Monday, April 22, 2013

Service Virtualization Brings Speed Benefit and Lower Costs to TTNET Applications Testing Unit

Transcript of a BriefingsDirect podcast on how Türk Telekom subsidiary TTNET has leveraged Service Virtualization to significantly improve productivity.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Dana Gardner: Hello, and welcome to the next edition of the HP Discover Performance Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your moderator for this ongoing discussion of IT innovation and transformation.

Once again we're focusing on how software improvements and advanced HP Service Virtualization (SV) solutions are enabling IT leaders to deliver better experiences and payoffs for businesses and end-users alike.

Today we’re going to learn about how TTNET, the largest internet service provider in Turkey, with six million subscribers, has significantly improved on applications deployment, while cutting costs and time to delivery.

With that, let's join our guest, Hasan Yükselten, Test and Release Manager at TTNET, which is a subsidiary of Türk Telekom, and they're based in Istanbul. Welcome to the show, Hasan.

Hasan Yükselten: Thank you.

Gardner: Before we get into this discussion of how you’ve used SV in your testing, what was the situation there before you became more automated and before you started to use more software tools? What was the process before that?

Yükselten: Before SV, we had to use the other party’s test infrastructures in our test cases. We're the leading ISP company in Turkey. We deploy more than 200 applications per year and we have to provide better and faster services to our customers every week and every month.

We mostly had problems on issues such as the accessibility, authorization, downtime, and private data for reaching the other third-party’s infrastructures. So, we needed virtualization on our test systems and we needed automation for getting fast deployment to make the release time shorter for greater virtualization. And of course, we needed to reduce our cost. So, we decided to solve the problems of the company by implementing SV.

Gardner: What did you do to begin this process of getting closer to a faster and automated approach? Did you do away with scripts? Did you replace them? How did you move from where you were to where you wanted to be?

Yükselten: Before SV, we couldn’t do automation, since the other parties are in discrete locations and it was difficult to reach the other systems. We could automate functional test cases, but for end-to-end test cases, it was impossible to do automation.

First, we implemented SV for virtualizing the other systems, and we put SV between our infrastructure and the third-party infrastructure. We learned the requests and responses and then could use SV instead of the other party infrastructure.

Automation tools

After this, we could also use automation tools. We managed to use automation tools via integrating Unified Functional Testing (UFT) and SV tools, and now we can run automation test cases and end-to-end test cases on SV.

Gardner: Was there anything about this that allowed you to have better collaboration between the developers and the testers. I know that in many companies, this is a linear progression, where they develop and then test, and it can be something that there's not a lot of communication on. Was there anything about what you've done that's improved how developers and testers have been able to coordinate and collaborate?

Yükselten: We started to use SV in our test systems first. When we saw the success, we decided to implement SV for the development systems also. But, we've just implemented SV in the development site, so I can't give results yet. We have to wait and see, for maybe one month, before I can reply to this question.

Gardner: Tell me about the types of applications that you’re using here as a large internet service provider. Are these internal apps for your organization? Are they facing out to the customers for billing, service procurement, and provisioning? Give me a sense of the type of applications we’re talking about?

Yükselten: We are mostly working on customer relationship management (CRM) applications. We deploy more than 200 applications per year and we have more than six million customers. We have to offer new campaigns and make some transformations for new customers, etc.

We have to save all the informations, and while saving the information, we also interact the other systems, for example the National Identity System, through telecom systems, public switched telephone network (PSTN) systems.

We have to ask informations and we need make some requests to the other systems. So, we need to use all the other systems in our CRM systems. And we also have internet protocol television (IPTV) products, value added services products, and the company products. But basically, we’re using CRM systems for our development and for our systems.

Gardner: So clearly, these are mission-critical applications essential to your business, your growth, and your ability to compete in your market.

Yükselten: If there is a mistake, a big error in our system, the next day, we cannot sell anything. We cannot do anything all over Turkey.

Gardner: Let's talk a bit about the adoption of your SV. Tell me about some of the products you’re using and some of the technologies, and then we’ll get into what this has done for you. But, let's talk about what you actually have in place so far.

Yükselten: Actually, it was very easy to adopt these products into our system, because including proof of concept (PoC), we could use this tool in six weeks. We spent first two weeks for the PoC and after four weeks, we managed to use the tool.

Easy to implement

For the first six weeks, we could use SV for 45 percent of end-to-end test cases. In 10 weeks, 95 percent of our test cases could be run on SV. It was very easy to implement. After that, we also implemented two other SVs in our other systems. So, we're now using three SV systems. One is for development, one is just for the campaigns, and one is for the E2E tests.

Gardner: Tell me how your relationship with HP Software has been. How has it been working with HP Software to attain this so rapidly?

Yükselten: HP Software helped us so much, especially R&D. HP Turkey helped us, because we were also using application lifecycle management (ALM) tools before SV. We were using QTP LoadRunners, QC, etc., so we had a good relation with HP Software.

Since SV is a new tool, we needed a lot of customization for our needs, and HP Software was always with us. They were very quick to answer our questions and to return for our development needs. We managed to use the tool in six weeks, because of HP’s Rapid Solutions.

Gardner: Let’s talk a little bit about the scale here. My understanding is that you have something on the order of 150 services. You use 50 regularly, but you're able to then spin up and use others on a more ad-hoc basis. Why is it important for you to have that kind of flexibility and agility?
We virtualized all the web services, but we use just what we need in our test cases.

Yükselten: As you say, we virtualized more than 150 services, but we use 48 of them actively. We use these portions of the service because we virtualized our third-party infrastructures for our needs. For example, we virtualized all the other CRM systems, but we don’t need all of them. In gateway remote, you can simulate all the other web services totally. So, we virtualized all the web services, but we use just what we need in our test cases.

Gardner: And this must be a major basis for your savings when you only use what you need. The utilization rate goes up, but your costs can go down. Tell us a little bit about how this has been an investment that’s paid back for you.

Yükselten: In three months we got the investment back actually, maybe shorter than three months. It could have been two and half months. For example, for the campaign test cases, we gained 100 percent of efficiency. Before HP, we could run just seven campaigns in a month, but after HP, we managed to run 14 campaigns in a month.

We gained 100 percent efficiency and three man-months in this way, because three test engineers were working on campaigns like this. For another example, last month we got the metrics and we saw that we had a total blockage for seven days, so that was 21 working days for March. We saved 33 percent of our manpower with SV and there are 20 test engineers working on it. We gained 140 man-months last month.

For our basic test scenarios, we could run all test cases in 112 hours. After SV, we managed to run it in 54 hours. So we gained 100 percent efficiency in that area and also managed to do automation for the campaign test cases. We managed to automate 52 percent of our campaign test cases, and this meant a very big efficiency for us. Totally, we saved more than $50,000 per month.

Broader applications

Gardner: That’s very impressive and that was in a relatively short period of time. Do you expect now to be able to take this to a larger set of applications, maybe beyond your organization, more generally across Türk Telekom?

Yükselten: Yes. Türk Telekom licenses these tools and started to use these tools in their test service to get this efficiency for those systems. We have a branch company called AVEA, and they also want to use this tool. After our getting this efficiency, many companies want to use this virtualization. Eight companies visited us in Turkey to get our experiences on this tool. Many companies want this and want to use this tool in their test systems.

