Data scientists are the coolest kids on the block right now. Harvard Business Review called the role of a data scientist the “sexiest” job of the 21st century, and job satisfaction for data scientists is at an all-time high. But how we imagined data scientists a few years ago varies drastically from what the role looks like today. Not many of us wake up in the morning wanting to be a citizen data scientist, but chances are, we’re on our way to become one whether we know it or not. How? Let me explain.
Data Scientists as Explorers
The data scientist role emerged from the significant need to understand the often messy and massive amounts of data that fast-growing companies collected. Management hoped to glean actionable intelligence about their business and customers with this data — but the data scientists needed to make sense of it were in short supply. The shortage of talent, combined with the early days of monolithic business analytics software, made for a very limited use of data — it was typically a reflective process, used to look back on past business metrics. Data scientists faced an ever increasing backlog of requests, and were forced to prioritize only mission-critical questions. From here on out, data scientists were in high demand.
This demand arose because most organizations are data-rich, but not data-smart — there are large gaps between the technology, tools, techniques, and skills that employees use. But business leaders have finally begun to understand the importance of using data in an effort to predict the future. They now want to know not just what happened, but what is happening in the moment, what will happen in the future, and what to do about it. Business leaders want their employees to be action-oriented and able to base their decisions on data. This spurred a shift in how analytics is viewed: from an ivory tower function for a few specialized analysts and admins, to something that every employee and leadership is thinking about at all times.
The Rise of Citizen Data Scientists…
To cope with the shortage of data science talent and fuel this idea of analytics for the masses, the citizen data scientist arose. A citizen data scientist is defined by Gartner as “a person who creates or generates models that leverage predictive or prescriptive analytics but whose primary job function is outside of the field of statistics and analytics.” And now, the age of the citizen data scientist is dawning. Gartner predicted that through 2017, the number of citizen data scientists will grow five times faster than the number of highly skilled data scientists — that means that more people than ever before will be working with data to solve business questions. Now, citizen data scientists can’t do it alone. The analysts and experts are still needed — but the average employee, with a little help from technology, can complement the data analysts that are in such short supply.
That technology is artificial intelligence in the form of smart data discovery tools that provide insights from advanced analytics to business users or citizen data scientists without requiring them to have traditional data scientist expertise. Today’s AI is more accessible than ever before; it empowers the average business user to get past the complexities of algorithms by automatically surfacing the findings and insights that matter most to them — such as what a customer’s satisfaction score will be or a customer’s propensity to buy, and what business users can do to influence it.
…and the Smartphone of Analytics
When business users have the power of AI in the palm of their hand, advanced analytics become a tool to guide their workflow to the actions that make the most impact, and drive decisions that bring the most benefit. What used to be the equivalent of a super computer, kept away in a room and only accessible to a few people, is now available to us via our smartphone — with AI, every business user can now do their job as if they have a data scientist in their pocket, guiding them to make the best decision at every customer touch point. When more employees across an array of departments and business functions have data-driven insights at their fingertips, it means every customer interaction is truly personalized, and the competitive advantage cannot be overstated.
Analytics for the Masses
We aren’t that far off from a future when everyone will have the tools to be considered a citizen data scientist. This has been happening in the consumer world for awhile — when we need directions, we look to Google Maps to provide personalized recommendations in the form of alternate routes and real-time updates when we’re stuck in traffic — and it’s quickly catching on in the business world. And while business leaders may be intimidated by the cost and complexity of applying advanced analytics to their business in such a massive way, at it’s simplest level, analytics will make every employee better at their jobs and deliver ROI that dwarfs the investment required. As AI continues to undergo major disruption and democratization, citizen data scientists will be the ones leading the charge in changing how businesses operate.
About the Author
Arijit Sengupta is Head of Einstein Discovery at Salesforce. He has guest lectured at Stanford and other universities on globalization and outsourcing; spoken at conferences in a dozen countries; and was written about in The World Is Flat 3.0, New York Times, San Jose Mercury News, Harvard Business Review, The Economist, and other leading publications. Arijit held leadership positions at several Big Data, Cloud Computing and eBusiness industry associations and previously worked at Oracle, Microsoft, and Yankee Group. Arijit holds an MBA with Distinction from the Harvard Business School and Bachelor degrees with Distinction in Computer Science and Economics from Stanford University.
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