Knowledge Management and Big Data in Business

Jerzy Goluchowski and Barbara Filipczyk

University of Economics in Katowice

Introduction

Organizations operating in a dynamic, complex, and sometimes hard to predict business and social environment need up-to-date knowledge to conduct their business best (Abhishek & Divyashree, 2019; Soniewicki & Paliszkiewicz, 2019; Ying-Yen, 2019).

As a result of progressive digitization and related profound changes—not only technological but also social—the “parameters” of known situations as well as the framework (“boundary”) conditions of business activity change; new, previously unknown situations appear and are unlike the previous ones (Obitade, 2019).

This chapter aims to present the perspectives on the use of Big Data as evidence in the management of the knowledge necessary to improve business processes. In this chapter, we initially focus on the challenges within the area of knowledge management that the organizations face during the time of Big Data and Al Analytics. It is followed by the presentation of the approach toward knowledge management in the context of Big Data. In order to illustrate the presented theoretical solutions and emerging technological possibilities of improving knowledge management, we outline a conception that targeted for the acquisition and utilization of Big Data to improve knowledge management in the student onboarding process. This chapter ends with a conclusion summarizing the undertaken considerations.

Situation and Challenges in Theory and Practice of Knowledge Management in the Era of the Big Data

Organizations today also acquire the resources they need to conduct business, including not only raw materials, machines (tools), capital but also knowledge (Al-Azzam & Al-Qura’an, 2019; Hidalgo-Penate et al., 2019). Do they do it differently than before? Do they have new possibilities, and what are they? How do organizations acquire knowledge? How do they procure it from the outside, and how do they create it inside? What processes do they realize based on knowledge? How do they manage knowledge resources and processes based knowledge? What knowledge management strategies, technologies, and IT tools do they use? Where do organizations obtain the knowledge necessary to operate and conduct business? How are the processes of generating new knowledge organized, leading to innovation in organizations? How are these processes managed? How to improve the management of knowledge, resources, and knowledge processes? These are only selected questions that bother the organizations’ practitioners and theoreticians.

The management’s thinking, even when they consider the past and the present, is focused on shaping the future either by adapting to the perceived changes or by conducting innovative interventions. Thus, each of the above questions regarding knowledge management, when formulated by a practitioner (a manager), has a subtext regarding the future. For example, by asking the question of how organizations acquire new knowledge from Big Data, they are trying to determine how their organization is to do it in the future.

Running a business can be considered not only through the prism of resource management but also through the prism of managing business processes implemented in the organization, and process patterns can be treated as a significant knowledge resource.

Undoubtedly, changes in the environment should be seen and analyzed as soon as possible to optimize business processes and get the best direction for the organization. Managers of organizations must, therefore, analyze the processes or commission analyzes. This is seen in the example of conducting e-commerce: it is possible to dynamically change prices depending on the state of balance of demand and supply of individual goods. In the case of e-commerce, the knowledge about what and how to analyze and how to decide based on these results (at least part of these decisions) is built into the sales system.

Knowledge is necessary not only for efficient business processes but also to improve them. In order to improve the business process, e.g., customer service (sales) processes, you need a different kind of knowledge: knowledge about the course of processes, about potential changes in the attitudes or preferences of potential customers, the undertaken and planned activities of competitors, etc. The changes mentioned above in the area of e-commerce are an example of new trends initiated by the digital revolution. Digital technologies cause not only the transformation of the organization toward a so-called digital organization, affect not only the change in the implementation of many business processes implemented so far but they also affect the processes of analyzing business processes. Such opportunities arise due to the accumulation of rich knowledge about the course of business processes and the conditioning of these processes in a digital form, Big Data, and the access to new analysis tools (data processing) based on artificial intelligence and deep learning. Tire digital form increases the availability of knowledge and greatly facilitates the analysis of large data sets.

The need for current knowledge in management is not something new that only appeared in the 20th or 21st century. Information (knowledge) has always been valuable and necessary to make meaningful decisions. However, relatively recently, it has been realized that it is an important resource of the organization, and therefore, like any other resource of the organization, it should be managed. Such an approach to the organization’s information and knowledge is new in both management research and management practice. Tire perspective of knowledge management of an organization allows to perceive new management situations and propose new, more relevant solutions for the efficient running of the business by business and non-business organizations.

The list of questions that knowledge management researchers are trying to answer is open. The first research questions in this theoretical and managerial perspectives were formulated by Drucker (1992, 2012), Probst, Raub and Romhardt (2000), Nonaka and Takeuchi (1995), Liebowitz and Wilcox (1997), Liebowitz (1999, 2005), Davenport and Prusak (2000), and Gasparski (2007). After approximately 20 years of research work on knowledge management, many of them are still valid, and new ones have appeared. New research issues are not only the result of obtaining answers to existing ones, but they also result from a change in the reality of business at the threshold of the third decade of the 21st century. The business reality is constantly evolving, also under the influence of technological changes, so new research challenges and the need to re-think on the questions that were once formulated are understandable. Such issues include the issue of organizational knowledge management in the era of almost universal access to Big Data.

