Over the years, numerous digital transformations have occurred. By doing so, we’ve gained a perspective on how complex a real digital transformation really is and what it takes to succeed. Digital transformation isn’t for the faint-hearted — the unfortunate reality is that so far, many such attempts have failed, such as transformation programs in general.
Success requires a far greater range of effort to be put together and coordinated than most leaders appreciate. A poor performance in any of the four inter-related domains — technology, data, process, or organizational change capabilities, can scuttle a transformation that is otherwise well thought out. The most important thing is about people, from creating and communicating a compelling vision, creating a strategy, changing it on the fly, and slogging through the information.
Talent in Digital Transformation requires more than anything else. Indeed, assembling the right technology, data, and process team of people who can work together with an influential leader who can bring change can be the most critical step a company can take to contemplate digital transformation. Even the best talent does not, of course, guarantee success. But a lack of this nearly guarantees failure.
Let’s explore the talent requires in Digital Transformation
The raw potential of new technologies is astounding, from the IoT to blockchain, to data lakes, and artificial intelligence. And while many of these are becoming more comfortable to use, it is incredibly complex to understand how any particular technology leads to transformational opportunities, adapt the technology to the business’s unique needs, and integrate it with existing processes. Complicating matters, most companies have substantial technical debt — embedded and difficult-to-change legacy technologies. Only people with technological depth and breadth, and the ability to work hand-in-hand with the business, can solve these problems.
As challenging as these difficulties are, an even more critical issue is that many business people have lost faith in the ability of their IT department to drive significant change since many IT functions focus primarily on “keeping the lights on.” However, eventually, digital transformation needs to integrate systemic IT, so it’s essential to rebuild trust. This means that for any advancement in technology, technologists will include and demonstrate the business benefit. Thus, technology domain leaders need to be great communicators, and they need the strategic sense to make technological choices that balance innovation and deal with technical debt.
The unfortunate reality is that most data is not up to basic standards at many businesses today, and the transformation rigors require much better data quality and analytics. The transformation includes almost certainly understanding new forms of unstructured data ( e.g., a driver-supplied picture of the damage to a car), vast quantities of data external to the company, exploiting proprietary data, and bringing it together, all while shedding large amounts of data that have never (and will never) been used. Data poses a fascinating contradiction: most businesses know that data is critical and that quality is poor, but they are wasting massive resources by failing to put in place the proper roles and responsibilities. They also blame all of those shortcomings on their IT functions.
You need talent with great breadth and depth in data, just as with technology. The ability to convince more people at the front lines of organizations to take on new roles as data clients and data creators is even more critical.
Transformation requires a clear mindset, a rethinking of ways to satisfy customer needs, a seamless interconnection of work activities, and the capability to manage future silos. An orientation to the process is a natural fit for these needs. But many have found process management challenging to reconcile with traditional hierarchical thinking – horizontally, across silos, and focused on customers. As a consequence, a strong idea has remained stuck. Without it, the transformation will be reduced to a series of incremental improvements – essential and helpful but not really transformative.
Looking for the ability to “herd cats” in building talent in this domain – aligning silos in the customer’s direction to improve existing processes and design new ones, and a strategic sense to know when incremental process improvement is enough and when radical process reengineering is needed.
Capability for Organizational Change
In this field, we include leadership, teamwork, courage, emotional intelligence, and other change management elements. It must be noted that anyone responsible for digital transformation must be well-versed in the area. While we have no substantial evidence to support this, it appears that those who gravitate toward technology, data, and process are somewhat less likely to embrace the human side of change. Of course, we have urged leaders in our recommendations above to seek out those with excellent skills for the people. If you can’t find them, a good option is to place some “purple people” on the transition squad, those willing to work on both sides.
So far, as though they existed in isolation, we have addressed the realms of technology, data, process, and organizational change capability, which they obviously don’t. Instead, they’re part of a larger whole. Technology is the engine of digital transformation, and fuel is data, guidance system processes, and landing gear is organizational change capability. You need them all, and they have to work well together.
Consider the “our systems don’t talk” problem, which is anathema to digital transformation and overwhelms most businesses. But which domain is it in? It is a tech issue, as mentioned above, but it also contributes to significant inefficiencies in processes. Yet it stems from a lack of reliable data architecture, and it can involve difficult-to-change organizational structure and political issues. So one might argue any domain should take the lead. But the best solution is that the four of them work together.
Without a deep understanding of each domain, it is hard for almost all business leaders to see the full potential of digital transformation — a factor contributing to many failed digital transformations. But of course, no one individual holds all the requisite knowledge and skill. Hence it is suggested that talents from all areas should be assembled.
Finally, technology, data, and process work must be performed in a suitable sequence. It is widely agreed that there is no point in automating a process that does not work, so process improvement or reengineering must come first in many cases. On the other hand, large doses of artificial intelligence will feature some transformations. Given the development of bad data inhibits and the deployment of good AI models, work on data should come first in these cases. Start with your end goals and then develop the best-suited sequence of steps to achieve them.
Digital transformation can and should concentrate on the company’s issues of greatest need. Such goals would also give the talent needed a flavor; if the emphasis is on improving consumer relationships, for example, the team ‘s technology talent may have unique expertise in customer data, process talent in sales and marketing processes, and so on.