Today is Episode 2 of the Interview series on Expert-talks @MAAVRUS, with Leaders in the Analytics, AI, and Transformation space. For this episode, I am in conversation with Dr. Prashanth Southekal, Founder & Managing Principal of DBP Institute Canada, which is a data & analytics consulting, research, and education firm. Prashanth has consulted for over 75 global companies including GE, P&G, SAP, and Apple to name a few. Prashanth is the author of 3 books – Data for Business Performance, Analytics Best Practices, and Data Quality. He is also an adjunct professor for data & analytics at IE business school, Madrid, Spain. He writes extensively for Forbes, FP&A Trends, and CFO University.
It was wonderful to speak with Prashanth and understand how he uses the education & training of corporate leaders, as a key step in the organization's analytics & Transformation Journey. Am listing below, some key learning from the interview.
- He sums up his overall approach to business as follows
- It's all about building networks. You help some people and either they help you back or somebody pays it forward for you. So you always have to be part of the community and help people.
- The fundamental point is educating the business community about how data and analytics can be used for solving business problems, and it creates both the funnel and opportunity for him.
- Data analytics he explains is about Digitization & Data Management, Data Integration, Data Science, and Decision Making/execution. He believes that while Data Science is considered more glamorous, the opportunity to make serious business change is in data management, integration & practical execution.
- It is important to know clearly - ”What is the question one is wanting to answer” & “What if” before embarking on any data & analytics projects. His experience is that in 90% of cases, this is not defined upfront. So he says “No Questions” +”No Data” = “No Analytics”
- There is nothing called Perfect quality data, and businesses have to be comfortable with this truth, so “Perfection is the enemy of Progression”
- For businesses to make the leap from Performance Insights to Actionable Insights, requires Business Resources, Leadership, and Openness to change. So he recommends that for data analytics to yield sustainable value, one must start with “the end in mind”.
- For effective data analytics adoption, it is important to move companies gradually across the measurement continuum – start with initial descriptive analytics and move to prescriptive recommendation models. The biggest block to this is organizational inertia. Also jumping the queue does not give great results on account of poor measurement quality and decision rigor.
- Dark data is data that is not being used for any specific use, and it is costly to collect & maintain. So before deciding to collect data, it is good to check if they serve one or any of the purposes – help run operations, needed for compliance, and improve the quality of decision making.
- In the next few years, AI and Digital will increase the level of automation, but the role of good Data Analysts / Scientists will be to assess the quality of data, engage with businesses to help articulate the right questions given decision constraints, and enable businesses to act on recommendations. So the future of work as far as data analytics is concerned will mostly be influenced by soft skills, rather than hard technical skills.
- His new book “Data Quality” uses a framework called DARS, and uses 16 approaches to identify why businesses have bad / problem data, and 10 approaches to fix the data quality.
