The interaction of activity, space and cost variables in office workstation sharing

Abstract

Purpose -The growth in flexible working by employees in many office-based organisations means that workstation sharing at the employer's premises is increasingly attractive. However, because of peaks and troughs in demand it is difficult to decide how many workstations should be provided. The purpose of this paper is to investigate the cost-effectiveness of alternative workstation sharing strategies. Design/methodology/approach -The study used an agent-based simulation model with two input variables: the employees' reaction if they are blocked (i.e. they find that all workstations are already occupied), and the number of workstations at the employer's premises. The simulation was run for 56 scenarios. The results were evaluated by assigning cost penalties for workstations, blocking and displacement; there were eight cost regimes reflecting different organisational characteristics. Findings -The simulations showed trade-offs between the activity and space variables, in terms of utilisation, blocking and displacement. When costs were applied the output of the simulation runs, the most cost-effective scenarios varied markedly with the different cost regimes.Research limitations/implications -The variation in optimum strategies with different model input values suggests that cost-effective workstation sharing strategies must be developed on a case-by-case basis. The simplifying assumptions in the model must be considered when applying the findings to real organisations. Originality/value -Quantified analysis of the cost-effectiveness of workstation sharing strategies has not been found previously in the literature.

Investigating the Effect of Ergonomics on Employee Productivity: A Case Study of the Butchering and Trimming Line of Pioneer Food Cannery in Ghana

“…Correlations between work ergonomics and employee productivity. This finding is confirmed in previous studies by Roelofsen [3], Haynes [8], and Fawcett and Rigby [23] which suggested that there exists a positive and significant correlation between general design and workplace décor and employee productivity. Also, De Been and Beijer [24] posited that there is a high positive impact of workplace type on employee productivity.…”

“…This implies that whenever the organization enhances its spatial arrangement and furnishing, it results in improving its employee productivity. Similar studies by Becker [25], Fawcett and Rigby [23], and Saleem et al [10] have shown a significant positive association between spatial arrangement and furnishing, and employee productivity.…”

Analysis of factors influencing office workplace planning and design in corporate facilities

“…Examples of these solutions include: touchdown areas that allow staff to access information quickly; bookable offi ces; and group collaborative workspaces such as board rooms equipped with technology to provide teleconferencing capabilities; and hot-desking ( Pitt and Bennett, 2008 ). Hot-desking refers to the approach of compelling employees to share workstations through providing fewer workstations than employees to achieve the objectives of attaining higher workstation utilization and reducing the costs of providing workstations ( Fawcett and Rigby, 2009 ).…”

“…Therefore, organizations have started to devise approaches to minimize this cost through requiring employee to share workstations ( Fawcett and Rigby, 2009 ). However, attempts to achieve cost-savings in this trait might result in decreasing the employees ' productivity due to frequent distractions and loss of concentration ( Erlich and Bichard, 2008 ).…”

PACT: Calculating nWOW accommodation that suits the organisations’ work processes

“…In other words, a larger margin of available workplaces is needed to accommodate bigger fluctuations in the demand for space. In another article he describes a simulation model that aims to find out whether the option of sharing places is suited for an organisation (Fawcett & Rigby, 2009). By using an agent based simulation model that takes different elements into account and simulates the demand for places in different 'runs', it uses probability to visualise demand for workplaces at different times.…”