Showing posts with label data science. Show all posts
Showing posts with label data science. Show all posts

Tuesday, March 05, 2019

Where the Rubber Meets the Road: How Users See the IT4IT Standard Building Competitive Business Advantage

 
Transcript of a panel discussion on how the IT4IT Reference Architecture for IT management works in many ways for many types of organizations and the demonstrated business benefits that are being realized as a result.

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

Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions, and you’re listening to BriefingsDirect. Our next IT operations strategy panel discussion explores how the IT4IT[tm] Reference Architecture for IT management creates demonstrated business benefits – in many ways, across many types of organizations.

Gardner
Since its delivery in 2015 by The Open Group, IT4IT has focused on defining, sourcing, consuming, and managing services across the IT function’s value stream to its stakeholders. Among its earliest and most ardent users are IT vendors, startups, and global professional services providers.

To learn more about how this variety of highly efficient businesses and their IT organizations make the most of IT4IT – often as a complimentary mix of frameworks and methodologies -- we are now joined by our panel:
Welcome to you all. Big trends are buffeting business in 2019. Companies of all kinds need to attain digital transformation faster, make their businesses more intelligent and responsive to their markets, and improve end user experiences. So, software development, applications lifecycles, and optimizing how IT departments operate are more important than ever. And they need to operate as a coordinated team, not in silos.

Lars, why is the IT4IT standard so powerful given these requirements that most businesses face? 

One framework to rule them all

Rossen
Rossen: There are a number of reasons, but the starting point is the fact that it’s truly end-to-end. IT4IT starts from the planning stage -- how to convert your strategy into actionable projects that are being measured in the right manner -- all the way to development, delivery of the service, how to consume it, and at the end of the day, to run it.

There are many other frameworks. They are often very process-oriented, or capability-oriented. But IT4IT gives you a framework that underpins it all. Every IT organization needs to have such a framework in place and be rationalized and well-integrated. And IT4IT can deliver that.

Gardner: And IT4IT is designed to help IT organizations elevate themselves in terms of the impact they have on the overall business.

Mark, when you encounter someone who says IT4IT, “What is that?” What’s your elevator pitch, how do you describe it so that a lay audience can understand it?

Bodman
Bodman: I pitch it as a framework for managing IT and leave it at that. I might also say it’s an operating model because that’s something a chief information officer (CIO) or a business person might know.

If it’s an individual contributor in one of the value streams, I say it’s a broader framework than what you are doing. For example, if they are a DevOps guy, or a maybe a Scaled Agile Framework (SAFe) guy, or even a test engineer, I explain that it’s a more comprehensive framework. It goes back to the nature of IT4IT being a hub of many different frameworks -- and all designed as one architecture.

Gardner: Is there an analog to other business, or even cultural, occurrences that IT4IT is to an enterprise?

Rossen: The analogy I have is that you go to The Lord of the Rings, and IT4IT is the “one ring to rule them all.” It actually combines everything you need.

Gardner: Why do companies need this now? What are the problems they’re facing that requires one framework to rule them all?

Everyone, everything on the same page

Esler
Esler: A lot of our clients have implemented a lot of different kinds of software -- automation software, orchestration software, and portals. They are sharing more information, more data. But they haven’t changed their operating model.

Using IT4IT is a good way to see where your gaps are, what you are doing well, what you are not doing not so well, and how to improve on that. It gives you a really good foundation on knowing the business of IT.

Bennett: We are hearing in the field is that IT departments are generally drowning at this point. You have a myriad of factors, some of which are their fault and some of which aren’t. The compliance world is getting nightmare-strict. The privacy laws that are coming in are straining what are already resource-constrained organizations. At the same time, budgets are being cut.

The other side of it is the users are demanding more from IT, as a strategic element as opposed to simply a support organization. As a result, they are drowning on a daily basis. Their operating model is -- they are still running on wooden wheels. They have not changed any of their foundational elements.

If your family has a spending problem, you don’t stop spending, you go on a budget. You put in an Excel spreadsheet, get all the data into one place, pull it together, and you figure out what’s going on. Then you can execute change. That’s what we do from an IT perspective. It’s simply getting everything in the same place, on the same page, and talking the same language. Then we can start executing change to survive.
Gardner: Because IT in the past could operate in silos, there would be specialization. Now we need a team-sport approach. Mark, how does IT4IT help that?

Bodman: An analogy is the medical profession. You have specialists, and you have generalist doctors. You go to the generalist when you don’t really know where the problem is. Then you go to a specialist with a very specific skill-set and the tools to go deep. IT4IT has aimed at that generalist layer, then with pointers to the specialists.

Gardner: IT4IT has been available since October 2015, which is a few years in the market. We are now seeing different types of adoption patterns—from small- to medium-size businesses (SMBs) and up to enterprises. What are some “rubber meets the road” points, where the value is compelling and understood, that then drive this deeper into the organization?

Where do you see IT4IT as an accelerant to larger business-level improvements?

