Operating cost analyses of long‐term care facilities

Identification, classification and shortlisting of performance indicators for hospital facilities management

Purpose

This paper aims to report on a study that aims to establish a list of systematically classified key performance indicators (KPIs) that are useful for hospital facilities management (FM).

Design/methodology/approach

A review of literature was conducted to identify indicators that are applicable to hospital FM. Each indicator was classified using a phase–hierarchy (P-H) model, which is a two-dimensional matrix comprising three phases (input, process and output) of facilities services delivery and three hierarchical FM levels (operational, tactical and strategic). The classified indicators were further shortlisted via a focus group study.

Findings

From the literature review, 61 indicators were identified as applicable to hospital FM. Most of the indicators, according to the P-H model, are for evaluating the FM input or output phase, at the strategic or tactical level. Further refinement and shortlisting of the indicators by the focus group experts resulted in 18 KPIs, which fall into 4 aspects: “physical”, “safety”, “environmental” and “financial”.

Research limitations/implications

The study illustrates that the P-H model is useful for classifying the performance indicators systematically along the two fundamental FM dimensions – phase and hierarchy. Further research may use this model to classify performance indicators in other contexts.

Practical implications

The method of this study can be adapted for use in identifying, classifying and shortlisting FM performance indicators for other types of buildings. The shortlisted KPIs can be used for assessing the FM performance of hospitals.

Originality/value

To the best of the authors’ knowledge, this study is the first of its kind that used the P-H model to classify hospital FM performance indicators.

Pitfall benchmarking of cleaning costs in hospitals

Purpose

It is typical of public real estate benchmarking reports to show only highly aggregated benchmarks based on buildings’ floor areas. They hardly provide disaggregated benchmarks for usage clusters. The aim of this study is to show the caveats from highly aggregated benchmarking without consideration of cluster-specific characteristics.

Design/methodology/approach

Based on the parameters of the German facility management association 812 standards, cleaning costs and costs for the surfaces of seven hospitals have been collected and allocated to specific room clusters. Using these basic data, a calculation and simulation conducted with the aim of simulating facilities that are comparable in the sum of costs yet feature varying sub-clusters as cost drivers. In particular, during this simulation, area ratios were varied randomly and the average cleaning costs per cluster were held constant for all hospitals. Therefore, the costs per square meter in the clusters of all simulated hospitals are identical and the full costs only depend on the area ratios.

Findings

The simulation shows that highly aggregated cleaning costs lead to large spans, and thus, to misinterpretations in the field of action. In the case, the aggregate benchmark ranges from 40.6 to 66.5 EUR/m², although, for all hospitals the same costs per square meter had been used. Thus, the bias results only from varying the share of area across the clusters. This finding is caused by a well-known statistical problem: the Simpson’s paradoxon, which currently receives little attention in real estate benchmarking.

Practical implications

The results show, that the regular benchmarking with high aggregated data, often used in practice, cannot be recommended. The author consider using a detailed benchmarking as meaningful and purposeful. To be able to make a detailed benchmarking, it is essential to identify and collect the influencing factors. Only if all important factors, in this case, the clusters will be regarded in the benchmarking, a reasonable benchmarking and useful interpretation can be given. Using a simple benchmarking to get a rough overview is refused steadfastly.

Originality/value

The study highlights that a comparison with public benchmarking reports (operation costs) must be taken with great caution. The author has quantified the bias from the aggregated benchmarking and have shown, that the Simpson’s paradox fully explains the consequences.

Organising in-house cleaning services in public FM

Purpose

This paper aims to describe and discuss in-house cleaning services in local authorities to gain a better understanding of current practices. These descriptions are intended to increase researchers’, practitioners’ and educators’ understanding of the studied issue, as there at present does not exist a solid understanding of in-house cleaning services in local authorities. Previous studies provide little detailed information regarding the internal environment of facility management (FM) organisations, in particular with regard to FM organisations’ individual services.

Design/methodology/approach

This research is based on two descriptive case studies, one from Norway and one from the UK. The case studies are based on semi-structured, face-to-face in-depth interviews and document reviews.

Findings

The cases demonstrate that in-house cleaning services can be structured and managed in different ways, particularly with respect to the split in services, the management of staff and customer contracts, the span of control, the chain of command, self-managed leadership, cleaners’ hours of duty and the use of outsourcing.

Research limitations/implications

Although the previous research on particular FM services is limited, this paper’s detailed descriptions may stimulate further development and research within the field. The knowledge brought forward is part of bridging a knowledge gap on cleaning in FM research. This knowledge can contribute to advancements in the way this service is discussed and measured across contexts by encouraging more rigour and specific studies on cleaning.

Originality/value

This paper constitutes one of the first detailed descriptions of in-house cleaning organisation in local authorities. This is a type of service supply that is common in certain contexts and identified as beneficial to cost-saving in other contexts.

Reputation and public awareness of facilities management – a quantitative survey

Purpose

The purpose of this paper is to develop an empirically tested framework for public awareness and reputation of facilities management (FM) as a business sector.

Design/methodology/approach

A national survey of representative sections of the population was designed and carried out to determine the level of public awareness and the reputation of FM. This survey was based on image/reputation categories from the international European Performance Satisfaction Index studies.

Findings

The findings provide a highly differentiated picture and give an interesting insight into the varied understanding of FM. Only a small fraction of the population has a realistic understanding of what the term FM means. The additional information collected about selected features of the respondents (age, gender, occupation, education, household income, etc.) facilitates interesting cross‐references to the level of public awareness and reputation of FM thus allowing an illuminating analysis of the findings.

Practical implications

A framework for measuring public awareness and reputation of FM is presented and tested. It can be used in the development of a cross‐national survey. In this study, the measurement of public FM awareness and reputation is applied only to one pilot country and further international research is needed to validate this tool within other geographical settings.

Originality/value

This survey represents the first quantification of public awareness and reputation of FM and is planned to be repeated on an international level at a two‐year interval, thus enabling comparisons between countries and corporations.

Strategic factors affecting warehouse maintenance costs

Purpose

The purpose of this paper is to determine the fundamental factors influencing maintenance costs of logistic buildings and to provide benchmark indications for designing maintenance efficient warehouses that contribute to the enhancement of business performance.

Design/methodology/approach

The relations between factors and indicators of building facilities maintenance costs are examined using regression analysis of a dataset collected from about 100 distribution warehouses leased by a leading global freight provider throughout Italy.

Findings

Maintenance cost reduction can only be achieved by making appropriate design decisions on the strategic characteristics of warehouse facilities. In particular, the location and the age of a building are relevant factors of breakdown maintenance, while the monthly volume of freight transiting the warehouse is a significant cost factor of maintenance due to damage.

Research limitations/implications

This paper is limited to logistic service providing organisations, has local impact, and does not consider operational requirements in suggesting design criteria. Further research may gainfully generalise the model by examining other businesses, geographical areas and industrial operations issues. Leasing and frequently relocating facilities have emerged as appropriate distribution management strategies to control location, size and age of a building, and thus to face dynamic business conditions.

Originality/value

This paper provides maintenance cost benchmarks and supports design decision making of distribution warehouse facilities.