customers that if we can deliver a service fully automatically and standardized, they know what they get because they see it in a catalog. Then, we should be able to report on it live for the users.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
You may also be interested in:
Cloud Service Automation
Posted By Dana L Gardner,
Wednesday, July 30, 2014
| Comments (0)
Over the past five years, the impetus for cloud adoption has been primarily about advancing the IT infrastructure-as-a-service (IaaS) fabric or utility model, and increasingly seeking both applications and discrete IT workload support services from Internet-based providers.
But as adoption of these models has unfolded, it's become clear that the impacts and implications of cloud commerce are much broader and much more of a benefit to the business as a whole as an innovation engine, even across whole industries.
Recent research shows us that business leaders are now eager to move beyond cost and efficiency gains from cloud to reap far greater rewards, to in essence rewrite the rules of commerce.
Our latest BriefingsDirect discussion therefore explores the expanding impact that cloud computing is having as a strategic business revolution -- and not just as an IT efficiency shift. Join a panel of experts and practitioners of cloud to unpack how modern enterprises have a unique opportunity to gain powerful new means to greater business outcomes.
Our panelists are: Ed Cone, the Managing Editor of Thought Leadership at Oxford Economics; Ralf Steinbach, Director of Global Software Architecture at Groupe Danone, the French food multinational based in Paris; Bryan Acker, Culture Change Ambassador for the TELUS Transformation Office at TELUS, the Canadian telecommunications firm, and Tim Minahan, Chief Marketing officer for SAP Cloud and Line of Business Solutions. The panel is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: What has the research at Oxford Economics been telling you about how cloud is reshaping businesses?
Cone: We did a survey for SAP last year, and that became the basis for this program. We went out to 200 executives around the world and asked them, "What are you doing in the cloud? Are you still looking at it for just process speed, efficiency, and cost cutting?"
The numbers that came back were really strong in terms of actually being a part of the business function. Beyond those basics, cloud is very much part of the daily reality of companies today.
We saw that the leading expectation for cloud to deliver significant improvement was in productivity, innovation, and revenue generation. So obviously process, speed, efficiency, and cost cutting are still very important to business, but people are looking to cloud for new lines of business, entering new markets, and developing new products.
In this program, what we did was take that information and go out to executives for live interviews to dive deep into how cloud has become the new engine of business, how these expectations are being met at companies around the world.
Gardner: Are businesses doing this intentionally, or are they basically being forced by what's happening around them?
Minahan: Increasingly, as was just indicated, businesses are moving beyond the IT efficiencies and the total cost of ownership (TCO) benefits of the cloud, and the cloud certainly offers benefits in those areas.
But really what's driving adoption, what's moving us to this tipping point, is that now, by some estimates, 75 percent of all new investments are going into the cloud or hybrid models. Increasingly, businesses are viewing the cloud as a platform for innovation and entirely new engagement models with their customers, their employees, their suppliers and partners, and in some cases, to create entirely new business models.
Just think about what cloud has done for our personal lives. Who would have thought that Apple, a few years ago, would be used to run your home. This is the Apple Home concept that allows you to monitor and manage all of your devices -- your air-conditioning, your alarm, music, and television -- remotely through the cloud.
There's even the quasi business B2B and B2C models around crowd sourcing and crowd funding from folks like Kickstarter or payment offerings like Square. These are entirely new engagement models, new business models that are built on the back of this emergence of cloud, mobile, and social capabilities.
Gardner: Right, and it seems that one of these benefits is that we can cross boundaries of time, space geography, what have you, very easily, almost transparently, and that requires new thinking in order to take advantage of that.
Bryan, at TELUS as Culture of Change Ambassador, are you part of the process for helping people think differently and therefore be able to exploit what cloud enables?
Flexible work schedule
Acker: One hundred percent. It's actually a great segue, because at TELUS we have a flexible work arrangement, where we want 70 percent of our employees to be working either from home or remotely. What that means is we have to have the tools and the culture in place that people understand, that they can access data and relevant information, wherever they are.
It doesn't matter if they're at home, like I am today, on the road, or at a client site, they need to be able to get the information to provide the best customer experience and provide the right answer at the right time.
So by switching from some of the great tools we already offered, because collaboration is part of TELUS’s cultural DNA, we've actually been able to tear down silos we didn't even know we were creating.
We were trying to provide all the tools, but now people have an end-to-end view of every record for customers, as well as employees and the collaboration involving courses and learning opportunities. They have access to everything when they need it and they can take ownership of the customer experience or even their own career, which is fantastic for us.
Gardner: Ralf, at Danone, as Director of Global Software Architecture, you clearly have your feet on the IT path and you've seen how things have evolved. Do you see the shift to cloud as a modest evolution, or is this something that changes the game?
Steinbach: We've been looking at cloud for quite sometime now. We've started several projects in the cloud, mainly in two areas. One involves the supporting functions of our business which is HR, travel expenses, and mail. There, we see a huge advantage of using standardized services in the cloud.
In these functions we do not need any specifics. The cloud comes standard and you can not change, as you can with SAP systems. You can't adapt the code. But that is one area where we think there's value in using cloud applications.
The other area where we really see the cloud as valued is in our digital marketing initiatives. There, we really need the flexibility of the cloud. Digital marketing is changing every day. There's a lot of innovation there and there the cloud gives us flexibility in terms of resources that we need to support that. And, the innovation cycles of our providers are much faster than they would be on premises. These are the two main areas where we use the cloud today.
Cone: Ralf, it was interesting to me, when I was reading through the transcript of your interview and working on the case studies we did, that it is even changing business models. It's allowing Danone to go straight to the consumer, where previously your customer had been the retailer. Cloud in new geographic markets is letting you reach straight to the end user, the end buyer.
Steinbach: That's what I meant when I talked about digital marketing. Today, all consumer product goods company like Danone are looking at connecting to their consumers and not to the retailers as in the past. We're really focusing on the end-consumer, and the cloud offers us new possibilities to do that, whether it is via mobile applications or websites and so on.
One thing that's important is the flexibility of the systems, because we don't know how many consumers we'll address. It can be a few, but it could be over a million. So we need to have a flexible architecture, and on-premise we could not manage that.
Gardner: The concept of speed seems to come up more and more. We're talking about speed of innovation, agility, direct lines of communication to customers and, of course, also supply-chain direct communication speed as well. How prominent did you see speed and the need for speed in business in your recent research?
We're really focusing on the end consumer, and the cloud offers us new possibilities to do that.
Cone: Well, speed was important -- and it's speed across different dimensions. It's speed to enter a new market or it's speed to collaborate within your own company, within your own organization.
This idea of taking IT and pushing it out to the people, to the customer, and really to the line of business allows them to have intimate contact and to move quickly, but also to break down these barriers of geography.
