Cash flow management in construction firms

The level of insolvencies in the construction industry is high, when compared to other industry sectors. Given the management expertise and experience that is available to the construction industry, it seems strange that, according to the literature, the major causes of failure are lack of financial control and poor management. This indicates that with a good cash flow management, companies could be kept operating and financially healthy. It is possible to prevent failure. Although there are financial models that can be used to predict failure, they are based on company accounts, which have been shown to be an unreliable source of data. There are models available for cash flow management and forecasting and these could be used as a starting point for managers in rethinking their cash flow management practices. The research reported here has reached the stage of formulating researchable questions for an in-depth study including issues such as how contractors manage their cash flow, how payment practices can be managed without damaging others in the supply chain and the relationships between companies’ financial structures and the payment regimes to which they are subjected.

Discounted cash flow: accounting for uncertainty

Valuation is the process of estimating price. The methods used to determine value attempt to model the thought processes of the market and thus estimate price by reference to observed historic data. This can be done using either an explicit model, that models the worth calculation of the most likely bidder, or an implicit model, that that uses historic data suitably adjusted as a short cut to determine value by reference to previous similar sales. The former is generally referred to as the Discounted Cash Flow (DCF) model and the latter as the capitalisation (or All Risk Yield) model. However, regardless of the technique used, the valuation will be affected by uncertainties. Uncertainty in the comparable data available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the estimate of price. In a previous paper, we have considered the way in which uncertainty is allowed for in the capitalisation model in the UK. In this paper, we extend the analysis to look at the way in which uncertainty can be incorporated into the explicit DCF model. This is done by recognising that the input variables are uncertain and will have a probability distribution pertaining to each of them. Thus buy utilising a probability-based valuation model (using Crystal Ball) it is possible to incorporate uncertainty into the analysis and address the shortcomings of the current model. Although the capitalisation model is discussed, the paper concentrates upon the application of Crystal Ball to the Discounted Cash Flow approach.

The appraisal of data centres: deconstructing the cash flow

This paper analyses the appraisal of a specialized form of real estate - data centres - that has a unique blend of locational, physical and technological characteristics that differentiate it from conventional real estate assets. Market immaturity, limited trading and a lack of pricing signals enhance levels of appraisal uncertainty and disagreement relative to conventional real estate assets. Given the problems of applying standard discounted cash flow, an approach to appraisal is proposed that uses pricing signals from traded cash flows that are similar to the cash flows generated from data centres. Based upon ‘the law of one price’, it is assumed that two assets that are expected to generate identical cash flows in the future must have the same value now. It is suggested that the expected cash flow of assets should be analysed over the life cycle of the building. Corporate bond yields are used to provide a proxy for the appropriate discount rates for lease income. Since liabilities are quite diverse, a number of proxies are suggested as discount and capitalisation rates including indexed-linked, fixed interest and zero-coupon bonds.

Contemporary organizational theory in the management of construction projects

The level of insolvencies in the construction industry is high, when compared to other industry sectors. Given the management expertise and experience that is available to the construction industry, it seems strange that, according to the literature, the major causes of failure are lack of financial control and poor management. This indicates that with a good cash flow management, companies could be kept operating and financially healthy. It is possible to prevent failure. Although there are financial models that can be used to predict failure, they are based on company accounts, which have been shown to be an unreliable source of data. There are models available for cash flow management and forecasting and these could be used as a starting point for managers in rethinking their cash flow management practices. The research reported here has reached the stage of formulating researchable questions for an in-depth study including issues such as how contractors manage their cash flow, how payment practices can be managed without damaging others in the supply chain and the relationships between companies" financial structures and the payment regimes to which they are subjected.

