Business and Data-Driven Decisions: Where to Start and Why Start?

These three stages will be described in detail below, along with some of the most common things that can go wrong at each stage, so you can avoid making your own mistakes. Keep in mind that every decision is unique, so you’ll have to customize this process for each decision you make; however, this process is a good starting point for most business decisions.

1) Collect Data:

Gathering data is the first step to making good decisions, but it’s not a trivial task. Making sure you have all the facts that you need to make sound business decisions quickly becomes critical when you’re in a rush to evaluate your product or decide how much to raise capital investment. The problem is that rushing through this stage can lead to less-than-accurate decision-making, which can be costly. The problem lies in the fact that most managers do not understand how they make decisions and don’t know how they should be made more accurately.

The purpose of data collection is to gather facts, which are often unquantifiable. For example, in determining whether a customer will become a loyal customer, you may need to consider their location and purchase size over time.

It’s important not to solve the wrong problem when collecting data. It’s also important to understand which variables you’re going to look at in your analysis. Deciding on data values and variables is a crucial part of the analysis as well; misjudging these items will result in ill-informed decision-making.

2) Analyze the data:

Analyzing data is the second stage of data-driven decision-making and should be easy by now. By analyzing the facts that you’ve gathered, you will have a much better idea of what to do with them now, and if you’re doing it right, this should be obvious. Throughout this process, it’s important to remember that every decision is unique – although a lot of these steps may seem overarching, they are different depending on what you’re considering.

There are three main ways to analyze data: descriptive analysis, inferential analysis, and statistical analysis. 

3) Make a decision:

Once you’ve analyzed your data, it’s time to make a decision. The simplest way to do this is to simply go with your gut. However, relying on intuition over data can lead to psychological biases that drive your decisions in the wrong direction.

Before deciding on how to proceed, it’s important to clarify exactly what decision you’re making. Just as important is knowing why you’re making the decision and when it should be made. You may be trying to collect more data, or you may be trying to support a previous decision that has already been made – or maybe not.