This dissertation explores the complexities of an ageing workforce with a particular focus on employee and knowledge retention. With this extensive subject area 3 topics were established in order to narrow the area of research: How can an organisation plan for the departing ageing workforce; What motivates older employees to continue working; How can an organisation record knowledge and ensure its transfer? A case study was created for this dissertation from a willing organisation using high precision engineering technology within the medical device industry. To explore these topics in depth, a critical literature review was conducted, which also provided additional background. Historical literature, particularly on motivation (Maslow, 1943; Herzberg et al., 1959; McClelland, 1985) has been combined with recent literature from within the last 10 years on ageing workforces (CIPD, 2015) to analyse the existing narrative on the identified topics. Limitations and gaps highlighted in the critical literature formed the basis for the primary research of this dissertation. Eight semi-structured interviews with participants who are all employed by company X took place to gather data to back up or fill the gaps left by the existing literature. The evidence from the research found that all participants at company X currently have a succession plan, this does not consist of one sole individual but rather a pool of potential and willing candidates who are now on a development plan to ensure they have to right credentials if and when the time should come. It also highlighted that all the participants had different reasons for choosing when to retire. The majority of individuals had reasonings that were outside the organisations control. Therefore, the need is to focus on motivational factors which company X can control such as increased flexible working for those nearing or showing a legitimate interest in retirement. All participants shared that they have knowledge that they believe is currently not archived by the organisation. However, they go on to share that this knowledge is built upon experience, tacit knowledge, rather than explicit knowledge. The analysis highlights the difference between the two. Tacit knowledge is much harder to archive and transfer than explicit knowledge which creates weakness. Whilst not every recommendation sets out a full future plan it will provide a potential next step to company X.
PLEASE NOTE: You must be a member of the University of Lincoln to be able to view this dissertation. Please log in here.