We did a case study with another large company, Hero, which is a large maker of motorcycles and two wheeled vehicles in India. What they're doing with cloud- enabled customer-facing technology is moving their service operation outside of dealerships into the countryside, out across India. They go to parks and they set up what they call service camps.
There, the speed element is the speed and the convenience with which you are able to get your bike serviced, and that's having a large measurable impact on their business. So it is speed, but it is speed across multiple dimensions.
Minahan: At the core, the cloud is really all about unlocking new innovations, providing agility in the business, allowing companies to be able to adapt their processes very, very quickly, and even create entirely new engagement models, and that's what we are seeing.
It is not just the cloud, though. This convergence of cloud, big data, analytics, mobile and social, and business networks really ushers in ultimately a new paradigm for business computing, one where applications are no longer just built for enterprise compliance or to be the system of record. Instead, they're really designed to engage and empower the individual user.
It's one that ushers in a new era of innovation for the business, where we can enable new engagement models with customers, employees, suppliers, and other partners.
We've heard some great examples here, but some others were very similar to the experience that Danone has seen. T-Mobile is leveraging the cloud not to replace its traditional systems of records, but to extend them with the cloud, to create a new model for social care, helping monitor conversations on its brand, and engage customer issues across multiple channels.
This convergence of cloud, big data, analytics, mobile and social, and business networks really ushers in ultimately a new paradigm for business computing.
So not just their traditional support channels, but Twitter and Facebook, where these conversations are happening and really it is empowered them to deliver what has become a phenomenal kind of “Cinderella-worst-to-first” story for customer support and satisfaction.
Now, they're seeing first time resolution rates that have gone from the low teens to greater than 94 percent. Obviously, that has a massive impact on customer satisfaction and renewals and is all powered by not throwing out the systems that they've used so long, but by extending them with the cloud to achieve new innovations and then drive new engagement models.
Gardner: Tim, another factor here, in a sense, levels the playing field. When you move to the cloud, small-to-medium-sized enterprises (SMBs) can enjoy the same benefit that you just described for example from T-Mobile. Are you at SAP seeing any movement in terms of the size or type of organizations that can exploit these new benefits?
Minahan: What's interesting, Dana, is that you and I have been around this industry for quite some time and the original thought was that the cloud was the big, democratized computing power.
It allowed SMBs to get the same level of applications and infrastructure support that their larger competitors have had for years. That's certainly true, but it is really the large enterprises that have been aggressively adopting this on an equal pace with their SMBs.
All sizes of companies
The cloud is being used to not only accelerate process efficiency and productivity, but to unlock innovations for all sized companies. Large enterprises like UPS, Deutsche Bank, and Danone are using cloud-based business applications. In the case of UPS and Deutsche Bank, they're using business networks to extend their traditional supply chain and financial systems to collaborate better with their suppliers, bankers, and other partners.
It's being used by small upstarts as well. These are companies that we talked about in the past like Mediafly, a mobile marketing start-up. It's using dynamic discounting solutions in the cloud to get paid faster, fund development of new features, and take on new business.
There's Sage Health Solutions, a company started by two stay-at-home moms in South Africa that is really grown from zero to a multi-million dollar operation. That is all powered by the leveraging the cloud to enable new business models.
Cone: To follow on with what Tim said about the broad gamut of usage from company sites and also earlier mentioning mobile, what we saw in our survey is that mobile is of great importance to companies as a way of reaching their customers for internal productivity as well. But reaching customers is actually a higher priority and that comes down to the old adage: You have to fish where the fish are.
The cloud is being used to not only accelerate process efficiency and productivity, but to unlock innovations for all sized companies.
Look at what Danone is doing when they're setting up direct-to-customer technologies and marketing. They're going into markets where people don't necessarily have laptops or landlines. They're leapfrogging that to a world where people have mobile devices.
So if you have mobile customers, and as Tim said, think of the consumer experience, that is how we all live our lives now. No matter what size your company is, you have to reach your customers the way your customer lives now -- and that is mobile.
Gardner: Tell us a little bit about your research, how you have gone about it, and how that new level of pervasive collaboration was demonstrated in your findings.
Cone: In terms of the research, as I said, we went out to 200 execs around the world and asked them a series of questions about what their investment plans were. It was baseline survey information. What are you doing in the cloud, how much of it are you doing, and what are the key benefits that you're getting?
Then, as we went deeper in this phase of the project, we found that collaboration has different meanings. It can be collaboration within the company. It can be with partners, which cloud platforms allow you to do more easily. It's also this key relationship, a key area of collaboration between IT and the business.
What we see in this research is that IT is increasingly seen as a partner for the business as a way of driving revenue via the cloud. But across the four regions that we surveyed -- North America, Latin America, EMEA and APAC -- we saw a very high percentage of companies say that they see that IT is emerging as a valued partner of the business, not just a support function for the business. I think that's a key collaborative relationship that I'm sure our guests are seeing in their own companies.
Gardner: Just to be clear, Ed, this is ongoing research. You're already back in the field and you'll be updating some of these findings soon?
We're really interested to see how people are doing compared to the targets they set and what their new targets are.
Cone: Yes, we're really excited about that, Dana. We did this survey last year for SAP. Then, we jumped in about a year later using those numbers and did these in-depth research interviews to look at the use of the cloud to drive business. This summer, we're refielding the survey to see how things have changed and to see how the view of the future has changed.
We ask a lot of questions about where they are now, and where they think they'll be in three years. We're really interested to see how people are doing compared to the targets they set and what their new targets are. So we will have some fresh numbers and fresh reports to talk to you about by Q3 or Q4.
Gardner: Let us look into those actual examples now and go back to Bryan at TELUS.
Acker: I have a tangible example that might help express the value of collaboration at TELUS and something that people don't think about, and that is safety.
We have a lot of field technicians who are in remote areas, but have mobile access. A perfect example is that we can go into situation where a technician may be a little unsure of what to do in a situation and it's potentially unsafe.
Because of the mobile access and the cloud, we've enabled them to quickly record a video, upload it directly to our SAP Jam system, which is our collaborative tool suite that we use, and share it with a collection of other technicians, not just the person they can call.
What happens is then people can say this is unsafe, you need to do X, Y and Z. We can even push them required training, so they can be sure that they're making the right decision. All of a sudden, that becomes a safer situation and the technician is not putting themselves at risk. This is really important because people do not think of those real, tangible examples. They often feel that they're just sharing information back and forth.
But in terms of what we are doing and where we are going, I sit in HR, and we're trying to improve the business process. We now have all of our information, the system of record, an integrated learning management system (LMS), our ability to analyze talent, so we make the correct hires.
We now trust the information implicitly and we're able to make the correct decision, whether it means customer information, recruiting choices, hiring choices, or performance choices.
