Perform Magazine
Effective execution of strategy is a challenge for many organizations. The most common problem is that employees lack the measures to guide their behavior and decisions. Without clear goals and performance metrics, employees are myopic, focusing only on what is in front of them and not on the overall requirements.

The scorecard is designed to correct this problem. By deriving goals and measures from the strategic plan, and rolling these down to each part of the organization, the scorecard is the focal point from which each part of the organization and each person know their responsibilities to execute the strategy.

In addition to providing focus, scorecards highlight important variances in performance. These variances trigger investigation of problem areas, and may lead to diagnosis and corrective action.

The ability of scorecards to trigger corrective action and positively impact performance can be dramatically increased through the use of business analytics. Analytics is the extensive use of models and algorithms to analyze data from various sources. It produces knowledge that decision makers can use to improve business performance.

This article describes how organizations benefit from integrating scorecards with business analytics. It shows how analytics identifies performance gaps, analyzes problems, and helps select the decisions that lead to the best results. It describes five analytic tools—strategy maps, activity-based costing, activity-based budgeting, process analytics, and forecasting—that help users of scorecards understand and act upon the performance signals in their scorecards.

Scorecards and Business Analytics

An organization with a scorecard system has a different scorecard for each level and responsibility. For example, a manufacturing company has a company-wide scorecard, one for each functional area such as production, procurement, and distribution, and one for each responsible manager within each functional area. There may also be scorecards for initiatives such as six sigma. Each scorecard is linked both to strategy and to the scorecards above and below them in the organization.

The value of the scorecard system is determined by four factors:

• The measures in the scorecard must be relevant to strategy. Measures that aren’t tied or represented in the strategy could misdirect employee behaviors and actions, ultimately preventing a company from achieving its strategy.
• The data needed to calculate a score must exist; otherwise it will not be possible to measure progress towards a goal. For example, if customer satisfaction cannot be measured, it will be difficult to execute a goal to improve customer satisfaction.
• It should be possible to forecast the future value of a measure in a reasonably objective manner otherwise the target will not be relevant. Basing a measure solely on assumptions can produce measures which mislead decision makers.
• The users of scorecards must be able to understand and act upon the performance signals inherent in the scorecard measurements. For example, when the target and actual performance of a measure diverge, is this divergence significant? Does it call for investigation and possible corrective action? Does the manager responsible for the value of a measure have the authority to change the resources being used to accomplish the tasks the measure is based on?

What is the experience of organizations in deriving value from scorecards? While the score varies from organization to organization, the most common barriers to realizing value include:

• The performance measures in the scorecard are not derived from the strategic plan. They may be regarded as key performance indicators, but are missing the systematic link to corporate goals and objectives. Success on these measures cannot, therefore, be a guarantee of strategic success.
• Important performance measures related to strategic goals are missing from the scorecard. For example, a manufacturing company set goals to improve customer profitability. However, the company did not measure customer profitability, and was unable to provide scorecard measures for these goals. In the absence of measures, it was difficult to set and achieve targets to improve customer profitability.
• Measures relating to strategic projects and initiatives are often absent from scorecards. Many organizations do not measure—or are unable to measure—initiatives such as those designed to improve the performance of processes. In the absence of these measures, initiatives are often chosen without regard to their impact on performance, and are not managed for results.
• Predictions of future scores for key measures are not used to provide early warning of impending problems. If the scorecard owner is first aware of a problem when a measure flashes “red”, it may be too late for timely preventive or corrective action. A graph showing a trend of deteriorating performance can be helpful, but its significance may not be clear unless there is a forecast of the future score.

What analytic tools are available to correct these common limitations and enhance the value of the scorecard?  Below are five examples that have proven value.

Strategy maps. The relevance of scorecards to strategy is best achieved using a strategy map. A strategy map is a cause-and-effect diagram that organizes goals and objectives into four perspectives; financial, customer, internal process, and learning and growth. These perspectives are based on the idea that in order to succeed, an organization must balance short-term financial success with other factors, such as developing world-class processes, which ensure long-term success.

Figure 1: Example of a strategy map for a manufacturing company.

The value of the strategy map is its ability to link the strategic plan to the scorecards that cascade down the organization. The goals, objectives and measures of each scorecard are derived from the objectives of the scorecard directly above it. That scorecard, in turn, is derived from the one above it, and so on until you reach the strategy map. If this is done, there is a powerful logic between achieving targets in each scorecard and the successful execution of the strategic plan. The person responsible for the scorecard at the lowest level has a direct line of sight to the strategic plan.

Activity-Based Costing. ABC is a financial modeling and reporting tool. It provides accurate cost information about an organization’s resources, activities, products, services and customers. Originally developed as an improved cost accounting method, it today provides accurate cost and profit information for a variety of decision making, planning and performance measurement purposes.

ABC adds greater accuracy, relevance and understanding than traditional accounting information. ABC reports the cost of each activity in a process, as well as the cost of resources that contribute to the activity’s cost. In contrast, accounting systems typically report only the cost of depreciation, salaries, supplies and other line items that are only indirectly relevant to scorecard objectives.

ABC also reports cost and profit information about products, services and customers that is typically not available in accounting systems. For example, cost-to-serve activities such as order entry and sales are treated as period costs in accounting systems and not traced to the customers that benefit from the activities. Manufacturing companies may have a cost accounting system for reporting product cost, but these costs may not be complete or accurate. Many service organizations don’t have a cost accounting system at all.

