Predictive vs Prescriptive Analytics in Finance

Matthew Dziak

Predicting the future is nearly impossible, so much so that even Nostradamus and the Mayans missed a few of their predictions (remember the 2012 doomsday calendar ending). Nonetheless, Finance teams must find a way to forecast metrics and consider different scenarios for the most accurate potential outcomes for the business. It’s an uphill battle that requires an understanding of fundamental financial principles, and with the increased adoption of cloud-based solutions, requires technical and data management skills they simply don’t teach you in business school. 

If 2020 and the pandemic taught us anything, it’s that while the future is uncertain, the best-positioned companies utilize a combination of predictive and prescriptive analytics in finance, to prepare themselves for what’s to come. 

What is predictive analytics?

Predictive analytics is the exercise of utilizing data, statistics and modeling to a range of potential outcomes. As the name suggests, predictive analytics is a prediction of the future based on historical data.   

What is prescriptive analytics?

Prescriptive analytics is the exercise of aggregating metrics, analysis and forecasts to generate actionable insight and strategic initiatives in pursuit of a desirable business outcome.

Here’s a simpler way to think of these analytic concepts. Let’s say that you had a few too many glasses of wine at Friday’s happy hour.  Predictive analytics tell you that you may be fine in the morning, or that you may wake up feeling a bit fuzzy.  Based on your past experience, your age, and further reflection on the precise quantification of “a few too many”, you apply prescriptive analytics and elect to take aspirin before you go to bed in an effort to stave off the possible hangover. 

Comparing predictive vs prescriptive analytics

Predictive analytics identifies “what might happen,” while prescriptive analytics identifies “how can we make that happen.” These analytical methods aren’t just for business data analysts. For finance, predictive analytics consists of forecasts, reports and scenarios, while prescriptive analytics facilitates strategies or the actionable items necessary to achieve those targets. Therefore, prescriptive analytics offers the greatest value to a company because it provides the tangible solutions to reach the desired outcome.

Predictive vs Prescriptive vs Descriptive Analytics Defined and Explained for Finance

Predictive analytics:

  • Identifies the events that might occur
  • Tends to focus on singular metrics and trends in isolation
  • Identifies KPIs and metrics and predicts them in the future based on historical trends

Prescriptive analytics:

  • Suggests ways to optimize the course of events
  • Incorporates multiple data points and analytical insights
  • Produces actionable insights designed to improve projected trends or outcomes

A well-managed company combines descriptive analytics, (the production and summarization of basic data) often managed by accounting, predictive and prescriptive analytics to operate their business at a strategic level. At the foundation are descriptive analytics or the basic elemental data you need as a starting point for any analysis. Predictive analytics build on this foundation providing key metrics and forecasts. Prescriptive analytics then add even more value by leveraging predictive analytics to drive the company to its desired goals.

If you are a Company trying to build this hierarchy of analytics into your business, where do you start? Like most construction efforts, you start with the foundation or in this case the raw data. Much of the necessary financial and transactional data you need for predictive analytics is stored in your General Ledger or ERP System, but accessing it requires manual data extraction and further manipulation to stage it for predictive analysis.

Remember that the more time you spend staging your data for analysis, the less time you have to actually analyze it and derive prescriptive insights. Mature finance functions automate these manual data extractions so that they can devote more attention to higher level prescriptive analysis.

General ledger and ERP systems are great when it comes to capturing actual historical data, the building block of predictive analytics, but they are lacking when it comes to organizing future-related information like budgets and forecasts — the essence of prescriptive analytics.  At this point, many companies resort to Excel; however, this plan is doomed to fail. To compile, track and manage multiple versions of your budgets, forecasts and scenarios across many departments requires a robust FP&A Platform.

Real-world examples of predictive and prescriptive analytics in finance

To be impactful, a finance function must utilize both predictive and prescriptive analytics. Once finance provides scenarios and predictive forecasts, a company will need strategies to improve upon those forecasts — this is a prescription for success. 

To better explain how these analytical approaches work, let’s focus on a prescriptive analytics example for finance

Say your company sells widgets and wants to maintain, or even exceed, its growth trajectory. Based on predictive analytics, you project sales will grow at a level comparable to GDP (~5%), a lackluster outcome for most. This is where prescriptive analysis comes into play, where you provide insight and strategies to exceed that rate (alpha). While remaining within the confines of the annual budget, your prescriptive analysis results in a need for the following actions to reach the intended outcome of increasing revenue. 

  1. The Sales Department requires three additional headcount and a six-month ramp period for new reps to hit their widget selling quotas. 
  2. The Marketing Department needs to increase lead conversion rates by 5% to ensure adequate sales pipeline growth. Additional campaigns to encourage a wider use of the widgets.
  3. The Product and Development Team needs to add a new tool to the widget by the end of next quarter to aid in the market’s desire for more features and functionality.

Predictive and prescriptive analytics fuel strategic conversations at the management and department level. Budget owners and department heads can utilize these guidelines to develop necessary campaigns, tasks and decisions from your strategic initiatives.

To take things a step further, monthly forecasts can track actual progress compared to projected targets, to ensure proper execution of strategies. In essence, both of these analytics methods include financial modeling (forecasting) with the addition of data science.

But you don’t have to be a data scientist or technical database expert to manage data and extrapolate it for scenario planning and forecasting. You certainly don’t have to be a robot to achieve this; however, it helps to leverage software with the necessary automations to efficiently predict future scenarios that could impact your business and outlook. 

Best practices for successful CFOs - FutureView Systems

How can FP&A Software improve your analytics processes? 

The digital transformation is in full force across enterprises and the finance function is no different. If you think you might be lagging behind, don’t fret. According to EY’s digital disruption in finance survey, only 11% of finance leaders believe they are in the advanced stage of the digital transformation of their finance function.

Many companies face a limited availability of resources in your finance function to efficiently provide predictive and prescriptive analytics that support your business objectives. If you are conducting analysis using a combination of an ERP System with Excel, you’re missing out. FP&A Software like the FutureView Platform provides direct integrations with your ERP System and other sources of truth to automate real-time data extraction while maintaining version control. 

Additionally, our Platform automatically organizes and structures the data for you to analyze, create reports and forecast without manual data manipulation. Not to mention, you can start your reporting and analysis prior to the books being closed to dramatically reduce the likelihood of reporting errors. You can’t predict the future, but you must prepare for it.

Transforming an entire workflow isn’t an overnight phenomenon, but you can expedite the process by partnering with the correct vendor that can have you up and running in weeks, not months. Schedule a personalized demo, and let’s discuss how our software solutions can greatly impact your analytical and finance function in a matter of days, not months.