Now, we're in a situation where we're only going to maximize and try to leverage the cloud for even more innovation, because now people are singing from the same choir sheet, so to speak.
We now trust the information implicitly and we're able to make the correct decision, whether it means customer information, recruiting choices, hiring choices, or performance choices.
We have access to the same system or record of truth, and that's the first time we've had that. Now, recruiting can talk to learning, who can talk to performance, who can talk to technicians and we know they all get a consistent version of the truth. That is really important for us.
Gardner: Those are some excellent examples of how mobile enhances cloud. That extends the value of mobile. That brings in collaboration and, at the same time, creates data and analysis benefits that can then be fed back into that process.
So there really is a cyclical adoption value here. I'd like to go back to the cultural part of this. Bryan, how do you make sure that that adoption cycle doesn't spin out of control? Is there a lack of governance? Do you feel like you can control what goes on, or are we perhaps in the period of creative chaos that we should let spin off on its own in any way?
Acker: That’s a great question, and I'm not sure if TELUS handles this in a unique way, but we definitely had a very detailed plan. The first thing we did was have collaboration as one of our valued attributes or one of our leadership competencies. People are expected to collaborate, and their performance review is dependent on that.
What that means is we can provide tools to say that we're trying to facilitate collaboration. It doesn't mean matter if you're collaborating through a phone call, through a water-cooler chat, or through technology. Our employees are expected to collaborate. They know that it’s part of their performance cycle and it’s targeted towards their achievements for the year. We trust them to do the right thing.
We actually encourage a little bit of freedom. We want to push the boundaries. Our governance is not so tight that they are afraid to comment incorrectly or afraid to ask a tough question.
Flattening the hierarchy
What we're seeing now is individual team members are challenging leadership positions on specific questions, and we're having an honest and frank discussion that’s pushing the organization forward and making us make the accurate correct choice at all time, which is really encouraging. Now, we're really flattening our hierarchy and the cloud is enabling us to do that.
Gardner: That sounds like a very powerful engine of innovation, allowing that freedom, but then having it be controlled, managed, and understood at the same time. That’s amazing. Ed, do you have any reactions to what Bryan just said about how innovation is manifesting itself newly there at TELUS?
Cone: When we spoke to TELUS, I was intertested in that cultural aspect of it. I'm sure the guys on the call would disagree with me on a technical level, but we like to say that technology is easy, and culture is hard. The technology works, and you implement it and you figure that out, but getting people to change is really difficult.
The example that we use in the case study, SAP on TELUS, was about changing culture through gamification, allowing people to learn via an online cloud-based virtual game. It was this massive effort and it engaged a huge number of employees across this large company.
It really shifted the employee culture, and that had an impact on customer service and therefore on business performance
It really shifted the employee culture, and that had an impact on customer service and therefore on business performance. It’s a way that the cloud is moving mountains and it’s addressing the hard thing to change, which is human behavior and attitudes.
Minahan: We talk about the convergence of these different technologies in cloud, social, and mobile and ultimately we had this convergence going on in technology that we talked about all the time. There is massive change going on in the workforce and what constitutes the workforce.
Bryan talked about how there is a leveling of the organization, doing away with the traditional hierarchical command and control, where information is isolated in the hands of a few, and the new eager employees doesn’t get access to solving some of the tough problems. All that’s being flattened and accelerated and powered by cloud and social collaboration tools.
Also, we're seeing a shift in what constitutes the workforce. One of the biggest examples is the major shift in how companies are viewing the workforce. Contingent and statement of work (SOW) workers, basically non-payroll employees, now represent a third of the typical workforce. In the next few years, this will grow to more than half.
It’s already occurring in certain industries, like pharmaceuticals, mining, retail, and oil and gas. It's changing how folks view the workforce. They're moving from a functional management of someone -- this is their job; this is what they do -- to managing pools of talent or skills that can be rapidly deployed to address a given problem or develop a new innovative product or service.
These pools of talent will include both people on your payroll and off your payroll. Tracking, managing, organizing, and engaging these pools of talent is only possible through the cloud and through mobile, where multiple parties from multiple organizations could view, access, collaborate, and share knowledge and experiences running on a shared-technology platform.
Customer is evolving
Acker: That extends quite naturally to the customer. The customer is evolving faster than almost anything and they expect 24x7 access to support. They expect authentic responses and they now have access to just as much information as the customer service agent.
Without mobile, if you can't connect with those customers and be factual, you're in trouble. Your customers are going to reply in social-media channels and in public forums, and you're going to lose business and you're going to lose trust with your existing customers as well.
Minahan: I fully agree. The only addition to that is that they also expect to be able to engage you through any channel, whether it’s their mobile phone, their laptop, or in some cases, directly face to face, on the phone, or in a retail outlet and have the same consistent experience and not need to reintroduce who they are and what their problem as they move from channel to channel.
Gardner: Clearly we're seeing how things that just weren’t possible before the cloud are having pervasive impacts on businesses. Let’s look at a new business example, again with Danone. Ralf, tell us a little bit about how cloud has had strategic implications for you. You have many brands, many lines of business. How is cloud allowing Danone to function better as a whole?
The cloud is definitely the best option for us to start these new businesses and connect to all consumers.
Steinbach: We have a strategy around digital marketing and, as you know, we're operating in almost every country in the world. Even though we're a big company, locally, we're sometimes quite small. We're trying to build up new markets in emerging countries with very small investments in the beginning. There, the cloud is definitely the best option for us to start these new businesses and connect to all consumers.
Money matters, even for a big company like Danone. That’s very important for us. If you look at Africa, there are completely different business models that we need to address.
People in Africa pay with their mobile phones. Some sell yogurt on a bicycle. Women pick up some yogurt in the morning and then they sell them on the road. We need to do businesses with these people as well. Obviously, an enterprise resource planning (ERP) system isn't able to do that, but the cloud is a much better adapted platform to do this sort of business.
Gardner: The C-suite likes to look at numbers. How do we measure innovation?
Cone: We're doing some research on another program right now on that very topic for a non-SAP program. That is showing us that metrics for success on basic things like key performance indicators (KPIs) for progress of migration into the cloud are lacking at a lot of companies. Basic return on investment (ROI) numbers are lacking at a lot of companies.
We're really old school. To go back to your definition of what a business is, we think it’s an organization that’s set up to make money for shareholders and deliver value for stakeholders. By those measures, at least by dotted line, the key metrics are your financial performance? Are you entering, as we mentioned before, new markets and creating new products?
So the metrics we're seeing that are cloud specific aren't universal yet. In a broader sense, as cloud becomes an everyday set of tools, the point of those tools is to make the business run better, and we are seeing a correlation between effective use of the cloud and business performance.
There are entirely new engagement models and business models that the companies hadn’t even thought of before.
