Point of View

Digital will drive the next wave of enterprise performance management transformation

Print This Page

Enterprise performance management (EPM) in financial planning and analysis has never been short of buzzwords. Zero-based budgeting, driver-based forecasting and balanced scorecards are just a few. Yet despite the fancy terminology—and compared to other areas of finance—EPM is lagging behind in improving decision making and helping businesses identify new opportunities.


A vast majority of enterprises still use Excel sheets to run analytics. These companies allocate an inordinate number of hours for collating management reports and carrying out ad-hoc manual data testing and business analyses. They spend close to 70 to 80 per cent of their time gathering and fine-tuning data as opposed to analyzing it and deriving intelligence. It's a common complaint by business leaders—and often reluctantly acknowledged by CFOs—that by the time they get insights from data analysis, it's often too inwardly focused and historical, offering too little too late for significant action.

As in so many other areas of business transformation today, going digital in EPM has the power to bring about a fundamental change. New technologies can provide self-service capabilities of dashboards and reporting, delivering access to results and reports instantly.

But transforming EPM needs to go beyond simply introducing technology. Organizations need to keep five cornerstones in mind to truly transform EPM.

1. Standardization with mass customization

EPM transformation has traditionally focused on standardizing information structures and reports. The objective has been to bring down the number of reports, say from 500 to 50, across the organization, so that everyone is talking the same language and wasted effort is minimized. But in the search for extra insight, many have felt the need for additional reporting and, after streamlining output, have gone back to producing a larger number of reports. Similar challenges exist in the search for one standard definition of master data.

To solve such challenges, EPM needs to be designed with principles we see in other areas, such as e-commerce. Take a travel portal like Expedia, for example. It has a common database and, depending on the demographics and purpose, hundreds of front ends allowing users to consume standardized data in multiple formats. Digital can enable finance functions to create mass customization to help EPM practitioners consume information in the manner they want in order to make business decisions.


Case Study: Report standardization for an insurance company
A leading insurance company redesigned and standardized its financial planning and accounting reporting process. The insurer implemented a reporting solution based on automation, process fixes, policy changes, and related IT changes, and brought down the number of reports from over 100 to 30. It also introduced self-service reporting, which allowed users to customize reports and reduced the time spent on data gathering and integration so they could focus on making decisions.


Figure 1: The five cornerstones of EPM transformation

SeeClose detailed view

2. User experience drives adoption and effectiveness

One of the major challenges facing EPM is simplifying the user experience and increasing system adoption to improve decision making. EPM practitioners must be able to easily interact with data and derive insights in the manner they want.

In recent years, the application of design thinking has marked a turning point in technology adoption, well beyond business-to-consumer markets. Bloomberg applications that help track investment portfolios are a case in point. Data is collated from stock markets, commodity markets and news aggregators, yet users interact with data differently depending on their investor profile or whether they are a short-term or a long-term trader.

Digital technologies allow organizations to quickly decide on the type and sources of information and the algorithms to run on data sets. They also give users the flexibility to select the kind of insights they want, how they want to access them and the actions they want to drive.


Case Study: Point-in-time reporting for a financial services company
A financial services company standardized reporting processes across five lines of business and created a virtual business intelligence platform to integrate data from multiple sources. It created point-in-time reporting that helped raise productivity by 18%, reduced the number of management reports for one business line by 79%, and decreased the time spent gathering and integrating data by 47%, bringing it in line with best-in-class standards.


Take a copy for yourself

Download PDF

3. Agility rather than accuracy is the name of the game

Accuracy can be a double-edged sword. Eighty percent of EPM efforts focus on the past and getting to the highest level of accuracy (mistaken for granularity), which leaves little time for generating insights and taking actions. The remaining 20% focuses on the future, drawing on bottom-up forecasting, which elongates the cycle time. In the current, rapidly shifting business environment, the whole cycle time from data to insight to action needs to be a fraction of what most organizations achieve. This requires a change in mindset to strike a balance between accuracy and agility using digital for directional guidance.

Outside of finance, take the case of the car fuel meter, which can indicate how long fuel will last. The algorithm can only provide directional guidance as it crunches multiple variables. It is almost never accurate as the variables rarely play out, but it does provide the driver with a bias for action and when to refuel. EPM processes should provide similar agile actionable insights, which, in most cases, have to be in the right order of magnitude and ranges rather than pin-point accuracy.

For consumer product companies this means using business intelligence and machine learning tools to get real-time stock-keeping—affected by pricing/margin impact due to external commodity-cost variations—correlated to inventory and demand patterns. This is a far more effective decision-making practice and a leading indicator than waiting for exact cost calculations based on actual data, which would include a lagging parameter.

4. Literacy is more important than numeracy

An example from other markets can help illuminate this factor. Amazon has made effective use of this concept by enabling smart use of data well beyond the traditional descriptive narrative. Using digital technologies, including big data, Amazon makes recommendations based on ratings and feedback to encourage consumption.

The same concept can be applied to EPM. For example, take the case of vendor risk management. Organizations need to look beyond a supplier's numbers and financial standing to consider qualitative aspects, such as reputation and industry trends, to determine if the vendor is a critical and sustainable source of supply. The ability to evaluate and manage risk profiles through dynamic scoring is more effective than periodic, static, segmented, and differential approaches.

In the same vein, EPM must move beyond its focus on data to integrate qualitative aspects and lead indicators to determine trends across sales, inventory, supplier performance, stock levels, and cash balances. This forces an external orientation and the need to look for influential data as opposed to just confirming numbers.

5. Operating model for specialization

Organizations typically have a fragmented EPM organization housed in each of their business and operating units staffed with highly educated, expensive, and often frustrated business analysts. They are expected to play multiple roles: data scientists, statisticians, data processors, business managers, and more. However, in reality, about 75% of their time is spent on data-related collection/aggregation, cleansing, and basic analysis. Only the remaining 25% is used for insight generation and business partnering, which should be the main focus of EPM.

The skills required to collate, synthesize and visualize structured and unstructured data are different from those needed to experiment with and fine-tune analytic algorithms. The latter are again different from the business and industry acumen that drives effective business partnering.

EPM transformation must address this complexity by driving the creation and maturation of centers of excellence for data management and analysis. They must house them in the best and most cost-effective location for that talent and ensure there is investment or partners to drive continuous innovation. This frees up capacity within the business and enables the EPM function to become a true business partner in order to help the drive the business.


Case Study: Operating model redesign for a Fortune 500 pharmaceutical company
A Fortune 500 pharmaceutical company reimagined its corporate management reporting process. It designed a new delivery structure based on a front-office/back-office model, realigning activities according to complexity and expected skill sets. It introduced a governance structure that helped improve quality of output and increase internal CXO satisfaction while also delivering significant productivity gains through arbitrage and efficiencies in data and report management.


It can be hard to bring these five cornerstones together, which is where methodologies such as Lean DigitalSM can make a material difference. Lean DigitalSM leverages digital technologies. It's an exploration enabled by design thinking practices and classic Lean management principles that encourage an end-to-end, enterprise view of process steps. Digital enables organizations to align their EPM initiatives to business priorities. For example, they can focus on dashboards that serve varying stakeholder needs (including the latent emotional ones) while deprioritizing those that require complex data preparation and have limited impact.

By embedding digital into EPM, finance functions can provide the organization with actionable insights, accelerate the planning and reporting cycle and offer a single view of the business to manage risk and streamline compliance. An EPM framework supported by digital technologies will have a lasting impact on business outcomes.

This paper was authored by Shantanu Ghosh, Senior Vice President and Global Head of CFO and Transformation Services at Genpact.

Continue Reading

Ready to
Explore?