Success via stability

Vijaykumar
Vijaykumar: When we look at the industry in general there are a lot of disruptive innovations, such as cloud computing taking hold. You have other trends like big data, too. These are driving a paradigm shift in the way IT is perceived. So, IT is not only a supporting function to the business anymore -- it’s a business enabler and a competitive driver.

Now you need stability from IT, and IT needs to function with the same level of rigor as a bank or manufacturer. If you look at those businesses, they have reference architectures that span several decades. That stability was missing in IT, and that is where IT4IT fills a gap -- we have come up with a reference architecture.

What does that mean? When you implement new tooling solutions or you come up with new enterprise applications, you don’t need to rip apart and replace everything. You could still use the same underlying architecture. You retain most of the things -- even when you advance to a different solution. That is where a lot of value gets created.

Esler: One thing you have to remember, too, is that this is not just about new stuff. It’s not just about artificial intelligence (AI), Internet of Things (IoT), big data, and all of that kind of stuff -- the new, shiny stuff. There is still a lot of old stuff out there that has to be managed in the same way. You have to have a framework like IT4IT that allows you to have a hybrid environment to manage it all.

https://publications.opengroup.org/it4it
Gardner: The framework to rule all frameworks.

Rossen: That also goes back to the concept of multi-modal IT. Some people say, “Okay, I have new tools for the new way of doing stuff, and I keep my old tools for the old stuff.”

But, in the real world, these things need to work together. The services depend on each other. If you have a new smart banking application, and you still have a COBOL mainframe application that it needs to communicate with, if you don’t have a single way of managing these two worlds you cannot keep up with the necessary speed, stability, and security.

Gardner: One of the things that impresses me about IT4IT is that any kind of organization can find value and use it from the get-go. As a start-up, an SMB, Jerrod, where you are seeing the value that IT4IT brings?

Solutions for any size business

Bennett
Bennett: SMBs have less pain, but proportionally it’s the same, exact problem. Larger enterprises have enormous pain, the midsize guys have medium pain, but it’s the same mess.

But the SMBs have an opportunity to get a lot more value because they can implement a lot more of this a lot faster. They can even rip up the foundation and start over, a greenfield approach. Most large organizations simply do not have that capability.

The same kind of change – like in big data, how much data is going to be created in the next five years versus the last five years? That’s universal, everyone is dealing with these problems.

Gardner: At the other end of the scale, Mark, big multinational corporations with sprawling IT departments and thousands of developers -- they need to rationalize, they need to limit the number of tools, find a fit-for-purpose approach. How does IT4IT help them?

Bodman: It helps to understand which areas to rationalize first, that’s important because you are not going to do everything at once. You are going to focus on your biggest pain points.

The other element is the legacy element. You can’t change everything at once. There are going to be bigger rocks, and then smaller rocks. Then there are areas where you will see folks innovate, especially when it comes to the DevOps, new languages, and new platforms that you deploy new capabilities on.

What IT4IT allows is for you to increasingly interchange those parts. A big value proposition of IT4IT is standardizing those components and the interfaces. Afterward, you can change out one component without disrupting the entire value chain.

Gardner: Rob, complexity is inherent in IT. They have a lot on their plate. How does the IT4IT Reference Architecture help them manage complexity?

Reference architecture connects everything

Akershoek
Akershoek: You are right, there is growing complexity. We have more services to manage, more changes and releases, and more IT data. That’s why it’s essential in any sized IT organization to structure and standardize how you manage IT in a broader perspective. It’s like creating a bigger picture.

Most organizations have multiple teams working on different tools and components in a whole value chain. I may have specialized people for security, monitoring, the service desk, development, for risk and compliance, and for portfolio management. They tend to optimize their own silo with their own practices. That’s what IT4IT can help you with -- creating a bigger picture. Everything should be connected.

Esler: I have used IT4IT to help get rid of those very same kinds of silos. I did it via a workshop format. I took the reference architecture from IT4IT and I got a certain number of people -- and I was very specific about the people I wanted -- in the room. In doing this kind of thing, you have to have the right people in the room.

We had people for service management, security, infrastructure, and networking -- just a whole broad range across IT. We placed them around the table, and I took them through the IT4IT Reference Architecture. As I described each of the words, which meant function, they began to talk among themselves, to say, “Yes, I had a piece of that. I had this piece of this other thing. You have a piece of that, and this piece of this.”

It started them thinking about the larger functions, that there are groups performing not just the individual pieces, like service management or infrastructure.
Gardner: IT4IT then is not muscling out other aspects of IT, such as Information Technology Infrastructure Library (ITIL), The Open Group Architecture Framework (TOGAF), and SAFe. Is there a harmonizing opportunity here? How does IT4IT fit into a larger context among these other powerful tools, approaches, and methodologies?