Minahan: What the cloud, mobile, and social bring to bear in addition to new collaboration models is that they kick off an unbelievable amount of new information, and oftentimes not in a structured way. There's a need to aggregate that information and analyze that in new ways to detect and predict propensity modeling on your customers, your supply chain, and your employees. Progression and development are extremely powerful.
I think we’ve just scratched the surface. As an industry, we provided the channels through which to collaborate, as we heard today. There are entirely new engagement models and business models that the companies hadn’t even thought of before. Once you have that information, once you have that connectivity, once you have that collaboration, you can begin to investigate and trial and error.
To answer your question about measurement on this, yes, we need measurement of the business process and the business outcome. Let’s not forget why companies adopt technology. It’s not just for technology sake. It’s to effect the change. It’s to effect more efficiency, greater productivity, and new engagement capabilities.
Measuring the business benefit is what we're seeing and what we’re advising our customers to do. And rather than just measuring, are we tracking towards an adoption of having more cloud in our infrastructure portfolios.
The focus today is largely driven by the fact that the lines of business are now more engaged in the buying decision and in shaping what they want from a technology standpoint to help them enable their business process. So the metrics have shifted from one of speeds and feeds and users to one of business outcomes.
Gardner: Bryan at TELUS in Toronto, you're closely associated with the human resources productivity and the softer metrics of the employee involvement and dedication that sort of thing. Are there any ways that you can think of that cloud adoption and innovation, as we’ve been describing, has this unintended set of consequences when it comes to employee empowerment or that innovation equation? How do you view measuring success of cloud adoption?
Simplifying the process
Acker: We measure our customers success by the likelihood to recommend. Will a TELUS customer recommend our services and products to friends, family, and peers?
We measure internal success by our employee engagement metric. If the customers are satisfied and the employees are engaged and fulfilled at work, that means that we're probably moving in the right direction. We can kind of reverse engineer to see what changes are helping us. That allows us to take our information and innovation from the cloud and inspire better behaviors and better process.
We can say, "You know what, in this pocket we’ve analyzed that our customers are likely to recommend it higher than anywhere else in Canada. What are they doing?" We can look back through the information shared on the cloud and see the great customer success stories or the great team building that’s driving engagement through the roof.
We can say, "This is the process we have to replicate and spread throughout all of our centers." Then, we can tweak it for cultural specifics. But because of that, we can use the cloud to inspire better behavior, not just say that we had 40,000 users and 2,000 hits on this blog post. We're really trying to get away from the quantitative and get into the qualitative to drive change throughout the organization.
Gardner: What comes next? Where do you see the impacts of cloud adoption in your business over the next couple of years?
Steinbach: There are still some challenges in front of us. One of the challenges is China. China is one of the biggest markets, but cloud services are not always available or they're very slow. If your cloud solution is hosted outside of China, there's a big problem. These are probably technical challenges, but we have to find solutions with our partners there, so that they can establish their services in China.
That’s one of the challenges. The other is that that the cloud might change the role of IT in our organization. In the past we owned the systems and the applications. Today, the business can basically buy cloud services with a credit card. So you could imagine that they won’t need us anymore in the future, but that's not true.
As an IT organization, we probably have to find our role inside the organization, from just providing solutions or hardware to being an ambassador for the business and to help them to make the right decisions. There are still problems that will remain as the integration between different applications. It doesn’t get easier in the cloud, so that’s where I see the challenge.
And last but not least, it's about security. We take that really seriously. If we store data, whether it's employees or of our consumers, we have to make sure that that our cloud providers have the same standards of security and there are no leaks. That’s very, very important for us. And there are legal aspects as well.
We've just started. There are still a lot of things to do in the next few years, but we're definitely going on with our strategy towards the cloud and toward mobile. And, at the end of the day, it all fits together. I think it was said before that it's not only cloud, but it's the big data, collaboration, and mobile. You have to see the whole thing as one package of opportunities.
Gardner: What do you think might be some of the impacts a few years from now that we're only just starting to realize?
Acker: On a more positive note, which is just the other side of the coin, obviously the challenges are there, but we're actually just starting to be able to experience the fact that innovation at TELUS is moving faster than it used to. We're no longer dependent on the speed at which our pre-assigned resources can make change and develop new products.
IT can now look at it from a more strategic point of view, which is great. Now, we're maximizing quarterly releases from systems that are leveraging the input from multiple companies around the world, not just how fast our learning team can develop something or how fast our IT team can build new functionality into our products.
We're no longer limited by the resources, and innovation is flying forward. That, for us, is the biggest unexpected gain. We're seeing all this technology that used to take months or years to change now on a quarterly release schedule. This is fantastic. Even within a year of being on our cloud-computing system, we're so happy, and that is inspiring to people. They're maximizing that and trying to push the organization forward as well. So, that’s a real big benefit.
Gardner: Tim, do you have any thoughts about where this can lead us in the next few years that we haven’t yet hit upon, things you're just starting to see the first really glimmers of it?
I think the biggest thing is that the cloud is going to unlock new business models and new organization models.
Minahan: A lot of it has been touched on here. We're seeing a massive shift in what the role of IT is, moving from one of deploying technology and integrating things to really becoming business process experts.
We talked a bit about the amount of data and the insights that are now available to help you better understand and predict the appetites of your customers to help you even determine when your machines might fail and when it's time to reorder or set a service repair.
I think the biggest thing is that the cloud is going to unlock new business models and new organization models. We talked a bit about TELUS and their work patterns, in which most of the workers are remote and how they are engaging the field service technicians in the field.
We talked about the growing contingent workforce and how the cloud is enabling folks to collaborate, onboard, and skill up those employees, non-payroll employees much more quickly. We're going to see your new virtual enterprises. We're talking about borderless enterprises that allow you to organize not just pools of talent, but entire value chains, and be able to collaborate in a more much transparent way.
We mentioned before about Apple Home. You're beginning to see it with 3D printers. It's this whole idea where more and more companies become digital businesses. This isn’t just about on-the-channel commerce providing a single customer experience across multiple channels.
It's actually about moving more and more of what you deliver, the solutions you deliver, the former products your deliver, to digital bits that can be tested, experienced, and downloaded all online.
All of this is being empowered by this massive convergence of cloud, mobility, social and business networks, and big data.
What comes next
Cone: To follow on what Tim said about the borderless enterprise, when we ask people what’s in the cloud now and what’s going to be substantially cloud based in three years, three of the highest growth areas were innovation in R and D, supply chain, and HR. All of those go straight to this idea that boundaryless digital enterprises are emerging and that cloud will be the underpinning of these enterprises.
We're working with Tim right now on a big global study about the workforce. When I talk about culture and the way companies function internally, a year ago, when we started this research, HR was the least likely function of the ones we queried to be in the cloud, and it's going to have massive growth in the next couple of years.
