Linking Key Metrics Through Flowprinting

A key advantage of the flowprint is its ability to draw relationships among key metrics that are used regularly in various organizations to gauge the health of the firm. Some might even argue that managers spend an inordinate amount of their time monitoring and influencing these key metrics to enhance organizational performance. Some very commonly used metrics include measures of defect and rework, problem incidence and resolution, product availability, measures of product and service quality, customer satisfaction, brand equity, market share, growth, revenue, margins, and profitability. This list is by no means exhaustive, but we have observed that across industries these metrics are often reviewed with zest and interest, as though they were gauges indicating if the organization is headed in the right direction. More often than not, these metrics are viewed as isolated numbers and not viewed in the context of a systems approach to organizational management.

In a recent client engagement, for instance, we observed two teams that worked on improving brand equity and customer satisfaction scores in the marketplace. Ironically, these teams worked in independent silos and never had an opportunity to cross-pollinate their thinking and efforts. Their measurement approaches were thus very different and divergent. The result was a discordance of scores, where the organization continued to see improvements in brand equity scores, with an erosion of customer satisfaction scores. The teams however never got the opportunity, or for that matter expressed an interest, in getting together to ask the question about how could they have a stronger brand if the customers are increasingly unhappy with their experiences. After all, customer satisfaction is a key pillar of a strong brand! Likewise, in many organizations that we have consulted with, we found high walls separating employee and customer measurements. One part of the organization could thus make claims about improvements in the engagement of its workforce, including customer-facing employees, without ever examining if such improvements led to superior customer experiences. For one service organization, we found that not only was such a relationship missing but also no attempts had been made to seek association between measures of employee engagement and employee productivity or reduction in voluntary employee turnover.

Thus while key organizational metrics then capture important performance information, a flowprinting approach to decision making brings value by identifying the relationship among these metrics. It helps draw systematic conclusions among the observed phenomenon instead of just observing the more noticeable symptoms. If you can think of a series of gauges connected to each other in a series of consciously designed patterns, then a flowprinting approach does not just study the change in reading of an individual gauge and then recommend a solution or cause. Instead, it identifies the relationship among the observed movement in other gauges to identify possible causes and propose correction, if required. Such investigation is conducted until the management can identify directly actionable causes that can be altered to make downstream changes.

In one such implementation, we observed that a retail institution was unable to retain a majority of its customers. Such churn was proving to be very expensive for the organization, and therefore it undertook an evaluation of probable causes. A flowprint session was conducted at the onset of the investigation, and over the next few weeks, the research led us down a path wherein we observed that in the recent past these customers had reported less favorable perceptions of their shopping experience at the store outlets. Within the same time period, we also observed eroding levels of engagement among employees, including the frontline employees that worked at these stores and interacted with the customers. When we investigated further, we discovered that because of certain changes in corporate policies in the recent past, employees perceived a reduction in their benefits received, while other organizations were actually providing similar or improved benefits to their employees. The employees were clearly unhappy with the change, especially as those were more plentiful economic times, and this also led to an exodus of the more experienced and higher performing employees to other competitive retail organizations. The retention of less-engaged employees and the departure of better performers therefore led to inferior customer shopping experiences.

When management discussed the issue internally, they realized that one of their internal communication issues seemed to have misfired. Management had actually not reduced the quality of benefits it provided to its employees, and had only enhanced the flexibility to move these benefits to suit individual situations. For instance, an employee and spouse could cash in on the health care benefits of one of them since they both could be covered by the policy of the other partner. The communication around the increased flexibility however was not perceived as such by the employees, who misconstrued management action as one of financial stringency. Armed with this information, management launched an intense campaign to correct employee perceptions, launched a web-based campaign solely for this purpose, and held information sessions to provide accurate information around the changes. We then went back after a period of 6 months and observed that the investment seemed to have worked in the expected direction. Employee engagement levels had risen, customers were reporting more favorable in-store experiences, and customer churn was on the decline. Thus the movement of the customer retention gauge was systematically identified to a cause that could be directly acted upon.

