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Three considerations for realizing true digital transformation

Digital technologies are changing everything. A neural network re-created a Picasso painting that had never been publicly seen. MRIs can depict high-quality images of moving joints without going under the skin. From checking Google Maps for traffic to asking your phone where the nearest coffee shop is, digital technologies touch every aspect of our lives.

Digital technologies have also opened opportunities for transformation. However, we must curiously discover and consciously embrace them.

I recently learned a lesson from my children. We travel a lot, and I'll check the weather at the destination with Amazon's Alexa and decide what to pack. My boys, on the other hand, just ask Alexa, "Do I need a raincoat in Boston this week?" I realized I had "digitized" a two-step process from my childhood. First, I acquired the weather information. Second, I converted that knowledge into packing decisions. My kids didn't grow up with the previous process – so they intuitively transformed it.

In the business world, I meet leaders who understand this need for digital transformation, but challenges remain about where to start. Too often, providers offer technology as the answer that's looking for the question. Then, although there's plenty of choice in digital technologies, some require complex implementations. Broad horizontal solutions can often be too generic, and change management difficult to achieve.

And yet, the sense of urgency around digital transformation is palpable – and for good reason. The cost of computing and storage is coming down. Data usage is exploding, and natural language understanding has become human-grade, lighting up dark data in documents and conversations. As a result, artificial intelligence (AI) and machine learning are expanding the opportunities for digital transformation at scale.

So, how do enterprises use these digital technologies to realize true transformation? Let's look at three critical considerations:

1. Transform – don't digitize

It's easy to take a slow and cumbersome process, break it down, automate, and rebuild it. But this linear approach just leads to marginal improvements. The process might move faster and cost less, but it isn't transformed.

The largest transformations happen outside a process and true innovators are those who create a better future. It's worth noting that Uber didn't just automate ride-hailing with a mobile front end. And Airbnb didn't just automate accommodation bookings. Instead, they reimagined the entire experience and end-to-end processes, from offerings and booking to payments and support.

Experience as true north is one of the most powerful drivers of digital innovation. Journey mapping, future state visions, tech landscaping, and component architecture all have a part to play in building a new experience. This allows us to go from piecemeal automation to real transformation.

2. Innovate at scale

The difference between experimentation at the edges and transformation at the core is innovation, and this happens at the intersection of domain and digital expertise. Domain is the knowledge of how an industry functions, the nuances around how businesses connect, and the handshakes between processes that form the connective tissue.

From AI and machine learning that requires goal orientation to data science that requires distillation, domain knowledge provides the canvas upon which the colors of digital technologies can be painted into a masterpiece.
Without this intersection between domain and digital expertise, organizations risk applying technology for technology's sake.

To innovate at scale, you need the right talent – namely "bilinguals." A bilingual is neither the most experienced machine learning engineer nor the highest-performing supply chain planner. This is someone who understands enough about the two to realize the value at their intersection. These intersections involve upskilling employees across disciplines and promoting a culture of curiosity and change.

3. Minimize new risks

From our experience transforming processes across industries, we have found three risks that enterprises need to proactively manage.

Change management: transformation, and change of any kind, is always challenging. Adoption is a path with many potholes. Change management becomes something that must be thought through, planned for at every step, and applied across projects.

Governance: digital transformation is a journey, not a destination. What starts as a robotic process automation (RPA) project can evolve into a machine learning exercise. This can morph into a chatbot initiative to take advantage of machine predictions. This journey requires a foundation that can accommodate these evolving directions – we call this a digital business platform – and a governance framework that allows for lights-out operations in a digital-first world.

In the meantime, make sure that machine learning is not picking up unintended bias. You must establish ethical AI frameworks for effective decision-making without the misuse of data.

Governance and ethics: biases in AI algorithms and unintended use present ethical considerations. The rights, use, and security of data also introduce new complications. As governance becomes an increasingly pressing issue, we foresee a future in which digital ethics committees will be a regular part of board oversight.

In summary, the key to real digital transformation is to put the end user experience first. Then, build a network of bilingual talent capable of innovation at scale and able to meet the challenges of change management, governance, and digital ethics head-on.

A version of this blog originally appeared on Forbes Technology Council.

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