Gardner: Do you have any advice for other organizations like those you've been describing, now that you have done this? Any recommendations on what you would advise others that might help them improve on how they do it?

Yükselten: Companies must know their needs first. For example, in our company, we have three blockage systems for third parties and the other systems don't change everyday. So it was easy to implement SV in our systems and virtualize the other systems. We don’t need to do virtualization day by day, because the other systems don't change every day.

Once a month, we consult and change our systems, update our web services on SV, and this is enough for us. But if the other party's systems changes day by day or frequently, it may be difficult to do virtualization every day.
Companies should think automation besides virtualization. This is also a very efficient aspect, so this must be also considered while making virtualization.

This is an important point. Companies should think automation besides virtualization. This is also a very efficient aspect, so this must be also considered while making virtualization.

Gardner: As to where you go next, do you have any thoughts about moving towards UFT, using cloud deployment models more? Where can you go more to attain more benefits and efficiencies?

Yükselten: We started to use UFT with integrating SV. As I told you, we managed to automate 52 percent of our campaign test cases so far. So we would like to go on and try to automate more test cases, our end-to-end test cases, the basic scenarios, and other systems.

Our first goal is doing more automation with SV and UFT and the other is using SV in development sites. We plan to find early defects in development sites and getting more quality products into the test.

Rapid deployment

Of course, in this way, we get rapid deployment and we make shorter release times because the product will have more quality. Using performance test and SV also helps us on performance. We use HP LoadRunner for our performance test cases. We have three goals now, and the last one is using SV with integrating LoadRunner.

Gardner: Well, it's really impressive. It sounds as if you put in place the technologies that will allow you to move very rapidly, to even a larger payback. So congratulations on that.

Well, Hasan, I'm afraid we’ll have to leave it there; we've run out of time. We’ve learned how TTNET the largest internet service provider in Turkey has significantly improved on mission-critical application deployment, while also cutting costs and reducing that important time to delivery.
We plan to find early defects in development sites and getting more quality products into the test.

I like to thank first our supporter for this series, HP Software, and remind our audience to carry on the dialogue on the Discover Performance Group on LinkedIn. Of course, I'd like to extend a huge thank you to our special guest Hasan Yükselten. He is the Test and Release Manager at TTNET, which is a subsidiary of Türk Telekom in Istanbul. Thanks so much. Hasan.

Yükselten: You're welcome, and thank you for your time too.

Gardner: And you can gain more insights and information on the best of IT Performance Management at And you can always access this and other episodes in our HP Discover performance podcast series on iTunes under BriefingsDirect.

I'm Dana Gardner, Principal Analyst at Interarbor Solutions, and I've been your host and moderator for this discussion part of our ongoing series on IT Innovation. Thanks again for listening, and come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Transcript of a BriefingsDirect podcast on how Türk Telekom subsidiary TTNET has leveraged Service Virtualization to significantly improve productivity. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.

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Tuesday, April 09, 2013

Agnostic Tool Chain Approach Proves Key to Fixing Broken State of Data and Information Management

Transcript of a BriefingsDirect podcast on how Dell Software is working with companies to manage internal and external data in all its forms.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Dell Software.

Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions, and you're listening to BriefingsDirect.

Today, we present a sponsored podcast discussion on better understanding the biggest challenges businesses need to solve when it comes to data and information management.

We'll examine how a data dichotomy has changed the face of information management. This dichotomy means that organizations, both large and small, not only need to manage all of their internal data that provides intelligence about their businesses, but they also need to manage the reams of increasingly external big data that enables them to discover new customers and drive new revenue.

Lastly, our discussion will focus on bringing new levels of automation and precision to the task of solving data complexity by embracing an agnostic, end-to-end tool chain approach to overall data and information management.

Here now to share his insights on where the information management market has been and where it's going, we're joined by Matt Wolken, Executive Director and General Manager for Information Management at Dell Software. Welcome, Matt. [Disclosure: Dell Software is a sponsor of BriefingsDirect podcasts.]

Matt Wolken: Dana, thanks for having me. I appreciate it.

Gardner: From your perspective, what are the biggest challenges that businesses need to solve now when it comes to data and information management? What are the big hurdles that they're facing?

Wolken: It's an interesting question. When we look at customers today, we're noticing how their environments have significantly changed from maybe 10 or 15 years ago.

About 10 or 15 years ago, the problem was that data was sitting in individual databases around the company, either in a database on the backside of an application, the customer relationship management (CRM) application, the enterprise resource planning (ERP) application, or in data marts around the company. The challenge was how to bring all this together to create a single cohesive view of the company?

That was yesterday's problem, and the answer was technology. The technology was a single, large data warehouse. All of the data was moved to it, and you then queried that larger data warehouse where all of the data was for a complete answer about your company.

What we're seeing now is that there are many complexities that have been added to that situation over time. We have different vendor silos with different technologies in them. We have different data types, as the technology industry overall has learned to capture new and different types of data -- textual data, semi-structured data, and unstructured data -- all in addition to the already existing relational data. Now, you have this proliferation of other data types and therefore other databases.

The other thing that we notice is that a lot of data isn't on premise any more. It's not even owned by the company. It's at your software-as-a-service (SaaS) provider for CRM, your SaaS provider for ERP, or your travel or human resources (HR) provider. So data again becomes siloed, not only by vendor and data type, but also by location. This is the complexity of today, as we notice it.

Cohesive view

All of this data is spread about, and the challenge becomes how do you understand and otherwise consume that data or create a cohesive view of your company? Then there is still the additional social data in the form of Twitter or Facebook information that you wouldn't have had in prior years. And it's that environment, and the complexity that comes with it, that we really would like to help customers solve.

Gardner: When it comes to this so-called data dichotomy, is it oversimplified to say it's internal and external, or is there perhaps a better way to categorize these larger sets that organizations need to deal with?

Wolken: There's been a critical change in the way companies go about using data, and you brought it out a little bit in the intro. There are some people who want to use data for an outcome-based result. This is generally what I would call the line-of-business concern, where the challenge with data is how do I derive more revenue out of the data source that I am looking at?

What's the business benefit for me examining this data? Is there a new segment I can codify and therefore market to? Is there a campaign that's currently running that is not getting a good response rate, and if so, do I want to switch to another campaign or otherwise improve it midstream to drive more real value in terms of revenue to the company?

That’s the more modern aspect of it. All of the prior activities inside business intelligence (BI) -- let’s flip those words around and say intelligence about the business -- was really internally focused. How do I get sanctioned data off of approved systems to understand the official company point of view in terms of operations?
How do I go out and use data to derive a better outcome for my business?

That second goal is not a bad goal. That's still a goal that's needed, and IT is still required to create that sanctioned data, that master data, and the approved, official sources of data. But there is this other piece of data, this other outcome that's being warranted by the line of business, which is, how do I go out and use data to derive a better outcome for my business? That's more operationally revenue-oriented, whereas the internal operations are around cost orientation and operations.

So where you get executive dashboards for internal consumption off of BI or intelligence for the business, the business units themselves are about visualization, exploration, and understanding and driving new insights.

It's a change in both focus and direction. It sometimes ends up in a conflict between the groups, but it doesn't really have to be that way. At least, we don't think it does. That's something that we try to help people through. How do you get the sanctioned data you need, but also bring in this third-party data and unstructured data and add nuance to what you are seeing about your company.