These stories start to converge of boundaryless and culture, all coming together via the cloud.
These stories start to converge of boundaryless and culture, all coming together via the cloud. That’s the segue to say that we're really excited to see how these numbers look when we refield this survey this summer, because that progress is snowballing and accelerating beyond even what people thought it was the last time we asked them.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: SAP.
You may also be interested in:
Posted By Dana L Gardner,
Wednesday, July 23, 2014
| Comments (0)
Three years ago, Systems Mechanics Limited used relational databases to assemble and analyze some 20 different data sources in near real-time. But most relational database appliances used 1980s technical approaches, and the ability to connect more data and manage more events capped off. The runway for their business expansion just ended.
So Systems Mechanics looked for a platform that scales well and provides real-time data analysis, too. At the volumes and price they needed, HP Vertica has since scaled without limit ... an endless runway.
To learn more about how Systems Mechanics improved how their products best deliver business intelligence (BI), analytics streaming, and data analysis, BriefingsDirect spoke with Andy Stubley, Vice President of Sales and Marketing at Systems Mechanics, based in London. The discussion, at the HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: You've been doing a lot with data analysis at Systems Mechanics, and monetizing that in some very compelling ways.
Stubley: Yes, indeed. System Mechanics is principally a consultancy and a software developer. We’ve been working in the telco space for the last 10-15 years. We also have a history in retail and financial services.
The focus we've had recently and the products we’ve developed into our Zen family are based on big data, particularly in telcos, as they evolve from principally old analog conversations into devices where people have smartphone applications -- and data becomes ever more important.
All that data and all those people connected to the network cause a lot more events that need to be managed, and that data is both a cost to the business and an opportunity to optimize the business. So we have a cost reduction we apply and a revenue upside we apply as well.
Gardner: What’s a typical way telcos use Zen, and that analysis?
Stubley: Let’s take a scenario where you’re looking in network and you can’t make a phone call. Two major systems are catching that information. One is a fault-management system that’s telling you there is a fault on the network and it reports that back to the telecom itself.
The second one is the performance management system. That doesn’t specify faults basically, but it tells you if you’re having things like thresholds being affected, which may have an impact on performance every time. Either of those can have an impact on your customer, and from a customer’s perspective, you might also be having a problem with the network that isn’t reported by either of the systems.
We’re finding that social media is getting a bigger play in this space. Why is that? Now, particular the younger populations with consumer-based telcos, mobile telcos particularly, if they can’t get a signal or they can’t make a phone call, they get onto social media and they are trashing the brand.
They’re making noise. A trend is combining fault management and performance management, which are logical partners with social media. All of a sudden, rather than having a couple of systems, you have three.
In our world, we can put 25 or 30 different data sources on to a single Zen platform. In fact, there is no theoretical limit to the number we could, but 20 to 30 is quite typical now. That enables us to manage all the different network elements, different types of mobile technologies, LTE, 3G, and 2G. It could be Ericsson, Nokia, Huawei, ZTE, or Alcatel-Lucent. There is an amazing range of equipment, all currently managed through separate entities. We’re offering a platform to pull it all together in one unit.
The other way I tend to look at it is that we’re trying to turn the telcos into how you might view a human. We take the humans as the best decision-making platforms in the world and we probably still could claim that. As humans, we have conscious and unconscious processes running. We don’t think about breathing or pumping our blood around our system, but it’s happening all the time.
We use a solution with visualization, because in the world of big data, you can’t understand data in numbers.
We have senses that are pulling in massive amount of information from the outside world. You’re listening to me now. You’re probably doing a bunch of other things while you are tapping away on a table as well. They’re getting senses of information there and you are seeing, and hearing, and feeling, and touching, and tasting.
Those all contain information that’s coming into the body, but most of the activity is subconscious. In the world of big data, this is the Zen goal, and what we’re delivering in a number of places is to make as many actions as possible in a telco environment, as in a network environment, come to that automatic, subconscious state.
Suppose I have a problem on a network. I relate it back to the people who need to know, but I don’t require human intervention. We’re looking a position where the human intervention is looking at patterns in that information to decide what they can do intellectually to make the business better.
That probably speaks to another point here. We use a solution with visualization, because in the world of big data, you can’t understand data in numbers. Your human brain isn’t capable of processing enough, but it is capable of identifying patterns of pictures, and that’s where we go with our visualization technology.
Gather and use data
We have a customer who is one of the largest telcos in EMEA. They’re basically taking in 90,000 alarms from the network a day, and that’s their subsidiary companies, all into one environment. But 90,000 alarms needing manual intervention is a very big number.
Using the Zen technology, we’ve been able to reduce that to 10,000 alarms. We’ve effectively taken 90 percent of the manual processing out of that environment. Now, 10,000 is still a lot of alarms to deal with, but it’s a lot less frightening than 90,000, and that’s a real impact in human terms.
Gardner: Now that we understand what you do, let’s get into how you do it. What’s beneath the covers in your Zen system that allows you to confidently say you can take any volume of data you want?
If we need more processing power, we can add more services to scale transparently. That enables us to get any amount of data, which we can then process.
Stubley: Fundamentally, that comes down to the architecture we built for Zen. The first element is our data-integration layer. We have a technology that we developed over the last 10 years specifically to capture data in telco networks. It’s real-time and rugged and it can deal with any volume. That enables us to take anything from the network and push it into our real-time database, which is HP’s Vertica solution, part of the HP HAVEn family.
Vertica analysis is to basically record any amount of data in real time and scale automatically on the HP hardware platform we also use. If we need more processing power, we can add more services to scale transparently. That enables us to get any amount of data, which we can then process.
We have two processing layers. Referring to our earlier discussion about conscious and subconscious activity, our conscious activity is visualizing that data, and that’s done with Tableau.
We have a number of Tableau reports and dashboards with each of our product solutions. That enables us to envision what’s happening and allows the organization, the guys running the network, and the guys looking at different elements in the data to make their own decisions and identify what they might do.
We also have a streaming analytics engine that listens to the data as it comes into the system before it goes to Vertica. If we spot the patterns we’ve identified earlier “subconsciously,” we’ll then act on that data, which may be reducing an alarm count. It may be "actioning" something.
It may be sending someone an email. It may be creating a trouble ticket on a different system. Those all happen transparently and automatically. It’s four layers simplifying the solution: data capture, data integration, visualization, and automatic analytics.
Developing high value
Gardner: And when you have the confidence to scale your underlying architecture and infrastructure, when you are able to visualize and develop high value to a vertical industry like a telco, this allows you to then expand into more lines of business in terms of products and services and also expand into move vertical. Where have you taken this in terms of the Zen family and then where do you take this now in terms of your market opportunity?
