Digital Transformation: Talent is the key in four crucial areas

What does it take to succeed with true digital transformation? The reality is that, to date, many digital transformation efforts, such as general transformation programs, have failed.

Most leaders don't realize how much work goes into bringing things together and coordinating them. People are everything - from creating and communicating a compelling vision to crafting a plan and adjusting it on the fly, to slogging through the details.

Digital transformation requires talent more than anything else. In order to prepare for a digital transformation, a business must put together the right team of technology, data, and process experts who can work together - with a strong leader who can make things happen. Even the best talent isn't guaranteed success. Lacking it almost guarantees failure.

Let's go over each of the four domains one at a time:

Technology

Emerging technologies have a lot of potential from the Internet of Things to blockchains, to data lakes, to artificial intelligence. Despite the ease of using many of these technologies, it's still challenging to understand how particular technologies contribute to transformation, adapt them to the business's specific needs, and integrate them with existing systems. Furthermore, most companies have a lot of technical debt - outdated tech that's hard to replace. Solving these issues requires people with the right technology depth and breadth and a business-savvy approach.

While these challenges are daunting, an even more critical issue is that many business people do not believe that their IT department can drive significant change because IT functions are mostly about "keeping the lights on." Eventually, digital transformation must integrate institutional IT, so rebuilding trust is essential. Therefore, technologists need to show business value with every innovation. Consequently, tech leaders must be great communicators and make strategic choices that balance innovation and technical debt.

Data

Unfortunately, most data at many companies today aren't up to basic standards, and transforming them requires much better data quality and analytics. Transforming your company probably involves understanding new types of unstructured data, leveraging external data, integrating everything, and getting rid of tons of data that's never been used (and never will).?Almost every company knows that data is important and that data quality is bad, but they waste a lot of money by not setting up the right roles and responsibilities. It's usually the IT department that gets blamed for all these problems.

With technology, you need data gurus who can do a lot. More important is persuading people at the front lines of an organization to take on new roles as data customers and data creators. To do that, you'll need to figure out what they need now and what they'll need after the transformation. That means helping front-line workers improve their work processes and tasks to make data right.

Process

To transform, one must think end-to-end, rethink customer needs, connect work activities seamlessly, and manage across silos. A process-based approach makes a lot of sense. However, many organizations have found that process management - horizontally, across silos, and focused on customers - is difficult to reconcile with traditional hierarchical thinking. Result: this powerful concept has sat idle. Without it, transformation becomes a series of incremental improvements - which are helpful, but aren't truly transformational.

If you're hiring in this space, look for the ability to "herd cats" - align silos toward the customer to improve existing processes and create new ones, and have a good sense of when incremental improvement is enough and when reengineering is needed.

Organizational Change Capability

This domain covers leadership, teamwork, courage, emotional intelligence, and more. This domain has been well written about for many years, so we won't rehash it here, other than to say that anyone responsible for digital transformation needs to know what they're doing.?We don't have any hard evidence to back this up, but people who gravitate toward technology, data, and process are somewhat less likely to embrace change involving people. The recommendations above have urged leaders to hire people with great people skills. If you can't find them, an alternative is to put "purple people" on the team, the ones who can work on both sides.

Pulling It All Together

To this point, we've talked about technology, data, process, and organizational change capability domains as if they existed in isolation, which they don't. They're all interconnected.?In digital transformation, technology is the engine, data is the fuel, the process is the steering wheel, and organizational change capability is the landing gear.?These things must work in harmony.

Try to solve the "our systems don't talk to one another" problem, which is anathema to digital transformation. So what domain does this fall under? It's a tech problem, but it also leads to huge process inefficiencies. It's still the result of a lack of solid data architecture, and it may involve politics and organizational issues that are difficult to change. Maybe whoever takes the lead should stand up for it. I think the best solution is for all four of them to work together.

Without a deep understanding of each domain, it's hard for business leaders to see the full potential of digital transformation - and that's why so many projects fail. No individual has all the skills and knowledge. So we need to assemble talent in every area.

Lastly, technology, data, and processes need to be handled in the right order. Most people agree that there's no point in automating a bad process, so reengineering or improving processes should come first in some cases. Nevertheless, some transformations will feature a lot of AI. When it comes to AI modelling, bad data stymies development and deployment. So, in these cases, focus on data first.?Decide what your end goal is, and then develop a plan to get there.

Digital transformation should be focused on the problems the company is facing most. The priorities will also influence the kind of talent required; if the team focuses on transforming customer relationships, the data talent may have particular expertise in customer data, and the process talent may have experience with sales and marketing processes, etc. Ultimately, it's more important that the talent possesses the four types of expertise we have described and has already been successful at creating and executing technology-driven transformations.

Courtesy: hbr