Making Data-Driven Decisions

In business, there’s always an element of risk, but data-driven decisions make you less vulnerable to risky decisions going wrong.

Instead of going with a strategy you think is best, data-driven decision-making is a strategy that uses data to inform business decisions.

Through data, you can group together historical information to analyze trends and make decisions for the future based on what’s worked in the past – rather than make decisions based on gut feelings, opinion, or experience.

Additionally, data-driven decision-making is a great way to gain a competitive advantage, increase profits, and reduce costs.

Now that you know how you can benefit from data-driven decision-making, the next step is to identify how your organization can use data to make decisions for how to grow your business.

• Finance: What’s the most cost-effective way to hire new staff, or the cheapest way to promote a new product?
• Growth: What activities can you do to prevent churn? How do you improve customer loyalty? Are the new features you’re planning likely to impact your business’ goals?
• Marketing and Sales: Which advertising channel gets the best ROI? Which sales activities generate the most leads?
• Customer service: What’s the most cost-effective way to handle support tickets? Which channels improve response times?

Before you analyze your company’s dashboard, it’s best to start with a plan of action that details how you’ll find the data you need and, more importantly, interpret the data to make the right business decisions.

Here’s a five-step process you can use to get started with data-driven decisions:

1. Look at your objectives and prioritize: Any decision you make needs to start with your business’ goals at the core. So, start by asking yourself: What goals do you want to improve? Begin with the most important when you are making decisions.
2. Find and present relevant data: Once you have identified the problem you want to solve and the decision you’re going to make, it’s time to find and present relevant data. You don’t want to spend hours analyzing data that won’t have any impact on your final decision. So, keep the data relevant, and only collect the data that relates to your objective.
3. Draw conclusions from that data: Take a look at the historical data you’ve collected and try to identify patterns or trends. This means looking at your historical data to see if there’s any indication that a rewrite would perform well.
4. Plan your strategy: You’ve found the goal you want to improve and analyzed the data to make a decision on whether you’re going ahead with a new strategy. Next, you’ll need to create a plan of action to put your decision into practice. The key at this stage is to make clearly defined goals on what needs to be done and when, by whom, why you’re doing it, and what is the outcome you expect – rather than creating vague goals that “need to be done before the end of the year”.
5. Measure success and repeat: Your decision-making process is never over! Look at the data you originally collected and based on your initial decision. Then, once the deadline for your goal arrives, compare the historical data with the new data you have collected and ask yourself: Did your data-driven decision have a positive growth impact on your business? If your decision was successful, congratulations! But if it wasn’t, that’s okay. Your decision might not have had an immediate impact, but at least now you know what doesn’t work. And sometimes, that’s equally as important as knowing what does work.