Elnur - stock.adobe.com

Setting the high bar in digital transformation

Roel Louwhoff, Standard Chartered’s chief transformation, technology and operations officer, outlines what it takes for the company to become a client-focused, data-driven bank

Roel Louwhoff, Standard Chartered’s chief transformation, technology and operations officer, believes in setting the bar high in areas such as availability and implementation speed to get his teams out of their comfort zones.

Efforts are also underway to build a pool of full-stack engineers who not only build applications, but are also responsible for maintaining them while working with business teams to deliver projects in shorter cycles, tearing down organisational silos.

The focus on people and change management is a key tenet in Standard Chartered’s transformation strategy that involves, among other things, technology consolidation, skills development and tapping artificial intelligence (AI) to drive business impact and achieve its goal of becoming a client-focused, data-driven bank.

In an interview with Computer Weekly in Singapore, Louwhoff, whose career has spanned companies such as Accenture, BT and ING Bank, assessed Standard Chartered’s transformation strategy and how he is leading the bank to navigate the fast-moving technology landscape.

Standard Chartered has been active in leveraging cloud, automation and other capabilities. Can you tell us more about your overall technology strategy and what you’d want to achieve with it?

Louwhoff: You started with asking the question in the right way – technology is not the target, but the enabler to deliver what we want to become, which is to be a client-focused, data-driven digital bank.

Those are only a few words, but they also mean a lot. By being client-focused, we want to start with the client in mind and then work backwards to cater to the needs of clients in specific countries for specific products.

Key to our strategy are technology platforms that cut across the organisation where there doesn’t need to be any differentiation from a business unit, product or process perspective. The easiest way to think about that is the internet or a data service for which no one should care about where it comes from, whether it’s from the cloud or your own datacentres. You just need something that’s reliable.

Part of our platform strategy is what we call the value cloud platform. That means instead of moving everything to cloud, we’d only move relevant workloads that fit our needs to cloud. Other things can remain on-premise in markets where regulators require data to be residing in the country.

What we try to do with benchmarking is to set an extremely high bar on where we need to be, whether it's availability or implementation speed. We may not get there as there’s no organisation that’s great at everything, but if that's our aspiration, we can start pushing people to the limit
Roel Louwhoff, Standard Chartered

Then, we work upwards to application and middleware layers, and at the edge where the customer is. The more we show differentiation for the customer, the more impact we’ll have from our overall strategy. We are focusing more on the lower layers at this point in time, but we will start focusing on the front-end capabilities towards the end of this year.

What sorts of capabilities would those be, specifically those at the application level?

To give you an idea, we had five different CRM [customer relationship management] platforms. After a long process, which took months, we came to an agreement that we’d just have one CRM platform. The considerations are very simple: business owners provide the requirements and it’s up to tech to come up with the right solutions.

What I’ve learned in my previous organisations is that most technologies will not be used to their full capacity. When I was at Accenture, people started losing faith that huge investments in big technology programmes were going to deliver results. Then, they introduced two words which I use quite often: technology assimilation.

Technology assimilation is about bringing the technologies you have to the forefront and ingraining them across the organisation. The more assimilated they are, the higher your return on investment (ROI). The ROI from five CRM platforms is going to be very low, but if you have just one CRM platform, it can be higher. Even then, you’d still need a programme to drive what you need to do in order to get it to meet 70-80% of your needs. Those are the discussions we’re having now.

How are you making sure that whatever you’re driving from a technology perspective is aligned with the goals of the business? Are there common metrics for business and IT teams?

When we launched our strategy in December 2022, we came up with 45 different KPIs [key performance indicators] and identified those we wanted to achieve by the end of 2023 and 2024. Those KPIs arose out of discussions we had with the business.

For instance, when it comes to the KPI for availability, that number would vary depending on who you ask. The technology person responsible for availability probably wants it to be lower because it’s easier to achieve. But an operations person would want 100% availability because that means there are fewer things to work on. That’s what the business wants as well, but the trade-off to get to 100% would require double the infrastructure, so your cost goes out of the window. So, you have to have a debate about where we are today and where we want to be. Those are the sorts of discussions we have with the business.

But we cannot achieve the KPIs as a technology organisation alone. Operations and business teams will have different views, and so we’re moving to a more agile way of working by bringing business and DevOps teams together to deliver in shorter cycles. It’s a new phenomenon in the bank and it’s against what we’ve done for over 160 years. That’s why we’re still on that transformation journey, which is predominantly around culture. How do we work together? We have the technology, funds and great people. We have every vendor you can think of, and some of them are fantastic and want to help. It’s about how we move all of this together.

This has got to do with mindset as well, right? How do you get people out of their comfort zones?

There are a couple of things, such as benchmarking, which people find extremely annoying, but it’s extremely effective as well. When they say they’ve made progress from what they’ve done two years ago, it’s not relevant. To be relevant, you need to be where your competition is. So, what we try to do with benchmarking is set an extremely high bar on where we need to be, whether it’s availability or implementation speed. We may not get there, as there’s no organisation that’s great at everything, but if that’s our aspiration, we can start pushing people to the limit. Instead of having incremental change, you get transformational change.

