Page 286 - DMGT308_CUSTOMER_RELATIONSHIP_MANAGEMENT

Unit 11: CRM Measurements

At the other extreme are non-causal measurement schemes in which successful solutions proceed Notes
without establishing the causal linkages between related or rolled-up solutions. In some (most?)
companies, this is the default approach to measuring successful initiatives. Lack of enterprise-
wide coordination between various initiatives can lead to conflicting, redundant and sub optimal
solutions. In this Darwinian model, however, successful CRM solutions are advanced, unsuccessful
programs are weeded out and the company does receive some benefit. In fact, one could, in
theory, design a measurement system that measures competing CRM programs on operational
measures to help the company weed out what shouldn’t be done.
Key concepts from successful programs can be shared and cross-pollinated across multiple
teams. Proving causal linkages between human (customer or employee) behaviour and business
success can be dispensed with or downplayed. Instead, surviving programs and the key concepts
behind them, however cross-pollinated they have become, represent the “causal” linkages
“explaining” behaviour or “predicting” performance. The key concepts, which inform new
CRM programs, are more like memes, units of cultural information that successfully spread
throughout the company. No one engineers a comprehensive behavioural model around
customers nor does anyone engineer how customer knowledge is created. Is this a valid
measurement approach?
Perhaps, if speed of adaptation is important, companies may not have the time to identify the
right measures and the right causal relationships, which may take months or years to develop,
as it sometimes does for balanced scorecard methods (Smith, 2001). Are causal measurement
models better than correlated or non-causal ones at finding useful patterns? Perhaps, but the real
issue is whether the measurement system is finding the right knowledge in timely way. While
a non-causal CRM measurement system can detect conditions that provide opportunities quickly,
determining the right business response will require some root cause analysis for diagnosing
and fixing customer problems. Time becomes the pivotal variable.

All the things that can and should be measured across the enterprise regarding customers, be
they value-creation, value delivery or customer insight activities, can be compared to that
opaque sea. While the business can cast its net (its measurement system) to find fish (useful
knowledge) where the fish usually swim, all sorts of things can cause the fish to swim in other
hidden waters. Overly developed and non-adapting measurement systems are like the persistent
fisherman casting his or her old nets in the same place, waiting for the fish that may never
return. In this regard, the sea of activity between a company and its customers and within itself
as it serves customers is that sea of complexity.

Notes The theory of measurement advanced here is neutral on this question of causal
versus non-causal customer knowledge. Investing in identifying causality is a decision
that folds within the framework offered here and will be influenced by many factors. The
CRM practitioner that complained that CRM stands for “can’t really measure” was most
likely responding to the cost of identifying causality that made proving CRM investments
more difficult.

How does a business go about consistently measuring that field of complexity in a way that will
detect new and unseen patterns? Most companies assume that this can be engineered in a
predictable way. Some argue that it can’t. At best, a business can create an adaptive internal
environment that seems best suited for detecting and acting upon this field of dynamic complexity.
Stacey (2000) argues that the mainstream thinking about knowledge management that says
knowledge is stored within the minds of individuals in tacit form and has value only when
extracted as explicit knowledge, is wrong. For Stacey, knowledge assets lie in the “pattern of
relationships between its members.” Knowledge is “the act of conversing and new knowledge

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