Answers to research questions posed on the organization’s knowledge management are formulated as part of three basic theoretical approaches: the resource approach, the process approach, and the system (Japanese) approach (see Paliszkiewicz, 2017, 2019). Sometimes, the integrated approach is also mentioned, e.g., Pourdehnad, Wexler and Wilson (2011). Each of them presents research problems differently, assesses them differently, and, as a result, receives different answers. Accepting research perspectives is like observing a room from different places and reporting what we see, e.g., when we look at it through a keyhole, the door ajar, or a slightly exposed window.

Both managers and scientists must not only study but also shape (study and shape) the organizational reality. The scientists do this, especially utilizing the formulation of postulative theories, in the postulate, normative movement. The managers do this through decisions, most fully in the processes of designing a future organizational reality, including designing patterns of future business processes. We treat design, after Gasparski (1978, 1991, 2007), as a conceptual preparation of activities (work). Therefore, it applies not only to physical artifacts but also to services, ideas, strategies, and business processes.

Based on the data and knowledge about the situation in the past and present, organizations want to “construct a future”, which we only partially influence. It seems that the system and design approach aids in dealing with the challenges of thinking about the future. System thinking supports what is being constructed. Design thinking supports both how the future is being constructed (designed) and how to construct it (future activities, products, services, messages, etc.). In literature, one can also encounter considerations that integrate both approaches— integrated thinking (e.g., Douglas, 2003; Martin, 2009).

As shown above, in terms of improving business processes as well as managing knowledge in business processes, knowledge is necessary in order not only to utilize resources optimally but also to improve organizational processes, also taking into account the resources required for their implementation. The starting point of the optimization of processes of effective usage of available data and information is the stocktaking of knowledge regarding all business processes or the ones selected for improvement. Their course can be documented by, among others, Big Data. This approach to the usage of available knowledge leads to the application of the idea of evidence-based management in the area of business process management (BPM), including in the area of knowledge management, and the improvement of these processes.

Evidence-Based Management versus Knowledge Management in the Big Data Era

The term “evidence-based” was originally developed in the 1990s in the field of medicine (see Sackett et al., 2000). Today, the term is used in various disciplines, such as education, criminology, public politics, social work, and (recently) management. The concept of evidence-based practice refers to it. The starting point for the concept of evidence-based management is the belief that decisions in the field of organization management should be based on the connection (integration) of critical thinking with the collection of the best available evidence (see Rousseau, 2006). “Evidence” means information, facts, or data confirming (or negating) an assertion, an assumption, or a hypothesis (Steglitz et al., 2015). Evidence can come from scientific research, but it can also be created by internal business information and work experience. Undoubtedly, Big Data are perspective evidence for process management and knowledge management. This is illustrated by the success of IBM’s Watson system, i.a. in diagnosing diseases and the development of epidemics. The Watson system is a cognitive computer system—capable of answering questions asked in natural language. It was developed as part of the IBM-DeepQA project by a research team led by David Ferrucci. The system was named after IBM’s first president, Thomas J. Watson. Answers are formulated based on evidence (e.g., in the form of cases collected in practice, test results, etc.).

All managers base their decisions on some “evidence”. One could, therefore, consider that all management is evidence-based. However, many managers do not pay enough attention or pay insufficient attention to the quality of evidence on which they base their decisions. There is a deficiency in their thinking and action, as well as the reflection on the sources of knowledge that they use in the decision-making processes. As a result, management decisions are often based on so-called “best practices” or storytelling about the reasons for the success of famous or known managers. The management practice-based/founded on the concept of evidence-based management aims to remedy this state of affairs, helping managers to critically assess the legitimacy, generalization, and usefulness of their evidence and how to find the “best available evidence”. This also applies to the “treatment” of business processes and the improvement of knowledge management processes using Big Data.

In order to use Big Data as a source of evidence in making decisions that shape business processes, managers should make better use of both their knowledge management achievements as well as Big Data and business intelligence or have employees with such competences at their disposal. For example, they should know how to search for evidence (e.g., research results) in online databases, how to analyze Big Data to extract valuable knowledge, and how to assess the validity and usefulness of the research found. Knowledge managers, and in particular participants in improving business processes, should be aware of making assumptions in practice—consciously or not fully consciously—and of the need to reflect on the assumptions mentioned above. This includes not only knowledge in the field of research and methodology, in particular, knowledge management and critical thinking methods to balance the subjectivity of their assessments and cognitive limitations (see Filipczyk & Goluchowski, 2019). They must be aware of the need to understand what type of situation is being analyzed (e.g., ordinary or extraordinary). Understanding the situation conditions the use of Big Data when the situation is ordinary and when it is extraordinary (VUCA—four dimensions of a situation: Volatility, Uncertainty, Complexity, Ambiguity)? What knowledge of the past can be used to construct the future of the organization? What will Big Data analyses be useful for this?

 
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