One of the most difficult things about any transformation is defining the end state. "When do you know the transformation is complete?". It is even more complicated as you start thinking about the overall enterprise.
As you think about Digital Transformation, there are probably three stages of it:
- Digitized Enterprise
- Intelligent Enterprise
- Agile Growth Enterprise
Clearly articulating the difference between these three becomes a bit of a problem. Guess what everything is digital. One of the analogs that best describes it is the journey of autonomous cars and human behaviors around it.
In 2002, when I first migrated to the United States, one of the many fascinating things was Yahoo or Map Quest maps. Me and my fellow immigrant roommates would enter the destination, print the directions, and pretty much everyone in the car navigated "take the exit","ugh we need to turn around off the next exit", "take left in two lights" all of these were typical statements. This to me is a perfect example of Digitized Enterprise.
All the directions are in a database, you can pull a query, check, and manually take actions. Today, when I see such situations it is symptomatic of an enterprise that is either just digitizing itself (or) has done a half-ass job of digitizing itself.
Companies that are implementing or re-implementing ERPs are a great example. They have spent years documenting their processes, defining business rules, implementing it, supporting it with hyper care, complained about it, and eventually compromised to use the ERP solution. The processes are digitized, the information is all there, and decision making is akin to our car rides in 2002.
This worked in 2002 and was a competitive advantage. Not anymore.
Each one of us experiences this in our day-to-day. You get into your car, ask Apple Maps, Google Maps, or Waze to tell us the direction and we start moving. The maps is intelligent enough to look at the traffic patterns, lights, speed limits, and other things. These insights help you do your job more efficiently and relatively more safely than printing a map.
A supply chain planner who used to receive thousands of alerts and do the right thing relies on a system to do it for him/her. He/she first trains the systems to work for them and then exercise caution if there are exception.
If this phases is led by only the tech department, business will not do anything with the output and if it is only led by the business, it will have silos/scalability issues. Every business leader will solve it for their department. It requires businesses and tech folks to work together to look at all the data in and outside the enterprise and start training AI models to pull them altogether.
Bringing the cross-functional teams together and clearly articulating the problem becomes half the challenge. The next half is empowering the team and staying out of micro-managing the actions!
Agile Growth Enterprise
Think about this as Full Self-Driving (FSD) or auto-driving functionality of Tesla or a WayMo. The external environment is auto detected and internal decisions are automated. The cameras and/or the LIDARs recognize the crazy environment outside, compute millions of data points in less than milliseconds and automatically make the decisions.
The computer knows the destination, the constraints, and the possibilities as well as understands the decisions you would make as a human being 70% of the time. It makes it for you. Humans we move from thinking about tasks to outcomes, directions, and training the systems to work alongside us!
In the same supply chain example, if the deployment planner accepted the system recommendations 90% of the time, he/she should feel comfortable that the system automatically do this for him/her and only alert only in case of complete ambiguity.
This new type of enterprise is a Growth Enterprise because it frees up the human potential to actually focus on growth. It unlocks them to think about doing things quickly and at scale.
It is the most toughest phase. As humans, we have been all rewarded for our functional expertise and ability to do a job well. We now have to be rewarded for training a computer to do the job well and include it as part of our work! That requires a change in culture and a massive upgrade to every skillset.
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