Applying Analytics in a Human Way
Applying Analytics in a Human Way
Big data has been one of the big trends of the past year. But by its very nature it can be dehumanizing, distancing us from the reality of people’s lived experience. The challenge we must face this year, and going forward from it, is how to connect that analytics into the lived experience of employees and so use big data in a more human way.
One of the growing trends in big data is using its power to understand and manage talent. At the moment, this is often viewed from a high level. Managers use the data to identify gaps in the talent pool within their organizations, as well as for opportunities to grow the existing skill base. That insight becomes the basis for broad talent development strategies, which eventually filter down into individual training and development.
But there’s a disconnect between the data and the ways that employees experience the results. While the organization is using data to self-reflect and improve, it isn’t using it to give employees the same opportunity.
The best learning and development comes from understanding ourselves. If we can use the available data to increase employees’ self-awareness then we can make them agents of their own talent development, not just recipients of training courses. We should use the data to help them understand their own performance, put that performance in the wider context of the business, and show them what they could be achieving.
It’s about connecting the abstract numbers to the people on the ground.
Training the Analysts
We spend a lot of time considering how we use big data, but not so much on the processes behind acquiring and analyzing it. The fact is, if we want to get more meaningful, human outputs then we need to think about the people doing the work in meaningful, human ways.
The first instinct whenever a new approach is introduced is for it to be taught and developed in old-fashioned ways. We become so focused on the novel content that we forget the important business of how it’s delivered. But there are few more depersonalized, inhuman experiences than old-fashioned rote learning.
Steps are already being taken to ensure that analytics is taught and developed in more human ways, such as through gamification and modern training techniques. Building up tools for this sort of training, and the infrastructure to support them, will help to ensure that big data is used to its fullest potential.
Admit to Flaws
Sometimes we’re so blinded by the power and potential of data that we ignore the flaws in the numbers that we’re using. Again, this comes from forgetting the human element behind all of this, the fact that one way or another human beings have got this data into the system, and that we all make mistakes.
Recognizing the flaws and limits of our data is vital if we’re to use it well. We shouldn’t ignore flaws in our data or make excuses for them, but neither should we expect an impossible degree of perfection. Recognizing how far we can rely on that data, what questions it can answer and which ones it can’t, is as important to using it well as any statistical tool.
There will be times when the data contradicts the views of human beings doing the work. Often, this will be because people can’t see the big picture or are blinded by their assumptions. But sometimes it will be because the data is flawed. We have to look out for both options.
We need to be careful not to ignore the lived human experience in our rush to use big data, but instead use that experience to understand the data better.