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As the London Stock Exchange Group has gone global, IT has had to evolve in both familiar and organization-specific ways.
By Chris Corrado , Chief Operating Officer and Chief Information Officer, London Stock Exchange Group
We all know that IT has grown it’s focus in recent years, from “error reducer” and “money saver” (principally through automation) to more of an enabler of business models and therefore much more embedded in helping to set business strategy. And IT at the London Stock Exchange is no exception to that transition.
But IT here has also grown in capabilities because the LSE Group has changed. When you’re running an exchange that provides a significant amount of the capital formation for a country, it’s as if you are part of the fabric of that country – there’s so much tied to keeping the infrastructure safe, secure, and being nearly perfect at what you do. You really want to get it right and make it stay right, because there’s so much at stake, including the sheer pride involved.
When you expand, as we have, to multiple exchanges, multiple countries, and new businesses and business models, you create a lot of complexity. It scares the daylights out of people who are used to something that is relatively easy to get your arms around – not that what they’ve been doing is easy, but conceptually it’s easy to understand the underlying rationale for expansion.
Learning to love change
What we do now is very complex – Since 2009, LSEG has completed and integrated 23 acquisitions, which requires a different kind of IT professional. These days, when I hire, I look for people who love change and see it as an opportunity to learn new and important skills. And I’ve realized over the years that not everybody feels this way about change.
I try to find people who embrace change because they always want to work on that next project or task that will make things better. I look for people who are inspired but not careless: You need to have a good execution capability that dots all the I’s, and crosses all the T’s. You’d better have integrated and institutionalized the last thing you did, because if not, you’re just creating a mound of complexity and potential fragility.
At the same time, you have to be willing to learn, because if you believe you’re a know-it-all in the midst of growing complexity, that’s a dangerous place to be. You have to respect people who’ve been doing this for a while. You have to listen and learn, understand the constraints, what is working and what may not be working and wait to do things until you have enough confidence that what you’re going to do won’t hurt anything. I call it “sitting on my hands” for a period of time.
Because we’re now truly global and are tapping into staff and capabilities in different cultures around the world, we may have to approach our jobs differently. First and foremost, you have to appreciate the cultural sensitivities. What works in Chennai may not work in Sri Lanka. To bring out the best in people, you have to understand what’s desirable and acceptable behavior in the culture you are now working with. This is part of the continuous learning process that reduces any potential resistance and enables change to be successful.
We also have to be asking ourselves what innovative moves and investments we need to make to stay ahead of the competition and how we can fund them. With constraints on spending, the funding of those initiatives may have to come from reducing the cost of supporting the current environment, which may entail stopping some existing services and initiatives that may not be as important as the newer ones.
This is especially true for us, because the LSE Group is different from other “market infrastructures,” in that we’re not solely vertically integrated. We have embarked upon an “open access” strategy for market infrastructure, which means that clients can do business with us in either a “bundled” (that is, vertically integrated) or “unbundled” fashion. Our competitors, companies such as CME and ICE in the US, typically operate in a vertically integrated fashion only, thereby requiring that clients use their respective vertically integrated stacks.
Our three major businesses—index and analytics, clearing businesses, and stock exchanges—comprise the LSEG today, in conjunction with a technology business that enables those businesses. The IT operating model used to support LSEG, consists of CIOs that interface with each of the major businesses; a shared services group providing application support; infrastructure services; property; procurement; HR and Finance. We also have capabilities that include a firm-wide PMO, CTO, CISO, and our LSEG Technologies unit, which provides strategic software services. I may be the ringleader of all this but it’s the team who make it work.
Our latest innovation is the creation of the Emerging Technology Group. It’s a team of approximately ten staff globally, run by our CTO, whose mission is to explore new technology by testing it’s application to a variety of business problems and opportunities. The idea is to run “strategic experiments” through partnerships with some of our key suppliers in new areas of opportunity. Right now, the group is focusing on analytics, distributed ledger technology, AI, and large-scale data manipulation.
Most of the ideas we’re evaluating through testing begin with a business idea or with a problem that a client, business area, or key supplier brings to our attention. We’re fortunate enough to have trusted relationships with clients and a great brand in the market. This makes it easier to move from ideas into agile experiments—proofs of concept—not only with clients but also with existing and potential suppliers of technology, who are often knocking on our door to sell us things. Those contributing to the tests/experiments in the form of POCs often are happy to have skin in the game, ensuring that there is true commitment. The logistics are typically a six-to-eight week experiment that teaches us something about an important technology, and that may or may not lead to a business opportunity for us collectively in the future.
This team has helped us make some important advances. We are implementing a truly distributed database that should prove to be highly scalable and reliable. Very few companies have done that. A distributed database is hard to come by: the architecture has to be foolproof, especially when you’re running data businesses, stock exchanges, and securities clearing businesses.
We’ve recently run a proof-of-concept data lake to bolster the LSE’s stock market surveillance capability. It’s built out of open source technology and includes some algorithms that we’ve developed as well as purchased, and it makes it easier to detect unusual activity anywhere in the system. It enables our surveillance analysts to be more productive, making them smarter and their jobs easier.
There are probably a dozen other areas where we could also be experimenting with artificial intelligence and sooner or later we will. I can’t think of a way we work where AI won’t benefit us at some point down the road.
Of course we’re doing work with blockchain technology, focused on the Hyperledger open source implementation of distributed ledger functionality. We’ve selected Hyperledger due to the fact that it is open source and it’s not clear yet which of the proprietary solutions will become more standardized. We’ve done a few proofs of concept which include trade reconciliation, and digitized stock certificates, to name a few. Overall, it’s a very immature area and there’s a lot of development and experimentation that’s still going to take place, where one can see broad applicability over time. As with any speculative investment, there will be numerous winners and losers. We don’t see ourselves making a series of relatively small investments in tech or fintech companies that are part of the blockchain/DLT ecosystem. Rather, we want to implement solutions in regulated entities as a way of proving the technology and operating model. Since we do not see ourselves as a venture capital firm; we make fewer bets but try to bet on surer investments. For an immature area like blockchain, open source is logical, as it kind of hedges your risk in the long term.
Beyond the cloud
Of course, we’re also active with the cloud, but I don’t consider it advanced technology or an advanced operating model these days. That’s not to say it’s unimportant: the cloud really levels the playing field for small and large companies in computing capabilities, analytical tools, and development tools. Its generic capability puts frictionless, virtually unlimited computing capacity at your fingertips. Now the speed at which you can obtain IT is no longer a constraint. The tools are there. The keys are there. The infrastructure is there. The environments are there. All the old constraints are gone. The cloud speeds everything up a lot for all of us in IT; we’re like a carpenter who was using a hammer and now has a nail gun.
This has shifted the source of competitive advantage. When carpentry no longer gives you an edge, architecture matters more. In IT, it comes down to how you aggregate and analyze data. What analytics are you bringing to bear, and against what data streams, that will make you smarter and empower you to make decisions faster? And build faster without making mistakes?
In the end, of course, making the right choices about what to do with your data depends on the strength of your team, and that in turn depends on the strength of your vision: you really need a set of objectives and a feasible, meaningful, mission that people can believe in and work hard to achieve.
Today, IT isn’t just about making things more efficient; it’s about helping to set business strategy.
In an environment of transformation, hire people who love change—and not everybody does.
Six to eight-week experiments are a great way to study a technology.