PROJECT RISK ASSESSMENT: A EUROPEAN FIELD STUDY

British Accounting Review (1999) 31, 347–371

Article No. bare.1999.0106, available online at http://www.idealibrary.com on

PROJECT RISK ASSESSMENT: A EUROPEANFIELD STUDY

ELAINE HARRISUniversity College Northampton, UK

One of the practical problems faced by managers when appraising strategic investmentopportunities, is how to deal with the uncertainty of the outcome(s). They often makesubjective judgements about the riskiness of prospective projects, but these are rarelyformalized into their strategic decision-making processes. Little attention is paid to thisqualitative side of investment appraisal in the corporate finance literature. This paperreports on a field-based study carried out in the logistics industry, which followedan innovative action research approach, operationalized by the use of focus groupsand repertory grids. Using a repertory grid technique, constructs were elicited, whichmanagers used to explain the riskiness of a particular project, compared to otherprojects of a similar type that they had knowledge of from past investment appraisals.The results of the study include a set of 12 project risk attributes, a project typologywhich defines three types of project, each with a set of weightings reflecting the relativeimportance of the attributes to the participants. These provide a useful insight intomanagers’ perceptions of the risk attached to strategic investment projects in a largeEuropean group. In addition to the context-specific results, conclusions are drawnregarding the use of repertory grids as a framework for a risk assessment technique inother organizational settings.

1999 Academic Press

INTRODUCTION

At the interface between Corporate Strategy and Financial Managementtheory stands the analysis of investment opportunities. These opportunitiesmay be defined as strategic options or as projects. However described, themanagement problem is to evaluate the strategic fit of the project, andthe financial problem is to evaluate the likely outcome of committingsignificant resources, before making a strategic investment decision (SID)which impacts upon shareholder value.

The risk and uncertainty attached to such decisions may be analysed froma variety of perspectives. Risk may be defined as ‘a condition in which thereexists a quantifiable dispersion in the possible outcomes from any activity’(CIMA, 1996, p. 101). Uncertainty may be distinguished as unpredictable

Received July 1998; revised February 1999; accepted May 1999.

0890–8389/99/030347+25 $30.00/0 1999 Academic Press

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events or outcomes, which are not quantifiable in the same way. Whilst adistinction may be made from a theoretical viewpoint, the assumption hereis that managers are unlikely to draw that distinction, and may use the termrisk in a broader sense, which is adopted throughout this paper.

Corporate Strategy literature tends to position Strategic InvestmentAppraisal (SIA) as one of a number of steps in the Strategic Planningprocess, for example, Quinn, Mintzberg & James (1987). King (1975)identified evaluation involving financial analysis as the fourth of six steps inthe decision-making process, which may be viewed as a subset of strategicplanning.

Corporate Finance theory, largely derived from neo-classical economics,positions SIA within the conceptual framework of the optimization ofthe value of the firm (Hirshleifer, 1958; Tobin, 1958). Techniques nowembedded in the domain of Accounting and Finance theory such asDCF analysis reflect an economic rationality which is increasingly beingchallenged (Jones & Dugdale, 1994; Dempsey, 1997; Northcott, 1991;Tomkins et al., 1996).

Capital budgeting research has largely focused on whether or nottechniques such as DCF analysis are being used (Mills & Herbert, 1987;Pike, 1982; Pike, 1988; Scapens et al., 1982). Now that increasing evidencefrom surveys suggests that such techniques are being used (Drury & Tayles,1997; Pike & Ho, 1991; Pike, 1996) questions as to whether and how riskis analysed in SIDs in practice are being asked (Abdel-Kader & Dugdale,1998).

The received wisdom in texts (such as Dyson, 1990, p. 224; Hull, 1980,p. 30) prescribe complex probabilistic approaches to risk analysis, usuallybased on Hertz’ (1964) simulation methodology. Tomkins (1991, p. 36),having described Monte Carlo simulation, acknowledges that such methods‘tend to diverge somewhat from the way such models are often currentlyused in practice’. Pike & Neale (1996, p. 235) having set out probabilisticapproaches to risk analysis, summarize the evidence of current practice asfollows:

‘The evidence suggests that firms are increasingly conducting risk analysis.This does not mean that the risk dimension is totally ignored by other firms;rather, they choose to handle project risk by less objective methods such asexperience, feel or intuition.’