Gardner: Just as 10 or 15 years ago the problem to solve was the silos of data within the organization, is there any way in traditional technology offerings that allows this dichotomy to be joined now, or do we need a different way in which to create insights, using both that internal and external type of information?

Wolken: There are certainly ways to get to anything. But if you're still amending program after program or technology after technology, you end up with something less than the best path, and there might be new and better ways of doing things.

Agnostic tool chain

There are lots of ways to take a data warehouse forward in today's environment, manipulate other forms of data so it can enter a data warehouse or relational data warehouse, and/or go the other way and put everything into an unstructured environment, but there's also another way to approach things, and that’s with an agnostic tool chain.

Tools have existed in the traditional sense for a long time. Generally, a tool is utilized to hide complexity and all of the issues underneath the tool itself. The tool has intelligence to comprehend all of the challenges below it, but it really abstracts that from the user.

We think that instead of buying three or four database types, a structured database, something that can handle text, a solution that handles semi-structured or structured, or even a high performance analytical engine for that matter, what if the tool chain abstracts much of that complexity? This means the tools that you use every day can comprehend any database type, data structure type, or any vendor changes or nuances between platforms.

That's the strategy we’re pursuing at Dell. We’re defining a set of tools, not the underlying technologies or proliferation of technologies, but the tools themselves, so that the day-to-day operations are hidden from the complexity of those underlying sources of vendor, data type, and location.
We’re looking to enable customers to leverage those technologies for a smoother, more efficient, and more effective operation.

That's how we really came at it -- from a tool-chain perspective, as opposed to deploying additional technologies. We’re looking to enable customers to leverage those technologies for a smoother, more efficient, and more effective operation.

Gardner: Am I right then in understanding that this is at more of a meta level, above the underlying technologies, but that, in a sense, makes the whole greater than the sum of the parts of those technologies?

Wolken: That’s a fair way of looking at it. Let's just take data integration as a point. I can sometimes go after certain siloed data integration products. I can go after a data product that goes after cloud resources. I can get a data product that only goes after relational. I can get another data product to extract or load into Hive or Hadoop. But what if I had one that could do all of that? Rather than buying separate ones for the separate use cases, what if you just had one?

Metadata, in one way, is a descriptor language, if I use it in that sense. Can I otherwise just see and describe everything below it, or can I actually manipulate it as well? So in that sense, it's a real tool to actually manipulate and cause the effective change in the environment.

Gardner: I'd like to go into more of the challenges, but before we do that, what are the stakes here? What do you get if you do this right? If you can, in fact, manage across various technology types and formats, across relational and unstructured data, internal and external data sources and providers.

Are we talking iterative change, a step change, or is it something that is a bit larger and that we might have some other examples of companies when they do this well can really demonstrate something perhaps quite unique in terms of a new level of accomplishment?

Institutional knowledge

Wolken: There are a couple of ways we think about it, one of which is institutional knowledge. Previously, if you brought in a new tool into your environment to examine a new database type, you would probably hire a person from the outside, because you needed to find that skill set already in the market in order to make you productive on day one.

Instead of applying somebody who knows the organization, the data, the functions of the business, you would probably hire the new person from the outside. That's generally retooling your organization.

Or, if you switch vendors, that causes a shift as well. One primary vendor stack is probably a knowledge and domain of one of your employees, and if you switch to another vendor stack or require another vendor stack in your environment, you're probably going to have to retool yet again and find new resources. So that's one aspect of human knowledge and intelligence about the business.

There is a value to sharing. It's a lot harder to share across vendor environments and data environments if the tools can't bridge them. In that case, you have to have third-party ways to bridge those gaps between the tools. If you have sharing that occurs natively in the tool, then you don't have to cross that bridge, you don't have the delay, and you don't have the complexity to get there.

So there is a methodology within the way you run the environment and the way employees collaborate that is also accelerated. We also think that training is something that can benefit from this agnostic approach.
You're reaching across domains and you're not as effective as you would be if you could do that all with one tool chain.

But also, generically, if you're using the same tools, then things like master data management (MDM) challenges become more comprehensive, if the tool chain understands where that MDM is coming from, and so on.

You also codify how and where resources are shared. So if you have a person who has to provision data for an analyst, and they are using one tool to reach to relational data, another to reach into another type of data, or a third-party tool to reach into properties and SaaS environments, then you have an ineffective process.

You're reaching across domains and you're not as effective as you would be if you could do that all with one tool chain.

So those are some of the high-level ideas. That's why we think there's value there. If you go back to what would have existed maybe 10 or 15 years ago, you had one set of staff who used one set of tools to go back against all relational data. It was a construct that worked well then. We just think it needs to be updated to account for the variance within the nuances that have come to the fore as the technology has progressed and brought about new types of technology and databases.

Gardner: As for business benefits, we hear a lot about businesses being increasingly data driven and information driven, rather than a hunch, intuition, or gut instinct. Also, there's an ability to find new customers in much more cost-effective ways, taking advantage of the social networks, for example. So when you do this well, what are typically some of the business paybacks, and do they outweigh the cost more than previous investments in data would have?

Investment cycles

Wolken: It all depends on how you go about it. There are lots of stories about people who go on these long investment cycles into some massive information management strategy change without feeling like they got anything out of it, or at least were productive or paid back the fee.

There's a different strategy that we think can be more effective for organizations, which is to pursue smaller, bite-size chunks of objective action that you know will deliver some concrete benefit to the company. So rather than doing large schemes, start with smaller projects and pursue them one at a time incrementally -- projects that last a week and then you have 52 projects that you know derive a certain value in a given time period.

Other things we encourage organizations to do deal directly with how you can use data to increase competitiveness. For starters, can you see nuances in the data? Is there a tool that gives you the capability to see something you couldn't see before? So that's more of an analytical or discovery capability.

There's also a capability to just manage a given data type. If I can see the data, I can take advantage of it. If I can operate that way, I can take advantage of it.

Another thing to think about is what I would call a feedback mechanism, or the time or duration of observation to action. In this case, I'll talk about social sentiment for a moment. If you can create systems that can listen to how your brand is being talked about, how your product is being talked about in the environment of social commentary, then the feedback that you're getting can occur in real time, as the comments are being posted.
There's a feedback mechanism increase that also can then benefit from handling data in a modern way or using more modern resources to get that feedback.

Now, you might think you'll get that anyway. I would have gotten a letter from a customer two weeks from now in the postal system that provided me that same feedback. That’s true, but sometimes that two weeks can be a real benefit.

Imagine a marketing campaign that's currently running in the East, with a companion program in the West that's slightly different. Let's say it's a two-week program. It would be nice if, during the first week, you could be listening to social media and find out that the campaign in the West is not performing as well as the one in the East, and then change your investment thesis around the program -- cancel the one that's not performing well and double down on the one that's performing well.

There's a feedback mechanism increase that also can then benefit from handling data in a modern way or using more modern resources to get that feedback. When I say modern resources, generally that's pointing towards unstructured data types or textual data types. Again, if you can comprehend and understand those within your overall information management status, you now also have a feedback mechanism that should increase your responsiveness and therefore make your business more competitive as well.