Stubley: We focus on mobile telcos. That’s our heritage. We can take any data source from a telco, but we can actually take any data source from anywhere, in any platform and any company. That ranges from binary to HTML. You name it, and if you’ve got data, we could load it.
That means we can build our processing accordingly. What we do is position what we call solution packs, and a solution pack is a connector to the outside world, to the network, and it grabs the data. We’ve got an element of data modeling there, so we can load the data into Vertica. Then, we have already built reports in Tableau that allows us to interrogate automatically. That’s at a component level.
Once you go to a number of components, we can then look horizontally across those different items and look at the behaviors that interact with each other. If you are looking at pure telco terms, we would be looking at different network devices, the end-to-end performance of the network, but the same would apply to a fraud scenario or could apply to someone who is running cable TV.
The very highest level is finding what problem you’re going to solve and then using the data to solve it.
So multi-play players are interesting because they want to monitor what’s happening with TV as well and that will fit in exactly in the same category. Realistically, anybody with high-volume, real-time data can take benefit from Vertica.
Another interesting play in this scenario is social gaming and online advertising. They all have similar data characteristics, very high volume and fixed data that needs to be analyzed and processed automatically.
Gardner: How long have you been using Vertica, and what is it that drove you to using it vis-à-vis alternatives?
Stubley: As far as the Zen family goes, we have used other technologies in the past, other relational databases, but we’ve used Vertica now for more than two-and-a-half years. We were looking for a platform that can scale and would give us real-time data. At the volumes we were looking at nothing could compete with Vertica at a sensible price. You can build yourself any solid solution with enough money, but we haven’t got too many customers who are prepared to make that investment.
So Vertica fits in with the technology of the 21st century. A lot of the relational database appliances are using 1980 thought processes. What’s happened with processing in the last few years is that nobody shares memory anymore, and our environment requires a non-shared memory solution. Vertica has been built on that basis. It was scaled without limit.
One of the areas we’re looking at that I mentioned earlier was social media. Social media is a very natural play for Hadoop, and Hadoop is clearly a very cost-effective platform for vast volumes of data at real-time data load, but very slow to analyze.
So the combination with a high-volume, low-cost platform for the bulk of data and a very high performing real-time analytics engine is very compelling. The challenge is going to be moving the data between the two environments. That isn’t going to go away. That’s not simple, and there is a number of approaches. HP Vertica is taking some.
There is Flex Zone, and there are any number of other players in that space. The reality is that you probably reach an environment where people are parallel loading the Hadoop and the Vertica. That’s what we probably plan to do. That gives you much more resilience. So for a lot of the data we’re putting into our system, we’re actually planning to put the raw data files into Hadoop, so we can reload them as necessary to improve the resilience of the overall system, too.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
You may also be interested in:
Posted By Dana L Gardner,
Tuesday, July 15, 2014
| Comments (0)
An expected deluge of data and information about patients, providers, outcomes, and needed efficiencies is pushing the healthcare industry to rapid change. But more than dealing with just the volume of data is required. Interoperability, security and the ability to adapt rapidly to the lessons in the data are all essential.
The means of enabling Boundaryless Information Flow, Open Platform 3.0 adaptation, and security for the healthcare industry are then, not surprisingly, headline topics for The Open Group’s upcoming event, Enabling Boundaryless Information Flow on July 21 and 22 in Boston.
And Boston is a hotbed of innovation and adaption for how technology, enterprise architecture, and open standards can improve the communication and collaboration among healthcare ecosystem players.
In preparation for the conference, BriefingsDirect had the opportunity to interview Jason Lee, the new Healthcare and Security Forums Director at The Open Group. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: I'm looking forward to the Boston conference next week and want to remind our listeners and readers that it's not too late to sign up to attend. You can learn more at www.opengroup.org.
Let’s start by talking about the relationship between Boundaryless Information Flow, which is a major theme of the conference, and healthcare. Healthcare perhaps is the killer application for Boundaryless Information Flow.
Lee: Interesting, I haven’t heard it referred to that way, but healthcare is 17 percent of the US economy. It's upwards of $3 trillion. The costs of healthcare are a problem, not just in the United States, but all over the world, and there are a great number of inefficiencies in the way we practice healthcare.
We don’t necessarily intend to be inefficient, but there are so many places and people involved in healthcare, it's very difficult to get them to speak the same language. It's almost as if you're in a large house with lots of different rooms, and every room you walk into they speak a different language. To get information to flow from one room to the other requires some active efforts, and that’s what we're undertaking here at The Open Group.
Gardner: What is it about the current collaboration approaches that don’t work? Obviously, healthcare has been around for a long time and there have been different players involved. What are the hurdles? What prevents a nice, seamless, easy flow and collaboration in information that creates better outcomes? What’s the holdup?
Lee: There are many ways to answer that question, because there are many barriers. Perhaps the simplest is the transformation of healthcare from a paper-based industry to a digital industry. Everyone has walked into a medical office, looked behind the people at the front desk, and seen file upon file and row upon row of folders, information that’s kept in a written format.
When there's been movement toward digitizing that information, not everyone has used the same system. It's almost like trains running on different gauge track. Obviously if the track going east to west is a different gauge than going north to south, then trains aren’t going to be able to travel on those same tracks. In the same way, healthcare information does not flow easily from one office to another or from one provider to another.
Gardner: So not only do we have disparate strategies for collecting and communicating health data, but we're also seeing much larger amounts of data coming from a variety of new and different places. Some of them now even involve sensors inside of patients themselves or devices that people will wear. So is the data deluge, the volume, also an issue here?
Lee: Certainly. I heard recently that an integrated health plan, which has multiple hospitals involved, contains more elements of data than the Library of Congress. As information is collected at multiple points in time, over a relatively short period of time, you really do have a data deluge. Figuring out how to find your way through all the data and look at the most relevant [information] for the patient is a great challenge.
Gardner: I suppose the bad news is that there is this deluge of data, but it’s also good news, because more data means more opportunity for analysis, a better ability to predict and determine best practices, and also provide overall lower costs with better patient care.
We, like others, put a great deal of effort into describing the problems, but figuring out how to bring IT technologies to bear on business problems.
So it seems like the stakes are rather high here to get this right, to not just crumble under a volume or an avalanche of data, but to master it, because it's perhaps the future. The solution is somewhere in there, too.
Lee: No question about it. At The Open Group, our focus is on solutions. We, like others, put a great deal of effort into describing the problems, but figuring out how to bring IT technologies to bear on business problems, how to encourage different parts of organizations to speak to one another and across organizations to speak the same language, and to operate using common standards and language. That’s really what we're all about.
And it is, in a large sense, part of the process of helping to bring healthcare into the 21st Century. A number of industries are a couple of decades ahead of healthcare in the way they use large datasets -- big data, some people refer to it as. I'm talking about companies like big department stores and large online retailers. They really have stepped up to the plate and are using that deluge of data in ways that are very beneficial to them -- and healthcare can do the same. We're just not quite at the same level of evolution.
