5.8 Knowledge Acquisition

5.8 Knowledge Acquisition

          In KM community, knowledge acquisition is defined as a process that involves the acquisition of knowledge from human experts, books, documents, sensors, or computer files. The knowledge may be specific to the problem domain or to the problem-solving procedures, it may be general knowledge (e.g., knowledge about business), or it may be meta- knowledge (knowledge about knowledge).  

          The field of knowledge acquisition has been a challenging topic among automated machine learning approaches e.g., perceptrons (Rosenblatt, 1962), to semi-automated knowledge engineering (Buchanan & Shotcliffe, 1984), to more robust automated approaches like neural networks (Rumelhart, 1986), symbolic rule learning (Rastogi, 2000), and most recently to proven, practical methods (Witten & Frank, 2005), successful applications (Probst, 2001) and mature theoretical frameworks (Kearns & Vazirani, 1994).

          Knowledge acquisition is a very broad topic. Some of its aspects extend well outside the scope of this book.            In this section we will restrict our discussion upto the knowledge available to the organization from different sources, and the managerial issues that must be considered.

          In a business environment, the main sources for knowledge acquisition are customers, suppliers, competitors, and partners/alliances.  These can be considered external sources of knowledge.  External knowledge sources are important and one should therefore take a holistic view of the value chain (Gamble & Blackwell, 2001). In below paragraphs we will discuss the role of these resources in knowledge acquisition process:

  • Customer knowledge comes in different forms. Discussing about the importance of customer knowledge Gerbert et. al. (2002) state: “Our research shows that by managing the knowledge of their [organizations] customers, corporations are more likely to sense emerging market opportunities before their competitors, to constructively challenge the established wisdom of “doing things around here”, and to more rapidly create economic value for the corporation, its shareholders, and last, but not least, its customers. They have suggested the five styles of customer knowledge management:
    • Prosumerism,
    • Group learning,
    • Mutual innovation,
    • Communities of creativity, and
    • joint intellectual capital.  A

           Any company, depending on the nature of its various customers, can apply several of these five styles of customer knowledge management simultaneously.

          Gerbert et. al. (2002) has identified three different types of customer knowledge:

    • Knowledge for customer: The knowledge that the customers can gain in order to satisfy their knowledge needs. It can include product, market, and supplier knowledge. It can be sourced within the organization or from other external sources like other customers and competitors (Zanjani, et. al., 2008).
    • Knowledge about customer: The kind of knowledge that enables us to know the customer better, to understand their motivations, and to address them better. This includes their requirements, expectations, and purchasing activities.
    • Knowledge from customer: The kind of knowledge that deals with the feedback from customers regarding products, suppliers, and markets. It can be used to improve organizations’ products and services.

          These three categories apply to customer knowledge acquisition as well as to data and information, which can be processed and used to create knowledge (Zanjani, et. al., 2008); e.g. data on purchasing habits could be analyzed to create knowledge that could improve marketing strategies or product design decisions. Following methods could be used to collect customers’ Knowledge (Gerbert, et. al. 2002):

    • Collecting customer’s feedback
    • Collecting and processing marketing related information
    • Collecting customers’ suggestions
    • Customers’ involvement in development/design

          Effective acquisition of customer knowledge depends on customer relationship management. It is equally important to consider customers as equal co-creators of organizational value. IT can be used in this context both as a means of collecting feedback and enhancing communication and cooperation between partners. It is also useful as a way to gather data and information regarding sales, trends, feedback, and so on, which can then be used to create new knowledge within the organization.

  • Suppliers’ knowledge is also very important.  Chan (2009) presents a classification for supplier knowledge based on the concepts outlined by Gerbert, et. Al. (2002). These are:
  • Knowledge for suppliers: This is the knowledge that suppliers require. It includes "production needs and forecasts, inventory, products, customers, and markets" (Chan 2009).
  • Knowledge about suppliers: This is knowledge that is used to understand how the supplier can match the requirements of the organization. It provides insight regarding quality, delivery, defects, financial risks etc.
  • Knowledge from suppliers: This refers to the knowledge that suppliers have gathered from their dealings with the organization.

          The role of IT is similar to the ones    presented for customer, organization now taking on the role of customer. Knowledge acquisition in this case also includes data and information which can be processed and used as building blocks for new knowledge creation.

  • Talking about the role of Competitors’ knowledge, it is important to note that the outcome of a successful knowledge acquisition process also depends on competitors to a reasonably extent; particularly in today’s online business environment where competitors’ products are only three mouse-clicks away. In such a volatile environment, the competitors’ knowledge becomes a fairly important aspect of knowledge acquisition.  In this case knowledge acquisition involves collecting, organizing and presenting the data, information, and knowledge that the organization has acquired from its’ competitors in such a way that one can search, retrieve, and analyze. Some of this falls within the scope of information management, but it is particularly the process of using these components to create better decisions and new knowledge that provide a competitive edge to the organization.

          IT systems are equally useful in this case as well, since the sources are largely explicit and presumably require frequent updating and manipulation. Data mining and analysis, document management systems with suitable search functions and expert systems are most relevant here.

  • The knowledge of Partners/alliances is also important for knowledge acquisition. Alliances’ knowledge is a valuable potential resource. However these must be properly managed. Key success factors include fostering trust, learning from your partner, and effectively managing the creation of knowledge relevant to both parties. Knowledge transfer can be facilitated by personnel exchanges, common projects and other forms of regular interaction, technology sharing, etc. (Gamble & Blackwell 2001). Focusing on informal communication, collaboration, and socialization is of paramount importance for valuable tacit knowledge acquisition and for extending communities of practice beyond the organization's borders.

          Chan (2009) once again formulates a set of knowledge types based around the work of Gerbert, et. al. (2002):

  • Knowledge for partners: Knowledge which satisfies their needs, including "knowledge about products, markets, and suppliers" (Chan 2009).
  • Knowledge about partners: Knowledge acquisition focused on understanding the ability of partners to perform their role in the relationship. It includes distribution channels, products, services, etc.
  • Knowledge from partners: The knowledge that partners have accumulated from dealing with the organization.

          IT can be used in this case similar to the way it is used inside the organization for knowledge sharing and knowledge creation (including data/information analysis) - in other words supporting communication, collaboration, experimentation, expertise location, analysis tools, etc. The  system has to fit the nature of the relationship and the business model.

          What is of particular importance in this case is to safeguard the system so that only that knowledge which the organization is willing to share becomes available. In the 80s, joint ventures between American and Japanese firms often resulted in a lopsided endeavor favoring the latter, since the Japanese were far more willing to listen and the Americans were far more willing to talk. It is important to remember that the goal here is two way learning; that a relationship will not last forever; and that a partner today may be a competitor tomorrow. KM must therefore be very aware of what knowledge is being shared, and the IT systems must reflect this policy.


By meta knowledge, we mean information about how experts use their knowledge to solve problems and about problem-solving procedures in general.