1. The rise of the chief analytics officer. In some cases combining analytics with other functions has worked well. In other cases, analytics efforts have been buried under those executives’ myriad other priorities.
To give analytics the attention it merits, some companies have appointed chief analytics (or big data) officers in recent years. Today, a growing number of companies have dedicated chief analytics officers charged with leading the effort to derive new insights, products, and services from expanding troves of data.
2. The data scientist shortage. It’s no wonder some companies are having such a difficult time recruiting data scientists. The role of a data scientist traditionally calls for someone trained in math and statistics, who understands the business, knows how to design and test predictive models, can manipulate raw data, and can use that data to tell compelling stories.
Some companies are addressing the talent shortage by creating teams made up of professionals with different strengths and skills, rather than trying to find that one elusive data scientist.
3. The misuse of visualization technologies. Visualization software has made complex data understandable to almost everyone. Because the software is generally easy to use, many employees, from inventory managers to actuaries, can explore data on their own, often without the guidance of analytics professionals. But in their eagerness to dive into data, users risk glossing over important insights and producing erroneous results.
4. The proliferation of data products. It seems nearly every company these days wants to make money from its data. They’ve witnessed leading social and professional networking sites rise to prominence by monetizing big data; now they want a piece of the action.
But companies should think critically before pinning their strategies to creating new data-based products and services.