Case Studies in Knowledge Management

Implementing Knowledge-Enabled CRM Strategy in a Large Company 255

Copyright © 2005, Idea Group Inc. Copying or distributing in print or electronic forms without written

between corporate investments and the satisfaction of customer needs to generate the
maximum profit. CRM emerged as an amalgamation of different management and infor-
mation system (IS) approaches, and entails the following processes (Gebert, Geib, Kolbe,
& Brenner, 2003):

• Measuring inputs across all functions, including marketing, sales, and service
  costs as well as outputs in terms of customer revenue, profit, and value;


• Acquiring and constantly updating knowledge on customer needs, motivation,
  and behavior over the lifetime of the relationship;


• Applying CK to constant improvement of performance through a process of
  learning from successes and failures;


• Integrating marketing, sales, and service activities to achieve a common goal;


• Continuously contrasting the balance between marketing, sales, and service
  inputs with changing customer needs in order to maximize profit.

CK that flows in CRM processes can be classified into three types:

1. Knowledge about customers: accumulated knowledge to understand customers’
   motivations and to address them in a personalized way. This includes customer
   histories, connections, requirements, expectations, and purchasing pattern (Dav-
   enport et al., 2001).


2. Knowledge for customers: required to satisfy information needs of customers.
   Examples include knowledge on products, markets, and supplies (Garcia-Murillo
   & Annabi, 2002).


3. Knowledge from customers: customers’ knowledge of products and services they
   use as well as about how they perceive the offerings they purchased. Such
   knowledge is used in order to sustain continuous improvement, for example,
   service improvement or new product development (Garcia-Murillo & Annabi,
   2001).

Knowledge about customers is gathered through interactions with customers
through processing of customer orders as well as through different customer interaction
channels such as phone, e-mail, interactive voice recognition (IVR), fax, mail, e-com-
merce, and front-office stores (Figure 1). Operations knowledge about customers, for
example, customers’ personal information and purchasing history are held in computer-
ized operational data stores (ODS), that is, billing and provisioning data stores, and
accessed by staff of these units. For example, each time a customer makes contact with
the company, the customer’s needs, as well as the actions taken to satisfy these needs,
represent information that may be captured and processed to benefit future customer
interactions.
The knowledge about customers should be used to determine what to offer, when
to offer, and how much to charge. In the long term, the company has to design new
products, offer new services, compete in new markets, but even in the short term, the top
salesperson could get sick or be headhunted. What companies currently know about
their customers may not be sufficient in order to build and sustain stronger relationship
with customers. Companies may need to put in processes and systems to gather more
information and data about who their customers are, what they do, and how they think
in terms of future purchasing decisions. Therefore, analytical, or deduced, knowledge
about customers such as prediction of customers’ expectations and future-purchasing