Gardner: And to your point, the stakes are so much higher. Retail is, of course, a big deal in the economy, but as you pointed out, healthcare is such a much larger segment. So just making modest improvements in communication, collaboration, or data analysis can reap huge rewards.
Lee: Absolutely true. There is the cost side of things, but there is also the quality side. So there are many ways in which healthcare can improve through standardization and coordinated development, using modern technology that cannot just reduce cost, but improve quality at the same time.
Gardner: I'd like to get into a few of the hotter trends. But before we do, it seems that The Open Group has recognized the importance here by devoting the entire second day of their conference in Boston, that will be on July 22, to healthcare.
Maybe you could provide us a brief overview of what participants, and even those who come in online and view recorded sessions of the conference at http://new.livestream.com/opengroup should expect? What’s going to go on July 22?
Lee: We have a packed day. We're very excited to have Dr. Joe Kvedar, a physician at Partners HealthCare and Founding Director of the Center for Connected Health, as our first plenary speaker. The title of his presentation is “Making Health Additive.”
It will become an area where standards development and The Open Group can be very helpful.
Dr. Kvedar is a widely respected expert on mobile health, which is currently the Healthcare Forum’s top work priority. As mobile medical devices become ever more available and diversified, they will enable consumers to know more about their own health and wellness.
A great deal of data of potentially useful health data will be generated. How this information can be used -- not just by consumers but also by the healthcare establishment that takes care of them as patients -- will become a question of increasing importance. It will become an area where standards development and The Open Group can be very helpful.
Our second plenary speaker, Proteus Duxbury, Chief Technology Officer at Connect for Health Colorado, will discuss a major feature of the Affordable Care Act — the health insurance exchanges -- which are designed to bring health insurance to tens of millions of people who previous did not have access to it.
He is going to talk about how enterprise architecture -- which is really about getting to solutions by helping the IT folks talk to the business folks and vice versa -- has helped the State of Colorado develop their health insurance exchange.
After the plenaries, we will break up into three tracks, one of which is healthcare-focused. In this track there will be three presentations, all of which discuss how enterprise architecture and the approach to Boundaryless Information Flow can help healthcare and healthcare decision-makers become more effective and efficient.
One presentation will focus on the transformation of care delivery at the Visiting Nurse Service of New York. Another will address stewarding healthcare transformation using enterprise architecture, focusing on one of our platinum members, Oracle, and a company called Intelligent Medical Objects, and how they're working together in a productive way, bringing IT and healthcare decision-making together.
Then, the final presentation in this track will focus on the development of an enterprise architecture-based solution at an insurance company. The payers, or the insurers -- the big companies that are responsible for paying bills and collecting premiums -- have a very important role in the healthcare system that extends beyond administration of benefits. Yet, payers are not always recognized for their key responsibilities and capabilities in the area of clinical improvements and cost improvements.
With the increase in payer data brought on in large part by the adoption of a new coding system -- the ICD-10 -- which will come online this year, there will be a huge amount of additional data, including clinical data, that become available. At The Open Group, we consider payers -- health insurance companies (some of which are integrated with providers) -- as very important stakeholders in the big picture.
In the afternoon, we're going to switch gears a bit and have a speaker talk about the challenges, the barriers, the “pain points” in introducing new technology into the healthcare systems. The focus will return to remote or mobile medical devices and the predictable but challenging barriers to getting newly generated health information to flow to doctors’ offices and into patients records, electronic health records, and hospitals' data-keeping and data-sharing systems.
Payers are not always recognized for their key responsibilities and capabilities in the area of clinical improvements and cost improvements.
We'll have a panel of experts that responds to these pain points, these challenges, and then we'll draw heavily from the audience, who we believe will be very, very helpful, because they bring a great deal of expertise in guiding us in our work. So we're very much looking forward to the afternoon as well.
Gardner: I'd also like to remind our readers and listeners that they can take part in this by attending the conference, and there is information about that at the opengroup.org website.
It's really interesting. A couple of these different plenaries and discussions in the afternoon come back to this user-generated data. Jason, we really seem to be on the cusp of a whole new level of information that people will be able to develop from themselves through their lifestyle, new devices that are connected.
We hear from folks like Apple, Samsung, Google, and Microsoft. They're all pulling together information and making it easier for people to not only monitor their exercise, but their diet, and maybe even start to use sensors to keep track of blood sugar levels, for example.
In fact, a new Flurry Analytics survey showed 62 percent increase in the use of health and fitness application over the last six months on the popular mobile devices. This compares to a 33 percent increase in other applications in general. So there's an 87 percent faster uptick in the use of health and fitness applications.
Tell me a little bit how you see this factoring in. Is this a mixed blessing? Will so much data generated from people in addition to the electronic medical records, for example, be a bad thing? Is this going to be a garbage in, garbage out, or is this something that could potentially be a game changer in terms of how people react to their own data -- and then bring more data into the interactions they have with healthcare providers?
Challenge to predict
Lee: It's always a challenge to predict what the market is going to do, but I think that’s a remarkable statistic that you cited. My prediction is that the increased volume of person-generated data from mobile health devices is going to be a game changer. This view also reflects how the Healthcare Forum members (which includes members from Capgemini, Philips, IBM, Oracle and HP) view the future.
The commercial demand for mobile medical devices, things that can be worn, embedded, or swallowed, as in pills, as you mentioned, is growing ever more. The software and the applications that will be developed to be used with the devices is going to grow by leaps and bounds.
As you say, there are big players getting involved. Already some of the pedometer-type devices that measure the number of steps taken in a day have captured the interest of many, many people. Even David Sedaris, serious guy that he is, was writing about it recently in The New Yorker.
What we will find is that many of the health indicators that we used to have to go to the doctor or nurse or lab to get information on will become available to us through these remote devices.
There are already problems around interoperability and connectivity of information in the healthcare establishment as it is now.
There will be a question of course as to reliability and validity of the information, to your point about garbage in, garbage out, but I think standards development will help here This, again, is where The Open Group comes in. We might also see the FDA exercising its role in ensuring safety here, as well as other organizations, in determining which devices are reliable.
The Open Group is working in the area of mobile data and information systems that are developed around them, and their ability to (a) talk to one another, and (b) talk to the data devices/infrastructure used in doctors’ offices and in hospitals. This is called interoperability and it's certainly lacking in the country.
There are already problems around interoperability and connectivity of information in the healthcare establishment as it is now. When patients and consumers start collecting their own data, and the patient is put at the center of the nexus of healthcare, then the question becomes how does that information that patients collect get back to the doctor/clinician in ways in which the data can be trusted and where the data are helpful?
