Little Decisions Add Up

 judge leaders by how well they make big, strategic decisions. But corporate success also depends on how well rank-and-file employees make thousands of small decisions. Do I give this client a special price? How do I handle this customer’s complaint? Should I offer a seat upgrade to this passenger? By themselves, such daily calls—increasingly made with the help of enterprise decision-managementtechnology—have little impact on business performance. Taken together, they influence everything from profitability to reputation.
Companies need a system for measuring and managing the decision yield of customer-related decisions—that is, the impact of an individual decision on business results. Consider an insurance company that is acquiring a new customer through a call-center interaction.Terry, the service representative, gathers information from Linda, the potential customer, provides a premium quote, perhaps changes that quote on the basis of Linda’s feedback, and finally issues a policy. Traditionally, the insurance company measures this interaction as a tiny fraction of its year-end or quarterly underwriting results. No one evaluates the quality of Terry’s specific decisions.
Adecision yield approach would evaluate this interaction along five dimensions: precision, cost, speed, agility, and consistency. That information can be collected and calculations can be performed by the decision management systems that companies increasingly use to guide employee responses or execute fully automated decisions.
Precision. Did Linda receive the profit-optimal price and package, giventhe information Terry gathered? Did the underwriting system correctly classify her, and did the company’s statistical models accurately predict the likelihood of her filing a claim or renewing the policy, as well as her lifetime value to the company? Depending on the decision, precision is best assessed by metrics such as acquisition cost, loss ratio, and retention and by comparison of thosemetrics against expected performance, industry average, or best-in-class peers.
Cost. What was the total cost of the decision process, based on the time Terry spent talking to Linda, additional data required to validate Linda’s information, and system resources needed to issue a policy? Those figures can be obtained through standardized performance reports of decision management systems or throughactivity-based costing.
Speed. How long did Linda have to stay on the phone with Terry? This customer-centric aspect of decision making—distinct from the cost of labor—influences satisfaction and loyalty. Speed of decision making is measured by most call center software and other decision management applications.
Agility. Was Terry able to change the product configuration in real time and respond toLinda’s requests? Agility in customer interactions is measured by comparing the variety of a company’s decisions with an established baseline. In essence, agility describes a company’s ability to change business rules quickly in response to market and competitive changes.
Consistency. Would Linda have received the same quality of interaction and the same quote had she called a different customerservice representative on a different day? Consistency is probably the most difficult aspect of decision making to measure. Corporations with enterprise decision-management systems can assess consistency by running simulations on batches of hypothetical customers. Other organizations can deploy mystery shoppers to continually test and evaluate frontline employees.
The decision yield is calculatedby weighting these metrics according to how they affect customer satisfaction, competitive differentiation, and financial results. (The weights assigned to the metrics represent organizational priorities.) Those numbers are then combined to create an overall decision yield that measures the performance of the company’s customer interactions.
An organization can use a decision yield scorecard to...