WREN: electronic management system for facilities management

This paper describes a case study of an electronic data management system developed in-house by the Facilities Management Directorate (FMD) of an educational institution in the UK. The FMD Maintenance and Business Services department is responsible for the maintenance of the built-estate owned by the university. The department needs to have a clear definition of the type of work undertaken and the administration that enables any maintenance work to be carried out. These include the management of resources, budget, cash flow and workflow of reactive, preventative and planned maintenance of the campus. In order to be more efficient in supporting the business process, the FMD had decided to move from a paper-based information system to an electronic system, WREN, to support the business process of the FMD. Some of the main advantages of WREN are that it is tailor-made to fit the purpose of the users; it is cost effective when it comes to modifications on the system; and the database can also be used as a knowledge management tool. There is a trade-off; as WREN is tailored to the specific requirements of the FMD, it may not be easy to implement within a different institution without extensive modifications. However, WREN is successful in not only allowing the FMD to carry out the tasks of maintaining and looking after the built-estate of the university, but also has achieved its aim to minimise costs and maximise efficiency.

An entropy-based financial decision support system (e-FDSS) for project analysis in construction SMEs

Uncertainty contributes a major part in the accuracy of a decision-making process while its inconsistency is always difficult to be solved by existing decision-making tools. Entropy has been proved to be useful to evaluate the inconsistency of uncertainty among different respondents. The study demonstrates an entropy-based financial decision support system called e-FDSS. This integrated system provides decision support to evaluate attributes (funding options and multiple risks) available in projects. Fuzzy logic theory is included in the system to deal with the qualitative aspect of these options and risks. An adaptive genetic algorithm (AGA) is also employed to solve the decision algorithm in the system in order to provide optimal and consistent rates to these attributes. Seven simplified and parallel projects from a Hong Kong construction small and medium enterprise (SME) were assessed to evaluate the system. The result shows that the system calculates risk adjusted discount rates (RADR) of projects in an objective way. These rates discount project cash flow impartially. Inconsistency of uncertainty is also successfully evaluated by the use of the entropy method. Finally, the system identifies the favourable funding options that are managed by a scheme called SME Loan Guarantee Scheme (SGS). Based on these results, resource allocation could then be optimized and the best time to start a new project could also be identified throughout the overall project life cycle.

Entropy application to improve construction finance decisions

In financial decision-making processes, the adopted weights of the objective functions have significant impacts on the final decision outcome. However, conventional rating and weighting methods exhibit difficulty in deriving appropriate weights for complex decision-making problems with imprecise information. Entropy is a quantitative measure of uncertainty and has been useful in exploring weights of attributes in decision making. A fuzzy and entropy-based mathematical approach is employed to solve the weighting problem of the objective functions in an overall cash-flow model. The multiproject being undertaken by a medium-size construction firm in Hong Kong was used as a real case study to demonstrate the application of entropy. Its application in multiproject cash flow situations is demonstrated. The results indicate that the overall before-tax profit was HK$ 0.11 millions lower after the introduction of appropriate weights. In addition, the best time to invest in new projects arising from positive cash flow was identified to be two working months earlier than the nonweight system.

Tendering: optimization and rationality

There have been various techniques published for optimizing the net present value of tenders by use of discounted cash flow theory and linear programming. These approaches to tendering appear to have been largely ignored by the industry. This paper utilises six case studies of tendering practice in order to establish the reasons for this apparent disregard. Tendering is demonstrated to be a market orientated function with many subjective judgements being made regarding a firm's environment. Detailed consideration of 'internal' factors such as cash flow are therefore judged to be unjustified. Systems theory is then drawn upon and applied to the separate processes of estimating and tendering. Estimating is seen as taking place in a relatively sheltered environment and as such operates as a relatively closed system. Tendering, however, takes place in a changing and dynamic environment and as such must operate as a relatively open system. The use of sophisticated methods to optimize the value of tenders is then identified as being dependent upon the assumption of rationality, which is justified in the case of a relatively closed system (i.e. estimating), but not for a relatively open system (i.e. tendering).

