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Using Statistics for decision-making- 1st step to innovation

I must say that "Innovation" is one of the most misused words. CVs of management professionals boast about how innovative they are, and how innovative they have been in their current roles. Innovation is a crucial word in any minutes of board and management meetings. Without the use of "Innovation" in your business plan, you may never be funded by a VC or PE investor.

By focusing on "Innovation", more objective and measurable variables that impact/drive a business are often ignored. For instance, industry-specific variables, target customers, demand for product/service, the country where the business is located, the country where the business sells, the state of the economy, company-specific variables like the management team, years since operation, market share, business model, financial strength/financial slack, free cash, and the list has no end. I'm sure it's not an alien thought that we expect to land on earth.

One of the most crucial variables that keep a company ahead of its competition is its ability to foresee/forecast "Demand" better than its competitors. Just like what our equity players (FIIs, MFs, Investment bankers, PEs) try to do in equity markets- to predict the probabilities of a rise or a fall 'better' over competitors.

While all of them are now being criticized for being overtly mathematical without giving due consideration to economic fundamentals (Variable X increases when Variable Y increases assuming all other variables remaining constant), the ability to quantify your beliefs and possibilities is one of the most important attributes to have and hence key to being innovative.

In my limited work experience, I have seen decisions being made backed purely by hunches/beliefs and so-called back-of-the-envelope calculations. If the science of "Demand forecasting" had been used, probability weightages for "BEST" scenarios would have been higher, for sure. Further, communicating the failure or success of a product/service would have been far easier and clearer, to say the least. So statistics for decision-making is missing.

I recall the words of Prof. Tapan P. Bagchi (Adjunct Professor Industrial Engineering & Operations Research, IIT Bombay) when he taught us statistics as part of the Fellow Program curriculum at NITIE Mumbai. He said, "If you know even the basics of statistics, you can be a consultant to companies and help them make decisions." So there is money being left on the table by all those aspiring "Consultants" who are only working on their PowerPoint skills.

Statistics provide key inputs to the decision-maker, that if understood and interpreted better can help drive decisions that are later interpreted to be "Innovative". The ability to interpret data, not just restricted to interpreting trends (the curve is rising), is important. We need to know what mean, range, standard deviation, r2, common distributions like uniform, binomial, normal, Poisson, correlation coefficient, coefficient of variation etc., speak about the data. This is for sure expected to make decision-making more informative and verifiable.

Let's all try to make decisions and not just deliberate about them. I am left with less than 40 years of working life (assuming we retire at the age of 60) so let's learn and grow old.

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