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Leadership

Strategies, advice and opinions helping to define and develop the role of IT leaders and their staffs.

Becoming a Data-driven CIO

Q & A with Shawn Rosemarin, SVP & CTO, Global Field and Industry, Hitachi Vantara

I first met Shawn Rosemarin in 2014 at the Hitachi Product Launch World Tour where I was the emcee for its Toronto stop. At the time, Shawn was the CTO of VMware Canada, a Hitachi partner, and spoke about thought leadership and strategy. Shawn joined Hitachi in 2016 with global mandates for solutioning, technical strategy, and enterprise architecture. I had the opportunity to catch up with him recently at HitachiNEXT, the company’s global customer and partner conference. During an executive briefing, I picked his brain about industry trends, practical strategies, frameworks, and steps CIOs need to take in order to monetize their data assets. Shawn also shared what’s important for building talent.

You have a long history of working with IT leaders across industries in the role of field CTO before you joined Hitachi. As a global CTO for field and industry, what are your observations about the biggest challenges IT leaders face in the digital age?

Our CIO, Renée McKaskle, put it very well that the role of Chief Information Officer is very quickly becoming the Chief Innovation Officer. The old role of managing information systems across the organization is very different from a role that now says “I need to go further than that. I need to be able to manage the data across the organization in a way that it presents new business opportunities”. The CIO now becomes the thought leader who can look at what opportunities exist to bring in new business models. Contrast that with the traditional function within IT that was all about cost containment. How do I do more with less? How do I lower the cost of my storage, my servers, my network? That was very much an infrastructure conversation and it’s still relevant to get companies into the most modernized data centre operations. But now, we’ve got some new elements emerging. First and foremost, we have a very new concept of consumption. How and where do public, private, and hybrid cloud play? As I adopt this architecture across multiple silos, how am I going to pull my data together? You’ve got this changing role at the top, needing to come up with new ideas, but you’ve got a team that may not have been equipped or given a mandate to find new opportunities because their job was to run the business. We now look at growing the business as a very different dynamic. How do I locate where my information is? How do I enrich that information so that it’s usable and functional? How do I activate it, blend it, and integrate it? And then how do I take the result of that to fundamentally monetize a new business model?

What are your recommendations to CIOs who are dealing with these challenges? What should be the key considerations?

From my point of view there are three elements to focus on. First and foremost, organizations should continue to look at data center modernization and cloud acceleration as a prime priority. Specifically, where can they break down the silos within their existing environment? How can they look at getting away from the shiny red toy syndrome and instead, look at a standardized and dependable model for delivering key services? The cloud acceleration piece says “Hey, where are opportunities to move workloads outside of the walls of the data centre? Where can they better suit the needs of the enterprise? How do you accelerate that? How do you find a better way to not only migrate, but manage them with a common framework across the public cloud and the private cloud?” That covers off data centre modernization and cloud acceleration.

When we move forward to intelligent data governance, we get into concepts like “I’ve got this data sitting across the organization. Some of it is in production. Some of it may be copies I’ve given to business, so they can innovate. Some of it may be data sets that were acquired through streaming or social channels. How do I now govern this? How do I drive compliance?” We’re seeing a lot of interest in this space. GDPR is obviously kicked off in Europe, affecting every European citizen. How do I make sure that my clients have the right to be forgotten -- not just during data gathering, but also the data that’s in production and copies of data that may have been sold to partners? GDPR and the compliance discussion becomes very important.

Finally, if I think about the third angle of it, CIOs are now thinking about how to resolve the promise of Big Data that didn’t get realized the first time around. Many of our clients built out a “Big Data” data lake and some of them played with Hadoop. In many cases, that data lake turned into a data swamp. Companies must start to look at the entire data pipeline; the process of connecting the structured databases, unstructured videos and photos, streaming data from the internet, and live sensors; and give them one flow – one 360-degree view of a customer, of a citizen, or of an asset – so that the businesses can push down the path toward innovation.

Knowing what needs to be done may be the easy part but figuring out how to get started is difficult. Any suggestions?

One of the obvious places to start is to look at the existing state. We tend to have an infrastructure view of things, but I would encourage people to look at their applications first. No one builds out infrastructure and data without an application, so it all starts there. What does that framework look like? Now think about the best place for that application to live. Should it live in a data centre? Should it live in a partner as a managed service? Should it live in a public cloud? Start making the judgment call about which application should live where, build a future vision of what that looks like, and then standardize, modernize, and automate as much as possible. You’ve now taken your “run the business” mandate and you’ve driven the maximum amount of efficiency possible. Now take the savings and start focussing on data enrichment, data activation, and data monetization.

