The Evolution of Enterprise Performance Management (EPM)

Written by Bhaskar Sahay, Partner, Head of Accounting and Finance, KPMG Lower Gulf
As we continue to battle our way through the pandemic, uncertainty about the future has made scenario planning increasingly essential to the survival of most organizations. CFOs (chief financial officers) can play a key role in stabilizing the business and positioning it to thrive when conditions improve, directly contributing to the organization’s financial health and resilience.
A recent survey by Forbes suggests that CFOs’ optimism is on the rise, and they are preparing for explosive growth in 2022. It is imperative CFOs leverage EPM, as KPMG’s 2021 EPM survey shows that 72% of mature EPM clients have already embarked on their EPM journey through supporting centers of excellence, predictive forecasting, and upskilling their employees. They have witnessed a 20% increase in revenue over the past three years.
No longer a choice but a necessity
Enabled by technology, EPM is an enterprise-wide capability that provides a 360° business view to translating strategy into action for improved performance. It allows businesses to holistically align their strategies with plans and actions.
Despite its rewards, it presents a challenge for finance and accounting professionals as understanding and communicating value creation is an iterative undertaking, not an exact science. However, EPM has become a necessity for most organizations since the pandemic started, and has been pushed up on their agendas.
Sixteen years ago, FP&A (financial planning and analysis) was a team within the finance function that was notorious for working late nights and using PowerPoint, whilst the rest of finance were managing their own versions of “death by spreadsheet”. Leaders across organizations struggled to interpret insights from finance.
Today, EPM has evolved. According to Gartner, 54% of finance organizations still struggle to provide data that supports stakeholders’ decisions despite advancements in modern analytics and business intelligence (A&BI). Insight often lacks context and is not easily understood by most users who spend their time in predefined dashboards, which FP&A teams spend hours populating manually.
Globally, organizations who embarked on their EPM journey have shifted their EPM offering from ‘reactively descriptive’ to ‘forward-looking prescriptive’. In the UAE, this shift is less prevalent.
The basis of a successful business partnership
The evolution of EPM comprises four key phases.
Descriptive analytics is used by 90% of organizations today. It answers the question “what has happened?” by analyzing real-time and historical data for insight on how to approach the future by learning through previous success or failure.
Diagnostic analytics, meanwhile, is performed on internal data to understand the “why” behind what happened and obtain an in-depth insight into a given problem. For example, to understand why an organization missed its profit margin goals, they can drill the sales and gross profit down to various product categories.
Predictive analytics seeks to answer the question “what could happen in the future based on previous trends and patterns?”. A particularly relevant example where predictive analytics finds application within financial institutions is in producing credit scores.
In a recent KPMG EPM survey, 54% of respondents are planning to implement predictive modeling in the next 12 months. According to Gartner, 1 of the 3 key strategic actions for success for the CFO is to unlock the value of AI (artificial intelligence) and predictive analytics.
However, the accuracy of predictions is not 100%, as it is based on probabilities. To make predictions, algorithms fill in the missing data with the best possible guesses. This data is pooled with historical data present in various enterprise-wide systems to look for data patterns and identify relationships among various variables in the dataset. Data scientists are required to develop statistical and machine learning algorithms to leverage predictive analytics and design an effective business strategy.
Prescriptive analytics is the next step of predictive analytics: it incorporates an additional dimension of manipulating the future. It leverages both internal (within the organization) and external (e.g. social media data) data advising on possible outcomes, and results in actions that are likely to maximize key business metrics. It uses simulation and optimization to ask: “what should a business do?”
It is an advanced analytics concept based on simulating the future, under various sets of assumptions, allows scenario analysis—which, when combined with different optimization techniques, allows prescriptive analysis to be performed.
Organization leaders would be well advised to ask themselves these questions to evaluate if they need improved EPM capabilities:
- Does your executive team have insight into the group’s true profitability by product, service/channel, country/region, and customer?
- Is your organization combining financial, operational, and customer data to make better decisions and create a competitive advantage?
- Are you able to anticipate future regulatory changes and use insights to gain entry to new markets using innovative channels faster than your competitors?
- Do you know which channels currently provide the best growth and profitability?
- Do you have a plan for optimizing these challenges?
- Are you able to conduct collaborative planning across all of your business functions?
- Are you able to optimize investment decisions and improve shareholder return while maximizing efficiency?