A decision support system for evaluating local authority housing maintenance strategies in the United Kingdom
AuthorsSagoo, Amritpal S.
Gombera, Peter Pachipano
MetadataShow full item record
AbstractPurpose The lack of smart resources management and servicescape strategies within the social housing sector in the late 1970s influenced the rise of successive Governments to consider the restructuring of the traditional ‘cumbersome’ Local Authority based structures and approaches toward more ‘enterprise focussed’ management organisations (Sharp & Jones 2012). This change in central Government policy encouraged Local Authorities to assign through outsourcing their housing stock (including associated asset management services) as part of a Large Scale Voluntary Transfer (LSVT) via a process of compulsory competitive tendering to Housing Associations and / or set up Housing Trusts to increase the accountability, efficiency, and effectiveness of social housing and healthcare provision in the local community. As part of this modernisation process, all social housing and community care providers (also known as ‘Registered Social Landlords’ - RSLs) became subject to statutory audits, inspections and regulation, and performance management, to ensure the service quality delivery requirements. More recently, however, changes in the legislative framework have introduced choice-based letting policy, putting the customer first, service delivery and additionally RSLs are required to act as ‘Corporate Social Landlords’. These changes have focused RSLs attention on the need to sharpen service responsiveness, especially in the area of housing maintenance management (DETR 2000). Previous research (Holmes 1985; Spedding 1990; Johnston 1993; Stewart & Stoker 1995; Olubodun 1996, 2000, 2001; Sagoo et al. 1996; El-Haram & Horner 2002; Kangwa & Olubodun 2003, 2005; Boussabaine & Kirkham 2004; Jones & Cooper 2007; Prowle 2009; Babangida et al. 2012) has mainly concentrated on analysing maintenance management factors at the micro level; developing maintenance models and framework design for operational level. However, in the social housing sector, there have been no studies undertaken to date that have been focused on housing maintenance strategies – for example, how this is formulated, the key drivers of change and the impact on customer orientated service delivery. The purpose of this study is to identify the critical factors that drive the decision-making process in order to formulate responsive housing maintenance strategies and to develop a decision support model to improve customer service delivery of social housing provision. Research methodology Through a process of qualitative case study, pilot questionnaire surveys, workshops and qualitative in-depth interviews, the research has identified how the housing maintenance strategies are formulated and how social housing providers could enhance customer service delivery. The study comprised four phases in order to reflect the key objectives of the research. The first phase comprised a review of literature on social housing provision in the UK, identifying relevant changes in the legislative framework, an assessment of the challenges faced by RSLs and the key factors influencing performance of social housing provision. This phase also included undertaking a case study based on five different RSLs to examine the ‘real problems’ as to how and to what extent RSLs have adopted their organisation in order to meet the changes and challenges which they now face. The second phase investigated the key service factors impacting on housing maintenance strategy design and development through the use of a pilot study questionnaire directed to the asset managers (participating in the survey) and also included a selection of end users of the services (tenants). This phase identified the differences between the perceptions of service providers and the expectations of the service users. A key feature of this phase entailed conducting a workshop to disseminate findings of the pilot study. The workshop also formed a basis for ‘in-depth’ discussions for identifying the key factors, their descriptions, their interactions with each other, their inter-relationships with the tenant type, and their combined impact on formulating responsive housing maintenance strategy. The third phase of the study entailed eliciting qualitative data from the participants using the Repertory Grid (RG) ‘in-depth’ interview technique - a psychology tool in order to gain a deeper understanding of the core important ‘constructs’ and sub-constructs, their characteristics, their inter-relationships in the design and development of effective housing asset maintenance strategies. The fourth phase of this study entailed the development of a decision support system and the qualitative validation of the relationships found to exist between the constructs examined in phase three together with the testing of the model over a period of two months with four of the participating social housing providers. Findings The key findings arising from this research suggest that the design and development of value for money maintenance strategies within the public housing sector, are not solely based on physical factors related to the age, condition, location, construction type for example, but