Rossen: That’s an excellent question, especially given that a lot of people into SAFe might say they don’t need IT4IT, that SAFe is solving their whole problem. But once you get to discuss it, you see that SAFe doesn’t give you any recommendation about how tools need to be connected to create the automated pipeline that SAFe relies on. So IT4IT actually compliments SAFe very well. And that’s the same story again and again with the other ones.

The IT4IT framework can help bring those two things – ITIL and SAFe -- together without changing the IT organizations using them. ITIL can still be relevant for the helpdesk, et cetera, and SAFe can still function -- and they can collaborate better.

Gardner: Varun, another important aspect to maturity and capability for IT organizations is to become more DevOps-oriented. How does DevOps benefit from IT4IT? What’s the relationship?

Go with the data flow

Vijaykumar: When we talk about DevOps, typically organizations focus on the entire service design lifecycle and how it moves into transition. But the relationship sometimes gets lost between how a service gets conceptualized to how it is translated into a design. We need to use IT4IT to establish traceability, to make sure that all the artifacts and all the information basically flows through the pipeline and across the IT value chain.

The way we position the IT4IT framework to organizations and customers is very important. A lot of times people ask me, “Is this going to replace ITIL?” Or, “How is it different from DevOps?”


The simplest way to answer those questions is to tell them that this is not something that provides a narrative guidance. It’s not a process framework, but rather an information framework. We are essentially prescribing the way data needs to flow across the entire IT value chain, and how information needs to get exchanged.

It defines how those integrations are established. And that is vital to having an effective DevOps framework because you are essentially relying on traceability to ensure that people receive the right information to accept services, and then support those services once they are designed.

Gardner: Let’s think about successful adoption, of where IT4IT is compelling to the overall business. Jerrod, among your customers where does IT4IT help them?

Holistic strategy benefits business

Bennett: I will give an example. I hate the word, but “synergy” is all over this. Breaking down silos and having all this stuff in one place -- or at least in one process, one information framework -- helps the larger processes get better.

The classic example is Agile development. Development runs in a silo, they sit in a black box generally, in another building somewhere. Their entire methodology of getting more efficient is simply to work faster.

So, they implement sprints, or Agile, or scrum, or you name it. And what you recognize is they didn’t have a resource problem, they had a throughput problem. The throughput problem can be slightly solved using some of these methodologies, by squeezing a little bit more out of their glides.

Credit: The Open Group

But what you find, really, is they are developing the wrong thing. They don’t have a strategic element to their businesses. They simply develop whatever the heck they decide is important. Only now they develop it really efficiently. But the output on the other side is still not very beneficial to the business.

If you input a little bit of strategy in front of that and get the business to decide what it is that they want you to develop – then all of a sudden your throughput goes through the roof. And that’s because you have broken down barriers and brought together the [major business elements], and it didn’t take a lot. A little bit of demand management with an approval process can make development 50 percent more efficient -- if you can simply get them working on what’s important.

It’s not enough to continue to stab at these small problems while no one has yet said, “Okay, timeout. There is a lot more to this information that we need.” You can take inspiration from the manufacturing crisis in the 1980s. Making an automobile engine conveyor line faster isn’t going to help if you are building the wrong engines or you can’t get the parts in. You have to view it holistically. Once you view it holistically, you can go back and make the assembly lines work faster. Do that and sky is the limit.

Gardner: SoIT4IT helps foster “simultaneous IT operations,” a nice and modern follow-on to simultaneous engineering innovations of the past.

Mark, you use IT4IT internally at ServiceNow. How does IT4IT help ServiceNow be a better IT services company?

IT to create and consume products

Bodman: A lot of the activities at ServiceNow are for creating the IT Service Management (ITSM) products that we sell on the market, but we also consume them. As a product manager, a lot of my job is interfacing with other product managers, dealing with integration points, and having data discussions.

As we make the product better, we automatically make our IT organization better because we are consuming it. Our customer is our IT shop, and we deploy our products to manage our products. It’s a very nice, natural, and recursive relationship. As the company gets better at product management, we can get more products out there. And that’s the goal for many IT shops. You are not creating IT for IT’s sake, you are creating IT to provide products to your customers.

Gardner: Rob, at Fruition Partners, a DXE company, you have many clients that use IT4IT. Do you have a use case that demonstrates how powerful it can be?

Akershoek: Yes, I have a good example of an insurance organization where they have been forced to reduce significantly the cost to develop and maintain IT services.

Initially, they said, “Oh, we are going to automate and monitor DevOps.” When I showed them IT4IT they said, “Well, we are already doing that.” And I said, “Why don’t you have the results yet? And they said, “Well, we are working on it, come back in three months.”

IT4IT saved time and created transparency. With that outcome they realized, "Oh, we would have never been able to achieve that if had continued the way we did it in the past."
But after that period of time, they still were not succeeding with speed. We said, “Use IT4IT, take it to specific application teams, and then move to cloud, in this case, Azure Cloud. Show that you can do it end-to-end from strategy into an operation, end-to-end in three months’ time and demonstrate that it works.”

