Article Preview
TopIntroduction
The information technology (IT) industry has been at war for recruiting and retaining talent over the decades. The median employee tenure in the IT industry is significantly lower than many other global industries, such as the automotive, pharmaceutical, and telecommunications industries (PayScale, 2020). It ranges from 1.1 years at Amazon.com Inc. and Google Inc. to 6.4 and 7.2 years in IBM Inc. and Xerox Corporation, respectively (PayScale, 2020). Unsurprisingly, the high turnover rates in the IT industry have been attributed to the working environment, including workload amongst project members, variance in the working hours of project members, and imbalance in the working hours of project members (Bao et al., 2017). The transformation toward agile ways of working further intensifies the uncertainty of work environments. ING reduced its workforce by 25% during agile transformation (Kerr et al., 2018). Together these factors contribute to the loss of organizational knowledge that is embedded in departing employees.
In the face of the pressing need to remain digitally agile in an ultra-competitive business environment, IT organizations are likely to experience financial losses associated with the erosion of competitive advantage and poor organizational performance when critical knowledge is not retained (Daghfous et al., 2013; Harden et al., 2018). Knowledge retention (KR) is a management imperative for many IT organizations, especially for ones facing a greying IT workforce (Gonzalez, 2016) and/or those that rely on external labor and consultancy markets to fill talent shortages (Chaudhuri et al., 2018). KR is concerned with managing knowledge embedded in individuals and their relationships (Liebowitz, 2008; Martins & Meyer, 2012) and seeks to tackle knowledge loss (KL) challenges when knowledge is not captured, and knowledge workers leave organizations (Durst & Zieba, 2019; Huber, 1991). KR continues to be a major concern in information systems development (ISD). ISD knowledge is often not properly documented (Batra et al., 2011; Remus, 2012). Moreover, it is not uncommon for outgoing IT experts to be submitted to rushed exit interviews and for newcomers to be bewildered by unstructured handovers (Coombs, 2009). Losing information systems development (ISD) knowledge prevents IT personnel and/or contractors from delivering IT-enabled value (Lin et al., 2016) and cripples IT-dependent organizational agility (Fink & Neumann, 2007).
Building on risk management literature, Jennex (2014) suggests assessing the likelihood and impact of KL risks, formulating a KR plan, and monitoring whether risk responses are effective. Existing literature recommends various strategies to address risks of KL. Research has shown that knowledge management (KM) governance, talent management practices, electronic repositories, and KM routines embedded in ISD methods can address KL risks (Korimbocus et al., 2018; Kotlarsky et al., 2014; Levallet & Chan, 2019; Lin et al., 2016; Pflügler et al., 2018). Nevertheless, in a dynamic environment where the structure and the composition of the organization change constantly, sustaining KR remains elusive, as is evident in open source projects (Rashid et al., 2019) and software organizations (Alahyari et al., 2019).