Difference Between Older And Younger Workers Working With Data

The rise of the digital age brought with it the rise of data. Looking at the difference between older and younger workers working with data allows us to see the opportunities and challenges before all of us.

The Experiential Difference Between Older And Younger Workers

The primary difference between older and younger workers is one of experience. This plays out in two ways. The first seems obvious. Older workers have more experience. Younger ones have novel experience.

The second way is the degree to which they’ve experienced reality differing from what they’ve learned. Time teaches older workers that there is often a huge difference between reality and the book. Younger workers see less difference degree. Any difference is an aberration, not reality.

In other words, when it comes to data, older workers will trust their experience more since no data set can completely capture reality. However, this also creates a bias discounting data. That means older workers will have a harder time accepting data that conflicts with their experience and the powerful stories that support it.

On the other side, younger workers will have more faith in data. They don’t have the experience to distrust it especially in new situations. After all, data are historical. Their predictive powers are only as strong as the likelihood the future will be like the past. Thus, younger workers’ bias overweighs data.

The Power Difference Between Older And Younger Employees

We can grasp this difference between older and younger employees working with data by looking at the power differences between the two. Unless a younger worker is very talented, it’s very unlikely she’ll overcome the experience of an older worker in the field.

Nonetheless, she can counter it with new ideas, those outside the older worker’s field of expertise. She can also counter it by employing new processes, new data and new methodologies. After all, these, such as software, exist to reduce the difference between the skilled and the unskilled. Take a look at how the gun reduced the difference between a common laborer and a samurai. In short, data give her power against experience.

Yet, in the end, this difference between older and younger workers, each type’s pros and cons working with data, gives insights into how each helps the other, how all can optimally work with data.

It’s not a choice of sides. It’s an integration of human experience with hard data. Without data, our biases make the decision. Without experience, decisions become mechanical, failing to fit reality optimally. Thus, the difference between older and younger workers working with data, shows us how to strike the right balance for the situation before us.