Recently there has been a fair amount of discussion about the need for data scientists in a big data world. The base argument being that as access and ubiquity of data has exploded, so has the need for experts to absorb and interpret the data and put it to good use. This article of faith seems to be widely accepted and a recent study by McKinsey suggests lack of data scientists as a potential limitation to innovation and business growth.
This discussion took an interesting turn several weeks ago with Gil Press’s intriguing blog in Forbes suggesting that data scientists will actually be replaced by tools. This is a topic suggestion for SXSW and it also generated some interesting responses in the comments section of the blog as it opens the question of whether this is yet another area where machine learning will catch up and ultimately replace humans.
While the topic is interesting, the premise that data tools somehow replace humans is flawed. Our cars and automotive diagnostic equipment have gotten both much smarter and automated, but when your car breaks down or alerts you that it is time for a tune up, you still take it to a mechanic. A better question would be, how long will be before everyone is a “data scientist”?
In the developed world, the vast majority of adults are wired – at home, at work, and on their smart phones. Approximately 85% of adults have a high school education, where basic analytics, statistics, mathematics, deductive and inductive reasoning concepts are introduced. More than 20% going on to earn a bachelors degree. While a sub-set of these people go on to get specialized training in mathematics, economics, engineering and computer science – the domains that generally lead to what become the “data scientists” in an organization, many more users in an organization can and should be thought of as data scientists. These people just lack data access and applications to help them take advantage of that data for business advantage.
In the world of software, we tend to think of these people as “business users” – generally the non-technical teams in business lines, managing supply chains, launching products and managing enterprise accounts. These people are information producers and users, many with both education and on the job training in how to analyze and share business information. People who understand both data impact and business outcome. They want access, solutions and real value. Nobody wants more tools.
When we started Tidemark, we surveyed business owners in multiple roles from finance to sales, to operations, including senior executives to understand the challenge. Our survey found that the number one issue teams face in both large and mid-size organizations was the lack of analytic applications. We found no ability to do planning and scenario modeling. The second biggest issue was limited to no web access or remote access.
Business people are asking for smart apps and they are asking for access to these apps everywhere.
As a result, we set out to re-think how business people wanted to work and focused on building smart applications. With these applications we pre-built an analytic foundation and a completely new computation engine so users could take advantage of packaged applications on a powerful user platform, not be subjected to more tools with no context and limited value. You can see a quick intro to our approach on smart apps here.
There will always be a need for highly skilled data scientists in organizations of all sizes. In fact, based on his early work at LinkedIn, and now recognized as a top data scientist, DJ Patil has recently talked about the framework upon which data science and data scientists teams can be built and leveraged throughout an organization, leading to a bigger opportunity: unlock productivity and business value by making everyone a data scientist by giving them easy access to applications that allow them to capture data, do analysis and act from anywhere.
Today everyone is in the data business and the future of work is about everyone having access, control and a voice in helping their organizations compete and win in the marketplace.