Figure 2: This figure shows the profit per order for a company selling into seven segments in the financial services industry. Prior to an ABC study, the company was unaware of large variations in profits between segments. Armed with this information, the company implemented action plans to restore profitability in poor performing segments.

Activity-Based Budgeting. ABB is an ABC model running in reverse. ABC reports historical costs and profits, whereas ABB predicts costs and profits in a future period. An ABB model is an excellent source of targets for the scorecard.

ABB is a predictive model that derives the cost of resources needed to meet the plan. For example, the sales plan lays out the expected volume of sales of each type of product and services. This sales plan is converted by the ABB model into the demand for work for each activity (such as the number of shipments by the warehouse). Once the demand for each activity is understood, the model computes the resources required by each activity at the level of work required (such as the number of minutes of work in the warehouse). Finally, the price of each resource (cost per minute for people’s time) is applied to the quantity required to compute the budgeted cost.

Because the ABB model is based on the relationship between sales, activities and resources, it is possible to reflect changes in process performance. For example, an increase in productivity derived from an improvement initiative can be factored into the algorithms in the ABB model. As a result, the targeted cost for this process will be lower for a given set of outputs.

These computed targets are quite different from those derived from traditional budgeting exercises. ABB targets are accurate forecasts based on a predictive model that estimates the work needed to meet the plan. In contrast, traditional budgetary targets are derived from the accounting system and not susceptible to modeling the impact of demand and process changes on cost.

Process analytics. The use of process analytics in connection with operational improvement initiatives is another excellent source of objectives and measures for the scorecard. Process analytics provide measurements to guide the selection, planning and execution of change initiatives.

Process analytics convert improvement initiatives into scorecard objectives and target measures for cost savings and other performance improvements. These measures are tracked over time and surfaced in the scorecard.

For example, a government agency used an analytic method called Storysolve^® to derive objectives and targets relating to process improvement initiative. Managers could track progress on these measures and the overall success of the initiative on a monthly basis. Impressively, the agency averaged between 10 and 30% savings on analyzed cost using this method.

Figure 3: Example of process analytics. Scorecard shows analytics for an initiative to improve a machine patching process. Analytics enables measurement of cost reduction targets and tracking of outcomes via the scorecard.

Forecasting. Scorecards report actual performance on a periodic basis. These measurements are reported against targets to allow managers to separate success from failure. Forecasting using statistical methods can be used to set more accurate targets as well as to provide early warning of impending performance issues.

Reporting actual performance against target is important in a scorecard system. It provides an accounting of each manager’s responsibility for performance. It can be the basis for periodic performance reviews and corrective action.

Scorecard comparison of actual versus target performance is strong on accountability but weak on early warning of problems. For example, a measure may be trending down, but is not yet flashing yellow or red. The responsible or reviewing manager might miss the opportunity to correct a problem before it becomes too serious.

Statistical forecasts look forward and predict which problems are likely to become serious in the future. When automated, forecasts can provide a running prediction of what will happen in the next week, two weeks, month, quarter or six months. Managers can then take corrective action long before the measures flash red on the scorecard.

There are many different types of measures—and potential problems—that can be forecast. For example, percent utilization of an IT application can be forecast relative to trends in demand and anticipated changes in usage. Another example is forecasting the load on a critical process step to determine how much capacity is available under expected operating conditions. This could avoid situations where the resource becomes a constraint causing disruption to production and revenue losses.

Summary

Scorecards are powerful performance management tools. Their ability to execute strategy and drive successful performance is enhanced by the use of analytic tools. Analytic tools increase the strategic relevance of the scorecards, provide accurate measurements, and enhance the manager’s understanding of performance patterns.

The strategy map is a cause-and-effect diagram of strategy. It links strategy and the scorecards. When scorecards are tied to a strategy map, they are relevant to the success of the organization as a whole. Focusing on measures that are linked to strategy leads directly to strategic results.

Activity-based costing is a financial and organizational measurement and modeling tool. It feeds cost measures to the process perspective, and profit measures to the customer perspective of the scorecard. ABC is the single most important tool for resolving missing measures. Organizations with ABC systems derive as many as 25% of their measures from ABC. These measures include the cost of activities in the process perspective of the scorecard, and the profitability of products, services and customers in the customer perspective of the scorecard.

Activity-based budgeting is a forward looking version of ABC. ABB models the relationship between the plan, the demand for work, and the need for resources to complete the needed work. It provides accurate forecasts of costs that can be used as targets in the scorecards.

Process analytics provide measurements for change associated with operational improvement programs. Action plans can be loaded into scorecards along with their estimated impact on future performance. Process analytics also track—and report—changes in performance that occur when action plans are implemented.

Forecasting the value of future scores increases the accuracy of targeted scores, and also the diagnostic and early warning power of scorecards. Forecasts include trending of historical performance data as well as predictions based on multiple external and internal variables. These allow corrective action to be taken before scorecard measures flash warning signs.

Taken together, these tools increase the value of scorecard systems. They become more relevant, include more accurate measures, and are easier to understand and use. They support early warning and intervention, and lead to better decisions and improved results.

About Cost Technology

Cost Technology designs and implements solutions to support fact-based decision making.  These solutions transform existing data into strategically meaningful and actionable insights in areas such as cost and profit management, financial forecasting, analytics, and performance management.  Since 1991, the firm has helped public and private sector organizations across the world improve performance by creating the knowledge needed to make every decision count.

By Dr. Peter Turney
CEO, Cost Technology