When businesses the world over are spending $1.3 trillion a year on digital transformation according to the International Data Corporation, you might expect dramatic results. But the return on that investment has often proved disappointing – and one man thinks he knows why.
“Too many businesses do not understand the value of their data assets,” says Herman Heyns, CEO and co-founder of Anmut Consulting. “That makes it very difficult to increase that value – to identify where the return on your investment is likely to be greatest.”
Heyns launched Anmut after a long career working at blue-chip consulting firms such as EY and Accenture, advising clients on how to put their data to work. “What I realised over time was that while almost every CEO we worked with recognised the importance of data, very few of them felt they were executing well on their efforts to make that data pay.”
The problem, Heyns believes, is that businesses are looking in the wrong places as they search for the holy grail. He likens the value chain of data and analytics to the oil industry, where exploration is the foundation for everything else that follows – without an oil strike, after all, there is nothing to refine and no end product to sell. In the oil sector, this has naturally meant investment has flowed into exploration, with the aim of maximising the value of oil companies’ assets.
The penny has not dropped in the same way when it comes to data, Heynes argues. Research conducted by Anmut suggests that 88% of businesses are devoting most of their budget to the technologies needed to exploit data, rather than to the data itself. But rubbish going into those technologies means rubbish going out; too many businesses are failing to strike oil and therefore have nothing useful to work with.
“Our role is to help businesses understand what their data assets are and how they are linked to the value of the company,” Heynes said. “Once we’ve done that, we can begin to think about how to increase the value of those assets.” Businesses are very used to investing in physical assets in order to drive their value higher, but have not got their heads around the idea that the same applies to their data assets, he suggests. Once Anmut is able to show them just how much value is locked up in those assets – and which data has the most value – the idea sinks in.
It is a different way of thinking. In Anmut’s research, 91% of business leaders said data was critical for their success, but only 67% said their board regarded data as a material asset – and just 34% claimed to be managing data to the same standard as other assets.
There are some good reasons for this. One problem is that financial accounting rules make it very difficult to capitalise the value of data on a balance sheet, so businesses simply aren’t used to looking it in those terms.
Another issue is that valuing data accurately – each different set of data that each business holds – is difficult. Anmut has invested heavily in sophisticated tools that harness neural nets and artificial intelligence, as well as thousands of its own data points, to make those valuations with more precision. It also helps that Heyns’ co-founder is Professor Andy Neely, a Pro-Vice-Chancellor at Cambridge University with years of experience of transformation projects.
To be clear, Anmut is not suggesting that businesses have wasted their money with the substantial investments they have already made in transformation, or that they should give up on analytics tools and similar technologies. “But when this investment is producing little discernible change, something is wrong,” he argues.
The missing piece in the jigsaw, Heyns and Neely argue, is a clear-headed focus on which data matters most and how to ensure this data is of the highest quality. Feeding such data into the tools on which businesses have spent big will produce dramatic results, says Heyns – the step-change in performance that digital transformation has promised for so long.
In facilitating that transition, of course, Anmut itself is well-placed to benefit. It is slowly pivoting from a business model built on consulting services to a platform structure in which it sells its technology through software as a service. And Heyns doesn’t expect the business to replace the consultants he once worked for; rather, it will ensure his former employers’ clients have the data they need to get the value they deserve from such relationships.
Strikingly, Heyns believes the data revolution is only just beginning. “The comparison to the oil industry is a valid one – in its early years, the oil sector struggled to standardise its products and to define its value; as it matured, it became so powerful that it shaped geo-political forces around it,” he argues. “The same thing will happen with data.”
One early example of the phenomenon is the way in which vaccine manufacturers have worked with countries such as Israel in the battle against Covid-19. Israel’s willingness to given those manufacturers access to huge amounts of data about the impacts of the vaccine on their population helped it clinch supplies, so valuable is that information as the programme rolls out globally. This is just the start, Heyns argues – but first, organisations have to understand the value of their asset.