Enterprise-wide Analytics: There is no recipe

With the ubiquity of the Internet, more and more data is in the hands of people. This democratization of data can bring with it the power to make better decisions and for businesses to be more competitive, but only if you know what to do with that data.

At Intel, our theory is that you don’t have to be a data scientist with an advanced degree to be able to benefit from or participate in advanced analytics. We are training employees in the concepts of advanced analytics, and earlier this year we released a white paper, Broadening Access to Advanced Analytics in the Enterprise, about this program.

Since writing that paper, I find that I am focusing more on teaching the basic course to functional work teams than I was previously. This team-coverage approach gives these teams a shared conceptual approach to business problems, and the result is that more of them are getting closer to using advanced analytics on a daily basis.

I believe that if you educate your employees on the concepts and vocabulary, it empowers them to understand the value of advanced analytics and to be able to work with data scientists and contribute to the analytics. Just being able to frame a business issue as a data mining problem can be half of the work, and with the proper training in the basic concepts, many people can learn to do this.

Leading your team into data analytics

So what’s the recipe for fostering advanced analytics in your organization? Unfortunately, there isn’t one.

However, a solid first step is to make sure that the value of advanced analytics is understood at every level of the organization. The paper Strength in Numbers: How Does Data-Driven Decision making Affect Firm Performance says that the use of data analytics leads to reliable increases in productivity and output. From this (and other sources) I conclude that your data and analytics are your competitive advantage, whether you manufacture widgets, fly airplanes, or whatever.

Next, dispel the myth that advanced analytics is too advanced for mere mortals and that only PhD data scientists can contribute to it. Many people think about advanced analytics and they immediately invoke the words big data and think of a galaxy’s-worth of data on a room-sized supercomputer. In reality, the size of the data most business users work with is in a spreadsheet on their laptop.

You want everybody to participate in the analytic process, at least a little bit. Some will naturally pursue more training, and you’ll still need data scientists. The goal is an organization made up of workers who see the value of advanced analytics and who understand how to frame business problems in terms of analytics. It is within this organization that advanced analytics will be applied to decision making in a way that creates sustainable competitive advantage.

Are you fostering advanced analytics in your organization?

Intel values advanced analytics. I’d love to hear from other people who are thinking the same way at other companies and maybe going down a similar path. What do you think about this idea and approach? What are you doing in your organization differently, the same, or better? Let’s compare notes and see how we can learn from each other!


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