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Driver-Based Planning: A Competitive Advantage

Originally published January 18, 2005

In 2002, the book Moneyball hit the stores. In it, Author Michael Lewis recounts the untraditional approach taken by the Oakland Athletic’s general manager, Billy Beane, to build a competitive baseball team for a fraction of the cost of other winning franchises. The story outlines the steps taken by the team’s office staff to statistically measure the drivers of individual players and team success at the major league level. Contrary to common practice, this analysis has led the Oakland A’s management to draft successful college players over the scout-hyped speed, style and brawn of raw high school talent. Whether you like the book or not, and whether you care for Beane’s style or not, the book exposes the club’s insatiable desire to identify and recruit the true drivers of winning baseball teams.

Similarly, in the business world, driver-based planning seeks to identify and manage the true drivers of corporate financial success. Driver-based planning is an area of emerging interest within the discipline of Corporate Performance Management, also referred to as Business Performance Management. Analogous to the Oakland A’s, the objective of driver-based planning is to develop a more accurate picture of expected future business performance via the intentional management of the key operational activities that drive those results. This is an untraditional approach that runs counter to the outcomes-based financial planning that is typical in most organizations.

To explore this core Corporate Performance Management topic of driver-based planning, let’s first take a look at the general process of planning. All companies create forward-looking plans to aid their preparedness for the future. They create these plans so they can align their limited corporate resources, both in terms of people and dollars, against those strategies that they believe best leverage their competitive advantage within their markets. Planning is the business process by which the various entities within a corporation coordinate and collaborate to examine and allocate the finite resources of their company. The belief is that the companies that can best detect market opportunities and quickly align their resources to capture them will be the winners.

However, traditional financial planning approaches have a number of shortcomings, which keep businesses from creating a highly accurate representation of anticipated future results. Often, plans are based mainly on historical data. For example, many companies make new expense budgets based on simple percentage increases over last year’s numbers. This is an oversimplification of the business model that does not take into account the dynamic internal and external factors that have changed since the last budget was put together. In addition, the planning process has also been so time-consuming that there is virtually no ability to run multiple “what if” scenarios in order to optimize plans based on differing assumptions. Only minor tweaks can be made to the original pass of the budget without excruciating effort by the finance staff.

With these well-known shortcomings and others as a back-drop, several key market developments have contributed to the recent emergence of driver-based planning. First, corporate governance is demanding that more people have greater visibility to the “tangible” signs of the health of the business. Policies like those of Sarbanes-Oxley are redefining the level of disclosure and public scrutiny to which larger corporations must submit for compliance. And second, business data and information technology continue to evolve. Over the last decade, there has been a proliferation of rich business data stemming from the implementation of enterprise applications such as ERP, CRM and e-commerce applications. This increase of rich business data has been complemented by a new generation of software tools that provide a platform for more efficient modeling of business scenarios. As a result of the intersection of both heightened management scrutiny and increased technology capabilities, businesses are increasingly running their key business assumptions through models to provide the insight to proactively manage the volatility of their future financial performance. This is driver-based planning.

At its root, driver-based planning is a variant of traditional planning aimed at modeling controllable operational activities to forecast those same uncontrollable financial outcomes. The idea is to center the planning process on the controllable activities that can be impacted through focus and hard work and to de-emphasize those that cannot be impacted. For example, a high-tech manufacturer of computer peripherals was struggling to forecast the revenue and expense from their growing services business. Their service lines included professional services, maintenance services, and call center support. After thoughtful analysis, they determined that the drivers of each service line were different. For example, professional service expenses were driven by headcount while call center support expenses were driven by the number of current policies and client service level agreements. After fully understanding the drivers of the business, this company built a driver-based model that allowed business line analysts to create different scenarios based on their differing assumptions about the future.

To build on these concepts, let’s consider a large consumer goods company that needed to easily and accurately predict the consumption of its products within each of its worldwide regions over a five-year span. This forecast is invaluable as the basis for revenue growth estimations and appropriate resource allocation. However, the forecasting system they had in place had their business assumptions “hard-wired” into it, thereby making it difficult to factor in changes in internal strategy or the external environment. To address this problem, a driver-based volume forecasting solution was created that allowed for the automated and flexible creation of differing assumption-based scenarios, based on real-world drivers such as ad spending, price changes and distribution assumptions. The company’s annual product volume forecast is now driven directly by a set of key marketing assumptions. Changes in these key marketing drivers immediately impact forecasted consumption, which leads to modified unit forecasts. The result is a volume forecast that is more accurate, as well as less-manually intensive to produce.

In another example, a growing office supplies retailer recognized that store labor costs were one of its largest controllable expenses, and understanding and monitoring these costs could have a significant impact on the bottom line. Originally, the company primarily used store sales to calculate a labor budget for each store. That model required a full week for calculation and consolidation and did not handle key business changes—such as store redistricting—efficiently. With 10 new stores opening every month, the company realized it needed a more effective labor budgeting model that could take a variety of internal and external factors into account. They developed a new planning model within a multi-dimensional database for business intelligence that identified and incorporated more than 100 drivers of labor costs. These activity drivers, along with new cost allocation methods for fixed and variable costs across similar store configurations, allowed the company to pinpoint proper staffing levels by job title. With a better understanding of labor costs, the company was able to more efficiently staff its stores, improving the bottom line while also providing its customers with superior service.

As evidenced by the examples above, adopting a driver-based approach increases the efficiency, accuracy and meaningfulness of your planning processes. In turn, better planning becomes the conduit for driving improvements in your organization’s overall Corporate Performance Management strategy. When working properly, your planning processes are the means by which operational execution is aligned to strategic direction. In this way, a good planning process enables your company to better execute on its strategic objectives.

As companies are becoming more focused on the intentional management of their performance, driver-based planning is emerging as a vital advantage. By focusing attention on the key operational activities that truly drive results, businesses are becoming more agile and adaptive. This allows management teams to rigorously test business assumptions to gauge the plausibility and feasibility of specific operational plans. In this way, corporations are better able to deploy the correct level of resources to achieve the financial outcomes they desire. Driver-based planning is becoming a key enabler for maintaining your company’s competitive advantage.

SOURCE: Driver-Based Planning: A Competitive Advantage

  • George Veth

    George is President and CEO of Painted Word, a professional services firm focused on corporate performance management. He is responsible for managing the overall operations of the business and guiding the development and implementation of Painted Word's strategic vision. George founded the company in July 1996. Prior to that, he was a Principal and Co-Founder of Navigator Systems, an information technology consulting firm, from 1992 to 1996 and also served as an analyst with Grantham, Mayo, Van Otterloo & Co. from 1990 to 1991. George received a B.S. in Finance from the University of Virginia. George can be reached at george_veth@paintedword.com.

 

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