Case Study: Knowledge-based theory of the firm

Knowledge-based theory of the firm

 

 

Knowledge-based theory of the firm

Introduction

In the past decade, information technologies have advanced so rapidly that they now play a leading role in determining the success of an organization. As such, the knowledge-based theory of the firm was formulated in this contemporary context. This theory asserts that knowledge is the most important factor of production and resource in any given organization. Therefore, performance differences among businesses exist because they tend to have dissimilar stocks of knowledge as well as capacities to use and develop the knowledge they have. This implies that a firm’s ability to create, transform and transfer knowledge is a determinant of its competitiveness in the market. A primary characteristic of knowledge is that it is related to humans. Thus, the people within an organization are the agents of knowledge and can give a firm its competitive advantage if they are intelligent enough to use it aptly. Even though this theory posits that knowledge is a resource, it cannot be managed in the same sense as other kinds of resources. Instead, its management entails creation of appropriate contexts and cultivation of a knowledge-hungry workforce (Sveiby, 2001).

Application of data, information and knowledge in this theory

            In the past, knowledge was viewed as the truth-value in a particular statement. However, this is not necessarily the perception in the contemporary management science. Knowledge is actively ever changing. This implies that it can be re-interpreted and modified to suit a particular situation. Scholars have since differentiated knowledge from other constructs that often confusing in the past: data and information. Data are mere signs and symbols and represent facts or observations without considering the context (Zins, 2007). As a result, they do not have any meaning. For example, the digits 1, 2, 3 bear no meaning when they are not associated with anything. On the other hand, information results when data is placed within some meaningful context. For instance, when the digits 1, 2, 3 are used to represent the number of boys, girls, and teachers in a classroom, they are transformed from data to information since they have a meaning.

Knowledge is an active concept since it includes decoding information and making sense of its impact. In essence, it is what a person comes to believe and appreciate based on the eloquently accumulation of information through inference, experience and communication. Both information and knowledge carry some meaning to a person. However, unlike information, knowledge is founded in the beliefs and commitment of the holder. It is also related to action (Kakabadse et al., 2003).

Even though the knowledge-based theory of the firm focuses on the knowledge of employees, it indirectly infers to the construct of data and information. The role of humans is central to its assertion since they are the ones capable of finding the relevant data, analyzing it and drawing conclusions from it. Individuals have the liberty to decide how they would like to not only use their intellect and skills, but also to manage their efforts based on individualistic motivations. An organization that has inspired employees who are ready to utilize their intellect and skills will be successful since there is a continuous flow of knowledge.

Gaining knowledge begins with creating data and trying to make sense of it. For example, when a firm wants to estimate whether consumers like its products, it may study their buying behavior. The numbers showing quantities bought (the data) will be analyzed to determine if they are low, average or high. If the number of buys are low, the firm will try to find out why this is so and what it can do to improve them. This type of knowledge is referred to as explicit knowledge. Explicit knowledge can be communicated and arranged easily in various forms which include numbers, theoretical models, verbal accounts and formulas. However, successful organizations are always more interested in tacit knowledge, which is based on experience, practice and expertise. Tacit knowledge is dependent on the person and the context in which it is placed.

The Curious case of Target Supermarket

In 2002, two marketers and Andrew Pole, all employees of Target supermarket set out to find out how the company could identify if a customer is pregnant even if she did not want them to know. To do this, Pole had to look at the spending habits of pregnant women especially during the second trimester when it is not always obvious. His purpose was to surprise them. Pole spent a lot of time collecting data on what women were buying. He was sure that some items were popular amongst pregnant women. After some time, he was able to observe some useful patterns. For example, he noted that pregnant women were purchasing large amounts of odorless lotions when their second trimester began. He also realized that in the first 20 weeks of pregnancy, expectant women bought more zinc, magnesium and calcium supplements. Women that were nearing the delivery date tended to buy scent-free soaps, hand sanitizers, washcloths and big bags of cotton balls (Duhigg, 2012).

Using this data, Pole was able to identify 25 products such that when they are analyzed together, they could predict whether a shopper is pregnant. He thus came up with a pregnancy prediction score. Furthermore, he could estimate her delivery date. He applied this analysis on female shoppers in the supermarket’s national database. The result yielded tens of thousands of probable pregnant women. This enabled the company to send them specific coupons to entice them to buy baby-related products. Using this tactic, Target surprised many women. There was even a man who accused the company of sending his teenage daughter baby related products as a way of encouraging her to get pregnant. He later apologized when he noticed that his daughter was actually expecting (Duhigg, 2012).

Conclusion

The Target case shows how companies can use data, information and knowledge to enhance their business operations. Pole started collecting seemingly regular data of items bought by female shoppers. However, he was able to turn this into information by identifying a pattern of shopping habits of pregnant women. This became knowledge once he linked it with the national database and was able to identify pregnant women and surprise them. In this regard, he had given Target a competitive advantage since it could send sales coupons to expectant women well before they develop visible signs or give birth.

 

 

 

References

Duhigg, C. (2012). How Companies Learn your Secrets. Retrieved 26 April 2014 from http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all

Kakabadse, N. K., Kakabadse, A., & Kouzmin, A. (2003). Reviewing the knowledge management literature: Towards taxonomy. Journal of knowledge management7(4), 75-91.

Sveiby, K. E. (2001). A knowledge-based theory of the firm to guide in strategy formulation. Journal of intellectual capital2(4), 344-358.

Zins, C. (2007). Conceptual approaches for defining data, information, and knowledge. Journal of the American Society for Information Science and Technology58(4), 479-493.