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Tuesday, March 3, 2015

Data Scientist or Entrepreneur: Who are the “Analytics Master”?

You need the data science to do the heavy lifting but with an entrepreneurial speed of delivery and focus.
Analytics is at the top priority of executive’s agenda in any forward-thinking organization, but most of projects do not achieve the expected result, what’re the symptoms, and what’s the root cause? From talent management perspective, how to build a high-performing team? Data scientists or entrepreneurs: who are the analytics master?


It’s important to get the right mix of people that listen and work together: It depends on what you want to do. Somewhere along the line you will need to hire someone who knows the meaning of the data and get the work done, while you will also need entrepreneur’s spirit and management expertise. There are so many projects fail or over run as they are run/managed by people that know nothing about data science or the domain data - a recipe for disaster - they cannot manage such projects by leaving major technical decisions to be made by “data illiterate.” So many projects just go so wrong because people in senior positions don't know what to ask or what to bring to the project. So the problem is therefore getting the right mix of people that listen and work together.


Data scientist with entrepreneur mind is better fit for analytics success: Many Data Scientists will tell you a majority of their work usually involves research of topics to understand deeply. Understanding these topics will help to visualize the data set more. To start with the data first without a topic is kind like starting to write a story without a plot. The Entrepreneur's mind revolves around quick understanding of subjective material. So ultimately, to have a data scientist that has a entrepreneurial headspace would be advantageous.


You need the data science to do the heavy lifting but with an entrepreneurial speed of delivery and focus. Entrepreneurs do have a vision; but vision comes from wisdom, which is somewhere derived from Raw Data. And it is the core component behind every entrepreneur venture ever set and successful. It's a very common and a proven methodology to go through Data -> Information -> Knowledge -> WISDOM.  If you've only got entrepreneurs you'll not get the technical detail; and if you've only got data scientists you'll end up boiling the ocean and getting answers to questions you didn't ask or need.


People with an entrepreneurial mindset, more specifically means "forward thinking, action oriented entrepreneurs" who can solve problems more innovatively. What is the benefit for people with entrepreneurial spirit and skills (intrepreneurs, engineers, designers, scientists and other breakthrough minds) to become entangled in the wired/wireless plugging of legacies, when they could freely sail away and create new systems and services? Whatever we sense as a human being, there is a methodology behind that.. See it - sense it -> get it processed in brain -> react. So Data comes first in its purest form. Now it’s up to a brain working on that to decide whether it’s relevant data or to be discarded, People who consider these patterns and visualize a better reaction based on their understanding of data and prediction and taking preemptive action are the ones who are supposedly entitled to be called as an Entrepreneur.


Doing the analytics or any kind of project is about the team that can communicate and collaborate. Within that team you need leadership, innovation, technical foresight, technical knowledge, technical ability, sales, marketing. If you don't have all these parts (just innovation and technical ability) then you get a problem - you cannot see what to do with the innovation. If you can get a single person with innovation and technical foresight (a data scientist that can see outside the box and where to go), then you have a good starting point. Even just Data mining, the project wouldn't make any sense if there are not good entrepreneur with "technical foresight" who can capitalize on real facts -> predict the future trends -> and be preemptive -> learn from mistakes -> analyze data. So it’s a repetitive cycle which can’t be traversed without going back in circles and find a way out through data and only data. There has to be a balance.


An analytic CIO is more welcomed at the big table in the digital age; the entrepreneurial mindset and analytic skills are good mix to build a high-performing team, to keep the end in mind, but also dive into the sea of data with technical expertise, laser focus on the goals to solve critical business problems, delight customers or discover the new opportunities for business grow and maturity.  




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