We live in an age where information is at everyone’s fingertips. Anybody can look up something on the internet and learn a new skill from online courses or tutorials. For more serious purposes, registering and paying a small fee can give further access to a library of valuable published research and scholarly journals.

When such a wealth of information is at your disposal, it’s almost negligent not to use it. And especially in the business world, it can seem as though data analytics is now a non-negotiable part of your operations.

But data can also lead you astray. Without keeping this in mind, many leaders can get things wrong by ignoring the empirical approach. They take information indiscriminately from various sources and use it as the basis for their decisions. Here’s why you need to be rigorous and intentional when using data in your decision-making process.

The easy way

Decision points come up all the time in business. There are rare, high-risk decisions that can shape the future of your business. Far more often, you’ll have to deal with day-to-day affairs; these are usually delegated to middle managers or teams of employees.

The volume of decisions involved often competes with the limited time and attention of people in a typical hierarchy. When this takes place at the upper levels, the intuition and experience of senior management are usually up to the task.

But at lower levels, employees might rely too much on what’s readily available to move forward and take action. They might simply look up common knowledge and best practices, find some frequently referenced case studies and use these as a guide.

Flawed conclusions

This doesn’t have to be a problem with delegated work. Such decisions usually tend to be low-risk, and allowing employees to fail on occasion is vital to their growth and empowerment. But the practice of unintentional data usage can permeate your organization and lead to bigger issues later on.

In research methodology, you approach a problem by reviewing the relevant data and find the gaps in knowledge. You can design an experiment to test a hypothesis. That hunch might be proven wrong or right; ultimately, what matters is progress towards understanding.

When people are inclined to take the easy route with data, they can ignore the basic step of gathering more information as needed. This can invalidate everything that follows. It can leave your business blind to risks or opportunities simply because no data is currently available.

Changing a culture

By renewing your focus on the empirical approach, you can empower employees to spend more time gathering data when necessary to solve a problem. This allows solutions to be rooted in your data, rather than merely relying on what worked for others.

Maybe your data tells you that your customers have a pleasant experience at every touchpoint, except product returns. If this isn’t a problem for your competitors, they will ignore it; it won’t show up in the research. By digging deeper, you realize that you can create value by working with a reverse logistics provider to improve this part of the customer experience.

Thus, applying a rigorous, empirical method to your use of data will encourage employees to break bad habits. And in their place, new potential opens up for collaboration and innovation. Instead of seeing data as a shortcut, a way to make their jobs more comfortable, they can relate it to a bigger purpose: the overall success of your business.

Getting it right with speed

But it’s essential to remember that data is still at its best when it enables swift and effective change. A study by McKinsey showed that the speed and quality of decision-making are correlated. Organizations that tend to be winners in this respect can make the right decisions in less time and thus act faster.

How can you make better use of data while still ensuring a rapid and effective decision-making process? The research suggests that speed is gained in other areas. Streamlining the hierarchy helps. If you assign decisions to the right level and minimize the number of levels people must report to, feedback flows faster through the chain. It translates into timely action.

Equally, stakeholder commitment is a significant factor. This goes back to your culture and your employees. If everyone trusts the decision-making process, they will buy-in. They won’t hesitate to act. And that trust is founded upon knowing that data is being used in the right way.

Take your time, do the hard work of research, and make sure that your business is acting based on your own data. You’ll be able to make winning decisions and adapt quickly to every level.