And that’s what has been done, it saved time and created transparency. With that outcome they realized, “Oh, we would have never been able to achieve that if we had continued the way we did it in the past.”

Gardner: John, at HPE Pointnext, you are involved with digital transformation, the highest order of strategic endeavors and among the most important for companies nowadays. When you are trying to transform an organization – to become more digital, data-driven, intelligent, and responsive -- how does IT4IT help?

Esler: When companies do big, strategic things to try and become a digital enterprise, they implement a lot of tools to help. That includes automation and orchestration tools to make things go faster and get more services out.

But they forget about the operating model underneath it all and they don’t see the value. A big drug company I worked with was expecting a 30 percent cost reduction after implementing such tools, and they didn’t get it. And they were scratching their heads, asking, “Why?”

We went in and used IT4IT as a foundation to help them understand where they needed change. In addition to using some tools that HPE has, that helped them to understand -- across different domains, depending on the level of service they want to provide to their customers -- what they needed to change. They were able to learn what that kind of organization looks like when it’s all said and done.

Gardner: Lars, Micro Focus has 4,000 to 5,000 developers and needs to put software out in a timely fashion. How has IT4IT helped you internally to become a better development organization?

Streamlining increases productivity

Rossen: We used what is by now a standard technique in IT4IT, to do rationalization. Over a year, we managed to convert it all into a single tool chain that 80 percent of the developers are on.

With that we are now much more agile in delivering products to market. We can do much more sharing. So instead of taking a year, we can do the same easily every three months. But we also have hot fixes and a change focus. We probably have 20 releases a day. And on top of that, we can do a lot more sharing on components. We can align much more to a common strategy around how all our products are being developed and delivered to our customers. It’s been a massive change.

Gardner: Before we close out, I’d like to think about the future. We have established that IT4IT has backward compatibility, that if you are a legacy-oriented IT department, the reference architecture for IT management can be very powerful for alignment to newer services development and use.

But there are so many new things coming on, such as AIOps, AI, machine learning (ML), and data-driven and analytics-driven business applications. We are also finding increased hybrid cloud and multi-cloud complexity across deployment models. And better managing total costs to best operate across such a hybrid IT environment is also very important.

So, let’s take a pause and say, “Okay, how does IT4IT operate as a powerful influence two to three years from now?” Is IT4IT something that provides future-proofing benefits?

The future belongs to IT4IT

Bennett: Nothing is future-proof, but I would argue that we really needed IT4IT 20 years ago -- and we didn’t have it. And we are now in a pretty big mess.

There is nothing magical here. It’s been well thought-out and well-written, but there is nothing new in there. IT4IT is how it ought to have been for a while and it took a group of people to get together and sit down and architect it out, end-to-end.

Theoretically it could have been done in the 1980s and it would still be relevant because they were doing the same thing. There isn’t anything new in IT, there are lots of new-fangled toys. But that’s all just minutia. The foundation hasn’t changed. I would argue that in 2040 IT4IT will still be relevant.
Gardner: Varun, do you feel that organizations that adopt IT4IT are in a better position to grow, adapt, and implement newer technologies and approaches?

Vijaykumar: Yes, definitely, because IT4IT – although it caters to the traditional IT operating models -- also introduces a lot of new concepts that were not in existence earlier. You should look at some of the concepts like service brokering, catalog aggregation, and bringing in the role of a service integrator. All of these are things that may have been in existence, but there was no real structure around them.

IT4IT provides a consolidated framework for us to embrace all of these capabilities and to drive improvements in the industry. Coupled with advances in computing -- where everything gets delivered on the fly – and where end users and consumers expect a lot more out of IT, I think IT4IT helps in that direction as well.

Gardner: Lars, looking to the future, how do you think IT4IT will be appreciated by a highly data-driven organization?

Rossen: Well, IT4IT was a data architecture to begin with. So, in that sense it was the first time that IT itself got a data architecture that was generic. Hopefully that gives it a long future.

I also like to think about it as being like roads we are building. We now have the roads to do whatever we want. Eventually you stop caring about it, it’s just there. I hope that 20 years from now nobody will be discussing this, they will just be doing it.

The data model advantage

Gardner: Another important aspect to running a well-greased IT organization -- despite the complexity and growing responsibility -- is to be better organized and to better understand yourself. That means having better data models about IT. Do you think that IT4IT-oriented shops have an advantage when it comes to better data models about IT?

Bodman: Yes, absolutely. One of the things we just produced within the [IT4IT reference architecture data model] is a reporting capability for key performance indicators (KPI) guidance. We are now able to show what kinds of KPIs you can get from the data model -- and be very prescriptive about it.

In the past there had been different camps and different ways of measuring and doing things. Of course, it’s hard to benchmark yourself comprehensively that way, so it’s really important to have consistency there in a way that allows you to really improve.