Turning to a further body of literature on decision-making (Slovic, 1972;Libby & Fishburn, 1977; Tversky & Kahneman, 1974; Moon, 1988; March& Shapira, 1987), drawn from behavioural studies, there is evidence thatfactors other than shareholder value are likely to drive decisions.

The role of risk and uncertainty in decision-making has been studied froma psychological perspective (Tversky & Kahneman, 1974; Kahneman &Tversky, 1979; 1986) indicating that human decision-makers follow simpleheuristics or rules of thumb rather than complex probabilistic approaches.

PROJECT RISK ASSESSMENT: A EUROPEAN FIELD STUDY 349

A field based method widely used and advocated for exploration ofpractice is the case study method, which often involves gaining access toa number of organizations, but rarely with the intention of changing ‘thestatus quo’. The aim of this research was not just to explore managers’perceptions of the risk factors attached to SIDs, but ultimately to devise abalanced framework for project risk analysis in SIDs.

In order to gather sufficiently rich data for such a study, it was importantto focus upon a relatively small number of cases, but in a large amount ofdetail. This was achieved by selecting one major organization involved infrequent investment in large scale projects, which could provide sufficientcases for study within a single corporate context. Since a high degree ofcollaboration between the researcher and the participants was required,it was also desirable to find an organization where the executives mightwelcome the external intervention of a researcher to help them to improvetheir decision-making processes.

Benefits in terms of management and organizational development playedan important part in gaining access for the research. The study was designedin phases as an action research programme, starting with an exploratoryphase, followed by explanatory and experimental phases where a balancedframework or process model could be expected to emerge. This paperfocuses on the early phases of the programme.

After describing the organizational setting and theoretical perspective forthe study, the paper sets out the research design. Key observations from theearly phases of the study are discussed, and the later phases mapped out.Conclusions are drawn on managers’ perceptions of project risk and howtheir evaluation of the risk profile of projects can be captured as part of theirSIA by using the action research process described.

ORGANIZATIONAL SETTING

The logistics industry has developed as a highly complex and competitivesector, which has evolved from what was once described as ‘distribution’.It is now characterized by large scale businesses applying high levels oftechnological expertise to the management of several steps in the valuechain in order to provide specialized logistics services to clients. This oftenincludes the management of many aspects of those clients’ businesses whichthey used to manage themselves. Logistics companies have taken advantageof the trend in corporate strategy to outsource peripheral activities and focuson core business. The key to success is the employment of sophisticatedtracking systems which aid the efficient management and delivery of goods(Batchelor & Terry, 1997).

The growth seen in the industry and in the business of the organizationstudied has been considerable over the last few years. The organizationselected is a major European group in the logistics sector. It is quoted on

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the UK Stock Exchange and was ranked amongst the top ten Europeanlogistics operators in the Financial Times Logistics survey (Batchelor &Terry, 1997).

The pace of change in work practices needed to support this organization’sgrowth has led the new Group Chief Executive to encourage innovationand flexibility to be embedded in the corporate culture. There is also a highlevel of expectation in terms of rewards for all stakeholders. The executiveteams of one UK division and one continental Europe division were the firstmanagers to participate in this study. As far as possible, a natural work-basedsetting was used to gather the data. This is important in research of thistype (Lincoln & Guba, 1986).

The participants’ job titles are given in Appendix 2. They are membersof the divisional boards, including managing directors, finance directors,operations and business development managers, project managers anddirectors of marketing and of human resource management. Theycollectively have many years of experience in the industry, but have amongstthem a number of bright up-and-coming executives, including at least onewho has moved up to the main group board since the research for thisproject began.

