Here is an excerpt from an article written by Thomas H. Davenport and Thomas C. Redman for Harvard Business Review and the HBR Blog Network. To read the complete article, check out the wealth of free resources, obtain subscription information, and receive HBR email alerts, please click here.
Credit: Jorg Greuel/Getty Images
* * *
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. Digital transformation 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 coordinating a far greater range of effort than most leaders appreciate. A poor showing in any one of four inter-related domains — technology, data, process, or organizational 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. Of course, even the best talent does not guarantee success. But a lack of it almost guarantees failure.
Let’s explore the talent needed in each of the [first two] domains in turn.
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 only resolve these issues with people who have 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 rigors 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, leveraging proprietary data, and integrating 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 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 at the front lines of organizations 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 transformation. It also means helping front-line workers to improve their own work processes and tasks such that they create data correctly.
* * *
Here is a direct link to the complete article
Thomas H. Davenport is the President’s Distinguished Professor in Management and Information Technology at Babson College, a research fellow at the MIT Initiative on the Digital Economy, and a senior adviser at Deloitte Analytics. He is the author of over a dozen management books, most recently Only Humans Need Apply: Winners and Losers in the Age of Smart Machines and The AI Advantage.
Thomas C. Redman, “the Data Doc,” is President of Data Quality Solutions. He helps companies and people, including start-ups, multinationals, executives, and leaders at all levels, chart their courses to data-driven futures. He places special emphasis on quality, analytics, and organizational capabilities.