How business transformation can be viewed as a value engine

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or many organisations, the completion of a multi-year digital infrastructure project was supposed to signify victory: the end of ‘transformation’ and the beginning of a streamlined future. Yet, a growing number of businesses are finding themselves stalled, having substituted old problems with new, high-tech ones, and now find themselves asking a crucial, unsettling question: what do we do now?

Brian Herron, director at digital and customer insight consultancy Each&Other, says the term ‘digital transformation’ has become a little unfashionable of late.

“This is largely due to the fact that many of the vast, years-long infrastructure projects, launched when the term was at its peak, have now either gone live or simply become business as usual,” he said.

However, while terminology comes and goes, the core objectives remain constant: ensuring access and storage of data, maintaining the ability to work quickly, achieving cost saving, and in certain cases, “getting new, innovative products and services up and running faster”.

Stopping the stall

With the initial technological heavy lifting complete, many companies find themselves in an unexpected phase of stagnation. Herron highlights a crucial challenge, saying: “Post-technology implementation, you can see companies stall, or they spend so long on a transformation that when they come up for air they need to ask, what do they do now?”

This crisis of direction has prompted many to ask what happens next.

“A number of companies have approached us in recent months, particularly in financial services, healthcare and utilities, asking this,” he said. “There are two ways of dealing with that: asking are we really nailing the efficiencies we were promised and providing that slicker experience to customers, and future vision, so asking, how can we do more than continue business as usual with slightly improved processes?”

The issue, Herron said, is that many organisations are merely replicating their old ways of working with new tools.

“The bad news after all this investment is that companies are replicating things: they might get some efficiencies but they’re basically doing the same as they did before.”

From minimum to moat

To navigate this post-transformation landscape, Herron says, it makes sense to employ a strategic framework that shifts the focus away from infrastructure and toward sustained customer and business value. The overarching principle is that business transformation should be seen as an enabling tool rather than an endpoint.

The framework operates in three distinct layers: table stakes, brilliant basics, and standouts, which offer an opportunity to create a ‘moat’.

“The table stakes layer represents the absolute minimum digital product required to interact with customers,” he said. “Brilliant basics is the second layer, focused on operational excellence.”

Herron says that brilliant basics, which in practical terms means being slick in terms of business as usual, is crucial.

“The real benefit for the customer is often in that second layer, the brilliant basics layer. That might be as simple as something being easier to achieve than expected. The standout layer is important for attracting new customers [but] the issue is that what is standout in 2025 might be table stakes within a few years. Businesses are looking for that moat but, at the same time, so many businesses are not achieving brilliant basics,” he said.

Businesses are looking for that moat but, at the same time, so many businesses are not achieving brilliant basics

At the core of any transformation is the fact that a transformation is never a one-off thing. Indeed, the rise of artificial intelligence (AI) is only the latest technological development that both promises improvements to the top and bottom lines but, at the same time, can cause chaos internally.

As organisations look to the future, AI presents a fresh dilemma: major software companies are now offering sophisticated tools, and many come with enticing handshake deals.

However, caution is needed. Herron advocates for an in-house development approach. “With third-party products the costs are going to rise, and probably rise significantly, and by then you’re on the hook.”

Building AI-based tools in-house is not only more realistic than people may realise, Herron said, but also allows businesses to configure the technology and apply it directly to its specific needs.

Herron’s recommended approach is to get specific: in other words, to target problem areas. This targeted experimentation involves low-cost trials, with a proof of concept achievable in a few weeks, an evaluation in a few months, and a market-ready product in six months to a year.

Ultimately, Herron said, the real, enduring value is realised by actively using a framework like ‘table stakes, brilliant basics and standout’.

“If you do that then you can assess what things will look like in six months’ time, in a year’s time, in two years’ time. That’s where real value can be had,” he said.