The procedures for the appraisal of major capital projects were set outin a paper which divisional finance directors had received from group headoffice (dated 1995). The paper included explanations and examples of theuse of established techniques, including IRR and scenario modelling. It alsoshowed how the company’s hurdle rate had been computed, using CAPMas the basis for the cost of equity employed. There was only one financialmanager participating in the focus group discussions at any time, butthe other managers demonstrated a reasonable understanding of financialappraisal through their contributions to the discussion.

The units of research were projects requiring a proposal for grouplevel funding. The type of projects being appraised initially were mainlybusiness development projects with some infrastructure investments. Nocompany acquisitions were included in the data analysed for this paper. Thecharacteristics of the type of projects included in the study are set out in theproject typology section of the key observations. Most projects appraisedwere business development projects where the decision was whether toproceed to contract with a client to provide logistics services for them ornot. Decisions were usually extremely time sensitive, as the client couldeasily choose to contract with an alternative provider, and appraisals rarelyinvolved choosing between two or more options.

THEORETICAL PERSPECTIVE

Corporate Finance theory assumes rational behaviour on the part ofinvestors in the stock market which has historically been extended tothe assumption that internal resource allocation decisions should follow


the same pattern of economic rationality (Northcott, 1995 p. 125). Thissuggests that the result of DCF analysis should drive the investment decisionin order to grow shareholder wealth.

Risk analysis, as generally advocated (Hull, 1980) is based on possibleproject outcomes and their estimated probabilities. Such analysis, includingsimulations (as developed by Hertz, 1964), depends on much preliminaryactivity to research and develop base case assumptions. Therefore it wouldusually take place as part of the DCF analysis.

However, empirical research has shown that identifying where the realdecision is made in organizations raises just one reason to challenge thistheoretical view of investment decision-making (Bower, 1988). The problemis that decisions may be being made early on in the appraisal process, beforethe DCF analysis has been completed.

Figure 1 shows a diagrammatic representation of the SIA process. Animportant practical feature is the system of feedback loops, indicating that itis an iterative process, not always recognized by other authors (for example,King, 1975). However, feedback loops are a vital part of the process ifinvestment appraisal is viewed as part of management control (Emmanuel& Otley, 1990).

Managers in Morone & Paulson’s study (1991) acknowledged the rolethat non-financial considerations played in their decisions, and highlightedthe role ‘executive judgement’ plays in the process (especially at step 5 inFigure 1).

The difficulty in terms of the literature is the location of a theorywhich helps the researcher to explore executive judgement in capitalinvestment decision-making practice. Control theory may be used as apoint of departure (see for example, Slagmulder, 1997). There is a view thatmanagers repeatedly override systems and controls to achieve ‘the answerthey want’ in a given case by operationalizing their cognitive analysis of theproject in an entirely unsophisticated and unsystematic way (Northcott,1995, p. 132).

Wilson & Zhang (1997) summarized the behavioural theories ofentrapment relevant to investment decision-making. Much of the referencedwork took place in a laboratory setting rather than in the field, butit emphasized the tendency for people to take early positions on theattractiveness or otherwise of a project, based on human informationprocessing, influenced by personal preferences. These studies demonstratedhow people then built up their psychological commitment to a project. A fieldbased study by Zanibbi & Pike (1996) focused on the impact that manageriallevel and educational background had in managerial consensus in investmentdecision-making. Consensus was found to occur more easily lower down inorganizational structures, for example at divisional level, which is relevantin the group based approach to risk assessment developed here.

These behavioural studies drew upon theories developed in psychology.The field of cognitive psychology also provided the key theory for this study,

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Figure 1. Strategic investment appraisal process


which was used as a basis for discovering how managers construe projectrisk, Kelly’s personal construct theory (Kelly, 1955). In essence, personalconstruct theory (PCT) is concerned with how people make sense of theworld and the experiences they encounter.

Kelly’s fundamental postulate was that ‘a person’s processes arepsychologically channelized by the ways in which he anticipates events’(Kelly, 1955, p. 103–104). This is supported by 11 corollaries based onobservations made in the field (clinical psychology cases) over a longperiod. He found that people make sense of what they encounter bymaking comparisons with what they already know, noting similarities anddifferences. Kelly identified a bipolar axis which acted as a reference pointfor cognition.

