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Taking Performance Management to the Next Level - Anthony Politan - Strategic Finance

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Anthony Politan: Taking Performance Management to the Next Level

Posted with permission from Strategic Finance, Aug 2003


When you're driving, you only glance into the rear-view mirror because, if you stare too long, you just might crash. Many businesses today are spending way too much time looking in the rear-view mirror at the road they've traveled by focusing on historical performance management methods. A few leading companies, however, are applying many of the basic principles and technology of historical performance management methods to forward-looking performance management. This new trend is scenario-based planning, and it concentration on the future rather than on what has already happened.

By generating multiple what-if scenarios using data you already have and applying performance management as if the scenarios were actual situations, you can take performance management to the next level. The result: You can integrate optimal what-if scenarios with traditional budgeting and planning systems to change faster than industry norms and increase your organization's competitive advantages.

Unfortunately, most businesses aren't intertwining scenario-based planning and performance management. Consider the frenzy to move to the Internet-based business model. Companies that moved into the dot-com world without the business intelligence to support the decision often failed in this model. You can just as easily replace the dicks-and-mortar example with changes like increased competition and a downturn economy.

Let's look at how most companies use performance management by and large for financial measures only and the shortcomings of most business intelligence solutions. I'll then explain performance management optimization (PMO), which combines the disciplines of scenario-based planning and performance management to provide a holistic, integrated view of the business.


Until recently, performance management has been focused solely on history. Companies could sec at a certain point in time how they had performed up until that day, but looking forward wasn't an option. Combining metrics, benchmarks, and processes, performance management analyzes financial as well as non-financial metrics. These combinations of metrics provide the complete-report card of an enterprise, but organizations often gauge themselves purely by financial measurements. The result: They overlook key indicators, such as customer satisfaction, on-time delivery, or employee retention rates. After all, even if financial figures are neutral or positive, other metrics can indicate a less-than-healthy enterprise.

This myopic view of financial measurements is often the result of two factors. First, external measurement of an enterprise by investors, analysts, and the markets are almost entirely financial measurements (revenue, margin, and the like). Second, financial measurements are usually readily available from existing systems, such as financial or accounting packages, while other metrics are more commonly buried deeper in an organization's systems and processes. Often these non-financial metrics aren't understood or are represented without empirical backing, and, worst of all, they aren't usually integrated with the financial metrics.

Beyond the focus on financial measurements, another problem is that most performance management systems are disjointed from the actual enterprise resource planning (ERP) or customer relationship management (CRM) systems from which they're getting their data. Thus, the technical aspects of creating a performance management system not only relate to the system itself but to the feeding from these upstream systems.


A widely known shortcoming of any business intelligence application is the separation of analytical and actionable processes. If you can't automatically translate the business intelligence into a process on which you can act, such as a completed budget or business plan, the analytics become nothing more than fancy and complex reporting. The information is useless.

This unnatural separation of analytical and actionable processes creates disconnects on both the business process and the technical implementation. Disconnects of this level lead to double work in the form of data entry and are prone to error, just like any double entry. The separation also robs the organization of valuable time that it could spend on what-if scenarios.


Budgeting has traditionally been one of the only forms of metric-based planning an enterprise uses. Most organizations use a yearly budget and attempt to track actual figures against the budget. These budgets can be highly aggregated at a corporate level and then pushed down to divisions and departments.

Until recently, companies barely had the time to create a budget and make minor adjustments to it. With scenario-based planning, they usually create a baseline budget, which is then used to generate multiple, sometimes hundreds of, scenarios. Top-down budgeting enables splashing — the ability to enter data at any level of aggregation (cost center, product line, division) — and have the data apportioned based on patterns or business rules. With splashing, enterprises can create what-if scenarios. For example, one organization creates a top-line revenue target. The budget is then shared with product line managers who are responsible for dozens of products. The product line managers can then adjust their target for each product or adjust their overall product target. With each change, the top-line numbers are being changed. The same budget is shared with regional sales managers. They can adjust their targets for sales representatives, and the data are also automatically combined. The sum of these changes is saved as a scenario, and the process is repeated. This collaborative processing among people throughout the enterprise allows multiple scenario building.