Gardner: I think the whole concept of the immediacy to feedback, applied across various aspects of business -- planning, production, marketing, go-to market, research, and to uses -- then that's been the Holy Grail of business for a long time. It's just been very difficult to do. Now, we seem to be getting closer to the ability to do it at scale and at reasonable cost. So, these are very interesting times.

Now, given that these payoffs could be so substantial, what's preventing people from getting to this Holy Grail? What's between them and the realization?

It's the complexity

Wolken: I think it's complexity of the environment. If you only had relational systems inside your company previously, now you have to go out and understand all of the various systems you can buy, qualify those systems, get pure feedback, have some proofs of concept (POCs) in development, come in and set all these systems up, and that just takes a little bit of time. So the more complexity you invite into your environment, the more challenges you have to deal with.

After that, you have to operate and run it every day. That's the part where we think the tool chain can help. But as far as understanding the environment, having someone who can help you walk through the choices and solutions and come up with one that is best suited to your needs, that’s where we think we can come in as a vendor and add lots of value.

When we go in as a vendor, we look at the customer environment as it was, compare that to what it is today, and work to figure out where the best areas of collaboration can be, where tools can add the most value, and then figure out how and where can we add the most benefit to the user.

What systems are effective? What systems collaborate well? That's something that we have tried to emulate, at least in the tool space. How do you get to an answer? How do you drive there? Those are the questions we’re focused on helping customers answers.

For example, if you've never had a data warehouse before, and you are in that stage, then creating your first one is kind of daunting, both from a price perspective, as well as complexity perspective or know-how. The same thing can occur on really any aspect -- textual data, unstructured data, or social sentiment.
Those are some of the major challenges -- complexity, cost, knowledge, and know-how.

Each one of those can appear daunting if you don't have a skill set, or don't have somebody walking you through that process who has done it before. Otherwise, it's trying to put your hands on every bit of data and consume what you can and learning through that process.

Those are some of the things that are really challenging, especially if you're a smaller firm that has a limited number of staff and there's this new demand from the line of business, because they want to go off in a different direction and have more understanding that they couldn't get out of existing systems.

How do you go out and attain that knowledge without duplicating the team, finding new vendor tools, and adding complexity to your environment, maybe even adding additional data sources, and therefore more data-storage requirements. Those are some of the major challenges -- complexity, cost, knowledge, and know-how.

Gardner: It's interesting that you mentioned mid-market organizations. Some of these infrastructure and data investments were perhaps completely out of their reach until a new way to approach the problems through the tool chain, through cloud, through other services and on-demand offerings.

What is it now about the new approach to these problems that you think allows the fruits of this to be distributed more down market? Why are mid-market organizations now more able to avail themselves of some of these values and benefits than in the past?

Mid-market skills

Wolken: As the products are well-known, there is more trained staff that understands the more common technologies. There are more codified ways of doing things that a business can take advantage of, because there's a large skill set, and most of the employees may already have that skill set as you bring them into the company.

There are also some advantages just in the way technologies have advanced over the years. Storage used to be very expensive, and then it got a little cheaper. Then solid-state drives (SSD) came along and then that got cheaper as well. There are some price point advantages in the coming years, as well.

Dell overall has maintained the status that we started with when Michael Dell started recreating PCs in his dorm room from standard product components to bring the price down. That model of making technology attainable to larger numbers of people has continued throughout Dell’s history, and we’re continuing it now with our information management software business.

We’re constantly thinking about how we can reduce cost and complexity for our customers. One example would be what we call Quickstart Data Warehouse. It was designed to democratize data to a lower price point, to bring the price and complexity down to a much lower space, so that more people can afford and have their first data warehouse.

We worked with our partner Microsoft, as well as Dell’s own engineering team, and then we qualified the box, the hardware, and the systems to work to the highest peak performance. Then, we scripted an upfront install mechanism that allows the process to be up and running in 45 minutes with little more than directing a couple of IP addresses. You plug the box in, and it comes up in 45 minutes, without you having to have knowledge about how to stand up, integrate, and qualify hardware and software together for an outcome we call a data warehouse.
We're trying to hit all of the steps, and the associated costs -- time and/or personnel costs – and remove them as much as we can.

Another thing we did was include Boomi, which is a connector to automatically go out and connect to the data sources that you have. It's the mechanism by which you bring data into it. And lastly, we included services, in case there were any other questions or problems you had to set it up.

If you have a limited staff, and if you have to go out and qualify new resources and things you don't understand, and then set them up and then actually run them, that’s a major challenge. We're trying to hit all of the steps, and the associated costs -- time and/or personnel costs – and remove them as much as we can.

It's one way vendors like Dell are moving to democratize business intelligence a little further, bring it to a lower price point than customers are accustomed too and making it more available to firms that either didn’t have that luxury of that expertise link sitting around the office, or who found that the price point was a little too high.

Gardner: You mentioned this concept of the tool chain several times. I'd like to hear a bit more about why that approach works, and even more detail about what I understand to be important elements of it -- being agnostic to the data type, holistic management, complete view, and then of course integrate it.

In addition to the package, it sounds from your earlier comments that you want to be able to approach these daunting issues iteratively, so that you can bite off certain chunks. What is it about the tool chain that accomplishes both a comprehensive value, but also allows it to be adopted on a fairly manageable path, rather than all at once?

Wolken: One of the things we find advantageous about entering the market at this point in time is that we're able to look at history, observe how other people have done things over time, and then invest in the market with the realization that maybe something has changed here and maybe a new approach is needed.

Different point of view

Whereas the industry has typically gone down the path of each new technology or advancement of technology requires a new tool, a new product, or a new technology solution, we’ve been able to stand back and see the need for a different approach. We just have a different point of view, which is that an agnostic tool chain can enable organizations to do more.

So when we look at database tools, as an example, we would want a tool that works against all database types, as opposed to one that works against only a single vendor or type of data.

The other thing that we look at is if you walk into an average company today, there are already a lot of things laying around the business. A lot of investment has already been made.

We wanted to be able to snap in and work with all of the existing tools. So, each of the tools that we’ve acquired, or have created inside the company, were made to step into an existing environment, recognize that there were other products already in the environment, and recognize that they probably came from a different vendor or work on a different data type.

That’s core to our strategy. We recognize that people were already facing complexity before we even came into the picture, so we’re focused on figuring out how we snap into what they already have in place, as opposed to a rip-and-replace strategy or a platform strategy that requires all of the components to be replaced or removed in order for the new platform to take its place.
We’ve also assembled a tool chain in which the entirety of the chain delivers value as a whole.

What that means is tools should be agnostic, and they should be able to snap into an environment and work with other tools. Each one of the products in the tool chain we’ve assembled was designed from that point of view.

But beyond that, we’ve also assembled a tool chain in which the entirety of the chain delivers value as a whole. We think that every point where you have agnosticism or every point where you have a tool that can abstract that lower amount of complexity, you have savings.

You have a benefit, whether it’s cost savings, employee productivity, or efficiency, or the ability to keep sanctioned data and a set of tools and systems that comprehend it. The idea being that the entirety of the tool chain provides you with advantages above and beyond what the individual components bring.

Now, we're perfectly happy to help a customer at any point where they have difficultly and any point where our tools can help them, whether it's at the hardware layer, from the traditional Dell way, at the application layer, considering a data warehouse or otherwise, or at the tool layer. But we feel that as more and more of the portfolio – the tool chain – is consumed, more and more efficiency is enabled.