To illustrate this, a person may experience a sunny day, and construe itin terms of brightness (on a scale of bright to dark) and warmth (on a scaleof hot to cold). What one person construes as hot and bright, may differfrom how another person construes the day. It may depend on what theyhave previously experienced, such that someone living in the tropics mightconstrue the brightness and warmth of the day differently from someonewho has never left Norway. Past experience of events thus limits how wemay construe the present and anticipate the future (range corollary).

Personal construct theory is based on the belief that each person has aunique set or portfolio of constructs, which Kelly called the individualitycorollary. However, two or more people may construe something in a similarway, especially if they have shared experiences, which make their thoughtprocesses psychologically similar (commonality corollary). This is relevant togroup behaviour in organizational decision-making, as is the sociality corollary,where one person construes the construction processes of another. Socialityis not the same as sharing the same construction (commonality), it is merelyunderstanding how someone else is thinking, without necessarily agreeing.

In order to bring the individual’s subconscious construction of theworld into the conscious mind such that personal constructs can bediscovered, Kelly developed a repertory grid technique, which has beenfurther developed as a research technique with many applications beyondclinical psychology, for example in Business Strategy (Ginsberg, 1989) andOrganizational Behaviour (Hunter & Coggin, 1988).

This study is breaking new ground by applying it to managerialperceptions of project risk, and developing it from a research tool usedby academics to a constructive assessment tool used by managers.

RESEARCH DESIGN

General methodThe aim of this study was to explore the use of a new approach to assessingrisk which practitioners would welcome as an additional investment

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appraisal tool. It was anticipated that managers may welcome an assessmenttool drawn from their own construction of the problem, which enabledthem to formalize their thinking, so developing and operationalizing theirown metrics. Important influences on the choice of method were thedevelopmental nature of the study, and the need to draw on managers’cognition in a group decision process.

The approach taken was primarily an action research methodology, firstsuggested by Lewin (1963), and further developed by Argyris and Schon(1978). The action research method chosen has some of the characteristicsof exploratory and experimental case studies (Scapens, 1990), but is moredevelopmental. Easterby-Smith et al. (1991, p. 81) identify change as a keyobjective of action research, and suggest ‘the researcher’s role can be viewedas a cross between an ‘‘importer’’ of new knowledge to organizationalmembers and a medium through which individuals can express the way theyview the organization or change’.

Within this approach a general method of eliciting views is by facilitatinga group discussion on the topic of interest, often termed a focus group.Features of this method include stimulated recall, where the facilitator asksthe group to recall an event or experience, and playback, where the facilitatorfeeds back data recorded to verify it.

The work that guided the use of focus groups, in this case for datacollection, is that of Morgan (1997) a social scientist whose research hascentred around social issues such as retirement, widowhood and risk factorsfor heart attack cases. He provides a guide to conducting focus groups asqualitative research, without the emphasis on marketing applications whichmany other authors give.

The principles of personal construct theory (Kelly, 1955) have beenapplied in group interviewing using repertory grids, particularly in strategydevelopment (Eden & Jones, 1984), where the technique has becomeknown as cognitive mapping. However, a common misinterpretation of therepertory grid technique, is that it is only applicable with individuals andnot groups (Grundy & Johnson, 1993, p. 256), which might explain whythis approach has apparently not been used in the study of managerial riskperceptions before.

To summarize, an action research method, operationalized by usingfocus groups and repertory grid techniques (RGT) was chosen to meetthe aims of both the research and the collaborating organization. Thissuited the researcher’s preference for a ‘middle ground’ approach in termsof ontological and epistemological dimensions (Laughlin, 1995) and thedevelopmental aims agreed with the organization.

Data collection

At a series of focus group meetings, the RGT was used to elicit the groupconstructs on the risk profile of projects (elements), guided by the work of


Fransella & Bannister (1977). This technique was chosen for data collectionfor three reasons. Firstly, as being drawn from personal construct theory,and the same behavioural area of cognitive psychology as the work onprospect theory by Kahneman & Tversky (1979).