In the past there had been different camps and different ways of measuring and doing things. It's hard to benchmark yourself that way. It's really important to have consistency in a way that allows you to really improve.
The second part -- and this is something new in IT4IT that is fundamental -- is the value stream has a “request to fulfill (R2F)” capability. It’s now possible to have a top-line, self-service way to engage with IT in a way that’s in a catalog and that is easy to consume and focused on a specific experience. That’s an element that has been missing. It may have been out there in pockets, but now it’s baked in. It’s just fabric, taught in schools, and you just basically implement it.

Rossen: The new R2F capability allows an IT organization to transform, from being a cost center that does what people ask, to becoming a service provider and eventually a service broker, which is where you really want to be.

Esler: I started in this industry in the mainframe days. The concept of shared services was prevalent, so time-sharing, right? It’s the same thing. It hasn’t really changed. It’s evolved and going through different changes, but the advent of the PC in the 1980s didn’t change the model that much.

Now with hyperconvergence, it’s moving back to that mainframe-like thing where you define a machine by software. You can define a data center by software.
Gardner: For those listening and reading and who are intrigued by IT4IT and would like to learn more, where can they go and find out more about where the rubber meets the IT road?

Akershoek: The best way is going to The Open Group website. There’s a lot of information on the reference architecture itself, case studies, and video materials.

How to get started is typically you can do that very small. Look at the materials, try to understand how you currently operate your IT organization, and plot it to the reference architecture.

That provides an immediate sense of what you may be missing, are duplicating areas, or have too much going on without governance. You can begin to create a picture of your IT organization. That’s the first step to try to create or co-create with your own organization a bigger picture and decide where you want to go next.

Gardner: I’m afraid we will have to leave it there. You have been listening to a sponsored BriefingsDirect discussion on how the IT4IT[tm] Reference Architecture for IT management creates demonstrated business benefits – in many ways across many types of organizations. And we’ve learned a variety of ways that IT4IT defines, sources, and manages services across the IT function’s value stream to its stakeholders.

So please join me in thanking our panelists:
  • Lars Rossen, Fellow at Micro Focus, in Copenhagen;
  • Mark Bodman, Senior Product Manager at ServiceNow, in Austin;
  • John Esler, Client Principal at Hewlett Packard Enterprise Pointnext, in Denver;
  • Rob Akershoek, IT Architect at Fruition Partners, a DXC Technology Company, in Amsterdam;
  • Varun Vijaykumar, Associate General Manager and ITSM Architect at HCL Technologies, in Raleigh-Durham, and
  • Jerrod Bennett, CEO and Co-Founder at Dreamtsoft, in San Diego.
And a big thank you as well to our audience for joining this BriefingsDirect modern digital business innovation discussion. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host throughout the series of BriefingsDirect discussions sponsored by The Open Group.

Thanks again for listening. Please pass this on to your IT community and do come back next time.


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

Transcript of a panel discussion on how the IT4IT Reference Architecture for IT management works in many ways for many types of organizations and the demonstrated business benefits that are being realized as a result. Copyright Interarbor Solutions, LLC and The Open Group, 2005-2019. All rights reserved.

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Wednesday, February 20, 2019

How the Data Science Profession is Growing in Value and Impact Across the Business World

Transcript of a discussion on how the role of the data scientist in the enterprise is expanding in both importance and influence that warrants a new level of business analysis professional certification.

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

Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions, and you’re listening to BriefingsDirect. Our next business trends panel discussion explores how the role of the data scientist in the enterprise is expanding in both importance and influence.
Gardner
Data scientists are now among the most highly sought-after professionals, and they are being called on to work more closely than ever with enterprise strategists to predict emerging trends, optimize outcomes, and create entirely new kinds of business value.

To learn more about modern data scientists, how they operate, and why a new level of business analysis professional certification has been created by The Open Group, we are now joined by our panel, Martin Fleming, Vice President, Chief Analytics Officer, and Chief Economist at IBM. Welcome, Martin.

Martin Fleming: Thanks, Dana.

Gardner: We are also joined by Maureen Norton, IBM Global Data Scientist Professional Lead, Distinguished Market Intelligence Professional, and author of Analytics Across the Enterprise. Welcome, Maureen.

Maureen Norton: Thank you very much, pleasure to be here.

Gardner: And we’re also here with George Stark, Distinguished Engineer for IT Operations Analytics at IBM. Welcome, George.

George Stark: Thank you, Dana.

Gardner: We are now characterizing the data scientist as a profession. Why have we elevated the role to this level, Martin? 

Data scientists add value 

Fleming
Fleming: The benefits we have from the technology that’s now available allow us to bring together the more traditional skills in the space of mathematics and statistics with computer science and data engineering. The technology wasn't as useful just 18 months ago. It’s all about the very rapid pace of change in technology.

Gardner: Data scientists used to be behind-the-scenes people; sneakers, beards, white lab coats, if you will. What's changed to now make them more prominent?

Norton: Today’s data scientists are consulting with the major leaders in each corporation and enterprise. They are consultants to them. So they are not in the back room, mulling around in the data anymore. They're taking the insights they're able to glean and support with facts and using them to provide recommendations and to provide insights into the business.