rather it was found that the majority of the asset management decisions made, were dependent upon a multivariate of key factors. The study identified 52 key factors, which when grouped together formed seven key cluster (Customer risk factors, Asset manager risk factors, Tenancy risk factors, Neighbourhood and community sustainability risk factors, Financial and economic risk factors, continuous service improvement risk factors and corporate risk factors) which are both ‘unique’ and ‘novel’ and are identified as having a direct influence on the formulation of housing maintenance strategy. These factors should not be considered in isolation and are more akin to the business success factors. The business ‘Balanced Scorecard’ (BSC) was evaluated and used as the basis for a ‘best fit’ model which was tested against four RSL to confirm its validity and its appropriateness. The responses obtained from these trials has indicated that the BSC provides a working tool capable of enhancing RSL organisational capabilities and service delivery effectiveness but also able to incorporate customer views regarding service delivery. This research makes major contributions to the existing limited pool of knowledge relating to strategic asset management within social housing sector and in addition, provides an insight into how housing maintenance strategy can be developed to incorporate feedback from customers (tenants) regarding the quality and responsive service delivery. The research also demonstrates the potential value of the BSC approach to the management tool capable of generating a competitive edge in line with government policy which is currently directed towards encouraging RSLs to adopt a commercial business approach to their operations. The research also demonstrates that the adoption of a decision support system in the form of BSC has the potential to provide useful assistance to RSLs intending to move away from the traditional public sector approaches to management (a more private sector orientated) approach to their operations. The research also shows that asset managers experience little difficulty in understanding the principles behind the BSC approach and its application. In addition, the cascading effect of BSC in housing maintenance strategy means that the strategy can be converted into measurable actions at the operational levels thereby providing a direct link between strategy and its implementation. Due to the absence of suitable benchmarking data, score rating derived from the RG were adopted by asset managers. This approach was found to be highly sensitive in assessing service delivery constructs. Furthermore, the research revealed that the individual constructs (52 key factors) had a profound influence in relation to the strategy formation and the assessment of customer service delivery. The study found that RSLs need to develop a deeper understanding and awareness of their customers concerns in that these factors may have a major impact in the development of a responsive housing maintenance strategy and overall improvements on RSLs performance. A close link was found between customer profile, their financial standing and their service expectations, patterns of behaviour and their interaction with their RSLs. High performance expectation was found on the part of affordable customers, presumably reflecting a higher level of social and economic dependency within this group and greater need for access to services thereby challenging RSLs to deliver higher standards of performance including housing maintenance provision. Other customer groups were noted as placing demand on their RSLs to adopt more holistic approach to formulation of housing maintenance strategy and embrace business-like approach to service delivery in order to facilitate a smooth transition from traditional public sector ethos to one closely akin to that associated with the private sector organisation. Practical implications The practical implications of this research are, that, if RSLs are to meet the demands of complying with a changed legislative framework, deliver responsive housing maintenance services to reflect the ever-changing customer expectations, and to adopt commercial approaches to the development of housing maintenance strategies, RSLs will need to re-engineer their business processes if the demands are to be satisfactorily accommodated. RSLs must also be prepared to adopt ‘smart business’ practices in the future, given that existing Key Line Of Enquiry (KLOEs) approaches now provide an inadequate tool for assessing performance in housing asset management nor are KLOEs sufficiently robust or possessing a sufficient degree of agility for modelling complex service delivery scenarios. As a result of this research, the BSC model has demonstrated its usefulness and its appropriateness to housing maintenance decision making within the current economic conditions and changed regulatory regime. The BSC model is simple in nature but nonetheless sufficiently flexible to allow factors to be added or omitted to accommodate the requirements and structures of individual RSLs. Academic implications To date, most housing asset management have concentrated on the technical and cost aspects of maintenance management aimed at the micro level and have attached little attention to the