Secondly, as a technique which although categorized as a qualitativetechnique utilizes measures which turn the data into quantitative data,making it possible to link the project risk analysis to the financial analysis.This does, of course, introduce the limitations of using a ‘Likert’ type scale.Also, for the executive teams to be able to continue using the technique ontheir own, the RGT was expected to be relatively user-friendly (with someguidance).

The grid dimensions are shown in Figure 2, with ‘risk attributes’ asthe ‘social constructs’ by which managers understand the ‘elements’ anddistinguish between the risk levels of ‘projects’. The research used stimulatedrecall by asking participants to reflect upon three recent investmentdecisions. The use of three elements or ‘triads’ is a feature of RGT designedto aid the construction of bipolar terms, by comparing two of the threeelements with the third.

This comparison, where two elements are perceived to be similar in somerespects but different from the third, could easily be applied to projectsof a uniform type which participants were familiar with. Familiarity withthe characteristics of projects is essential for the elements to be within theparticipants’ repertoire and therefore within their ability to construe (Kelly,1955).

The elements were selected with the aid of the Finance Director as a setof projects with differing levels of risk (low, medium and high), which werelikely to be recognized by the group as such. It was possible to use the triadmethod of RGT to elicit most constructs, which were then ‘measured’ usinga five-point scale and entered on the grid. No blank cells were allowed,such that all projects were assessed on all attributes. The ‘scores’ for thethree recent projects were obtained from the group discussion, arrived at byconsensus.

The group discussions, which took place in a natural board room setting,were tape-recorded for the researcher to play back when interpreting thegrids. The group’s risk assessment of further recent projects was used toscore the same ‘attributes’. From this data, the definitions of the constructswere refined, and they were grouped into ‘constellatory constructs’ or setsof related attributes. Figure 2 shows four of the 12 constructs to illustratethe method.

It was important, for scores in the grid to be arrived at for the group ratherthan individuals to encourage full discussion in a consensus seeking process.Arguments and counter-arguments were exchanged until agreement wasreached, in a way that the executive would operate in a normal businessmeeting. The score agreed was not expected to match a mean which couldhave been calculated from individuals’ ‘first impression’ scores, due to the

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Figure 2. Group repertory grid

exchange of information. Awareness of the dangers of ‘groupthink’ (Janis,1982) helped to inform the facilitation of group discussions.

Data analysis

Having teased out the risk attributes and enabled participants to assess themretrospectively for a range of high and low risk projects, the next step was togain an overall risk measurement for each project. Since the risk attributeswere of unequal importance, participants were asked to rank the attributesso that weightings could be assigned to them.

Participants were asked to identify the most important attribute andassign it a weight of 100. Then all other attributes were assigned a numberbetween 1 and 100 which reflected the importance of the attribute relativeto the most important. Once consensus had been reached, these weightswere summed and converted to percentages, which were applied to the rawscores, to compute a weighted risk score for each project.


Continuing field experiment

Participants were asked to continue testing their group risk assessmentgrids for further projects, as part of an experiment. The experiment wasconducted initially over a period of a year, for more than 12 live projects.The participants were asked if the weighted scores using the five-pointscale were satisfactory for the first three projects, before going on to assessprojects 4 to 12 and beyond in a similar manner.

The project risk attributes from the first team were presented to the secondteam in continental Europe, to stimulate discussions in order to validate thedefinitions of the risk attributes. Team two then discussed and agreed type1 and 2 weightings, and arrived at type 3 weightings. Live projects weresubsequently assessed in team 2 as part of the field experiment.

Validation

The data collected was largely captured, recorded, analysed and interpretedsimultaneously for live projects. However, the original ‘test cases’ used toformulate the grid were discussed at length during a series of tape-recordedfocus group meetings. The tapes were then used by the researcher to adddescription to the assessment results in an executive style report, which wasdistributed to group members shortly after each meeting.

