One on One with IBM’s Global VP for Data Analytics

As the Global Vice President of Systems Software and Growth Solutions for IBM, Jacqueline Woods has a tremendous amount of influence over a $12-billion portfolio of cloud, mobile, and big data solutions. Woods, who delivered a keynote at this week’s Leverage Big Data conference in Florida, recently sat down with Datanami to share her views on big data, and talk about how IBM is helping customers succeed with big data analytics.

Alex Woodie: There’s a tremendous amount of excitement around big data at the moment, but also a lot of confusion. Are you hearing from customers that big data is a challenge to be overcome, or an opportunity to get ahead of the competition?

Jacqueline Woods: It’s actually both. I think that most companies see it as an opportunity, that if they have the right data and information to leverage inside their organization, that they can clearly use that data to make better decisions, and it can be a competitive advantage.

Having said that, what obviously is important is understanding the type of data that you need in order to make those best decisions or next-best actions at the right time. And that is not so necessarily obvious, nor is it intuitive. Companies also want to be able to leverage data from external sources, which they obviously have far less control over than data they may have in their enterprise.

AW: What are the biggest challenges you’re hearing from customers? Are they struggling to get the right infrastructure or software, or do they need more data, or…..?

JW: Anytime you’re building something you always have to think about the infrastructure or the platform on which it’s built. That’s critical. If I need to ingest more terabytes of data at a certain rate, do I literally have network and other infrastructure available to do that? Do I have the capacity in my systems? Can my data center handle it?

The other thing that’s important for customers is not biting off more than they can chew. Some of the challenges that companies face, as with any significant project, is where to start. Who in the organization are the folks who are spearheading this? Who has the biggest relevance and clear ownership of this and is going to be the champion within the organization?

It requires an extraordinary amount of collaboration among multiple players in your enterprise. There has to be someone who is more of an orchestrator, who isn’t always directly out of the CIO’s office. But he has to be able to galvanize and integrate the right parts of his organization. We’re seeing a lot of that consternation, if you will–who has the lead. It’s not easy. This is about transformation, roles, and leaderships of certain types of projects. Those things over time have tended to change.

AW: If it’s not the CIO, who do you see leading the big data initiatives among IBM’s customers?

Jacqueline Woods (@JacWoods2020) is the Global Vice President of Systems Software and Growth Solutions for IBM’s Systems and Technology Group. She previously had executive roles at Oracle and GE.

JW: At a lot of companies now, there’s a new role that’s popping up and to me it’s a cross between the CIO and CTO, which is the Chief Data Officer. Sometimes that person reports to the CIO. But 100 percent of their role is to really understand what type of data requirements are needed inside of an organization and then helping the IT leadership understand those needs and requirements. And they tend to be the broker between the business constituency and the IT constituency.

This is moving beyond what would be the typical data analyst or data scientist role. This is a much higher-level role that really thinks and talks about the strategy, where it’s deployed, and what initiatives are done. They’re working with the leadership teams to decide what projects are going to be done first, and why and how they’re prioritized and what value those projects are going to bring to the organization, what are the expectations.

AW: How are Chief Data Officers helping their organizations be successful?

JW: They help the organization ensure that they’re not biting off more than they can chew, that they have clearly definable projects and business outcomes that they can build upon. Where we see success is where they have a clearly defined scope, where they can get some quick wins and people understand and see the value. They like that and want more of it.

Projects that have an opportunity to be less successful are ones that are way too broad in scope. People’s patience and tolerance for longer-term projects in today’s world just isn’t there anymore. If something is taking 18 months, that’s way too long. If you have a much smaller set of projects that are in these three-to-four month increments, then they can see success, they can see something building, they can start getting value right away, and then they can move onto the next thing. And then before you know it, a year-and-a-half has elapsed and it looks like you have had a tremendous amount of success, because you’ve probably had five small projects, and you’re already seeing value and outcomes from those projects. And that’s typically what companies are looking for now.

AW: IBM is a huge company with a dedicated Global Services unit. It’s anything but small. How can IBM help customers start small with big data?

JW: We have a number of services in the Systems and Technology Group where we’ll help a customer make an assessment predicted on the need those customers have identified, and determining through their work and assessment, what are the steps that should be done. What IBM brings to the table is a lot. It’s the number of analytic engagements that the company has done over many, many years. It has a history and a benefit of understanding all types of projects with all kinds of scopes. It’s bringing that expertise to the client and helping them define and develop a plan to meet their specific objective, which they would have jointly identified with a team from IBM.

AW: How well do the processes and policies that customers’ already have in place with existing business intelligence (BI) systems map to the new world of big data analytics?

JW: That’s an interesting question. The way that I look at technology, I’ve never seen anything that I would argue looks completely different. Over time you will see things that are completely different. Going from cassette to CD was completely different. Going from a CD to MP3 was completely different. But at the end the day, they were still opportunities to listen to music or provide a form of entertainment.

Yes things are changing when you think about big data. But I would argue that that’s more about an evolution than saying that you’re completely starting over, or that this stuff that you originally built is not useful anymore. A lot of the intelligence that companies would be getting from their legacy system they built in their analytic environment–the dashboards they have built–that’s helpful in them understanding what their constituents need internally, and also understanding what kind of data they would like to have going forward.

I would see those as a baseline to build on top of. I think most people would be looking at some sort of hybrid solution, where they would be utilizing information they have and custom applications that they built, and then augment that with newer technologies that are out there.

AW: Do you subscribe to the theory that says big data analytics will go away, because it will be embedded into other applications?

JW: I think that’s true.  I don’t know honestly know the timeframe for that. I think there will be analytics built into everything we do at some point, just based on the notion of Internet of Things and the fact that everything at some point, will be connected, or will feel like it’s connected. The more connectivity that you have, the more points of data that you generate, then the more collection you can do. And once you have the collection, you can do analysis.

I think that’s a natural derivative of how things will evolve. When that will be or how that will be has yet to be determined.  But I would argue that some of that is happening now, because many systems or applications today have internal analytics. They’re already doing that today. But is it complete pervasive? No. Will it be at some point in time? Probably so.

AW: What are the most disruptive big data technologies you see coming down the pike?

JW: I think the biggest disruption or change that we’ll see will be the intersection of analytics and mobility. There are many reasons why I believe that. When we look at the world at large, there’s much more pervasiveness of people using mobile than people using computers or other computational devices.

I think that that gravitational pull from mobile is going to be the thing that is the gravitational pull on big data and analytics as well. Those two things coming tougher will be the thing to me that’s most disruptive, for every business that’s out there, because the barriers to doing business and the barrier for people getting in to your space essentially are eliminated through the use of mobile.

AW: It’s why Airbnb is worth $10 billion–more than Hyatt, even though it doesn’t own any actual properties.

JW: It’s not exactly Airbnb or Uber or anything like that. The models are changing. People are thinking differently. Remember about 10 years ago, when exchanges were all the rage. These are just new ways of creating exchanges that are disintermediating traditional banking, disintermediating livery/transportation services/lodging. I believe that’s going to happen across a swath of industries and environments, and that will change the game.

AW: Thank you for your time and your insights.