needs of strategic management or the potential significance of the customer. These earlier researches have limited application to the needs of strategy management particularly under the current conditions which social housing providers are now required to operate (Sharp & Jones 2012). This study is first of its kind to attempt to evaluate housing maintenance strategy giving considerations to end user ‘the customer’ dimension in service delivery within the social housing sector. This study has adopted a novel approach to this area of research by employing a technique frequently encountered in clinical psychology, based upon the use of a Repertory Grid – a qualitative tool for triadic elicitation of key drivers with a view to providing a robust tool for assisting housing asset managers involved in the development of housing maintenance strategy. The RG personal interviews with senior asset managers revealed hidden and latent factors, which would not have been easily identified had a quantitative questionnaire been used. The hidden constructs which were identified as a result of the applications of this technique are considered to be ‘akin’ to business success factors. Originality This study is also unique in that it has given particular considerations to the provision of housing maintenance service as perceived from the view point of the end users rather than directing itself to the constructional and technical aspects of housing asset management. Also, the research recognises the need for asset managers to become more aware of the implications of social factors and the need for these aspects to be incorporated into strategic maintenance models. A further unique aspect of this research is that it has endeavoured to obtain an insight into the cognitive processes (mind mapping and analytical mental processes) behind the decision making of asset management, in order to identify and understand the nature of the drivers behind these processes to develop a rational decision support model for assisting in the rational formulating of housing maintenance strategy. KEYWORDS Social Housing, Registered Social Landlords, Social Housing Providers, Customer Service Delivery, Asset Managers, Customer, Tenants, Repertory Grid
PublisherUniversity of Derby
TypeThesis or dissertation
The following license files are associated with this item:
Showing items related by title, author, creator and subject.
Effect of the building maintenance and resource management through user satisfaction of maintenance.Pontan, Darmawan; Surjokusumo, Surjono; Johan, Johny; Hasyim, Cholil; Setiawan, M. Ikhsan; Ahmar, Ansari Saleh; Harmanto, Dani; Tarumanagara University; Trisakti University; Darul Ulum University; et al. (Science Publishing Corporation, 2018)PD Pasar Jaya manages 153 markets spread across Jakarta. Market building is a place of public services, in order to provide excellent service to the community, it is important to maintain it properly. Maintenance management of PD Pasar Jaya is still far from the expected. The purpose of this study was to determine the effect of directly and indirectly from the condition of the building and maintenance re-sources to user satisfaction through maintenance management. The research method is by taking a sample of 14 buildings market, then use the check list building condition assessment visually and dissemination of survey questionnaires to 216 respondents, namely the market manager, the kiosk, and visitors. The questionnaire consisted of four variables: the condition of the building (X1), maintenance resources (X2), as an variable, independent maintenance management (Y) as variable, an intervening while user satisfaction (Z) as the dependent variable. Furthermore, assessment data is processed by the descriptive analysis of the building, while the questionnaire survey data processed by path analysis using linear regression with SPSS ver. 22. The results of assessment of 14 buildings is a market average of 78 of the highest value of 100, this means that the condition of the building is being with only minor damage. The total yield of the influence of the condition of the building (42.38%) and maintenance resources (25.01%) towards satisfaction of a user through mainte-nance management (1.26%) is 68.65%
Geotechnical assessment strategy for bridge maintenance – case study.Hamza, Omar; University of Derby (CRC Press, 2017-06-12)This paper presents a practical strategy used to conduct a geotechnical assessment, drawing principally on a maintenance work carried out recently for Rashwood Interchange which carries the M5 Motorway over the A38. The bridge, which was constructed in the early 1960s, had experienced long-term settlement attributed to historical brine pumping activities in the proximity of the bridge area. In planning for its maintenance work several issues challenged the geotechnical assessment, including the review of settlement history and mining instability in the area, the exploitation of as-built data records and the determination of foundation response to additional loading during the bridge repair. The paper presents how these complex challenges were approached, yet using simple procedures and common design tools. The procedures are also applicable to other infrastructure maintenance projects, particularly in transportation geotechnics.