Participants were invited to comment on these reports individually andat the next group meeting to ensure that the record made by the researcherwas recognized as an accurate account of the group’s discussion. Wherethere was any ambiguity, the matter was reviewed at a later meeting, andthereby clarified in the subsequent report.

Having developed the grid framework with one management teaminitially, it was desirable to test its validity across the whole group. Thiswas phased such that the second team tested the application of the grid, byfollowing the same process.

The selection of the second team was partly based on the premise that ifthe framework worked when tested with a culturally different managementteam in a continental Europe location, then it was likely to be applicable tomost other management teams in the group. The other reason for selectionof team 2, was that they met the desired criteria in terms of sufficientexperience of project appraisal and the availability of both recent and liveexamples to use as cases for testing the grid framework.

Once the framework was found to work satisfactorily with team 2,such that resulting project scores reflected the level of risk perceivedby participants, it was presented to all managers across Europe at thegroup’s corporate conference. Following this presentation, and subsequentfeedback, the process has been followed in the remaining divisional teams.

It was necessary to explain the framework to the group board and gaintheir commitment to using it group-wide before the corporate conference.This was achieved by a presentation and by individual interviews with the

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Chief Executive and the Finance Director. This also served to add validityto the construction of the risk assessment technique, and to formulate animplementation plan, whereby the risk score and relevant supporting textwere called for by the group board in future SIAs.

A degree of external validation was possible in the field study, by observingthe reaction of new management team members who joined the organizationduring the study. For example, by monitoring their contributions to theproject discussions and questions on the risk assessment process. Externalvalidation of the risk attributes was undertaken by comparing them with theresults of other studies which explored managers’ perceptions of project risk(for example Grundy & Johnson, 1993; Chapman & Ward, 1997).

KEY OBSERVATIONS

The results are reported and discussed under five subheadings which reflectthe chronological findings of the exploratory and explanatory phases ofthe study:

ž Project risk attributesž Project typologyž Weightings and risk assessmentž Timing of risk assessmentž Use of group repertory grids in SIA

Project risk attributes

Initially many possible constructs were generated, which were graduallyrevised, aggregated and disaggregated as projects were compared andmeasured on a five-point scale. The result was 12 constructs by whichthe riskiness of projects was perceived by participants. After the participantsreached a common understanding, these were defined, and are listed (withbipolar terms in brackets) in Appendix 1.

Many attributes were construed as being linked in some way, butthe strongest links were found to lie in four groups or ‘constellations’,relating to the corporate factors, the project opportunity, the external ormarket-based factors, and the competitive position of contracting parties.The constellations or clusters emerged from the second meeting (seeAppendix 2).

The first group of attributes, corporate factors, were not industry specific,so may be transferable to other organizational settings. These tie in closelyto the literature on investment appraisal, in terms of the importance of‘strategic fit’ (Butler et al., 1993; Grundy & Johnson, 1993; Lefley, 1997;Marsh et al., 1988; Morone & Paulson, 1991). This factor is also seen aspart of the risk profile of projects in project management literature, as is


TABLE 1

Risk drivers and risk attributes

Chapman & Ward’s projectrisk drivers (Chapman,1997, p. 122)

Project risk attributesidentified in this study (seeAppendix 1)

Comments on commonelements

1. Definition of project 1. Strategic fit & 3 Image Strategic definition2. Concept and design 5. Complexity Technical design risk3. Financing arrangements 8. Quality of information DCF assumptions4. Logistics 6. Planning timescale Critical path analysis5. Local conditions 2. Expertise Capability of local team6. Resource estimates 4. Size Scale of investment7. Industrial relations 10. Environmental factors eg. TUPE, working

week etc.8. Communications 7. Cultural fit & 9 Demands Customer relations9. Project organization 12. Contract terms Statement of responsibilities

local expertise, particularly in Chapman and Ward’s (1997, p. 122) analysisof ‘risk drivers’. A comparative analysis of Chapman & Ward’s risk driversand the project risk attributes found in this study is summarized in Table 1.