Gardner: It sounds as if rather than look at the ecosystem that’s in place in an organization as a detriment, you're trying to make that into an asset, and then even looking further to new products available to bring that in. So I guess partnering becomes important.

Already-made investment

Wolken: Everything is an already-made investment in the company. If the premise to rip and replace is from the get-go, then you're really removing the institutional knowledge, the training of the staff, and the investment into the product, not to mention maybe the integration work. That's not something we wanted to start out with. We wanted to recognize and leverage what was there and provide value to that already existing environment.

One of the core values that we were looking at from a design point is how do you fit into an environment and how do you add value to it, not how do you cause replacement or destruction of an existing environment in order to provide benefit.

Gardner: We have been talking about the tool chain in terms of its value for analytics and intelligence about the business and bringing in more types of data and information from external sources.

It also sounds to me as if this sets you up for a lifecycle benefits, not just on the business benefits, but also on the IT benefits, for things like a better backup and recovery, a better disaster recovery strategy, perhaps looking towards more storage efficiency. Is there an intramural benefit from the IT side to doing this in the fashion you have been describing as well?

Wolken: We looked at the strategy and said if you manage this as a data lifecycle, and that’s really what we think about it as, then where does data first show up in a company? That’s inside of a database on the backside of an application most likely.
Doing that, you also solve the problem of how to make sure that the data that was provisioned was sanctioned.

And where is it last used inside of a company? That would generally be just before retirement or long-term retention of the data. Then the question becomes how do you manipulate and otherwise utilize the data for the maximum benefit in the middle?

When we looked at that, one of the problems that you uncover is that there's a lot of data being replicated in a lot of places. One of the advantages that we've put together in the tool chain was to use virtualization as a capability, because you know where data came from and you know that it was sanctioned data. There's no reason to replicate that to disk in another location in the company, if you can just reach into that data source and pull that forward for a data analyst to utilize.

You can virtually represent that data to the user, without creating a new repository for that person. So you're saving on storage and replication costs. So if you’re looking for where is there efficiency in the lifecycle of data and how can you can cut some of those costs, that’s something that jumps right out.

Doing that, you also solve the problem of how to make sure that the data that was provisioned was sanctioned. By doing all of these things, by creating a virtual view, then providing that view back to the analyst, you're really solving multiple pieces of the puzzle at the same time. It really enables you to look at it from an information-management point of view.

Gardner: That's interesting, because you can not only get better business outcome benefits and analytics benefits, but you can simplify and reduce your total cost of ownership from the IT perspective. That's kind of another Holy Grail out there, to be able to do more with less.

One of the advantages

Wolken: That's what we think one of the advantages can be, and certainly, as you have the advantage to stand on the shoulders of people who have come before you and look at how the environment’s changed, you can notice some of these real minor changes and bring them forward. That's what we want to do with IT as partners and with the solution that we bring forward.

Gardner: How should enterprises and mid-market firms get started? Are there some proven initiation points, methods, or cultural considerations when one wants to move from that traditional siloed platform and integrate them along the way, an approach more towards this integrated, comprehensive tool-chain approach?

Wolken: There are different ways you can think about it. Generally, most companies aren’t just out there asking how they can get a new tool chain. That's not really the strategy most people are thinking about. What they are asking is how do I get to the next stage of being an intelligent company? How do I improve my maturity in business intelligence? How would I get from Excel spreadsheets without a data warehouse to a data warehouse and centralized intelligence or sanctioned data?

Each one of these challenges come from a point of view of, how do I improve my environment based upon the goals and needs that I am facing? How do I grow up as a company and get to be more of a data-based company?

Somebody else might be faced with more specific challenges, such a line of business is now asking me for Twitter data, and we have no systems or comprehension to understand that. That's really the point where you ask, what's going to be my strategy as I grow and otherwise improve my business intelligence environment, which is morphing every year for most customers.
It's about incremental improvement as well as tangible improvement for each and every step of the information management process.

That's the way that most people would start, with an existing problem and an objective or a goal inside the company. Generically, over time, the approach to answering it has been you buy a new technology from a new vendor who has a new silo, and you create a new data mart or data warehouse. But this is perpetuating the idea that technology will solve the problem. You end up with more technologies, more vendor tools, more staff, and more replicated data. We think this approach has become dated and inefficient.

But if, as an organization, you can comprehend that maybe there is some complexity that can be removed, while you're making an investment, then you free yourself to start thinking about how you can build a new architecture along the way. It's about incremental improvement as well as tangible improvement for each and every step of the information management process.

So rather than asking somebody to re-architect and rip and replace their tool chain or the way they manage the information lifecycle, I would say you sort of lean into it in a way.

If you're really after a performance metric and you feel like there is a performance issue in an environment, at Dell we have a number of resources that actually benchmark and understand the performance and where bottlenecks are in systems.

So we can look at either application performance management issues, where we understand the application layer, or we have a very deep and qualified set of systems around databases and data warehouse performance to understand where bottlenecks are either in SQL language or elsewhere. There are a number of tools that we have to help identify where a bottleneck or issue might be from just a pure performance perspective as well.

Strategic position

Gardner: That might be a really good place to start -- just to learn where your performance issues are and then stake out your strategic position based on a payback for improving on your current infrastructure, but then setting the stage for new capabilities altogether.

Wolken: Sometimes there’s an issue occurring inside the database environment. Sometimes it's at the integration layer, because integration isn’t happening as well as you think. Sometimes it's at the data warehouse layer, because of the way the data model was set up. Whatever the case, we think there is value in understanding the earlier parts of the chain, because if they’re not performing well, the latter parts of the chain can’t perform either.

And so at each step, we've looked at how you ensure the performance of the data. How do you ensure the performance of the integration environment? How do you ensure the performance of the data warehouse as well? We think if each component of the tool chain in working as well as it should be, then that’s when you enable the entirety of your solution implementation to truly deliver value.
At each step, we've looked at how you ensure the performance of the data.

Gardner: Great. I'm afraid we we'll have to leave it there. We're about out of time. You've been listening to a sponsored BriefingsDirect podcast discussion on better understanding the challenges businesses need to solve when it comes to improved data and information management.

And we have seen how organizations, not only need to manage all of their internal data that provides intelligence about the businesses, but also increasingly the reams of external data that enables them to improve on whole new business activities like discovering additional customers and driving new and additional revenue.

And we've learned more about how new levels of automation and precision can be applied to the task of solving data complexity and doing that to a tool chain of agnostic and capability.

I want to thank our guest. We have been here with Matt Wolken, Executive Director and General Manager for Information Management Software at Dell Software. Thanks so much, Matt.

Wolken: Thank you so much as well.

Gardner: This is Dana Gardner, Principal Analyst at Interarbor Solutions. Thanks again to our audience for joining us, and do come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Dell Software.

Transcript of a BriefingsDirect podcast on how Dell Software is working with companies to manage internal and external data in all its forms. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.

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Wednesday, April 03, 2013

On the Road to Sydney: The Open Group Gets Under Enterprise Architecture, Business Architecture and Enterprise Transformation

Transcript of a BriefingsDirect podcast on the role that architects and analysts play in optimizing business capabilities and performance.

