This is a guest post by Gary Cokins, founder of Analytics-Based Performance Management LLC. Gary discusses his evolutionary theory of data scientists and how analysts can evolve to gain insights and make better decisions. This model helps data scientists and companies alike in evaluating their work, and we thank Gary for his contribution.
I enjoy maturity and evolution models of all kinds, especially for business. There is a stages of maturity model for information technologies and others such as for management accounting practices. What I like about stages of maturity models is they provide confidence that regardless what stage one is at low or high there is a next step further up that can be attained in an evolutionary way.
In biology there is an evolution of humans that has in earlier stages Australopithecus, then Homo erectus, then Neanderthals, and our current stage Homo sapiens. Examples of important changes are brain size, hand grip, and a larynx for speaking.
Homo Analyticus the primitive analysts
Just to have some fun I will take the position that some statisticians and analysts are primitive Homo Analyticus. Just as with humankind there are overlap periods where primitive statisticians co-exist with more sophisticated ones with more capabilities and skills. This implies they have evolutionary steps in their future. A stereotype of a statistician is they are geeks with pen pocket protectors who rarely stray from their cubicle. These are the Homo Analyticus. In the evolutionary ladder they can become decision makers and executives. They can add value beyond just analyzing data to assisting their organization to gain insights and make better decisions.
I am obviously not suggesting that many analysts are prehistoric humans with beards wielding clubs and appear like the Flintstone cartoon characters wearing animal clothing (although fashionable clothes may not be in their wardrobes). I am suggesting that some analysts have yet to evolve to fulfilling their potential to be truly creative and imaginative. For example, when examining a population of event data, dont just calculate an average. Ever hear the joke about an average? My feet are in the hot oven and my head is in the refrigerator, but on average I feel OK. A basic step is to calculate a median and beyond that investigate the data distribution which in many cases does not follow the bell-shaped standard normal distribution where random variables cluster symmetrically on each side of a peak mean.
The evolving analyst species
Consider the healthcare debate in the USA about the Affordable Care Act legislation. Critics suggest that introducing consumerism with its marketplace pricing can reduce healthcare costs. Perhaps. However research by the Commonwealth Fund reports that 10 percent of the population accounts for 60 percent of health outlays implying the 10 percent are the very sick and not in a position to make cost-conscious choices about treatments and surgeries. I choose this example not to create debate about healthcare but rather to illustrate that analysts who reveal something not commonly understood can shift thinking to consider more options.
Gaining insights from data gets to the heart of what differentiates the advanced analytics species from the primitive ones. It is not having bigger brains. The advanced analysts have a mission. They want others to see things that have not been seen before. They want to reveal clues, in many cases unarguably supported with facts, that can solve problems and surface unknown opportunities. They want to help their colleagues make better decisions.
What motivates analysts? The primitive Homo Analyticus have basic needs not too dissimilar from food, warmth, and shelter. They want to earn a living by solving problems. The author Daniel Pinks book Drive stimulated me to think that the advanced analyst species has greater motivational elements. They want autonomy to be self-directed to explore and investigate. They seek mastery of their craft which can be painful like exercise. They want purpose to pursue causes that are larger than themselves. Higher forms of the analyst species possess these special traits.
What kind of analysts in your organization are producing studies and reports for users to gain insights and make better decisions? Are they Homo Analyticus? How far along the evolutionary continuum are they?
