Richard Kirkham

Re-engineering the whole life cycle costing process

The application of Whole Life Cycle Costing (WLCC) within the construction industry is rapidly increasing; notwithstanding, the underlying methodology of many WLCC models is variable and inconsistent. The deficiency in detailed recording of decisions based on WLCC analyses is a particular concern and moreover, attempts to capture the data related to these decisions are not evident. Data capture is vital in facilitating the iterative and logical application of WLCC. In an attempt to re‐engineer the WLCC design process, the evolving research described hereinafter reports on the development of the ‘Logbook’, a WLCC model decision‐support software application. The application works simultaneously with a WLCC model to provide the designers of buildings with a repository of decision data (via the WLCC model), and a sequential, chronological record of the decisions made based on this data – from inception through to final design optimization. It is anticipated that the software will encourage the application of WLCC models as an iterative rather than retrospective process.

Probability distributions of facilities management costs for whole life cycle costing in acute care NHS hospital buildings

Whole life cycle costing (WLCC) can provide a valuable insight into the economic efficiency of National Health Service (NHS) acute care hospital buildings. The costs of the facilities management function form an integral part of that process. However, the nature of facilities management cost data collated by NHS Estates informs the analyst little about the relationship between the physical characteristics of hospital buildings and the facilities management costs. The data can only be used to benchmark trusts total facilities management spending, but what the NHS now requires is a way of being able to model the facilities management costs for particular buildings. The purpose of this paper is to demonstrate, using a case study, a methodology for modelling stochastically the facilities management costs in NHS acute care hospital buildings. The data used in this research were obtained from NHS Estates on the facilities management costs of over 450 acute care NHS Trusts in England and Wales. The data were analysed to obtain the parameters of the theoretical distributions that best describe the facilities management costs for a ward block building in a large university acute care teaching hospital. The accuracy of these distributions was then validated using various hypotheses and goodness-of-fit tests. The result of this work provides analysts with a framework whereby the facilities management costs in acute care hospital buildings can be modelled as stochastic assumptions in the modelling of WLCC. The paper also reveals that for acute care hospital buildings with a similar gross floor area to that of the building used in the case study (that is approximately 20% of the entire acute care hospital estate), the underlying distribution of costs is likely to belong to the loglogistic distribution

Forecasting the residual service life of NHS hospital buildings: a stochastic approach

Service life appraisal is an important facet of the management of the NHS estate portfolio. Existing approaches to remaining service life estimation use simple deterministic methods, which could yield inaccurate results. An alternative approach to forecasting the remaining life of hospital buildings, based upon a combination of weighted average techniques and a Markov property; the minimum of exponentials, is presented. The results from this model were compared with those obtained by means of existing techniques, and revealed an average percentage difference of 56.26%. This confirms the notion that stochastic approaches in combination with elemental weightings could yield greater accuracy. Whilst the results obtained can be used primarily to determine the overall residual service life of a hospital building, the model also allows the condition state transition probabilities to be calculated at a given time. On the macro level, this information can be used for optimization of maintenance strategies.

Simulation of maintenance costs in UK local authority sport centres

The costs of building maintenance, particularly in high-demand public sector facilities, can account for a significant proportion of the whole life cycle costs. The ability to accurately predict these maintenance costs can provide an essential management tool during the operational stages. A thorough investigation of existing techniques and metrics to predict these costs provides the basis of this research, which proposes an innovative simulation-based approach to maintenance costs modelling in UK local authority sports buildings. The results obtained show that gross floor area, swimming pool size, and the number of users are the critical factors influencing maintenance costs in sport centre buildings. Probabilistic representations of these variables are used in a stochastic cost-forecasting model, which reveals that the Weibull distribution is suitable for representing the maintenance cost function. The results are validated through the application of the Kolmogrov-Smirnov test, the importance of this test, and the data pre-analysis used in the construction and validation of the input probability distributions, are also discussed.

Whole life cycle performance measurement re‐engineering for the UK National Health Service estate

Purpose – The measurement of the performance of built assets with the UK National Health Service portfolio is based on simple benchmarking techniques such as £/m2. The purpose of this paper is to examine an alternative approach, which could produce a more informed and balanced approach to performance measurementDesign/methodology/approach – The existing benchmarking and clustering techniques used within the NHS are examined. These reveal inadequacies in truly representing asset performance. Data envelopment analysis techniques are applied here to map the estate costs against the outputs of the estate (i.e. number of inpatient days). Operational and maintenance cost data was collated from 15 NHS acute teaching trusts outside of London, these were mapped against two outputs (in‐patient days and occupied beds per available beds) in order to determine how effectively each NHS Trust translates input resources into inpatient days and occupancy of available beds.Findings – The results from the models generate ef...

Modelling total energy costs of sport centres

Providing and maintaining safe and comfortable conditions in sport centres raises many issues, particularly cost. The paper gives an overview of the factors associated with sport centre servicing and attempts to highlight the governing factors associated with this, particularly energy costs. A total of 19 sport centres in the City of Liverpool in the UK are investigated, using data elicited from the Liverpool Leisure Services Directorate. The energy operating costs were analysed using statistical methods. Six models were developed to predict total energy costs. Testing and validation results showed a high level of model accuracy. The models would be of use to professionals involved in feasibility studies at the design stage.