The Blueprint to a Robust KPI Framework
Given the margin for error in FP&A, using the most effective and up-to-date methods for performance analysis is a crucial step to take in the new fiscal year. Among such measurement methods are Key Performance Indicator (KPI) frameworks, which lead finance professionals to a new level of predictive, prescriptive, and descriptive insights that maximize the results of their labor to set a great foundation of financial information for their enterprise. By understanding the basic tenets of KPI frameworks, the benefits of these frameworks, how specific technologies enable the calculation of KPIs, and the best strategies in this powerful performance evaluation method, finance teams can maximize their ability to comprehend where they are in relation to their performance objectives.
A KPI is a quantifiable measure used to evaluate the success of the FP&A organization in meeting its performance objectives. A good KPI framework covers the leading (predictive and prescriptive insights) and lagging (descriptive insights) metrics. Descriptive insights help to answer the question “what happened?”, predictive insights answer the question of “what will happen?” and prescriptive insights answer the question “what should be done?” Basically, if a business entity including the FP&A function is using KPIs to measure its performance, those KPIs typically drive business behavior, results, and the organization culture.
How to Best Strategize KPIs
Effective FP&A performance management is founded on the fundamental principle that “what gets measured gets done.” KPIs provide the visibility to measure and manage business performance. Recently, Aberdeen Group examined the use of KPIs in more than 350 companies and discovered that the best-in-class companies derive performance improvements (including 10% increase in the time-to-decision making; 9% increase in both profitability and revenue growth; and customer performance improvements of 9%) in both net-new customers gained and customer satisfaction.
There is no one-size-fits-all when it comes to choosing a suitable KPI framework for your business. Building the FP&A KPIs framework that is specific to your organization starts by formulating the questions appropriate to the unique context of your enterprise. Questions are important as they provide the context to the insights or KPIs.
An important factor to consider while formulating good questions is the framing bias. The framing bias is a cognitive bias that impacts decision making based on the manner in which the question is formulated, considering that we are all influenced by the manner in which the question is presented. For example, take two vendors whose quality of delivery needs to be assessed. One vendor performance could state “10% defects” and another could state “90% defect-free”. The framing effect will lead to us picking the second option because we naturally tend to value options that are framed positively. Hence having the KPI definition i.e., “defect-free” or “defect prone” is very important as it impacts the data selected and ultimately the decisions made from the KPIs.
So how can an FP&A function implement an effective KPI framework? First and foremost, the questions in formulating the KPIs should be tied to the strategic objectives of the business - the value drivers. Once the right questions are selected for the KPIs, three foundational elements discussed below should be considered in building a strong FP&A KPI framework. FP&A teams should be very selective in choosing KPIs because the wrong KPIs can potentially harm the organization.
1. Quality Data:
Reliable KPIs are dependent on quality data given that most businesses are plagued with low quality data. Recent research published in Harvard Business Review says that just 3% of the data in a business enterprise meet data quality standards.
To pin down what “quality” data means: Data is considered to be of good quality if they are fit for use in operations, compliance, and decision making. In this specific area, while quality data in business is contextual (based on time, location, data consumers, business environment, and so on) and multidimensional (such as accuracy, correctness, completeness, timeliness, and more), defining the context and selecting the pertinent data quality dimensions will help decision-makers trust the insights offered to them through the KPIs and ultimately help them make better decisions.
2. Reliable Insights:
While there is a natural inclination in every business and in every individual to know more, one needs to evaluate how these insights from the KPIs will be used for making decisions. Albert Einstein once said, “not everything that can be counted, counts.” However, trying to analyze all the data to derive insights might be expensive and time-consuming. Instead, it is better to form a hypothesis or a logical proposition as the hypothesis will provide you with an indicator of what data to acquire while helping you stay on track. Once a good hypothesis is formulated, design the KPI model, by asking these important questions for an accurate and deep understanding. Why do you want to know - articulate the root cause? How much do you want to know – the scope? What is the value of knowing and not knowing – the strategy to convert insights into actions? This begs the question on the recommended number of KPIs in the framework. Cognitive science researchers believe that human beings can normally cope with just five to nine pieces of information at a time. This means 7 +/- 2 KPIs (leading and lagging) is the recommended count of KPIs in your KPI framework or FP&A dashboard.
Although it is difficult to implement and design the KPI framework, it is even more challenging to realize the change; integrating the insights from the KPIs into a business’s operating model can prove very complex. While change is inevitable, it is most often uncomfortable. How effectively can we use these insights and bring change in compliance, operations, and decision making? How can KPIs be an active part of FP&A operations? Successful change initiatives are often associated with accountability. This means having an accountable CFO who is close to the KPI being tracked for performance. For example, if the KPI is on “Days Payable Outstanding (DPO)” to improve the cash conversion cycle (CCC), it is advisable to have the Account Payable (AP) Manager track and improve the DPO KPI.