How can a CIO take the framework of “data stairway to value” and apply it in their own environment?

We start off at the base with “store” and “protect”, and within that store and protect mandate how do I standardize the way in which I store data? You should look for organizations that can give you scale, flexibility, and breadth of portfolio. The protection part is also key. How do I leverage some of the current technology to start eliminating costs associated with DR while keeping my recovery time objectives where they need to be?

Most organizations have done a pretty good job at store and protect, but enrichment is where a lot of them have struggled. That’s really the second step of the data stairway to value. While databases are naturally enriched because they have indexes that sit within them, when I look at unstructured data and streaming data, which is where 90% of the growth is happening, most of that data is unusable. That’s because we have photos, videos, audio recordings from our call centres, and streaming data, all of which has not been indexed. The metadata that tells us what’s in those files has not been adequately captured. Because it’s not captured, many organizations are sitting on a mountain of unstructured data that requires a major undertaking to enrich it. My suggestion is that they should look at solutions such as HCP, a content platform that is able to enrich the metadata of files in path, making it much easier to develop value.

Now that I’ve brought down my operational cost in store and protect and I’ve enriched all my data, I now have the capability to move into activation. That means that once I have full access to where everything is, I can start to make connections to create a single view of a customer, citizen, or an asset. I can build automated connections leveraging technologies, such as Pentaho, to help create a much simpler and more object-oriented framework than what was available in the past.

Now that I’ve activated it, what’s interesting is the data will tell me where I can drive incremental value. We’ve seen some large stock exchanges who, after going through the store-protect-enrich-activate process, say “we were very large consumers of research in order to run our stock exchange, but when we connected our data we actually started a whole new service where we are now in the research business. We can get insights from our data that are not only marketable to the outside community but provide more value to us than some of the research that we used to pay millions of dollars for.”

If you could take an internal view of Hitachi which has been around for over 100 years, how does the company apply the concept of “data stairway to value” in its own journey to digital transformation?

That fundamentally gets to the core of what makes us unique. We talk about OT + IT = IoT. If I take a Hitachi business, such as our train business, what we’re seeing is that the traditional model of a government purchasing a train, financing it, and figuring out a working business model to charge their citizens to use that train is changing. Nowadays, governments have moved to a train-as-a-service model. If we look at UK Rail for instance, that model is very much predicated on when the train arrives in the station, Hitachi gets paid. Hitachi provides the software, infrastructure, services to operate that kind of environment while working closely with our key partners. We’re paid as a service. If I look at our energy business, more and more organizations, as they build new communities and new services, are looking at energy-as-a-service. One thing that becomes evident is that all the things I talked about, such as data enrichment, data activation, data monetization – they’re engines that power the transformation of our own business models. Without the technology from Hitachi Vantara, building out trains-as-a-service just can’t happen within the walls of Hitachi Rail. They would have to go build their own technologies and their own architecture. We’re able to stitch together blueprints that solve problems and then solution a course to activate new business models. As solutions are proven and delivered to the marketplace, we’re able to harvest the best models and offer them to the rest of the industries around the world.

When it comes to assets of an organization, people are more important than data. What’s your leadership style towards building talent?

Let me provide a high-level view of one of the philosophies I’ve lived through. As the company goes through the ebbs and flows of development and growth, they demand either builders or operators. When a company or industry is moving through significant transformational change, like what we’re seeing today with cloud, data, analytics, and IoT, you really require a significant amount of builder-DNA – folks that can come in and understand what needs to happen, take the appropriate steps to get it in motion, fail fast, watch the instrumentation of their business, and then adjust course. That’s very different from a mature business that’s operating on a defined principle. In that case, you generally would scale out operators – folks who are given a manual to do 10 things and do them well. The most exciting thing about Hitachi Vantara is that we have an opportunity to fulfill the builder mentality. When I joined two years ago, I focussed on hiring and investing in people who have a passion to build; people who really love to be empowered and do what it takes to not just grow the business but grow relationships with their customers and also grow their careers. My job is to ensure they understand the strategy, the KPIs of their internal and external customers, and support them in every way possible, but get out of their way to let them do their jobs.


Nasheen Liu is the Managing Partner and SVP, CIO Program Strategy at the IT Media Group spearheading the company’s business plan and leading our media and executive branding practice. She also chairs our CIO Advisory Board comprised of senior IT executives from industry and academia.

 

 

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