Listen to the podcast. Find it on iTunesDownload the transcript. Sponsor: The Open Group.

Dana Gardner: Hello, and welcome to a special BriefingsDirect Thought Leadership interview series, coming to you in conjunction with The Open Group Conference on April 15, in Sydney, Australia.

I'm Dana Gardner, Principal Analyst at Interarbor Solutions, and I'll be your host and moderator throughout these business transformation discussions.

The conference, The Open Group’s first in Australia, will focus on "How Does Enterprise Architecture Transform an Enterprise?" And there will be special attention devoted to how enterprise transformation impacts such vertical industries as finance and defense, as well as exploration, mining, and minerals.

We're here now with two of the main speakers at the conference -- Hugh Evans, the Chief Executive Officer of Enterprise Architects, a specialist enterprise architecture (EA) firm based in Melbourne, Australia; and Craig Martin, Chief Operations Officer and Chief Architect at Enterprise Architects.

As some background, Hugh is both the founder and CEO at Enterprise Architects. His professional experience blends design and business, having started out in traditional architecture, computer games design, and digital media, before moving into enterprise IT and business transformation.

In 1999, Hugh founded the IT Strategy Architecture Forum, which included chief architects from most of the top 20 companies in Australia. He has also helped found the Australian Architecture Body of Knowledge and the London Architecture Leadership Forum in the UK.

Since starting Enterprise Architects in 2002, Hugh has grown the team to more than 100 people, with offices in Australia, the UK, and the U.S.

With a career spanning more than 20 years, Craig has held executive positions in the communications, high tech, media, entertainment, and government markets and has operated as an Enterprise Architect and Chief Consulting Architect for a while.

In 2012, Craig became COO of Enterprise Architects to improve the global scalability of the organization, but he is also a key thought leader for strategy and architecture practices for all their clients and also across the EA field.

Craig has been a strong advocate of finding differentiation in businesses through identifying new mixes of business capabilities in those organizations. He advises that companies that do not optimize how they reassemble their capabilities will struggle, and he also believes that business decision making should be driven by economic lifecycles. [Disclosure: The Open Group is a sponsor of BriefingsDirect podcasts.]

So welcome to you both. How are you doing?

Hugh Evans: Great, Dana. Welcome everyone.

Craig Martin: Thanks very much for having us.

Big-picture perspective

Gardner: I look forward to our talk. Let's look at this first from a big-picture perspective and then drill down into what you are going to get into at the conference in a couple of weeks. What are some of the big problems that businesses are facing, that they need to solve, and that architecture-level solutions can really benefit them. I'll open this up to both Hugh and Craig?

Evans: Thanks very much, Dana. I'll start with the trend in the industry around fast-paced change and disruptive innovation. You'll find that many organizations, many industries, at the moment in the U.S., Australia, and around the world are struggling with the challenges of how to reinvent themselves with an increasing number of interesting and innovative business models coming through.

For many organizations, this means that they need to wrap their arms around an understanding of their current business activities and what options they've got to leverage their strategic advantages.

We're seeing business architecture as a tool for business model innovation, and on the other side, we're also seeing business architecture as a tool that's being used to better manage risk, compliance, security, and new technology trends around things like cloud, big data, and so on.

Martin: Yes, there is a strong drive within the industry to try and reduce complexity. As organizations are growing, the business stakeholders are confronted with a large amount of information, especially within the architecture space. We're seeing that they're struggling with this complexity and have to make accurate and efficient business decisions on all this information.

What we are seeing, and based upon what Hugh has already discussed, is that some of those industry drivers are around disruptive business models. For example, we're seeing it with the likes of higher education, the utility space, and financial services space, which are the dominant three.

There is a lot of change occurring in those spaces, and businesses are looking for ways to make them more agile to adapt to that change, and looking towards disciplined architecture and the business-architecture discipline to try and help them in that process.

Gardner: I think I know a bit about how we got here -- computing, globalization, outsourcing, companies expanding across borders, the ability to enter new markets freely, and dealing with security, but also great opportunity. Did I miss anything? Is there anything about the past 10 or 15 years in business practices that have led now to this need for a greater emphasis on that strategic architectural level of thinking?

Martin: A lot has to do with basically building blocks. We've seen a journey that’s traveled within the architecture disciplines specifically. We call it the commodification of the business, and we've seen that maturity in the IT space. A lot of processes that used to be innovative in our business are now becoming fairly utility and core to the business.

In any Tier 1 organization, a lot of the processes that used to differentiate them are now freely available in a number of vendor platforms, and any of their competitors can acquire those.

Looking for differentiation

So they are looking for that differentiation, the ability to be able to differentiate themselves from their competitors, and away from that sort of utility space. That’s a shift that’s beginning to occur. Because a lot of those IT aspects have become industrialized, that’s also moving up into the business space.

In other words, how can we now take complex mysteries in the business space and codify them? In other words, how can we create building blocks for them, so that organizations now can actually effectively work with those building blocks and string them together in different ways to solve more complex business problems.

Evans: I'll add to that Dana. EA is now around 30 years old, but the rise in EA has really come from the need for IT systems to interoperate and to create common standards and common understanding within an organization for how an IT estate is going to come together and deliver the right type of business value.

Through the '90s we saw the proliferation of technologies as a result of the extension of distributed computing models and the emergence of the Internet. We've seen now the ubiquity of the Internet and technology across business. The same sort of concepts that ring true in technology architecture extend out into the business, around how the business interoperates with its components.
This type of thinking enables organizations to change more rapidly.

The need to change very fast for business, which is occurring now in the current economy, with the entrepreneurship and the innovation going on, is seeing this type of thinking come to the fore. This type of thinking enables organizations to change more rapidly. The architecture itself won't make the organization change rapidly, but it will provide the appropriate references and enable people to have the right conversations to make that happen.

Gardner: So architecture can come as a benefit when the complexity kicks in. When you try to change an organization, you don’t get lost along the way. Give me a sense about what sort of paybacks your clients get when they do this correctly, and what happens when you don’t do this very well?

Evans: Business architecture, as well as strategic architecture, is still quite a nascent capability for organizations, and many organizations are really still trying to get a grip on this. The general rule is that organizations don’t manage this so well at the moment, but organizations are looking to improving in this area, because of the obvious, even heuristic, payoffs that you get from being better organized.

You end up spending less money, because you're a more efficient organization, and you end up delivering better value to customers, because you're a more effective organization. This efficiency and effectiveness need within organizations is worth the price of investment in this area.

The actual tangible benefits that we're seeing across our customers includes reduced cost of their IT estate.

Meeting profiles

You have improved security and improved compliance, because organizations can see where their capabilities are meeting the various risk and compliance profiles, and you are also seeing organizations bring products to market quicker.

The ability to move through the product management process, bring products to market more rapidly, and respond to customer need more rapidly puts organizations in front and makes them more competitive.

The sorts of industries we're seeing acting in this area would include the postal industry, where they are moving from a traditional mail- to parcels, which is a result of a move towards online retailing. You're also seeing it in the telco sector and you're seeing it in the banking and finance sector.

