Accidental Entrepreneur: Data Driven Decision Making Process for Professional Success

Hi Everyone,

Welcome to my 37th weekly article as this week is called “Data Driven Decision Making Process for Professional Success.”

From my observations and personal experiences the folks who proactively plan and leverage data to make decisions are able to create successful results in all areas of life.

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“எண்ணித் துணிக கருமம் துணிந்தபின்

எண்ணுவம் என்பது இழுக்கு”. — திருக்குறள் (467)

“Consider, and then undertake a matter;

after having undertaken it, to say ‘We will

consider,’ is folly.” — Thirukkural (467)

In life, we encounter people who are well thought out and proactively plan every aspect of their life from their professional career choices to life at home. These people seemed to have accomplished a lot in their professional career with minimum stress or confusion in all the tasks they have undertaken. While it may appear that they have everything under control with a clear vision, by looking a bit deeper into the process of their working style would highlight how they manage and navigate through all the various hurdles . Next 3–4 articles, I plan to dive deep into the mindset of these people and explain the process these people follow to accomplish the results. I categorize these as:

• Data Driven
• Knowledge Drives
• Goal Driven
• Results Drives

I start with data driven decision making as the first fundamental topic since it’s a basic thing everyone can do with the abundance of data available in the current connected world and use that data to drive people to achieve great results.

My last 15+ years of career has been in the Storage market and have seen firsthand the expansion of data which has been accumulated and then processed to make meaningful decisions. While it may be new to many people, even before the latest craze in data, I was fortunate enough to work in industries which used a lot of data. My first semiconductor chip had billion transistors, and created a methodology to sort through those data efficiently and accurately to build successful complex products. Here are a few basic concepts I have used successfully with my small teams to create billion dollar ideas and deliver products:

• Process: First step in gathering and executing a successful data driven project is to have a clear end to end process established from the beginning. It provides clear direction and purpose for collecting/analyzing the data. This doesn’t mean that the process doesn’t change as time goes by and new information is gathered. I have made many adjustments/modifications, but starting without a plan can be very disastrous. Therefore have a clear process and discuss with stakeholders to align on the next steps in the process.
• Tools: Dataset sizes have significantly changed over time. As I mentioned in my early career I had to collect and analyze the dataset from billions of transistor designs. This is where the tools and automation come into play. When I joined my first job at Rockwell, they had the data collected in the computers but the analytical tool was not there. I had to go through thousands of pages of printed pages to identify issues/anomalies and report to my senior manager. Rather than just following the orders from my superiors, I asked them for the digital data and used scripting to analyze them and report them in simple Excel spreadsheet format. These were simple scripting tools (In 1990’s it was Csh and Perl and now Java and Python) and visualization using spreadsheets such as Excel.
• Analysis: Once the process and tools are in place, the next step is to understand the purpose of the data collection and what kind of results we are looking for. During this analysis process, the first step is to take a small sample of data to validate the tools and scripts. Lately AI/ML people define this as a training sample set. Once the basic algorithms and analysis are validated, the automated batch scripts with minimal human intervention can process billions of datasets in days rather than in months by people.
• Visualization/Presentation: Most important part of any data analysis and decision making is to present the results in a consumable manner. This is key for communicating the results of all your hard work to others and convincing/educating others to make useful decisions. There are many ways to visualize this data and present it to others. I use a simple scheme of stating the facts, providing some parallels from prior experiences or similar common life situations. Basic idea here is for others to understand the points you are making and be able to follow your conclusions.
• Refinement: Finally, no situation is static as well as there are experiences from others that can provide different perspectives. I use the presentation process and discussions with experts to continually refine the analysis process in addition to re-validating the conclusions.

I have used these simple but detailed processes to analyze the data and make well educated decisions. The problems have changed significantly but the fundamental analysis process has not changed. I learned this from my early years at Rockwell Semiconductor and still continue to apply in my career in Sales. Once you create an intuition for analyzing complex or a lot of data with proper methodology, sky’s the limit for making successful decisions and becoming successful.

Let me know what you think about the data driven decision making and how it helped or hamper your success.