The same method of splashing also allows multiple scenario building using non-financial metrics in the planning process. If you understand the trends of past metrics, such as employee attrition, on-time delivery rate, or average lead-time for new products, you can derive forward-looking forecasts. For example, you may use past on-time delivery percentages to forecast next year's expected percentage. Also, you can modify certain constraints and variables to determine a new forecast for the on-time delivery percentage. Although some organizations are performing this type of forecast, which is actually quite similar to forecasting financial values, few are integrating it with their other metrics, particularly financial metrics.


Performance management optimization finds the optimal solution through a three-step process:

1. Using the disciplines and tools of performance management to
create a static snapshot that serves as a baseline to future scenarios.
2. Using what-if scenario planning tools to create dozens of
scenarios for best and worst cases. There can be simultaneous adjustments to multiple views of the business. For example, product managers can update their what-if measures while the research and development managers are updating theirs against the same model. The what-if scenarios are for financial and non-financial metrics. A centralized group keeps versions of these scenarios for later analysis.

At the same time, performance management is being done against the what-if scenarios. By measuring these future states, you can determine strengths and weaknesses before committing resources to any changes. Besides measuring each scenario individually, you can analyze cross-scenario measurements to determine if a hybrid of two scenarios may be optimal.

3. Selecting an optimal scenario based on both financial and non-financial measures. The optimal solution may not always be the solution with the highest revenue or margin (although these measures typically are weighted higher). For example, an optimal scenario for revenue may be a dismal scenario for projected customer churn.


The data for performance management optimization will come from internal and external sources. Here's a look at both.

Many organizations will start with the internal focus to test the PMO methodology and to provide early return on investment (ROI). Their own financial and non-financial measures with existing ERF and CRM systems provide much of the information. There are two benefits of concentrating on your processes and data. First, the data are usually readily available, although the quality and usability of the data may be questionable. Second, understanding how the raw data were created should be information obtainable.

This internal focus, though, won't provide a complete view. Global supply chains, business partnerships, outsourced relationships, and changing corporate structures have driven the need for an external as well as internal focus for performance management optimization.

The external focus does add a new set of challenges, which may not only be difficult to implement but difficult to understand. Generally, the processes and data outside an organization won't follow the same structure, documentations, and standards as internal processes. Take, for example, an organization that outsourced the delivery of end products via a third-party logistics (3PI.) company. While much may be understood regarding the products being developed and produced, including common naming and product codes, this level of data may not be available from outside systems. A third-party company may just be able to track batches or distribution of products as compared to internal systems that can link products to sales to customers.

It isn't impossible to obtain data from third parties. If business partners are truly partners, their information technology staff will communicate the structure and content of the data. There are a number of emerging technology standards, based on Internet protocols, to facilitate this data sharing.

In a truly networked performance management optimization environment, the internal focus of one organization will be the external focus of another business partner. In the outsourced logistics example, the logistics company has certain key performance indicators (KPIs), such as on-time delivery, average lead-time, empty container percentage, and the like. If these measures are being managed as internal-focused PMO indicators, they can be shared with the product manufacturer for integration as external focus measures for their PMO system. This two-way sharing of measures will drive further mutual benefit for true business partners.

One caveat in the networked PMO environment, though, is data security and privacy. Existing technologies, such as segmentation of servers and firewalls, can safeguard the data. But these technical safeguards need to be complemented by process safeguards including policies, procedures, and audits.

One final note on data gathering. When obtaining data from other systems, you must build a framework and technical architecture that doesn't hard-wire the organization to any internal or external systems. It's almost certain that one or more of these systems will be retired, swapped, or upgraded within a two-year period. Implementations must be flexible enough to avoid being at the mercy of technical limitations and upgrades. Thus, the framework must be built for business measures, not technical fields or jargon.


