Leslie Willcocks

Professor Emeritus

London School of Economics and Political Science

“Digital transformation is one of those terms where so many people have said it for so long. It's a buzz word in danger of losing meaning. What does digital transformation really mean?”

Well, it means what most people AREN’T doing! But they use the phrase to describe what they ARE doing. So, digital transformation is a whole organisation, radical restructuring of people, processes data and technology, to become a digital business, essentially. Most organisations are really having problems with that, because, as we mentioned before, they are heavily siloed. Those are the legacy silos of the organisation because the organisation was set up to run in a different way, and then you bring in technologies which allow you to run in a different way again. But you need to reorganise and restructure in order to allow those technologies to reveal their potential. So that's what digital transformation is to us—breaking those silos down and utilising the potential of digital technology to become digitally-propelled businesses.

But we think a lot of people have redefined it. So, for example in the downturn in 2023, all the signs suggested that organisations were really cutting down on technology investments, including the hi-tech businesses which had over-expanded, thinking that the technology would take off. The COVID-19 experience gave them positive, warm signals about the role of technology in a future economy. By early 2023 we found businesses talking more about cost transformation through digital technologies. And that's the way that digital transformation was being reconfigured for most organisations during 2023. The terminology has been the same, but the purpose morphed into: how can we use digital transformations to keep our costs under control and achieve economies and process improvement without really doing those fantastic strategic things or using the top leading-edge technologies that people have been trying to sell us for the previous decade.Such an executive team will fund and resource the technology as a long-term strategic investment to build a digital business platform that delivers necessary internal changes much faster, can support new product/service and can seize business opportunities as they arise.

So that's what where we were by mid–2023, Even the go-head companies, the leaders, seemed to be coming back into defining digital transformation in practice as cost transformation. So, they were seeing a role for RPA, intelligent automation, and AI, but it has been much more redirected into narrow goals.

In early 2023 we reviewed how representative organisations in our KCP database were dealing with current economic conditions. We found that organisations had responded to post-COVID-19 conditions in four ways. By 2023, some 20 percent were ‘Sweating the Assets’—that is, making the most of existing technologies to achieve short-term business survival goals, including customer retention, cash flow maintenance, and cost cutting. The figure for July 2022 had been 35 percent. Meanwhile, another 45 percent (30 percent in July 2022) were in a more advantageous position, pursuing the short-term goal of ‘Underpinning Today’s Business’ towards which new automation and digital technology investments were directed.

A further 20 percent were ‘Slowing the Digital Strategy’—they had a long-term digital strategy in place, but it was proceeding at a slower rate, and some of the new digital investments were being channelled into short-term objectives. Only 15 percent of organisations were ‘Adapting Strategy and Building Resilience’. These had a long-term, adaptive strategy and were future-proofing and building resilience with large new digital investments.

What can we learn from this, going forward? Clearly one can see business imperatives driving technology investments—no bad thing. But short-termism in the digital arena can be dangerous in eroding resilience and sustainability the next time economic conditions are adverse. Moreover, we think it is leading to a digital divide in each sector, creating competitive advantage for the long-term digital investors that could become irreversible. Digital leaders are emerging representing 15–24 percent of organisations, depending on sector. Several studies combined with our own work show the general picture that they gain something like 20 percent profit gains from their digital investments, representing twice more than digital laggards. They also get 20–25 percent more revenue, higher market valuations than their peers, and offer superior dividends.

A general finding is that this performance gap between the best and worst digital performers was widening between 2018 and 2023. It’s not just that digital leaders are investing more strategically and on a greater scale. They are also improving faster than their competitors in their ability to do digital. Thus studies, including our own, show that they test ideas more quickly than before, move faster on digital than before, are scaling over five-year periods faster than before, whilst improving their digital execution capabilities along the way. This trend will continue, we suggest, unless organisations seriously adopt the management guidelines and key digital capabilities we detail throughout this book.

Now intelligent automation/’AI’ applications generally require large data training sets, and thereafter are set up to deal with massive amounts of variable data. Processing power and memory race to keep up. If a great deal of data is not fit for purpose, then this bad data will create misleading algorithms and results. The idea that very big samples solve the problem—what is called ‘Big Data’—as used in ChatGPT, for example, is quite a naïve view of the statistics involved. It is not really possible to correct for bad data. And, as we said before, the dirty secret of Big Data is that most data is dirty.

“Looking ahead, where is the sweet spot that can make automation and digital transformation work?”

This needs a complicated answer, rather than a clear one, but we think it's about where you start from. We recall, back in the 1990s, there was a big thing about business process reengineering, and radical reform. It was overstated in terms of the radical ‘digging up the roots’ change required, but we do think that you have to start with the processes of the organisation—identify what the core processes are, and how you're going to digitise them, and then the other processes as well.

So, for us, it begins with process discovery, really. What are the core processes given the sort of business we want, and how do we utilise digital technologies to leverage those processes? And how do we organise our data to run those processes? That, to us, is the fundamental starting point. And how do you do that in an organisation? We don't think you can do it from a bottom-up approach, but we don't think you can do it from a top-down approach—which is where radical, business process reengineering went wrong. A 75 percent failure rate tells you something about radical re-engineering, but recall also that digital transformation records a 2023 ‘failure’ rate of around 65 percent. We think you have to do it from the middle. Because somehow, it's a shorter communication path, and it links with the bottom-up people who are saying, “Well, we're really having problems here,” and the top-down, people saying, “Well, strategically, we need to go here,” so you then say, “Well, what processes do we need in place?” and you invent some form of governance that allows you to do process discovery in different parts of the business. What are key business processes to deliver on your business imperatives? And then you start organising your data and your technology around that.

Robotic process automation has been—and in some places still is being—sold as a bottom-up approach, and all too frequently it's a one-off process. You know: “We've automated this and look at the benefits we're getting from this process. So, let's look at another process!” But do we ever look at it from a more holistic perspective? People tend to automate the processes easiest to automate first, but is it more strategic to look at the ones that are going to give you the most value?