FP&A practitioners rely on raw materials, i.e. data, to conduct their work.  In order to conduct their work a variety of data types should be utilized. There are three types of data that FP&A practitioners should utilize.

The first type of data is financial numbers. Financial numbers must be utilized due to the goal of FP&A. The goal of FP&A is to assess whether wealth is or will be created based on decisions within businesses. These decisions can be assessed through elements within financial statements. Income, stockholders’ equity, and cash are the elements most commonly used to assess wealth. These elements are expressed through financial numbers so it seems foolish to describe their importance but it is necessary to do so. This is due to the role of other data types.

The second type of data is non-financial numbers. In accounting non-financial numbers have been emphasized through measurement systems like The Balanced Scorecard. The purpose of The Balanced Scorecard is to assess the performance of businesses through perspectives other than financial like the perspectives of customers, internal processes, and employees. Assessing performance through perspectives other than financial rely on measurements that are numerical but non-financial; examples are the number of customer complaints, the amount of time to fulfill an order, and the number of employee suggestions per month. It is non-financial measurements like these and others that can be utilized by FP&A practitioners. FP&A practitioners can use these measurements to acquire insight into activities that ultimately affect traditional measurements used by FP&A practitioners like revenues and expenses. It is the use of non-financial numbers that FP&A practitioners can rely on to conduct their work but numbers should not be the only type of data used.

The third type of data is qualitative. Examples of this type of data are customer names, product names, and vendor names. These examples help FP&A practitioners acquire insight into who companies conduct relationships with and what they not only acquire but also provide in order to develop these relationships. These examples are typically found within accounting software however the desire to learn more about how businesses function has created the opportunity to access qualitative data through other software packages. Statistical software like Python and R can access data from social media services like Facebook and Twitter. These services contain qualitative data that provides deeper insight into how businesses conduct relationships through comments within posts and tweets. This deeper insight can give FP&A practitioners another perspective into the current as well as future financial health of businesses.

There are a number of data types that can influence one’s actions. Financial numbers, non-financial numbers, and words can determine how people evaluate situations and respond to them. FP&A practitioners should take a leadership role in helping people understand the strengths as well as the weaknesses of using various types of data within their businesses.