Data-driven decision-making is by no means novel to the business world. Large corporations first began amassing data to form their operational and strategic decisions in the 1980s. As businesses began to see radical improvements in their bottom lines as a result of data analysis, the data-driven approach to decision-making began to catch on and spread to other fields as well. For instance, 2001′s No Child Left Behind Act required schools to make data-driven decisions to continually improve students’ standardized test scores. The theory behind the legislation is that, by examining test score data and discerning the patterns, educators can decide what strategies do and do not promote academic achievement.
Before the birth of data-driven decision-making, stakeholders tended to make decisions based on intuition, which is analogous to flying an airplane in bad weather with no navigational equipment. Like the instrument panel of a plane, data tells the pilot where he is, where he is heading, and how to get there most efficiently. In what follows, you’ll find out why data-driven decision-making is imperative for success and how you can use data to decide the actions you should take.
How Data Help: When Common Sense and Intuition Fall Short
The importance and efficacy of the data-driven approach are best illustrated anecdotally. Consider Walmart’s efforts in 2004 to stock the correct items in its stores on the Atlantic Coast of Florida before Hurricane Frances hit. Executives scrambled to predict what Floridians would buy to prepare for the storm–flashlights, candles, bottles of water, canned goods, and batteries are what common sense would dictate. Rather than relying on intuition, however, the execs looked at purchase data from stores in similar situations in the past. Interestingly, the data showed that Pop-Tarts and beer are top sellers in pre-hurricane times. Walmart stocked these items, and they sold rapidly, all thanks to the insight provided by data mining.
Simple Steps for Making Data-Driven Decisions
Here are five steps for making accurate and effective data-driven decisions:
- Begin with the end in mind. Don’t dive into the data without a question in mind. Determine what you really want to know and what your goal is. Think of this step as the hypothesis-forming stage.
- Use your hypothesis to devise an analysis strategy. At this stage, you need to map out your methodology, or how you will make sense of the data. For instance, will you use a correlation or predictive analysis?
- Collect the data.
- Make observations. After collecting and organizing the data, use the analysis approach you’ve selected to find patterns and glean insights from what you have.
- Create action items and communicate your conclusions. Make a list of actions to take that align with your organization’s mission and goals. In sharing your results, focus on one overarching theme and try to communicate your findings in story form to maximize understanding.
From operations to high-level strategy, data-driven decisions can revolutionize your organization. If you would like to learn more about the data-driven approach to business, consider looking into EMBA programs that offer courses in data analysis, statistics, and decision-making.