Delivering an Innovative Vision from the Top - Spotlight on Paul Twigg

To deliver innovation and value, data leaders need to implement a cohesive vision from the top, argues Paul Twigg, Chief Technology Officer at Digital Commerce Bank. We spoke to Paul ahead of Corinium's CDAO Canada summit in Toronto on March 26th. Here's what he had to say:  

How does a top-down approach in data management strategy enhance efficiency and innovation in an organization?

"As an IT leader, there's got to be a vision from the top. Enacting that vision and making it understood is key to preventing the perception that IT is simply a cost center.

For us, that means creating data products that put data into the hands of people who need it from the top to the bottom of our organization. Ultimately, we have been able to innovate to deliver something that generates revenue, saves money, and benefits the organization.

Perhaps most of all data plays an important role in decision-making. In our business, we’ve certainly had occasions where we've been able to review decisions with our executive leadership. Of course, there are a lot of reasons that decisions are made in an organization, but having the data available to back those decisions up can be immensely valuable.

To achieve this, it’s essential to match that vision with the expectations of senior leaders in the business and how your vision can meet business requirements."

What are the key challenges in integrating various data flows within an organization, and how can they be overcome?

"Number one is data security. As an example, we’re working in a highly regulated industry so we can't send certain types of data beyond our PCI-certified infrastructure, and that makes reporting quite hard for some kinds of data.

In the modern world where we measure data in petabytes, we have to wrestle with how we effectively move and transform data to a place where it is effectively consumable by the people who need it. To do this we have to look at the aggregates of data to be able to distill that information in an effective way that is also compliant with relevant regulations.

Much of this will depend on the kind of data infrastructure that your organization uses. Does your data live in the cloud or is it on-premise? Many organizations operate some kind of hybrid data model. In fact, even if a business thinks they are fully in the cloud, I guarantee someone has an Excel workbook with data in it somewhere."

Why is aligning data management strategies with organizational objectives critical, and how do you ensure this alignment?

"Well-run IT organizations excel at both operations and innovation. My perspective is that if you have to get permission to innovate then you’re probably not going to innovate.

The reality is that if I put all of my data people inside a little box and don’t let them operate outside of those confines then I am not going to inspire them to come up with new ideas.

 I want my data people to be able to wake up and say, ‘Hey, I saw a video on Azure Arc yesterday and I think we should have a look at it because we've got a hybrid set of data’, as an example. Or to suggest ways that we can work with clients to improve their experiences. Let's innovate with them.

 We've just been through a transformation as an organization in the last few months. We’re a fintech firm that moves money. That’s what we do and we do it really well. Previously, everybody was getting fixed reporting but now we’ve got a whole new service line in being able to allocate data to clients.

 Now they can get something bespoke. Something that can save them thousands of dollars of development. And they are willing to pay for it.

 This is the practical effect of innovating around aligning data management strategies with business priorities."

What emerging trends do you foresee in data management, and how should organizations prepare for them?

"We saw the beginning of a major trend in data last year. Large language models (LLMs) have taken off over the last 12 months.

If I were to make a prediction, I expect to see an increase in the use of on-premise domain-specific LLM systems in the coming year. And specifically, in the rise of software as a service-enabled domain-specific LLMs.

The technology behind LLMs is amazingly useful, so if we start applying domain-specific knowledge to the technology of an LLM, all of a sudden, we can get something that's extremely powerful.

For example, while the regulatory environment in banking is quite different in Canada and the USA they share some significant challenges.

 Every single bank in the US has a fraud module in its core banking system and a dedicated fraud team. Still, globally there are trillions of dollars of fraud in the banking system every year.

But with a domain-specific LLM focused on financial fraud banks could in theory share data with other banks at an aggregated level so no personal information is shared. This will allow banks to better understand the patterns of fraud and reduce or even eliminate a cost that weighs heavily on the global banking industry."

Want to learn more?

Paul will be speaking at CDAO Canada on March 26th-27th, 2024 in Toronto. Join him and many other data and analytics leaders to learn about the latest trends and opportunities in the industry. Register to attend here.