Want your business to go digital? You need the right technology, data and process people

If you want your business to go digital, you need to pull together the right team.

Assembling the right team of technology, data and process people may be the most important step a company contemplating digital transformation can take.

Over the years, we’ve participated in, advised on or studied hundreds of digital transformations. In doing so, we’ve gained a perspective on just how difficult true digital transformation really is and what it takes to succeed. It is not for the faint of heart — the unfortunate ­reality is that, to date, many such efforts, like transformation programs in general, have failed. Success requires bringing together and co-ordinating a far greater range of efforts than most leaders appreciate. A poor showing in any one of four interrelated domains — technology, data, process or organisational change capability — can scuttle an otherwise well-conceived transformation. The really important stuff, from creating and communicating a compelling vision, to crafting a plan and adjusting it on the fly, to slogging through the details, is all about people.

More than anything else, digital transformation requires talent. Indeed, assembling the right team of technology, data and process people who can work together — with a strong leader who can bring about change — may be the single most important step that a company contemplating digital transformation can take.

Technology

From the internet of things, to blockchain, to data lakes, to artificial intelligence, the raw potential of emerging technologies is staggering. And while many of these are becoming easier to use, understanding how any particular technology contributes to transformational opportunity, adapting that technology to the specific needs of the business and integrating it with existing systems is extremely complex. Complicating matters, most companies have enormous technical debt; embedded legacy technologies that are difficult to change. You can resolve these issues only with people who possess technological depth and breadth, and the ability to work hand in hand with the business.

Challenging as these difficulties are, an even more critical issue is that many business people have lost faith in their IT department’s ability to drive major change, as many IT functions are primarily focused on “keeping the lights on”. Eventually, however, digital transformation must incorporate institutional IT, so rebuilding trust is essential. This means that technologists must provide, and demonstrate, business value with every technology innovation. Thus, leaders of the technology domain must be great communicators, and they must have the strategic sense to make technological choices that balance innovation and dealing with technical debt.

Data

The unfortunate reality is that at many companies today, most data is not up to basic standards, and the rigours of transformation require much better data quality and analytics. Transformation almost certainly involves understanding new types of unstructured data (e.g., a driver-supplied picture of damage to a car), massive quantities of data external to your company, the leveraging of proprietary data and the integration of everything together, all while shedding enormous quantities of data that have never been (and never will be) used. Data presents an interesting paradox: most companies know data is important and they know the quality is bad, yet they waste enormous resources by failing to put the proper roles and responsibilities in place. They often blame their IT functions for all these failures. As with technology, you need talent with both great breadth and depth in data. Even more important is the ability to convince large numbers of people to take on new roles as data customers and data creators. This means thinking through and communicating the data they need now and the data they’ll need after the transformation. It also means helping frontline workers to improve their own work processes and tasks such that they create data correctly.

Process

Transformation requires an end-to-end mindset, a rethinking of ways to meet customer needs, seamless connection of work activities and the ability to manage across different silos going forward. A process orientation is a natural fit with these needs. But many have found process management — horizontally, across silos and focused on customers — difficult to reconcile with traditional hierarchical thinking. As a result, this powerful concept has languished. Without it, transformation is reduced to a ­series of incremental improvements, important and helpful, but not truly transformative. In building talent in this domain, look for the ability to “herd cats” — aligning silos in the direction of the customer to improve existing processes and design new ones, along with a strategic sense that knows when ­incremental process improvement is sufficient and when radical process re-engineering is necessary.

Change capability

In this domain we include leadership, teamwork, courage, emotional intelligence and other elements of change management. Fortunately, much has been written about this domain for many years, so we won’t review it here, other than to note that anyone responsible for digital transformation must be well-versed in the area. While we have no firm evidence to support this, it seems that those who gravitate towards technology, data and process are somewhat less likely to embrace the human side of change. We have urged leaders to seek those with excellent people skills. If you are unable to find them, a good ­alternative is to put some “purple ­people”, those able to work on both sides, on the transformation team.

Pulling it altogether

Technology is the engine of digital transformation, data is the fuel, process is the guidance system and organisational change capability is the landing gear. You need them all, and they must function well together.

Consider the “our systems don’t talk” problem, which bedevils most companies and is anathema to digital transformation. But in which domain does it belong? As described above, it is a technical problem, but it also leads to enormous process inefficiencies. Yet it stems from a lack of solid data architecture, and it may involve organisational structure and politics issues that are difficult to change. So one could argue that any domain should take the lead. But the best solution involves the four working together. Finally, work on technology, data and process must proceed in an appropriate sequence. There is no sense automating a process that doesn’t work, so in many cases, process improvement or re-engineering must come first. On the other hand, some transformations will feature large doses of artificial intelligence. Since bad data stymies development and deployment of good AI models, work on data should come first. Start with end goals, then develop the sequence best suited to achieving them.

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Thomas H. Davenport is a professor at Babson College, a research fellow at the MIT Initiative on the Digital Economy. Thomas C. Redman is president of Data Quality Solutions.
Copyright Harvard Business Reveiw 2020/Distrubted by News York Times Syndicate