Organizational knowledge retention and knowledge loss

Abstract

Purpose This paper aims to examine the effectiveness of organizational information technology (IT)-based and non-IT-based knowledge transfer mechanisms (KTMs) for the retention of different types of knowledge from mobile experts. It differentiates among four types of knowledge loss (KL), namely, conscious knowledge (i.e. individual explicit knowledge that can be codified); codified knowledge (i.e. explicit knowledge captured at the social level); automatic knowledge (i.e. implicit individual knowledge); and collective knowledge (i.e. implicit knowledge embedded in the organization). Design/methodology/approach A research framework connecting the organizational knowledge retention (KR) cycle to KL is developed and an exploratory analysis is conducted using data from two case studies in the Canadian federal public service. Findings are confirmed using a third government agency. Findings Without the right processes in place for organizational knowledge retrieval and reuse, the KR cycle is not complete, leading to KL. The lack of available social KTMs for the conversion of individual to social objectified knowledge leads to KL. KTMs shortcomings increase the risk of automatic and objectified KL. Research limitations/implications Exploratory results demonstrate that KL does not always equate to lack of KR. Implementing knowledge-specific organizational KTMs is important to encourage the retention of individual knowledge at the social level. Propositions and a framework are developed for future research. Practical implications Mobile experts hold valuable knowledge at high risk of being lost by organizations. This paper provides managers with a set of guidelines to develop a knowledge-specific strategy focused on KTMs that increase KR and mitigate KL. Originality/value This paper challenges the assumption that KL only results from poor retention and studies both retention and loss to identify additional types of unintentional loss that occur when individual knowledge is not converted to social knowledge.

Exploring the Challenges and Barriers of Knowledge Retention in Information Systems Development Teams: The Case of Pēke

“…KR is concerned with preserving and maintaining the knowledge embedded in individuals and their relationships with others, which is used to cope with challenges arising from the exit of employees [10,14]. It can be considered as a special form of knowledge transfer, which occurs "when knowledge has been transferred from a knowledge owner to the organization and can be reused by a knowledge seeker" [15]. It serves the purpose of transforming knowledge between individuals and their organization in two stages: (1) routine KR activities (e.g., transfer, capture and storage of knowledge of existing experts within the organization) and (2) exiting KR activities (e.g., transfer and storage of knowledge held by those departing from the organization) [16].…”

“…It serves the purpose of transforming knowledge between individuals and their organization in two stages: (1) routine KR activities (e.g., transfer, capture and storage of knowledge of existing experts within the organization) and (2) exiting KR activities (e.g., transfer and storage of knowledge held by those departing from the organization) [16]. While various KM strategies, including IT-oriented and people-oriented, have been proposed to enable KR, KL becomes inevitable either because knowledge is not retained properly or because it is too costly to reuse [10,15,17]).…”

Strategic enablement investments: Exploring differences in human and technological knowledge transfers to supply chain partners

“…Researchers could generate insights that would be useful for firms to tailor enablement programs to best support partners' employees in gaining knowledge. Building on existing knowledge transfer research (e.g., Levallet and Chan, 2019 ), additional studies would provide insights to direct firms in tailoring enablement programs to best support employees of a supply chain partner in gaining knowledge. For example, in complex learning environments (P6), a more bespoke hybrid approach that carefully balances human and technology enablers might produce a more effective and efficient means of knowledge transfer that is suited for employees where the outcomes are important (e.g., AI-assisted surgeries) or costly (e.g., satellite launches).…”

Why Should We Investigate Knowledge Risks Incidents? - Lessons from Four Cases.

“…Knowledge loss due to leaving employees is one of the more studied areas connected to knowledge risks [e.g. 18,23,31]. Even in this domain studying the impact of knowledge risk incidents empirically is scarce [e.g.…”