In the banking and finance sector, we've also seen a lot of this investment driven by the merger and acquisition (M&A) activity that’s come out of the financial crisis in various countries where we operate. These organizations are getting real value from understanding where the enterprise boundaries are, how they bring the business together, how they better integrate the organizations and acquisitions, and how they better divest.
We're seeing, especially at the strategic level, that the architecture discipline is able to give business decision makers a view into different strategic scenarios.

Martin: We're seeing, especially at the strategic level, that the architecture discipline is able to give business decision makers a view into different strategic scenarios.

For example, where a number of environmental factors and market pressures would have been inputs into a discussion around how to change a business, we're also seeing business decision makers getting a lot of value from running those scenarios through an actual hypothesis of the business model.

For example, they could be considering four or five different strategic scenarios, and what we are seeing is that, using the architecture discipline, it's showing them effectively what those scenarios look like as they cascade through the business. It's showing the impact on capabilities, on people and the approaches and technologies, and the impact on capital expenditures (CAPEX) and operational expenditures (OPEX).

Those views of each of those strategic scenarios allows them to basically pull the trigger on the better strategic scenario to pursue, before they've invested all of their efforts and all that analysis to possibly get to the point where it wasn’t the right decision in the first place. So that might be referred to as sort of the strategic enablement piece.

We're also seeing a lot of value for organizations within the portfolio space. We traditionally get questions like, "I have 180 projects out there. Am I doing the right things? Are those the right 180 projects, and are they going to help me achieve the types of CAPEX and OPEX reductions that I am looking for?"

With the architecture discipline, you don’t take a portfolio lens into what’s occurring within the business. You take an architectural lens, and you're able to give executives an overview of exactly where the spend is occurring. You give them an overview of where the duplication is occurring, and where the loss of cohesion is occurring.

Common problems

A common problem we find, when we go into do these types of gigs, is the amount of duplication occurring across a number of projects. In a worst-case scenario, 75 percent of the projects are all trying to do the same thing, on the same capability, with the same processes.

So there’s a reduction of complexity and the production of efforts that’s occurring across the organizations to try and bring it and get it into more synergistic sessions.

We're also seeing a lot of value occurring up at the customer experience space. That is really taking a strong look at this customer experience view, which is less around all of the underlying building blocks and capabilities of an organization and looking more at what sort of experiences we want to give our customer? What type of product offerings must we assemble, and what underlying building blocks of the organization must be assembled to enable those offerings and those value propositions?

That sort of traceability through the cycle gives you a view of what levers you must pull to optimize your customer experience. Organizations are seeing a lot of value there and that’s basically increasing their effectiveness in the market and having a direct impact on their market share.
What type of product offerings must we assemble, and what underlying building blocks of the organization must be assembled to enable those offerings and those value propositions?

And that’s something that we see time and time again, regardless of what the driver was behind the investment in the architecture project, seeing the team interact and build a coalition for action and for change. That’s the most impressive thing that we get to see.

Gardner: Let’s drill down a little bit into some of what you'll be discussing at the conference in Sydney in April. One of the things that’s puzzling to me, when I go to these Open Group Conferences, is to better understand the relationship between business architecture and IT architecture and where they converge and where they differ. Perhaps you could offer some insights and maybe tease out what some discussion points for that would be at the conference.

Martin: That’s actually quite a hot topic. In general, the architecture discipline has grown from the IT space, and that’s a good progression for it to take, because we're seeing the fruits of that discipline in how they industrialize IT components.

We're seeing the fruits of that in complex enterprise resource planning (ERP) systems, the modularization of those ERP systems, their ability to be customized, and adapt to businesses. It’s a fairly mature space, and the natural progression of that is to apply those same thinking patterns back up into the business space.

In order for this to work effectively well, when somebody asks a question like that, we normally respond with a "depends" statement. We have in this organization a thing called the mandate curve, and it relates to what the mandate is within the business. What is the organization looking to solve?

Are they looking to build an HR management system? Are they looking to gain efficiencies from an enterprise-wide ERP solution? Are they looking to reduce the value chain losses that they're having on a monthly basis? Are they looking to improve customer experience across a group of companies? Or are they looking to improve shareholder value across the organization for an M&A, or maybe reduce cost-to-income.

Problem spaces

Those are some of the problem spaces, and we often get into that mind space to ask, "Those are the problems that you are solving, but what mandate is given to architecture to solve them?" We often find that the mandate for the IT architecture space is sitting beneath the CIO, and the CIO tends to use business architecture as a communication tool with business. In other words, to understand business better, to begin to apply architecture rigor to the business process.

Evans: It’s interesting, Dana. I spent a lot of time last year in the UK, working with the team across a number of business-architecture requirements. We were building business-architecture teams. We were also delivering some projects, where the initial investigation was a business-architecture piece, and we also ran some executive roundtables in the UK.

One thing that struck me in that investigation was the separation that existed in the business-architecture community from the traditional enterprise and technology architecture or IT architecture communities in those organizations that we were dealing with.

One insurance company, in particular, that was building a business-architecture team was looking for people that didn’t necessarily have an architecture background, but possibly could apply that insight. They were looking for deep business domain knowledge inside the various aspects of the insurance organization that they were looking to cover.

So to your question about the relationship between business architecture and IT architecture, where they converge and how they differ, it’s our view that business architecture is a subset of the broader EA picture and that these are actually integrated and unified disciplines.
We're going to see more convergence between these two groups, and that’s certainly something that we are looking to foster in EA.

However, in practice you'll find that there is often quite a separation between these two groups. I think that the major reason for that is that the drivers that are actually creating the investment for business architecture are actually now from coming outside of IT, and to some extent, IT is replicating that investment to build the engagement capability to engage with business so that they can have a more strategic discussion, rather than just take orders from the business.

I think that over this year, we're going to see more convergence between these two groups, and that’s certainly something that we are looking to foster in EA.

Gardner: I just came back from The Open Group Conference in California a few weeks ago, where the topic was focused largely on big data, but analysis was certainly a big part of that. Now, business analysis and business analysts, I suppose, are also part of this ecosystem. Are they subsets of the business architect? How do you see the role of business analysts now fitting into this, given the importance of data and the ability for organizations to manage data with new efficiency and scale?

Martin: Once again, that's also a hot topic. There is a convergence occurring, and we see that across the landscape, when it comes to the number of frameworks and standards that people certify on. Ultimately, it comes to this knife-edge point, in which we need to interact with the business stakeholder and we need to elicit requirements from that stakeholder and be able to model them successfully.

The business-analysis community is slightly more mature in this particular space. They have, for example, the Business Analysis Body of Knowledge (BABOK). Within that space, they leverage a competency model, which in effect goes through a cycle, from an entry level BA, right up to what they refer to as the generalist BA, which is where they see the start of the business-architecture role.

Career path

There's a career path from a traditional business analyst role, which is around requirements solicitation and requirements management, which seems to be quite project focused. In other words, dropping down onto project environments, understanding stakeholder needs and requirements, and modeling those and documenting them, helping the IT teams model the data flows, the data structures but with a specific link into the business space.

As you move up that curve, you get into the business-architecture space, which is a broader structural view around how all the building blocks fit together. In other words, it’s a far broader view than what the business analyst traditional part would take, and looks at a number of different domains. The business architect tends to focus a lot on, as you mentioned, the information space, and we see a difference between the information and the data space.

So the business architect is looking at performance, market-related aspects, and  customer, information, as well as the business processes and functional aspects of an organization.