Gardner: Most companies now recognize that being data-driven is an imperative. They can’t succeed in today's world without being data-driven. But many have a hard time getting there. It's easier said than done. How can the data scientist as a professional close that gap?

Stark
Stark: The biggest drawback in integration of data sources is having disparate data systems. The financial system is always separate from the operational system, which is separate from the human resources (HR) system. And you need to combine those and make sure they're all in the same units, in the same timeframe, and all combined in a way that can answer two questions. You have to answer, “So what?” And you have to answer, “What if?” And that’s really the challenge of data science.

Gardner: An awful lot still has to go on behind the scenes before you get to the point where the “a-ha” moments and the strategic inputs take place.

Martin, how will the nature of work change now that the data scientist as a profession is arriving – and probably just at the right time?

Fleming: The insights that data scientists provide allow organizations to understand where the opportunities are to improve productivity, of how they can help to make workers more effective, productive, and to create more value. This enhances the role of the individual employees. And it’s that value creation, the integration of the data that George talked about, and the use of analytic tools that's driving fundamental changes across many organizations.

Captain of the data team

Gardner: Is there any standardization as to how the data scientist is being organized within companies? Do they typically report to a certain C-suite executive or another? Has that settled out yet? Or are we still in a period of churn as to where the data scientist, as a professional, fits in?

Norton
Norton: We're still seeing a fair amount of churn. Different organizing approaches have been tried. For example, the centralized center of excellence that supports other business units across a company has a lot of believers and followers.

The economies of scale in that approach help. It’s difficult to find one person with all of the skills you might need. I’m describing the role of consultant to the presidents of companies. Sometimes you can’t find all of that in one individual -- but you can build teams that have complimentary skills. We like to say that data science is a team sport.

Gardner: George, are we focusing the new data scientist certification on the group or the individual? Have we progressed from the individual to the group yet?

Stark: I don’t believe we are there yet. We’re still certifying at the individual level. But as Maureen said, and as Martin alluded to, the group approach has a large effect on how you get certified and what kinds of solutions you come up with.

Gardner: Does the certification lead to defining the managerial side of this group, with the data scientist certified in organizing in a methodological, proven way that group or office?
Learn How to Become
Certified as a
Data Scientist
Fleming: The certification we are announcing focuses not only on the technical skills of a data scientist, but also on project management and project leadership. So as data scientists progress through their careers, the more senior folks are certainly in a position to take on significant leadership and management roles.

And we are seeing over time, as George referenced, a structure beginning to appear. First in the technology industry, and over time, we’ll see it in other industries. But the technology firms whose names we are all familiar with are the ones who have really taken the lead in putting the structure together.

Gardner: How has the “day in the life” of the typical data scientist changed in the last 10 years?

Stark: It’s scary to say, but I have been a data scientist for 30 years. I began writing my own Fortran 77 code to integrate datasets to do eigenvalues and eigenvectors and build models that would discriminate among key objects and allow us to predict what something was.

The difference today is that I can do that in an afternoon. We have the tools, datasets, and all the capabilities with visualization tools, SPSS, IBM Watson, and Tableau. Things that used to take me months now take a day and a half. It’s incredible, the change.

Gardner: Do you as a modern data scientist find yourself interpreting what the data science can do for the business people? Or are you interpreting what the business people need, and bringing that back to the data scientists? Or perhaps both?

Collaboration is key

Stark: It’s absolutely both. I was recently with a client, and we told them, “Here are some things we can do today.” And they said, “Well, what I really need is something that does this.” And I said, “Oh, well, we can do that. Here’s how we would do it.” And we showed them the roadmap. So it’s both. I will take that information back to my team and say, “Hey, we now need to build this.”

Gardner: Is there still a language, culture, or organizational divide? It seems to me that you’re talking apples and oranges when it comes to business requirements and what the data and technology can produce. How can we create a Rosetta Stone effect here?

Norton: In the certification, we are focused on supporting that data scientists have to understand the business problems. Everything begins from that.

In the certification, we are focused on supporting that data scientists have to understand the business problems. Everything begins from that. Knowing how to ask the right questions, to scope the problem, and be able to then translate is essential.
Knowing how to ask the right questions, to scope the problem, and be able to then translate [is essential]. You have to look at the available data and infer some, to come up with insights and a solution. It's increasingly important that you begin with the problem. You don't begin with your solution and say, “I have this many things I can work with.” It's more like, “How we are going to solve this and draw on the innovation and creativity of the team?”

Gardner: I have been around long enough to remember when the notion of a chief information officer (CIO) was new and fresh. There are some similarities to what I remember from those conversations in what I’m hearing now. Should we think about the data scientist as a “chief” something, at the same level as a chief technology officer (CTO) or a CIO?

