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.
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.