Developing Strategic Flowprints

A typical flowprint is developed in an interactive, half-day work session with a team of cross-functional stakeholders, and is customized to each business unit, and sometimes to individual customer segments within a business unit. The output of such a session is a business model that draws out possible upstream and downstream relationships associated with the business objectives under consideration. These relationships are drawn out from a customer-centric perspective, that is, how do the upstream activities impact customer experience, and how do changes to such experience lead to changes in downstream measures? Beyond the benefits discussed here for undertaking a flowprinting approach to decision making, there is also published evidence to support its need. A Harvard Business Review study published a few years ago¹ presented evidence that while many companies regularly collect data on various performance measures, few attempt to draw relationships across these silo-based measures. The study concluded however that more successful companies have achieved superior performance by choosing their performance measures based on causal models, which layout possible cause-and-effect relationships that may exist between the chosen drivers of strategic success and outcomes. The study found that organizations implementing such an approach were able to achieve 3% higher return on assets (ROA) and 5% higher return on equity (ROE) vis-à-vis companies that did not deploy such a framework.

Attendees of the half-day flowprinting workshop walk out with a heightened appreciation of how the various performance metrics they monitor and try to affect on an ongoing basis are really linked to each other in a net of relationships. While some of these relationships might be obvious, it still helps to validate their presence and strength. Being customer centric, for instance, seems such an obvious relationship—more satisfied customers should engage in behaviors that should make the firm financially successful. However, the flowprint participation often leads the audience to ponder over some tough questions, such as whether the relationship would hold true for all customers. One such observation, for instance, led us to observe that only 30% of a firm’s customers were profitable, while it actually lost money on the remaining 70% of customers. The question that arises is whether, in this case, the firm should work on maximizing customer satisfaction to reap benefits across the board, or should it focus only on the profit generating customers? In other flowprint sessions, the audience has often pondered if they have been buying customer loyalty by spending excessively to please customers. What if these customers report more favorable attitudes as an outcome of the firm efforts but do not provide adequate returns to recoup such efforts? Can this then mean that the firm could be congratulating itself for improvements in customer satisfaction scores, even though there might not always be a reason to rejoice?

In one flowprinting session for a utility firm, for example, we were informed that the call centers treated high- and low-value customers identically. This firm does business in a nonmonopoly footprint, and customers have a choice of switching their utility supplier. To generalize, the firm had two types of customers—one set that had been with the firm for many years and paid a sizeable bill every month, while the other was a group of customers that switched suppliers every few months and was persistently delinquent in paying their utility bills. The firm initiated and implemented a uniform policy around late or missed payment for each of these two groups of customers, without recognizing that for one set of these customers it was habitual behavior, while for the other a missed payment often related to an outlier incident such as a long vacation during which the payment date fell. When we looked at data for each of these two customer groups, we observed that, unhappy with being treated harshly for missing an isolated payment, the high worth and long tenure customers began switching to competition, which was happy to have them. Since these households were no longer customers, they did not receive the customer satisfaction survey, and the pool of survey respondents shifted to the lower tenure customer group, which was happy with the aggressive price they received in switching to this firm during their short stint with the firm, before they were forced out because of their payment behavior. Survey-based customer satisfaction scores thus started improving, and it took an overall systems approach, wherein these scores were linked to decreases in average household level revenue, to recognize the complete picture. The utility firm immediately took corrective action and started adopting more forgiving policies for the long-tenure and high-value customers. When customers contacted the call centers, their phone numbers were used to route customers through preferred versus general queues, and the representatives were empowered to make decisions based on a customer grading system—higher value customers were given more flexibility and leniency in paying their bill. Lack of a systems approach would have let the bleeding go on for much longer, much like a previous case study, where reduction in the number of tellers boosted short-term profits but led down a steep slope of customer exodus.