Chief Data Officer defined 

Fleming: There are certainly a number of organizations that have roles such as mine, where we've combined economics and analytics. Amazon has done it on a larger scale, given the nature of their business, with supply chains, pricing, and recommendation engines. But other firms in the technology industry have as well.

We have found that there are still three separate needs, if you will. There is an infrastructure need that CIO teams are focused on. There are significant data governance and management needs that typically chief data officers (CDOs) are focused on. And there are substantial analytics capabilities that typically chief analytics officers (CAOs) are focused on.

It's certainly possible in many organizations to combine those roles. But in an organization the size of IBM, and other large entities, it's very difficult because of the complexity and requirements across those three different functional areas to have that all embodied in a single individual.

Gardner: In that spectrum you just laid out – analytics, data, and systems -- where does The Open Group process for a certified data scientist fit in?

Fleming: It's really on the analytics side. A lot of what CDOs do is data engineering, creating data platforms. At IBM, we use the term Watson Data Platform because it's built on a certain technology that's in the public cloud. But that's an entirely separate challenge from being able to create the analytics tools and deliver the business insights and business value that Maureen and George referred to.

Gardner: I should think this is also going to be of pertinent interest to government agencies, to nonprofits, to quasi-public-private organizations, alliances, and so forth.

Given that this has societal-level impacts, what should we think about in improving the data scientists’ career path? Do we have the means of delivering the individuals needed from our current educational tracks? How do education and certification relate to each other?

Academic avenues to certification

Fleming: A number of universities have over the past three or four years launched programs for a master’s degree in data science. We are now seeing the first graduates of those programs, and we are recruiting and hiring.

I think this will be the first year that we bring in folks who have completed a master’s in data science program. As we all know, universities change very slowly. It's the early days, but demand will continue to grow. We have barely scratched the surface in terms of the kinds of positions and roles across different industries.

That growth in demand will cause many university programs to grow and expand to feed that career track. It takes 15 years to create a profession, so we are in the early days of this.


Norton: With the new certification, we are doing outreach to universities because several of them have master’s in data analytics programs. They do significant capstone-type projects, with real clients and real data, to solve real problems.

We want to provide a path for them into certification so that students can earn, for example, their first project profile, or experience profile, while they are still in school.

Gardner: George, on the organic side -- inside of companies where people find a variety of tracks to data scientist -- where do the prospects come from? How does organic development of a data scientist professional happen inside of companies?

Stark: At IBM, in our group, Global Services, in particular, we've developed a training program with a set of badges. They get rewarded for achievement in various levels of education. But you still need to have projects you've done with the techniques you've learned through education to get to certification.

Having education is not enough. You have to apply it to get certified.

Gardner: This is a great career path, and there is tremendous demand in the market. It also strikes me as a very fulfilling and rewarding career path. What sorts of impacts can these individuals have?
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Fleming: Businesses have traditionally been managed through a profit-and-loss statement, an income statement, for the most part. There are, of course, other data sources -- but they’re largely independent of each other. These include sales opportunity information in a CRM system, supply chain information in ERP systems, and financial information portrayed in an income statement. These get the most rigorous attention, shall we say.

We're now in a position to create much richer views of the activity businesses are engaged in. We can integrate across more datasets now, including human resources data. In addition, the nature of machine learning (ML) and artificial intelligence (AI) are predictive. We are in a position to be able to not only bring the data together, we can provide a richer view of what's transpiring at any point in time, and also generate a better view of where businesses are moving to.

It may be about defining a sought-after destination, or there may be a need to close gaps. But understanding where the business is headed in the next 3, 6, 9, and 12 months is a significant value-creation opportunity.

Gardner: Are we then thinking about a data scientist as someone who can help define what the new, best business initiatives should be? Rather than finding those through intuition, or gut instinct, or the highest paid person's opinion, can we use the systems to tell us where our next product should come from?

Pioneers of insight

Norton: That's certainly the direction we are headed. We will have systems that augment that kind of decision-making. I view data scientists as pioneers. They're able to go into big data, dark data, and a lot of different places and push the boundaries to come out with insights that can inform in ways that were not possible before.

It’s a very rewarding career path because there is so much value and promise that a data scientist can bring. They will solve problems that hadn't been addressed before.

It's a very exciting career path. We’re excited to be launching the certification program to help data scientists gain a clear path and to make sure they can demonstrate the right skills.

It's a very rewarding career path because there is so much value and promise that a data scientist can bring. They will solve problems that hadn't been addressed before.
Gardner: George, is this one of the better ways to change the world in the next 30 years?

Stark: I think so. If we can get more people to do data science and understand its value, I'd be really happy. It's been fun for 30 years for me. I have had a great time.

Gardner: What comes next on the technology side that will empower the date scientists of tomorrow? We hear about things like quantum computing, distributed ledger, and other new capabilities on the horizon?

Future forecast: clouds

Fleming: In the immediate future, new benefits are largely coming because we have both public cloud and private cloud in a hybrid structure, which brings the data, compute, and the APIs together in one place. And that allows for the kind of tools and capabilities that necessary to significantly improve the performance and productivity of organizations.

