You’ve heard the old maxim, “You can’t manage what you don’t measure.” It’s true. The best business decisions are based on factual data, not hunches or gut feelings. Organizations often use descriptive analytics, which take a backward look at the past, but they sometimes neglect predictive analytics, which allow a business to better understand what action should be taken in the future.
Benefits of Using Predictive Analytics
The results of using your analytics effectively include better collections and dispute strategies, improved cash flow, and reduction of non-payment situations. Analytics can also give insight into customer behavior. AICPA-powered CGMA Magazine recently published an article that showed how analytics can deliver insights that help business owners make smarter decisions.
How to Gather and Use Predictive Analytics
With predictive analytics, you’re looking for insights that are action-focused and identify root causes. You want to understand the whys behind issues, and determine what you can do about them. To get the most out of your analytics:
- Understand your purpose. Why are you gathering the data? What do you want to learn? What problems do you need to solve?
- Make sure you have the right expertise and resources in place. Do you have a person or team who can effectively gather the data and analyze it? How much will it cost, either from the standpoint of an internal employee’s time from the standpoint of an outside provider’s fee? Have resources in place to accomplish what you need to.
- Create a clear roadmap for what action you’ll take as a result of the insights. Strategies often fail at the point of implementation. It’s not enough to have the data — you’ve got to know what you’re going to do as a result.
To implement a predictive analytics strategy:
- Understand each problem you want to solve. Don’t stop at surface issues, but understand what the real problems are.
- Create a model that explains your processes and what factors drive performance. You want to know what data is important and what’s missing.
- Capture relevant data. The data may be in databases that need to be integrated. Determine how to access the data you need.
- Apply analytical methods. Standard methods like cross tabulations, regressions, stochastic process modeling, factor analysis, cluster analysis, and experimental design are all helpful. You just need to know the strengths and weaknesses of each method and apply the ones that best fit your needs.
- Present your findings. Management needs to see the data and analysis in a way that they’ll be able to process and understand. Be specific and make it relevant to each person’s role.
When you follow this method, you can go from a defined problem to a data-based solution efficiently. And you can have confidence in your solution, knowing that it’s based on more than an educated guess. Predictive analytics are powerful, and successful businesses know how to use them to make better decisions.