The other day I was having a discussion with Inder Sidhu, who was speaking in our Engineering Leadership Professional Program. I wanted to understand his perspective on data and strategy. As you may know, he is a great person to talk to about these things. He joined Cisco and helped it grow from $1 billion to $50 billion. He has literally been ‘written’ into the Cisco case and he is most famous for developing their brilliant channel strategy. He is also the author of a leading book on technology strategy titled Doing Both: Capturing Today’s Profit and Driving Tomorrow’s Growth.
Our conversation was in the context of the work we have been doing in Data-X, a program which makes it possible to rapidly learn and implement amazing data and digital projects. I was mainly interested in his thoughts on the issues that leaders face as they implement data projects.
His initial reaction was really quite insightful. From his perspective, there are three parts to how any company or organization creates value using data, AI, or blockchain (i.e. Data-X).
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The first part is really about knowing “why” and understanding the relevance to the organization. Typically, this part is also related to developing the entrepreneurial data-story and recruiting stakeholders to a project. It may additionally include researching the use cases from other people or organizations. This is needed to evaluate what is possible and what the solution might look like within the current organization.
- The second part is the “what”, and it is related to understanding the capability of the actual technologies and algorithms that might be used.
- The last part is about the “how” and includes the ability to implement it. This is everything from the actual tools to the behaviors and processes that should be used. This part also includes the holistic thinking needed to combine all these elements in a way that leads to an on-time, and working implementation. Note that this is partially a learning process, not only an execution process.
An insightful point here is that when people study, teach, or discuss data, AI, and blockchain applications today, most of the focus is on the “what” in part 2. It feels like everyone only concentrates on the algorithms and technical capabilities. So in reality, the first and last parts are grossly underserved.
This is an important point. For years, we have been working on the “why” as well as the “how”. In our terminology, the “why” for organizations has been developed within Berkeley’s Method of Innovation Leadership. This perspective is the reason that leaders from Google, Apple, Samsung, and so many more global firms attend our innovation leadership programs. On the other hand, the “how” is what we have been developing in our Data-X program.
Through this conversation, Inder has helped reinforce to me how these frameworks are synergistic and really work together. My experience is that while executives benefit from innovation leadership (i.e. why), they also need to understand some of the “what” and some of the “how” in data frameworks; or else they really can’t lead digital transformation projects.
On the other hand, I’ve also experienced that while engineering or technical leaders learn powerful tools and technical understanding for developing data projects (i.e. “how” and “what”), they still need to understand some of the “why” in the form of innovation leadership and business “relevance;” else they simply cannot find common ground with the business executives, and eventually, their projects will implode.
This cross-pollination between implementation and leadership has proven to be critical for innovation. We have noticed that when you learn one, it is important to learn at least a little bit of the other. And with this focused insight, you can see our perspective on “making the magic happen” in your next innovation project.
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