Policy making without legislating: the self-regulation of commercial property leasing

The terms of a commercial property lease covers aspects such as rent, alterations to premises and the ability to leave; consequently they have a significant impact on cash flow and the ability of a business to develop. In contrast to the heavily-legislated residential sector, commercial landlords and tenants in the UK are largely free to negotiate the terms of their contract. Yet, since the property crash of 1989/90, successive governments have taken an interest in commercial leasing; in particular there is a desire to see landlords being more flexible. UK Government policy in this area has been pursued through industry self-regulation rather than legislation; since 1995 there have been three industry codes of practice on leasing. These codes are sanctioned by government and monitored by them. Yet, 15 years after the first code was launched, many in the industry see the whole code concept as ineffective and unlikely to ever achieve changes to certain aspects of landlord behaviour. This paper is the first step in considering the lease codes in the wider context of industry self-regulation. The aim of the paper is twofold: First a framework is created using the literature on industry self-regulation from various countries and industries which suggests key criteria to explain the effectiveness (or ineffectiveness) of self-regulation. This is then applied to the UK lease codes based on research carried out by the authors for the UK Government to monitor the success of all three codes. The outcome is a clearer understanding of the possibilities and limitations of using a voluntary solution to achieve policy aims within the property industry.

Data uncertainty in real estate forecasting

The rapid expansion of the TMT sector in the late 1990s and more recent growing regulatory and corporate focus on business continuity and security have raised the profile of data centres. Data centres offer a unique blend of occupational, physical and technological characteristics compared to conventional real estate assets. Limited trading and heterogeneity of data centres also causes higher levels of appraisal uncertainty. In practice, the application of conventional discounted cash flow approaches requires information about a wide range of inputs that is difficult to derive from limited market signals or estimate analytically. This paper outlines an approach that uses pricing signals from similar traded cash flows is proposed. Based upon ‘the law of one price’, the method draws upon the premise that two identical future cash flows must have the same value now. Given the difficulties of estimating exit values, an alternative is that the expected cash flows of data centre are analysed over the life cycle of the building, with corporate bond yields used to provide a proxy for the appropriate discount rates for lease income. Since liabilities are quite diverse, a number of proxies are suggested as discount and capitalisation rates including indexed-linked, fixed interest and zero-coupon bonds. Although there are rarely assets that have identical cash flows and some approximation is necessary, the level of appraiser subjectivity is dramatically reduced.

Valuation and arbitrage

The use of discounted cash flow (DCF) methods in investment valuation and appraisal is argued by many academics as being rational and more rigorous than the traditional capitalisation model. However those advocates of DCF should be cautious in their claims for rationality. The various DCF models all rely upon an all-encompassing equated yield (IRR) within the calculation. This paper will argue that this is a simplification of the risk perception which the investor places on the income profile from property. In determining the long term capital value of a property an 'average' DCF method will produce the 'correct' price, however, the individual short term values of each cash-flow may differ significantly. In the UK property market today, where we are facing a period in which prices are not expected to rise generally at the same rate or with such persistence as hitherto, investors and tenants are increasingly concerned with the down side implications of rental growth and investors may indeed be interested in trading property over a shorter investment horizon than they had originally planned. The purpose of this paper is therefore to bring to the analysis a rigorous framework which can be used to analyse the constituent cash flows within the freehold valuation. We show that the arbitrage analysis lends itself to segregating the capital value of the cash flows in a way which is more appropriate for financial investors

A critical review of methodologies for measuring rental depreciation applied to UK commercial real estate

Real estate depreciation continues to be a critical issue for investors and the appraisal profession in the UK in the 1990s. Depreciation-sensitive cash flow models have been developed, but there is a real need to develop further empirical methodologies to determine rental depreciation rates for input into these models. Although building quality has been found to be an important explanatory variable in depreciation it is very difficult to incorporate it into such models or to analyse it retrospectively. It is essential to examine previous depreciation research from real estate and economics in the USA and UK to understand the issues in constructing a valid and pragmatic way of calculating rental depreciation. Distinguishing between 'depreciation' and 'obsolescence' is important, and the pattern of depreciation in any study can be influenced by such factors as the type (longitudinal or crosssectional) and timing of the study, and the market state. Longitudinal studies can analyse change more directly than cross-sectional studies. Any methodology for calculating rental depreciation rate should be formulated in the context of such issues as 'censored sample bias', 'lemons' and 'filtering', which have been highlighted in key US literature from the field of economic depreciation. Property depreciation studies in the UK have tended to overlook this literature, however. Although data limitations and constraints reduce the ability of empirical property depreciation work in the UK to consider these issues fully, 'averaging' techniques and ordinary least squares (OLS) regression can both provide a consistent way of calculating rental depreciation rates within a 'cohort' framework.