Now that we’ve discussed how an individual or a group can arrive at a good decision, let’s talk about some of the things they need to consider when they’re making that decision. And by “some of the things,” we mean data.

Years ago, companies struggled and toiled over reports that would provide data on which to base a decision. Now, in this computerized universe, data is everywhere. It’s just a matter of harnessing it for your organization, reading it correctly, and making it work for you. Companies that use data in their decision making processes are more flexible and agile and stay competitive.

So how does an organization use data in its decision making processes? Well, let’s say that data just became available for the first time to your organization yesterday. These steps might be a good way to for you to approach the use of data in your decision making:

1. Decide on your strategy
2. Identify key areas and target data
3. Collect the data
4. Analyze the data
5. Make a decision about the data
6. Present your findings

Now, let’s dive a bit deeper into each of these steps!

Step 1: Decide on Your Strategy

It’s easy to get overwhelmed with all the data that’s out there to use, so when you’re incorporating data into your decision, it’s best to start with the strategy. What is it that you want to accomplish on behalf of the organization? What business areas do you want to improve? Get your action plan in place. If your goal is to increase the response speed to customers calling into your company’s service line, then you know where to start looking for information.

Step 2: Identify Key Areas and Target Data

Which questions do you want to answer about your customers calling into your company’s service line? You might want to know how many customers call in on average each day, but it might also be valuable to know which days are the busiest and which are the slowest. You may want to know how many customer service representatives are scheduled at any one given time and how long each of them spends on a call or email.

Step 3: Collect the Data

Where is your data coming from? Is it from internal sources, or are you looking to purchase external data? It’s likely you’ll need to contact data owners and harvesters and put in your request. If you want to see all data on product sales for the last quarter, you will probably have to contact the people in finance to handle that. If you want to understand your organization’s turnover, someone in HRIS might be your best bet.

In many cases, departments will set up reports to run with a certain set of criteria. An HR department’s turnover reports might include salary level, title and job classification. If you want to see length of employment or department added to their regular reporting, this will likely take a little extra time and a few extra work hours to accomplish. Allow for that extra time when you’re planning your own work schedule.

Data can also be purchased. You may look to a company that collects and sells their customers’ personal information, like their addresses, income range, age, and buying habits. These lists are valuable for companies that want to employ direct mail to sell their product. Another kind of data that is often purchased by organizations is industry data. For instance, the American Pet Product Association (APPA) produces a “bible” of information for veterinarians, pet retailers and pet service providers. For a few thousand dollars, the APPA will share their research on the growth of the pet industry, how many US households own pets, what kind of pets they own, what kind of income they have, how many kids they have, and so on.

Whatever data you’re collecting, keep your strategy in mind as you request it. Will the data help you make educated decisions around your strategy? If not, don’t ask for it, because that would be a waste of your time and everyone else’s.

Step 4: Analyze the Data

You’ve come this far, now it’s time to look at the data that’s been provided and determine trends and information that can help your strategy. It could be that you have just a small slice of data, a page or two of numbers that isn’t hard to sift through. Or, you could have a terabyte hard drive full of stats and figures that would be almost impossible to go through by hand. No worries—there are computerized platforms that will help you get through this part. We’ll cover those a bit later.

You may also have to “clean” the data up as you analyze it. Are there items showing up in the reporting that you know shouldn’t factor in to your final decision? Maybe you’re looking at a turnover report, and it includes all people who were fired in their first 90 days on the job. You may have to back that data out of the report to get a true idea of how many employees (who aren’t in their probationary period) are choosing to leave the company.

As you come to conclusions about the data, make sure they’re accurate and insightful, that there aren’t any bogus “correlations” included in your interpretations.

Step 5: Make a Decision about the Data

Be cognizant of the biases and other things that can trip you up as you make your decisions about the data, but determine the next steps for your strategy based on the information in front of you. Remember, the numbers never lie—but you can also make them say pretty much whatever you want. Don’t fall victim to confirmation bias when you’re lining up the data.

Step 6: Present Your Findings

Someone, somewhere, is interested in what you’re doing. Organizationally speaking, there are people who have hitched their wagons to your strategy’s star, and they’re waiting on your analysis to take action. Show them what you think the data is telling you, how you came to that decision, and how it will affect your decisions on your strategy moving forward. Agree, together or on your own, that you’re going to turn this data-based conclusion into action.

Those are the steps to using data to support decision making. Now let’s take a look at “big data” and how a person can get . . . well, a little overwhelmed with the amount of data that’s available to today’s decision maker.