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March 20, 2003

The Money Shift

Customer relationship management requires a radically new approach to financial analysis

by Thomas F. Richebacher

Michelle buys a video camera via the Internet and immediately mails the $100 coupon to the rebate center. Meanwhile, she realizes the zoom isn't powerful enough for her needs, and returns the camera to a local store, receiving a full refund. A few days later, she receives an email offer for a stereo promising a new, dynamic sound experience. She picks up the phone and orders.

How can your company grasp the full financial impact of these transactions? One way is through the development of a customer relationship management (CRM) system, which shifts the focus from product to customer management. The CRM concept is simple and intuitive: Interaction between a company and its customers is based on a common, universally accessible foundation of information. Access to all customer information in one place lets a company analyze the entire financial impact of customer-company interactions, rather than by an individual product line or business unit.

In effect, CRM modifies competition between companies from who sells the most products to who owns the customer. As an evolutionary process, the need for accountability at the product and business unit level doesn't disappear; rather, a new customer dimension adds to existing analytic toolkits based on the realization that customers are a company's most valued asset. Therefore, to support CRM objectives, your finance function can't continue to do business as usual.

The Foundation

The question "What is the profitability of a customer or customer segment?" is very different from "How much profit did Model X generate last year?" Analyzing customer profitability requires a high degree of collaboration and integration of information gathered across all business and sales channels: Sales provides customer acquisition data, marketing provides data on up- and cross-sells, services provides information about warranty and service activities, and finance provides revenue and cost numbers. This need for collaboration requires information from existing, unconnected systems to be integrated in a central area (such as a data warehouse), and that customer definitions be valid across the enterprise.

Some companies try to skip this step, assuming their analysts can find the data needed and clean, transform, analyze, and publish it on a project-by-project basis. This view is shortsighted for several reasons:

For CRM to succeed, customer analysis must become a permanent element of financial analysis. Ad hoc approaches create too many opportunities for inconsistencies, errors, and misrepresentations.
Ad hoc analysis is slow. Completion times of six weeks or more are common, almost ensuring that results are of little value when finally published.
The creation of a central repository forces you to resolve key issues. You must create definitions of customers, cost, revenue, and profit validated by the business groups, as well as CRM objectives and evaluation methods.

In summary, treating CRM financial analysis as a series of one-time projects is a dead end.

Finding Your Own Road

When you've decided to create a central repository for customer information, you need to decide which data belongs there. Many companies are realizing that existing systems don't contain pertinent data, or that the data is in an unsuitable format for finance to perform its three major CRM functions: customer profitability analysis, budgeting and forecasting, and performance management.

Customer profitability analysis. The company I work for, EDS, recently performed a research project for a nonprofit client. Its goal was to determine which media source (direct mail, telemarketing, Internet, magazine ads, television ads) would furnish the most generous donors. A lifetime value analysis, which calculates the net present value of individual customers based on cash flows ensuing from customer-company interactions, was chosen as the evaluation method.

Determining cash inflow was simple, because accounting systems are designed to track revenue (in this case, donations) at the customer level for billing purposes. Every donor record was clearly marked with donation amount and date. Assigning costs to donors proved to be a thornier issue, as these same systems have three problematic characteristics:

As point-of-sale systems, they collect only information about actual sales at the customer level — nothing about pre- or after-sale costs of activities not resulting in sales.
Even when costs are directly incurred from sales, such as product costs, they're accumulated separately from customer records in various accounts, such as "Cost of Goods Sold," for costing purposes.
Accounting systems exist in proud isolation from one another. Lack of common customer IDs complicates any analysis that crosses system borders.

Clearly, these characteristics are incompatible with the goals of customer profitability analysis. CRM requires that a single, valid customer ID for the whole enterprise must exist, direct revenues and costs from purchases be collected at the customer level, and all indirect costs from customer-company interactions be attributed to customers. It's equally clear that while the objective of understanding customer profitability is universal, there are many different ways to achieve it. Accordingly, decisions about which activities to measure, and how their financial impact is calculated at the customer level, is what ultimately distinguishes one company from another.

For example, Table 1 shows the results for two marketing efforts, campaigns A and B. Publisher 1 considers its existing information adequate; it measures customer profitability solely in the context of marketing campaigns. This method is cost-effective and the metrics involved are clear-cut. Its disadvantage is that the profitability of existing customers remains concealed, and therefore no customer segmentation can be created, which prevents the development of differentiated action plans.

Publisher 2 takes a different approach. By allocating all product and marketing costs to responders, each of the 20 responses from campaign A incurs $50 in product costs and $25 in marketing costs ($500/20). If no responders exist, as is the case with Publisher 2, marketing costs aren't attached to individuals. Because Publisher 2 can calculate profitability at the individual customer level, it's much closer to performing customer analytics than Publisher 1. The disadvantage is that by allocating marketing costs exclusively to responders, potential distortions are introduced. Frequent buyers might have to absorb the brunt of the costs from ill-conceived marketing efforts resulting in few responders, and therefore may appear less profitable than their marginal, unresponsive counterparts.

Publisher 3 takes Publisher 2's approach a step further. While it also attaches product costs to responders, marketing costs are distributed over the whole target universe. It believes that only costs that can be traced directly to customers should be allocated to them. Thus, within every individual's record, a $0.50 ($500/1,000) marketing charge is recorded, representing the total mail piece costs. The advantage of this approach is that Publisher 3 can now calculate the customer's true profitability and accordingly reap the benefits of segmentation and targeting practices. The disadvantages are that it takes considerable effort to determine which customer-company activities should be in the cost analysis, how they should be measured, what costs should be allocated to them, and how to create the systems that automatically assign them to the right customers.

As you can see, a company's decision about what customer-related activities to measure, how costs are assigned to the activities, and the manner in which activities are assigned back to customers has a huge impact on profitability calculations. Even under identical circumstances, conclusions can diverge widely and lead to significantly different actions.

All approaches are not created equal, however. Publisher 3's approach is the closest to creating a true foundation for customer analysis because it assigns the actual costs of resource consumption from company-customer interactions to individual customers. It's also an attractive option because it creates analytic flexibility: When costs are directly attached to customers at the activity level, they exist at their smallest granularity, allowing analysts to easily reorganize and aggregate them across any product, channel, division, or functional dimension. In turn, companies are enabled to create enhanced customer segmentation and targeting approaches that lead to better customer value propositions.

Budgeting and forecasting. The primary difference between CRM and conventional budgeting and forecasting models is that while the latter use isolated product-service categories that disconnect sales from customers, the former develop financial results based on projected customer activities for the entire enterprise. Because of the different ways companies relate to their customer base, CRM models span a spectrum, with one end being activity-based and the other continuity-based.