The second thing is we try to get tech people to be responsible for not only building applications, but also maintaining them. That concept has been around in many industries, but it’s adopted to a lesser degree in financial services. That means you have full-stack engineers who are also responsible for dealing with issues. Previously, people were building things and throwing them over the wall to those who maintain them. The maintainers said the builders have no clue about what was built, while the builders said the maintainers don’t know how the tech works. There was always conflict, and so by giving people end-to-end responsibility, they get the bigger picture and will take up more ownership.

Now, let’s get into some of the developments around AI. There’s so much hype around AI, and it’s easy to fall into the trap of deploying it for everything you do, but obviously nobody has unlimited budget and capability, so you need to prioritise. What is your thinking around that, particularly the risks that come with generative AI (GenAI)?

Let’s start with the fact that we’ve been working with machine learning and AI for a long time. It’s not new and we have developed some skill sets. But now that we’re moving to the next level, there are things we need to consider.

First of all, a bank needs to be safe and secure. People go to banks because they trust them. It’s where their money is, so we cannot expose their data to the outside world, and we cannot expose the data in some of the AI models internally as well. We need to come up with a way that’s almost like a sandbox where we can make sure what we are developing is working, and also import some external models that are impossible to build on our own with the same level of sophistication. That trade-off is still something we work on all the time to see what we can or can’t do.

Operations and business teams will have different views, and so we’re moving to a more agile way of working by bringing business and DevOps teams together to deliver in shorter cycles. It’s new phenomenon in the bank and it’s against what we’ve done for over 160 years
Roel Louwhoff, Standard Chartered

As for generative AI, some members of our board, advisory committee and the global management team recently visited Silicon Valley to look at where the technology is going and what we need to do. We talked to the big tech companies, financial services organisations, and also Stanford University about AI ethics and responsible AI.

The high-level conclusions we came back with are firstly, like everyone jumping on the bandwagon, we’ve accumulated over 200 use cases for GenAI. But we realised it’s not doable and too expensive. And so, we focused on use cases that are going to give us the most impact and scale them up.

Second, after having met the likes of Google, Microsoft, Cisco, Palo Alto Networks, Cisco and Visa, it’s clear that GenAI is a journey and not a destination. It is moving so rapidly that there was no organisation that claimed to have a return on investment. But you cannot leave that train – you have to be on the train and do it in such a way that you will learn, so that when the real big move comes along, you’ll know what to do.

That means you’re almost like a fast follower instead of being the first to adopt the technology. I try to understand what that means for us in terms of use cases and how to implement them. You don’t have to use GenAI to solve every problem. It’s not the hammer that you’re going use to hit every nail.

At the same time, we’re working with some of the bigger vendors to adopt some of their GenAI tools in a restricted way with a select group of people. We’re also going to roll out some of the tools to the whole organisation, assuming we can reach the right agreements with the vendors on cost. One of the main messages from the organisations we met in Silicon Valley was that GenAI is way more expensive than they thought it would be.

How are you upskilling teams to keep up with developments in AI and other emerging technologies?  

We truly believe in learning and progression, and bringing the organisation up to the next level. About four to five years ago, we started a technology training organisation that trains engineers who are encouraged to spend part of their total work time on training. We want them to get better – they can select the appropriate courses and if there’s some cost involved, their manager needs to sign off.

So, if you’re an engineer for a certain application, and you want to do something for another application that has nothing to do with you and we don’t see a career path for you, then it’s going to be a difficult conversation. But if it helps you to progress and move to something adjacent, then that’s absolutely something you can do.

We’re now gearing up to be a skills-based organisation. We have identified what skills we currently have and what other skills we need to be a client-focused, data-driven digital bank, as well as the training and the people we need. For example, we don’t have customer journey experts and we are making sure we will have them. They are focused on what we need to do in order to be client-focused, and they need to be able to pull people with technology, operations, data and risk backgrounds together to achieve that goal.

That also means the creation of roles that didn’t exist.

You’re absolutely right, and 20 years ago, being current meant you had to update your skills every 10 years. That’s not the case anymore with GenAI, which is evolving so quickly.

Now, have we completely figured out how we can change and move that quickly? To be honest, we haven’t, but as a skills-based organisation, we know where we’re going. For instance, we’re looking at our engineering folks to understand what level they need to be in terms of technical and leadership capabilities, and helping them get there. And if they have skills they can apply elsewhere, we’ll try to get them into those roles. Once more, this is a cultural transformation, not a technical transformation.

What’s at the top of your mind while you’re at work each day?

When you have a strategy and an implementation path that we have, it’s easy to accumulate all kinds of things to do. You’d want to control and drive these things, but that’s not how the world works. It’s too big, so how do you focus?

I mentioned about identifying the next level of impact, but I find that to be difficult sometimes because the impact can be indirect. Sometimes having indirect impact will get you way more direct impact, but it only comes two months later as opposed to focusing on something that will have a direct impact today, but it’s only in the short-term, and not in the longer term. And so, my answer would be prioritising what we need to work on in the short term and the longer term, and how that journey fits together.

Read more about IT in APAC

Read more on IT strategy

Data Center
Data Management