Combining the disciplines of performance management and scenario-based planning requires five critical success factors: usability, splashing, integration of non-financial measures, collaboration, and distribution. Without applying all five, the performance management optimisation methodology will be difficult, if not impossible, to implement.


A successful implementation of PMO will build on the successful budgeting systems of today. Business users need to view and manipulate data in their technology of choice. With a vast majority of financial users budgeting and planning in Microsoft Excel®, it's the logical platform choice. The increased functionality of pivot tables and multidimensional views are becoming more common, and Microsoft SQL Server provides a built-in multidimensional engine. Other platforms also have that support — DB2 and Oracle, for example — but not for free.


As mentioned earlier, splashing is the ability to enter data at any level of aggregation (cost center, product line, division) and have the data apportioned based on patterns or business rules. At the same time, the top-line rollup is also updated. This gives the user true middle-out planning capabilities. Much of the current technology can aggregate up when low-level figures are entered, fewer can apportion down, and even fewer can combine both.

Splashing must have multiple methods. First, even distribution will splash the aggregated number over all the elements below it at equal levels. Second, percent changes can be combined with the even distribution. Thus, a divisional number could be spread out evenly among departments but with each individual number increased by 10%. Third, and more complex, is contour distribution. With contouring, a number is entered at an aggregated level but is splashed based on a second set of numbers. Thus, a department could enter a forecast number for the revenue target but splash based on last year's product distribution. A true splashing environment combines all three forms in a workflow that leverages the concurrency of decentralized planning while retaining control of centralized functions.

For example, a tire manufacturer can allow country sales managers to forecast revenue. Using contour distribution splashing, distribution within that country of product revenue can be automatically generated based on past performance. Concurrently, product managers can update their cost projections and perform percent increases based on expected increased cost of raw materials. When completed, a central planning group can then fine-tune the top-line numbers and splash accordingly.

Integration of Non-financial Measures

Many systems can measure financial information, such as revenue, profit, and cost of goods. Some of these systems can also perform activity-based costing. Generally, though, organizations need to have a separate system for other types of performance, such as manufacturing, human resources, or supply chain. PMO delivers its greatest return on investment when all these measures can be integrated into one application.

Collaboration and Distribution

The optimal PMO environment will allow collaboration and distribution at all levels and various technologies without needing custom code or third-party add-ons. Technology has made collaboration possible for budgeting. Although many organizations don't take advantage of this technology yet, the ability exists to perform combined decentralized (sales field office, divisional) and centralized (home office, consolidated financial) budgeting. During this process, companies are using collaborative technologies such as intranets and shared databases to facilitate information sharing in real time.

This same process needs to be applied to scenario-based planning. Organizations can take advantage of the decentralized facilities to perform what-if plans on a field office or product-line level. At the same time, a centralized organization can apply enterprise-level assumptions to the same what-if scenarios.

Key to success is the planning of both financial and non-financial measures. For example, a sales manager in a Latin American subsidiary could plan for increased customer satisfaction by adding a local language help desk. This would be offset by the increased overhead for the Latin American office. The corporate office in California can be estimating the cost of rerouting all Spanish-speaking help desk calls to the new call center and examining economies of scale. This results in a collaboration of decentralized scenarios with centralized sharing control.

To cost effectively distribute the results and reports of these what-if scenarios, an intranet makes sense, and, on the executive level, the concept of a briefing book in a concise, easy-to-read business document or presentation is key.


Organizations can achieve significant competitive advantage through the use of performance management optimization. The two disciplines of performance management and scenario-based planning can be intertwined, creating an environment where not only the actual as-is state is measured, but the optimal what-if scenario is achieved.

Strategic Finance, by Anthony L. Politan ( Email: tpolitano@misag.net )

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