After all, if a patient is wearing a medical device, there is the opportunity to collect data, about blood-sugar level let's say, throughout the day. And this is really taking healthcare outside of the four walls of the clinic and bringing information to bear that can be very, very useful to clinicians and beneficial to patients.
In short, the rapid market dynamic in mobile medical devices and in the software and hardware that facilitates interoperability begs for standards-based solutions that reduce costs and improve quality, and all of which puts the patient at the center. This is The Open Group’s Healthcare Forum’s sweet spot.
Gardner: It seems to me a real potential game changer as well, and that something like Boundaryless Information Flow and standards will play an essential role in. Because one of the big question marks with many of the ailments in a modern society has to do with lifestyle and behavior.
So often, the providers of the care only really have the patient’s responses to questions, but imagine having a trove of data at their disposal, a 360-degree view of the patient to then further the cause of understanding what's really going on, on a day-to-day basis.
But then, it's also having a two-way street, being able to deliver perhaps in an automated fashion reinforcements and incentives, information back to the patient in real-time about behavior and lifestyles. So it strikes me as something quite promising, and I look forward to hearing more about it at the Boston conference.
Any other thoughts on this issue about patient flow of data, not just among and between providers and payers, for example, or providers in an ecosystem of care, but with the patient as the center of it all, as you said?
Lee: As more mobile medical devices come to the market, we'll find that consumers own multiple types of devices at least some of which collect multiple types of data. So even for the patient, being at the center of their own healthcare information collection, there can be barriers to having one device talk to the other. If a patient wants to keep their own personal health record, there may be difficulties in bringing all that information into one place.
There are issues, around security in particular, where healthcare will be at the leading edge.
So the interoperability issue, the need for standards, guidelines, and voluntary consensus among stakeholders about how information is represented becomes an issue, not just between patients and their providers, but for individual consumers as well.
Gardner: And also the cloud providers. There will be a variety of large organizations with cloud-modeled services, and they are going to need to be, in some fashion, brought together, so that a complete 360-degree view of the patient is available when needed. It's going to be an interesting time.
Of course, we've also looked at many other industries and tried to have a cloud synergy, a cloud-of-clouds approach to data and also the transaction. So it’s interesting how what's going on in multiple industries is common, but it strikes me that, again, the scale and the impact of the healthcare industry makes it a leader now, and perhaps a driver for some of these long overdue structured and standardized activities.
Lee: It could become a leader. There is no question about it. Moreover, there is a lot healthcare can learn from other companies, from mistakes that other companies have made, from lessons they have learned, from best practices they have developed (both on the content and process side). And there are issues, around security in particular, where healthcare will be at the leading edge in trying to figure out how much is enough, how much is too much, and what kinds of solutions work.
There's a great future ahead here. It's not going to be without bumps in the road, but organizations like The Open Group are designed and experienced to help multiple stakeholders come together and have the conversations that they need to have in order to push forward and solve some of these problems.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: The Open Group.
You may also be interested in:
The Open Group
The Open Group Conference
Posted By Dana L Gardner,
Monday, July 14, 2014
| Comments (0)
When Swedish communications services provider TDC needed network infrastructure improvements from their disparate networks across several Nordic countries, they needed both simplicity in execution and agility in performance.
Our next innovation case study interview therefore highlights how TDC in Stockholm found ways to better determine root causes to any network disruption, and conduct deep inspection of the traffic to best manage their service-level agreements (SLAs).
BriefingsDirect had an opportunity to learn first-hand how over 50,000 devices can be monitored and managed across a state-of-the-art network when we interviewed Lars Niklasson, the Senior Consultant at TDC. The discussion, at the HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: You have a number of main businesses in your organization. There’s TDC Solutions and mobile. There’s even television and some other hosting. Explain for us how large your organization is.
Niklasson: TDC is an operator in the Nordic region, where we have a network covering Norway, Sweden, Finland, and Denmark. In Sweden, we’re also an integrator and have a quite big consultant role in Sweden. In Sweden we’re around 800 people, and the whole TDC group is almost 10,000 people.
Gardner: So it’s obviously a very significant network to support this business and deliver the telecommunication services. Maybe you could define your network for us.
Niklasson: It's quite big, over 50,000 devices, and everything is monitored of course. It’s a state-of-the-art network.
Gardner: When you have so many devices to track, so many types of layers of activity and levels of network operations, how do you approach keeping track of that and making sure that you’re not only performing well, but performing efficiently?
Niklasson: Many years ago, we implemented HP Network Node Manager (NNM) and we have several network operating centers in all countries using NNM. When HP released different smart plug-ins, we started to implement those too for the different areas that they support, such as quality assurance, traffic, and so on.
Gardner: So you’ve been using HP for your network management and HP Network Management Center for some time, and it has of course evolved over the years. What are some of the chief attributes that you like or requirements that you have for network operations, and why has the HP product been so strong for you?
Quick and easy
Niklasson: One thing is that it has to be quick and easy to manage. We have lots of changes all the time, especially in Sweden, when a customer comes. And in Sweden, we’re monitoring end customers’ networks.
It's also very important to be able to integrate it with the other systems that we have. So we can, for example, tell which service-level agreement (SLA) a particular device has and things like that. NNM makes this quite efficient.
Gardner: One of the things that I’ve heard people struggle with is the amount of data that’s generated from networks that then they need to be able to sift through and discover anomalies. Is there something about visualization or other ways of digesting so much data that appeals to you?
Niklasson: NNM is quite good at finding the root cause. You don’t get very many incidents when something happens. If I look back at other products and older versions, there were lots and lots of incidents and alarms. Now, I find it quite easy to manage and configure NNM so it's monitoring the correct things and listening to the correct traps and so on.
Gardner: TDC uses network management capabilities and also sells it. They also provide it with their telecom services. How have you experienced the use in the field? Do any of your customers also manage their own networks and how has this been for your consumers of network services?
Niklasson: We’re also an HP partner in selling NNM to end customers. Part of my work is helping customers implement this in their own environment. Sometimes a customer doesn’t want to do that. They buy the service from us, and we monitor the network. It’s for different reasons. One could be security, and they don’t allow us to access the network remotely. They prefer to have it in-house, and I help them with these projects.
Now, I find it quite easy to manage and configure NNM so it's monitoring the correct things and listening to the correct traps.
Gardner: Lars, looking to the future, are there any particular types of technology improvements that you would like to see or have you heard about some of the roadmaps that HP has for the whole Network Management Center Suite? What interests you in terms of what's next?
Niklasson: I would say two things. One is the application visibility in the network, where we can have some of that with traffic that’s cleaner, but it's still NetFlow-based. So I’m interested in seeing more deep inspection of the traffic and also more virtualization of the virtual environments that we have.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.
You may also be interested in:
Network node management