KPIs: The Linchpin of Performance Management

In this edition, I want to get back to the basics. Using key performance indicators (KPIs) to your advantage is deceptively simple, yet most organizations go overboard with selecting too many KPIs, conflating KPIs with OPIs, and failing to tie metrics to overarching strategic initiatives.

I have included links throughout this article offering a deeper dive into the topics covered, should you be interested. Let's jump in.

You Can't Improve What You Don't Measure

Delivering successful data & analytics solutions that have a strong business impact is dependent on a litany of factors: culture, governance, technology, data quality, and more. However, the most fundamental source of support and stability is the key performance indicator (KPI). What is a KPI? Why does it hold such a significant position in data analytics? And finally, what can you do to design and build a robust KPI framework to deliver improved business performance?

First things first. What is a KPI? A KPI is a quantifiable measure used to evaluate the degree to which an entity is meeting its performance goals. The entity could be the entire enterprise, a business function such as procurement or finance, or a product category. A KPI is a way of measuring the leading (predictive and prescriptive analytics) and lagging (descriptive and diagnostic analytics ) effectiveness of the entity and its progress toward achieving its goals.

Basically, KPIs are a reflection of a company’s ability to drive business results toward a clear strategic goal. If a business is appropriately using KPIs to measure and improve its performance, those KPIs?drive organizational behavior and culture. This self-fulfilling cycle separates best-in-class companies from the rest.

Yes, KPIs are THAT Important

Why do KPIs hold such a significant position in data analytics? What is the business impact of KPIs? Strong enterprise performance management (EPM) rests on the fundamental management principle of “what gets measured gets done”. The value of data analytics is to offer real-time visibility into leading and lagging KPIs to sustainably manage business performance.

By mapping business goals to consistent KPIs, organizations can derive an immediate and accurate picture of their performance. Basically, a well-designed KPI framework holds the key to providing the right feedback to track and improve business performance. Aberdeen Group?examined ?the use of KPIs in more than 350 enterprises and found that the best-in-class companies experience drastic performance improvements from their KPI frameworks, including a 10% increase in time-to-decision, a 9% increase in profitability and revenue growth, and improvements of 9% in both new customers gained and customer satisfaction. The message is clear.

How To Take Action Today

So, what can organizations do to design and build a robust KPI framework? Fundamentally, the most effective KPIs are closely tied to strategic objectives and help to answer the most critical business questions. In building a solid KPI framework to improve business performance, three foundational elements should be considered.

1. Robust Insights

Measuring business performance using KPIs is an involved process. While there is a natural inclination in every business and in every individual to know more, one needs to evaluate how these insights or knowledge will be used for making decisions. Prioritization is critical.

Albert Einstein once said, “Not everything that can be counted counts”. So, while designing your KPI framework and dashboards to communicate insights, always ask these important questions: Why do you want to know XYZ? How much information do you need to take action on XYZ? What is the value of knowing and not knowing XYZ?

This exercise begs the question of the recommended number of KPIs in each framework. Cognitive science researchers believe that human beings can normally cope with just five to nine pieces of information at a time, popularly known as the “Magic Number .” This means 7 +/- 2 KPIs (including leading and lagging indicators) is the recommended count of KPIs in each framework.

Remember, each framework should relate to a key business entity (function, product area, or the entire enterprise), and contain KPIs governing the outcome of major strategic initiatives. An obvious example of this is the inclusion of revenue and net new customers as KPIs in the framework for a strategic growth/expansion initiative.

2. Accountability

This is also one of our core values at Astral Insights ; the importance of this section cannot be overstated.

While designing and implementing KPI frameworks is complex, integrating them into a business’ operating model is more challenging still. While change is inevitable, it can often be uncomfortable. How can we use these KPI-driven insights to bring change in operations, compliance, and decision-making across the organization? How can KPIs be an active part of daily management and operations??

Successful change initiatives are invariably correlated to accountability. This means having clear expectations from each individual, and the team as a whole, on how to achieve goals and helping one determine the gaps between expected and actual performance. It means taking ownership over results and responsibility for improving them. This is often uncomfortable when confronting problematic areas of the business, requiring leaders to set a strong example that enables a culture of collective accountability.

Notice that none of this is about data or technology. It is about PEOPLE. Data analytics is not a silver bullet, but rather a tool that is only as good as those who wield it.

3. Quality Data

Reliable KPIs are dependent on quality data, yet a staggering majority of organizations fall short in this area. Research published in?Harvard Business Review ?says that just 3% of the data in modern enterprises meets data quality standards. While quality data in business is contextual and multidimensional, defining that context and selecting the pertinent data quality dimensions will help focus your efforts. With accurate dashboards conveying KPIs, decision makers can trust the information presented to them and ultimately make better, faster decisions.

While many data analytics projects do a great job in identifying the consumers of the insights or KPIs, the business goals of these consumers are often poorly defined and do not align with the larger objectives of the enterprise. Research advisory firm?Gartner ?reported that 80% of data analytics insights do not deliver business outcomes. One effective solution is formulating an objective statement by asking powerful questions, formulating a strong hypothesis, and defining the KPI framework based on the three key elements we have discussed: robust insights, accountability, and quality data.

Leaders must work to identify the ideal blend of in-house resources and external partners to hit the ground running and quickly deliver an ROI on their data & analytics investments .

Management guru Peter Drucker once said, “You cannot manage what you cannot measure.” KPIs offer actionable insights by offering backward and forward-looking visibility into performance and the drivers of performance. Basically, value starts with visibility.

About the Authors

Dr. Prashanth Southekal is a Consultant, Author, and Professor. He has consulted for over 80 organizations including P&G, GE, Shell, Apple, and SAP. Dr. Southekal is the author of two books — “Data for Business Performance” and “Analytics Best Practices” — and writes regularly on data, analytics, and machine learning in?Forbes.com , FP&A Trends, and CFO. University. His second book, Analytics Best Practices was ranked as the top analytics book of all time in May 2022 by BookAuthority. Apart from his consulting pursuits, he has trained over 3,000 professionals worldwide in Data and Analytics. Dr. Southekal is also an Adjunct Professor of Data and Analytics at IE Business School (Madrid, Spain) and CDO Magazine included him in the top 75 global academic data leaders of 2022.?He holds a PhD. from ESC Lille (FR), and an MBA from Kellogg School of Management (US). He lives in Calgary, Canada with his wife, two children, and a high-energy Goldendoodle dog. Outside work, he loves juggling and cricket.

Christopher Andrassy is an entrepreneur focused on transforming data into sustainable business value on a global scale. He began his career at PwC in New York City, supporting the digital transformation of mature organizations struggling to innovate in a hyper-competitive world. After experiencing the shortcomings of traditional analytics practices, he decided to begin a new chapter alongside colleagues and industry veterans. His departure from New York marked the inception of Astral Insights , a Raleigh-based decision intelligence firm helping mid-market and enterprise clients transform data into profit. Chris is also an investor focused on innovative technologies including synthetic biology, sustainable energy, and artificial intelligence. Outside of work, he is an avid musician, skier, traveler, and fitness enthusiast.