A Review of “Does Big Data Mean Big Knowledge?”

Introduction

In their 2017 article titled “Does big data mean big knowledge? KM perspectives on big data and analytics,” Pauleen and Wang (2017) discuss their opinions on how the field of Knowledge Management (KM) should be involved in the process of “big data” and analytics. Pauleen and Wang (2017) also put forth a proposed model for how KM and analytics processes should interact with each other.

A Review of “Does Big Data Mean Big Knowledge?”

Pauleen and Wang (2017) frame KM as an established discipline that stands at an inflection point due to the growing emphasis on big data/analytics both in academia and in industry. They state that “big data/analytics has not only dominated information discourse, but threatens to run away with it” (Pauleen & Wang, 2017, Introduction section). Pauleen and Wang (2017) believe that the capacity of big data and analytics to uncover hidden patterns and insights in data brings many possibilities to the KM field that should be addressed.

The article puts forth a model to demonstrate how KM should be embedded in the process of big data/analytics, called the “Big data/analytics-knowledge management (BDA-KM) model” (Pauleen & Wang, 2017, Figure 1). The BDA-KM model uses problems, motivations, and goals as inputs and answers, decisions, and actions as outputs (Pauleen & Wang, 2017). In between the inputs and outputs, the model has two main sections: the knowledge domain, and cross-platform data storage (Pauleen & Wang, 2017). The knowledge domain begins with contextual knowledge which gets passed to cross-platform data storage through either “operations & activities” or “Analytics Tech. & Tools” (Pauleen & Wang, 2017, Figure 1). The cross-platform data storage section receives information from the knowledge domain into big data databases (Pauleen & Wang, 2017). Information is then extracted and passed back into the knowledge domain as “extracted new insights” (Pauleen & Wang, 2017, Figure 1).

In the article, contextual knowledge is defined as “how knowledge is situated in organizational contexts” and includes “the tacit knowledge of employees, implicit knowledge contained in organizational processes and activities, outputs such as products and services and stakeholders throughout the supply chain including intended markets” (Pauleen & Wang, 2017, Our take - a role for big data/analytics in KM section). The authors argue that contextual knowledge aids the analysis process by providing insight into the dataset itself and what analysts should be looking for (Pauleen & Wang, 2017). They also say that contextual knowledge includes information about the environments where data are collected and the business logic that the data collection is subject to (Pauleen & Wang, 2017).

Conclusion

The BDA-KM model proposed by Pauleen and Wang (2017) does not have a scientific foundation but rather attempts to paint a picture of how the discipline of KM should maintain relevancy while the popularity of big data and analytics continues to rise. Pauleen and Wang (2017) make a call for academics and practitioners to level up their big data/analytics skills to make sure the discipline is advancing sufficiently and not ceding control to newer market entrants. They also make a call for research into how the KM discipline can leverage big data/analytics to provide more value to the organizations they serve (Pauleen & Wang, 2017). There is, however, some research that suggests the importance of KM in the process of big data/analytics. One paper published in 2018 found “that firms that developed more BDA capabilities than others, both technological and managerial, increased their performances and that KM orientation plays a significant role in amplifying the effect of BDA capabilities” (Ferraris et al., 2019, Abstract).

References

Pauleen, D. J., & Wang, W. Y. (2017). Does big data mean big knowledge? KM perspectives on big data and analytics. Journal of Knowledge Management, 21(1), 1–6. https://doi.org/10.1108/jkm-08-2016-0339

Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2019). Big data analytics capabilities and knowledge management: impact on firm performance. Management Decision, 57(8), 1923–1936. https://doi.org/10.1108/md-07-2018-0825