Blockchain is making enormous progress and very quickly. It's essentially a data management and storage improvement, but then that opens up the opportunity for further ML and AI applications to be built on top of it. That’s moving very quickly.

Quantum computing is further down the road. But it will change the nature of computing. It's going to take some time to get there but it nonetheless is very important and is part of that what we are looking at over the horizon.

Gardner: Maureen, what do you see on the technology side as most interesting in terms of where things could lead to the next few years for data science?

Norton: The continued evolution of AI is pushing boundaries. One of the really interesting areas is the emphasis on transparency and ethics, to make sure that the systems are not introducing or perpetuating a bias. There is some really exciting work going on in that area that will be fun to watch going forward.

Gardner: The data scientist needs to consider not just what can be done, but what should be done. Is that governance angle brought into the certification process now, or something that it will come later?

Stark: It's brought into the certification now when we ask about how were things validated and how did the modules get implemented in the environment? That’s one of the things that data scientists need to answer as part of the certification. We also believe that in the future we are going to need some sort of code of ethics, some sort of methods for bias-detection and analysis, the measurement of those things that don't exist today and that will have to.

Gardner: Do you have any examples of data scientists doing work that's new, novel, and exciting?

Rock star potential

Fleming: We have a team led by a very intelligent and aggressive young woman who has put together a significant product recommendation tool for IBM. Folks familiar with IBM know it has a large number of products and offerings. In any given client situation the seller wants to be able to recommend to the client the offering that's most useful to the client’s situation.

And our recommendation engines can now make those recommendations to the sellers.  It really hasn't existed in the past and is now creating enormous value -- not only for the clients but for IBM as well.

Gardner: Maureen any examples jump to mind that illustrate the potential for the data scientist?

Norton: We wrote a book, Analytics Across the Enterprise, to explain examples across nine different business units. There have been some great examples in terms of finance, sales, marketing, and supply chain.
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Gardner: Any use-case scenario come to mind where the certification may have been useful?

Norton: Certification would have been useful to an individual in the past because it helps map out how to become the best practitioner you can be. We have three different levels of certification going up to the thought leader. It's designed to help that professional grow within it.

Stark: A young man who works for me in Brazil built a model for one of our manufacturing clients that identifies problematic infrastructure components and recommends actions to take on those components. And when the client implemented the model, they saw a 60 percent reduction in certain incidents and a 40,000-hour-a-month increase in availability for their supply chain. And we didn't have a certification for him then -- but we will have now.

Gardner: So really big improvement. It shows that being a data scientist means you're impactful and it puts you in the limelight.

Stark: And it was pretty spectacular because the CIO for that company stood up in front of his whole company -- and in front of a group of analysts -- and called him out as the data scientist that solved this problem for their company. So, yeah, he was a rock star for a couple days.

Gardner: For those folks who might be more intrigued with a career path toward certification as a data scientist, where might they go for more information? What are the next steps when it comes to the process through The Open Group, with IBM, and the industry at large?

Where to begin

Norton: The Open Group officially launched this in January, so anyone can go to The Open Group website and check under certifications. They will be able to read the information about how to apply. Some companies are accredited, and others can get accredited for running a version of the certification themselves.

IBM recently went through the certification process. We have built an internal process that matches with The Open Group. People can apply either directly to The Open Group or, if they happen to be within IBM or one of the other companies who will certify, they can apply that way and get the equivalent of it being from The Open Group.

Gardner: I’m afraid we’ll have to leave it there. You have been listening to a sponsored BriefingsDirect discussion on how the role of the data scientist in the enterprise is expanding both in importance and influence. And we learned how data scientists -- especially those with this new certification -- are being called on to work more closely than ever with enterprise strategies to predict emerging trends, optimize outcomes, and create entirely new kinds of business value.

IBM has built an internal process that matches with The Open Group. Other companies are getting accredited for running a version of the certification themselves, too.
So please join me in thanking our guests, Martin Fleming, Vice President, Chief Analytics Officer, and Chief Economist at IBM. Thank you, sir.

Fleming: My pleasure, Dana.

Gardner: We also have been here with Maureen Norton, IBM Global Data Scientist Profession Lead, Distinguished Market Intelligence Professional, and author of Analytics Across the Enterprise. Thank you so much, Maureen.

Norton: Thank you, Dana. It’s been a lot of fun.

Gardner: And lastly, we have been here with George Stark, Distinguished Engineer for IT Operations Analytics at IBM. Thank you, sir.

Stark: Thank you, Dana.

Gardner: And a big thank you as well to our audience for joining this BriefingsDirect modern digital business innovation discussion. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host throughout the series of BriefingsDirect discussions sponsored by The Open Group.

Thanks again for listening. Please pass this on to your IT community, and do come back next time.

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

Transcript of a discussion on how the role of the data scientist in the enterprise is expanding in both importance and influence that warrants a new level of business analysis professional certification. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

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