Most Analytics Projects Don’t Require Much Data
Small data projects involve teams of a handful of employees, addressing issues in their local workplaces using small data sets. They are tightly focused and utilize basic analytic methods that are accessible to all. Small data projects build the organizational data muscle that helps the entire company learn what it takes to succeed with data and breed the kind of culture that big data demands. And they can yield financial benefits of $10,000 to $250,000 annually per project.
But many managers and leaders don’t think to prioritize small data over more advanced data science, machine learning, and artificial intelligence. While the work to unlock of power of small data is not difficult, reorienting your thinking away from these areas can be tough. Get started by taking the following steps. First, get everyone involved, including yourself, by leading one small data projects with your direct reports a year. Then, follow a disciplined approach. Next, provide training to your team that provides both practical experience and explains the “whys” and “hows” behind the methods. Finally, define your unique area of expertise and carve out a niche for yourself.
In their headlong rush into advanced data science, big data, machine learning, and artificial intelligence, too many companies have ignored “small data.” This is a huge miss. The relative ease, ubiquity, and power of small data projects carry profound implications for all employees, managers, and leaders at all levels, in every department, in every organization.
Small data projects involve teams of a handful of employees, addressing issues in their local workplaces using small data sets — hundreds of data points, not the millions or more used in big data projects. They are tightly focused and utilize basic analytic methods that are accessible to all. They can be completed in a few months by people working part-time andyield financial benefits of $10,000 to $250,000 annually per project. Companies are loaded with potential small data projects, and it is reasonable to expect that a 40-person department to complete 20 projects a year. The cumulative benefits are enormous.
Unlike big data projects, which often involve dozens of people with disparate agendas, politics, enormous budgets, and high failure rates, the probability of success is high. Thus, small data projects build the organizational data muscle that helps the entire company learn what it takes to succeed with data, gain needed skills, build confidence, and breed the kind of culture that big data demands. And with many individuals worrying that they will be replaced by automation or that their jobs will change in ways beyond their control, participating in these projects enables everyone to take proactive steps toward building their data literacy and deal with their own fears.
Plus, they are fun! A first-line manager, a veteran of 20 years in telecom, exalted at a celebration dinner we attended, after leading her team through a series of small data quality projects: “It was the best experience of my 20-year career. It was the only time I felt like I had any control on where I was going.” We’ve helped launch hundreds, maybe thousands, of such stories from all over the world. People revel in understanding the numbers, what they mean, and the detective work to sort out what is really going on. They love working on teams and seeing the results of their labor improve their work and their company’s performance.
