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The KPI Profiler: CRM Case Study

  • November 01 2004, 1:00am EST

In my previous column, we described key performance indicators (KPIs) and their important dimensions of perspective, family, category and focus in some detail. This month, we will build on that discussion by translating these dimensions into a comprehensive KPI profiler that can be used to build, quantify and communicate KPIs throughout your organization. Incorporation of the KPI profiler in the KPI development process also ensures that a proper balance of metrics is selected that includes the four balanced scorecard perspectives (customer, financial, internal business process and learning/technology), multiple families of measures (cost savings, productivity, quality, profitability, etc.) and an appropriate mix of lead/lag indicators, internal/external views and qualitative/quantitative measures. The KPI profiler also captures information related to the data sources, benchmarks, targets and business initiatives.

The CRM Scenario

In recent years, customer relationship management (CRM) has emerged as an important business strategy. Although myriad sophisticated CRM definitions purvey the marketplace, CRM is really just about value creation - the value creation that results from acquiring, maintaining and servicing highly profitable customers. The premise is very basic: sell existing products to new customers (new acquisitions), sell additional products to existing customers (cross-sell), sell more expensive products to existing customers (up-sell) and maintain your existing customer base (customer retention) while economizing support activities (customer service). All the other business processes (campaign management, sales force automation, etc.) and IT ecosystems (data marts/data warehouses, data mining, etc.) just facilitate the value creation paradigm.

The multiple facets of CRM certainly provide a wealth of analysis and KPI development opportunities. Industry experience indicates that it costs a company six times more to sell a product to a new customer then it does to sell additional products to an existing customer. Our case study will therefore focus on defining an effective "customer cross-sell" KPI metric. To add industry-specific reality to the scenario, we will profile a financial services organization whose portfolio of products includes planning (retirement income, education funding, estate transfer), protection (life insurance, annuities) and investment (mutual funds, brokerage accounts, IRAs and 401(k) rollover) vehicles. Although the company offers 20+ products, the existing customers own (on average) only 1.60 products each. Significant upside revenue potential exists for cross-selling opportunities with a cross-sell index target set at 2.20 for Q3 2005. The company financial wizards estimate a 21-percent increase in profit potential from the forecasted 0.60 cross-sell index increase.

The Description Module

The first section of the KPI profiler (see Figure 1 - KPI Profiler Template) presents a high-level description of the key performance indicator that includes such basic information as the name, number and owner of the specific KPI. For our example, the measure name is customer cross-sell identified as measure number C01 and owned by Kevin Atkins. Also included is profile information that captures other key aspects of the KPI such as the perspective, strategy and objective. In this case, the selected perspective is customer with a strategy of revenue growth and an objective to increase customer cross-sell. This provides management and employees with an instantaneous summary of this specific KPI and facilitates cross-function and cross-business KPI comparisons and discussions.

The Dimension Module

Balance, balance and more balance is the operational mantra of the day. The most important decision in KPI development is the creation of multiple KPIs for each of the balanced scorecard perspectives - customer, financial, internal business processes and learning/growth. This will avoid the problem that plagues most KPI development efforts - overt dependency on financial measures. This is a common issue because financial measures are more accessible and typically have been in place for many years. The major drawback is that financial measures capture what has occurred in the past or what is happening today and are not predictive of what will take place in the future. Whenever possible, one always prefers lead versus lag indicators. A lead indicator that can predict future business health is worth its weight in gold. KPIs should also reflect a mix of measurement families such as cost, quality, resource utilization, process efficiency, innovation and growth. The tradeoffs between cost, quality and efficiency must be addressed and incorporated in the multiple KPIs via category metrics such as ratios, indices, percents and composite indicators.

In this section, we also describe the formula for the customer cross-sell index, which includes monthly tracking of active customers (those customers who have purchased a product over the last two years). For a financial services company, this may be an appropriate time frame, but for more dynamic industries such as e-commerce or retail, the time horizon will be much shorter. In addition to the internal quantitative measures mentioned, KPIs should also include results from external qualitative assessment tools such as surveys, interviews and focus groups. This provides another set of eyes that track issues such as customer satisfaction, product quality and corporate image. Finally, it is also important to understand how management will use the KPI. Is the KPI intended for planning the future, controlling a process or perhaps diagnosing a problem? The answer to this question dictates which individuals will access the KPI and how often the KPI needs to be updated.

The Data Profile Module

The development of effective KPIs is contingent on the ability to access comprehensive and high quality data at the appropriate level of granularity. Identification of the data source - CAPTURE marketing system - and the individual in charge of data collection - Jim Darcy - ensure that the appropriate data will be available on a timely basis. The data owner - Charles Sebring - (otherwise known in data quality circles as the data steward) is responsible for ensuring that the appropriate business definitions and business rules have been consistently applied. In terms of the data elements themselves, it is important to understand how reliable the data is and whether or not "high values" reflect good or poor business results. In this example, a high value for the customer cross-sell ratio is preferred. Another important aspect of the KPI is the frequency of analysis/reporting, which in turn drives the need for data source updates. Because sales of most financial products (life insurance, annuities, education funding, IRAs, etc.) move more at glacial rather than warp speed, monitoring the customer cross-sell index by month appears sufficient to capture significant cross-sell levels and trends.

The Benchmark and Target Module

KPIs in isolation are useless - they must be viewed in context and compared to relevant company or industry benchmarks. In our case study, the financial services company has developed a baseline customer cross-sell index of 2.20 that must be reached or exceeded by the second quarter of 2005. To reach this long-term goal, the company has established intermediate targets for 2004 through 2005. The company has also established three business initiatives that focus on a mix of marketing, product development and customer services to meet increased customer cross-selling goals (see Figure 1).

Figure 1: KPI Profiler Template

Regardless of what the CRM strategy, the KPI profiler can facilitate creation of effective and business focused KPIs. Additional applications include:

  • Customer Acquisition (number of new "quality" customers)
  • Customer Retention (percent of existing customer retained)
  • Customer Satisfaction (question results from survey and/or focus groups)
  • Customer Segmentation (percent of profit by customer demographics)
  • Customer Profitability (average profit per customer/per household)
  • Customer Servicing (average response time for customer complaint/inquiry resolution)

The bottom line - The KPI profiler with its visual framework and extensive level of detail provides a worthwhile addition to the toolkit of all performance management practitioners.

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