Imagine it’s D Day today: A major decision needs to be taken for your company, based on Data Science.
Who are you in this story? You are the celebrated hero of todays world, not the Superhero clad in the dark cloak with superpowers even nursery kids are no longer in awe of but the new superhero with a growing armor of super-powers like Cloud, Big Data, Python, IOT, (the list continues); the much talked about and much in demand, Data Scientist
You believe in data with all your heart and in your dreams you quote Sherlock Holmes:Data!data!data!” he cried impatiently. “I can’t make bricks without clay. Arthur Conan Doyle, The Adventure of the Copper Beeches
But even as you say “Elementary, my dear Watson“, you hear Mr. Holmes in your head, saying, there’s something missing. One D is missing. We need to find that before we take the decision. What would Holmes find?
Is it all about data? I believe, Data science is as much about change management as it is about solving business problems. For data science driven decisions to succeed then, knowing the data is not enough. The missing “D” in Data Science is a word we do not often associate with data science armor or job descriptions.
Its DOMAIN.
Drew Conway spoke about it as substantive experience in his DataScience Venn Diagram. Dr. Vincent Granville spoke about in DataScience Central and so did other people such as Jeff Heaton and Nathan Brixius. But it still seems to be a seldom voiced and unresolved debate, at best.
My point in this debate is that the best data scientists who can really drive business decisions and navigate the organizations through a culture of change are the ones who are not just data but also domain experts. Lets look at 2 such far-reaching data-driven change decisions from history:
Florence Nightingales famous Coxcomb Chart showing deaths from diseases started with her understanding of the prevailing healthcare domain.
Alan Turings war-time breaking of the Enigma code owed its success as much to his reasoning powers as it did to his programming expertise.
The people mentioned may not be the usual data scientists but more fit the pattern of what Gartner is terming as the increasing crowd of Citizen Data Scientists. The key point is that Data Scientists who are at this point of time dreaming of the next big Beer and Diaper Eureka insights moment, would need to start with their understanding of the business domain. Why, you ask?
Remember this dialogue from the same Mr. Holmes?
“‘Is there any point to which you would wish to draw my attention?’
‘To the curious incident of the dog in the night-time.’
‘The dog did nothing in the night-time.’
‘That was the curious incident,’ remarked Sherlock Holmes.'” Exchange between Inspector Gregory &Sherlock Holmes -Silver Blaze
Which brings home the point about domain in a very curious way. Sherlock Holmes knew his domain. Hence he knew what data mattered and what didnt. Knowing the domain, helps us create the right hypotheses which data science can help us test and prove or disprove. Without domain understanding, data science could become a long fishing expedition in the ever-increasing data-lake and the Iceberg of Business could start melting long before the changes needed are really implemented.
“The Game is On”. Would love to hear your thoughts on this debate.