You can see that the business analysts could almost be seen as the soldiers of these types of functions. In other words, they're the guys that are in the trenches seeing what's working on a day-to-day basis. They've got a number of tools that they're equipped with, which for example the BABOK has given them.

And there are all different ways and techniques that they are using to elicit those requirements from various business stakeholders, until they move out that curve up into the business architecture and strategic architecture space.
There is certainly a pattern emerging, and there are great opportunities for business analysts to come across into the architecture sphere.

Evans: There's an interesting pattern that I've noticed with the business-analyst-to-business-architecture career journey and the traditional IT track, where you see a number of people move into solution architect roles. There might be a solution architect on a project, they might move to multiple projects and ultimately do a program, and a number of those people then pop out to a much broader enterprise view, as they go through their career.

The business analyst is, in many respects, tracking that journey, where business analysts might focus on a project and requirements for a project, might look across at a high view, and possibly get to a point where they have a strong domain understanding that can drive high level sort of strategic discussions within the organization.

There is certainly a pattern emerging, and there are great opportunities for business analysts to come across into the architecture sphere. However, I believe that the broader EA discipline does need to make the effort to bridge that gap. Architecture needs to come across and find those connection points with the analyst community and help to elevate and converge the two sides.

Gardner: Craig, in your presentation at The Open Group Conference in Sydney, what do you hope to accomplish, and will this issue of how the business analyst fits in be prominent in that?

Martin: It’s a general theme that we're using leading right up to the conference. We have a couple of webinars, which deal specifically with this topic. That’s leading up to the plenary talk at The Open Group Conference, which is really looking at how we can use these tools of the architecture discipline to be able to achieve the types of outcomes that we've spoken about here.

Building cohesion

In other words, how do I build cohesion in an organization? How do I look at different types of scenarios that I can execute against? What are the better ways to assemble all the efforts in my organization to achieve those outcomes? That’s taking us through a variety of examples that will be quite visual. 

We'll also be addressing the specific role of where we see the career path and the complementary nature of the business analyst and business architect, as they travel through the cycle of trying to operate at a strategic level and as a strategic enabler within the organization.

Gardner: Maybe you could also help me better understand something. When organizations decide that this is the right thing for them -- as you mentioned earlier, this is still somewhat nascent -- what are some good foundational considerations to get started? What needs to be put in place? Maybe it’s a mindset. How do you often find that enterprises get beyond the inertia and into this discussion about architecture and about the strategic benefits of it?

Martin: Once again, it’s a "depends" answer. For example, we often have two market segments, where a Tier 1 type company would want to build the capability themselves. So there's a journey that we need to take them on around how to have a business-architecture capability while delivering the actual outcomes?

Tier 2 and Tier 3 clients often don’t necessarily want to build that type of capability, so we would focus directly on the outcomes. And those outcomes start with two views. Traditionally, we're seeing the view driven almost on a bottom-up view, as the sponsors of these types of exercises try to get credibility within the organization.
It's not just a bunch of building blocks, but the actual outcome of each of those building blocks and how does it match something like a business-motivation model.

That relates to helping the clients build what we refer to as the utility of the business-architecture space. Our teams go in and, in effect, build a bunch of what we refer to as anchor models to try and get a consistent representation of the business and a consistent language occurring across the entire enterprise, not just within a specific project.

And that gives them a common language they can talk about, for example, common capabilities and common outcomes that they're looking to achieve. In other words, it's not just a bunch of building blocks, but the actual outcome of each of those building blocks and how does it match something like a business-motivation model.

They also look within each of those building blocks to see what the resources are that creates each of those building blocks -- things like people, process and tools. How do we mix those resources in the right way to achieve those types of outcomes that the business is looking for? Normally, the first path that we go through is to try to get that sort of consistent language occurring within an organization.

As an organization matures, that artifact starts to lose its value, and we then find that, because it has created a consistent language in the organization, you can now overlay a variety of different types of views to give business people insights. Ultimately, they don’t necessarily want all these models, but they actually want insight into their organizations to enable them to make decisions.

We can overlay objectives, current project spend, CAPEX, and OPEX. We can overlay where duplication is occurring, where overspend is occurring, where there's conflict occurring at a global scale around duplication of efforts, and with the impact of costs and reduction and efficiencies, all of those types of questions can be answered by merely overlaying a variety of views across this common language.

Elevating the value

That starts to elevate the value of these types of artifacts, and we start to see our business sponsors walking into meetings with all of these overlays on them, and having conversations between them and their colleagues, specifically around the insights that are drawn from these artifacts. We want the architecture to tell the story, not necessarily lengthy PowerPoint presentations, but as people are looking at these types of artifacts, they are actually seeing all the insights that come specifically from it.

The third and final part is often around the business getting to a level of maturity, in that they're starting to use these types of artifacts and then are looking for different ways that they can now mix and assemble. That’s normally a sign of a mature organization and the business-architecture practice.

They have the building blocks. They've seen the value or the types of insights that they can provide. Are there different ways that I can string together my capabilities to achieve different outcomes? Maybe I have got different critical success factors that I am looking to achieve. Maybe there are new shift or new pressures coming in from the environment.

How can I assemble the underlying structures of my organization to better cope with it? That’s the third phase that we take customers through, once they get to that level of maturity.

Evans: Just to add to that, Dana, I agree with Craig on the point that, if you show the business what can actually be delivered such as views on a page that elicit the right types of discussions and that demonstrate the issues, when they see what they're going to get delivered, typically the eyes light up and they say, "I want one of those things."
It's not just enough to know the answer. You have to know how to engage somebody with the material.

The thing with architecture that I have noticed over the years is that architecture is done by a lot of very intelligent people, who have great insights and great understanding, but it's not just enough to know the answer. You have to know how to engage somebody with the material. So when the architecture content that’s coming through is engaging, clear, understandable, and can be consumed by a variety of stakeholders, they go, "That’s what I want. I want one of those."

So my advice to somebody who is going down this path is that if they want to get support and sponsorship for this sort of thing, make sure they get some good examples of what gets delivered when it's done well, as that’s a great way to actually get people behind it.

Gardner: I'm afraid we will have to leave it there. We've been talking with Hugh Evans, the CEO of Enterprise Architects, a specialist EA firm in Melbourne; and Craig Martin, the COO and Chief Architect at Enterprise Architects. Thanks to you both.

Evans: Thanks very much Dana, it has been a pleasure.

Martin: Thank you, Dana.

Gardner: This BriefingsDirect discussion comes to you in conjunction with The Open Group Conference, the first in Australia, on April 15 in Sydney. The focus will be on "How Does Enterprise Architecture Transform an Enterprise?"

So thanks again to both Hugh and Craig, and I know they will be joined by many more thought leaders and speakers on the EA subject and other architecture issues at the conference, and I certainly encourage our readers and listeners to attend that conference, if they're in the Asia-Pacific region.

This is Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator through these thought leadership interviews. Thanks again for listening, and come back next time.

Listen to the podcast. Find it on iTunesDownload the transcript. Sponsor: The Open Group.

Transcript of a BriefingsDirect podcast on the role that architects and analysts play in optimizing business capabilities and performance. Copyright The Open Group and Interarbor Solutions, LLC, 2005-2013. All rights reserved.

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