The project opportunity attributes, size, complexity and planningtimescale, fit extremely well with Chapman & Ward’s resources, conceptand design and logistics factors, and again could be viewed as quite generic,and therefore transferable. The external and market based attributes maybe viewed as more context specific, though communications may be a goodgeneric equivalent to the cultural fit and demands of customers attributesfound here.

The negotiating strength and contract terms attributes are perhaps evenmore specific to the logistics industry, but could be linked to Chapman& Ward’s project organization. From the definition of the constructs(Appendix 1), it is clear that these managers do not construe risk inthe same way as academics in corporate finance, in that it is not expressedas a possible outcome with an estimable probability (Hull, 1980; Levy &Sarnat, 1994; Lumby, 1994). Rather it corresponds more to uncertaintyand the possible sources or drivers of risk.

It is arguably more useful to analyse potential sources of risk, at an earlierstage in the project appraisal process, such that action may be taken to avoidor reduce the risk, or even abandon the project idea before conducting a fullfinancial analysis, and before psychological commitment has been made bythe managers involved. As Jackson & Carter (1992, p. 44–45) argue, causeneeds to be understood, as action at the effect level is limited.

Project typology

During the early discussions on possible weightings to be assigned torisk attributes, it became apparent that one set of weightings may not be

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appropriate for all projects. This was debated at length, with the resultthat two types of project were identified, with quite different characteristics.When the second team reached this stage, they found that typical projectsin continental Europe were a cross between the two, which resulted in athird type being identified.

It is now clear that further types are likely to emerge when the riskassessment technique is implemented across the remaining divisionalmanagement teams. Project typology is important, as different risk attributesand analysis techniques may be appropriate for different types of project. Forexample, advanced manufacturing technology projects, which have quitedifferent characteristics and SIA issues (Abdel-Kader & Dugdale, 1998).The project types found in this study are defined as:

1. ‘External client’ This type of project was usually specific to one customer.It would either represent additional business that is, a new contract withan existing customer, or it would involve a new customer. Often therewould be specialized equipment needed and investment in vehicles, whichmay ultimately belong to the company or a third party (but seldom thecustomer). The business would usually be covered by a relatively short-term (in capital budgeting terms) contract which would specify pricingarrangements and indicate likely volumes and destinations. Negotiatingthe precise terms of such contracts involves a considerable amount ofmanagement time.

2. ‘Infrastructure’ This type of project could share some common featureswith the first type, in terms of client contracts and the nature of fixed assetsrequired. However, it was more likely to involve several or all customersand would normally involve new or enhanced facilities in terms of buildingsand equipment, especially investment in computer systems. There may bean element of speculation involved in establishing new facilities without aspecific user in mind. Negotiations with suppliers and contracts for servicesor maintenance would be common to this type of project. Location andenvironmental considerations would often be important. The timescaleinvolved could well be longer-term, without necessarily having a finiteproject life. In such cases an ‘artificial’ or hypothetical cut-off point mightbe used in the discounted cash flow calculations.

3. ‘Shared user’ This type of project is a cross between types 1 and 2.It would usually involve the design, building and operation of specialistwarehouse and distribution facilities, with a multi-user objective. Suchfacilities would often be developed with one lead client, with the prospectof attracting further clients later, to fully utilize the capacity. Investmentrequired in this type of project would be high to provide the substantialcapacity needed to deal with the high throughputs of several largeEuropean customers in an efficient operation. Such projects might require


a development phase of up to 3 years before the facilities would be fullyoperational.

Weightings and risk assessment

Table 2 shows the weighting of project risk attributes agreed for projects oftypes 1 and 2. The significant difference is that complexity is deemed to bemore important in external client projects, and environmental factors aredeemed to be more important in infrastructure projects. It can be seen thatfor both project types only seven of the 12 factors are really contributingsignificantly to the overall weighted score.

However, the remaining five factors were deemed to be important enoughto leave them in the grid and force their discussion and evaluation to takeplace. Since blank cells were not allowed, every attribute required a score,but if the consensus for a project was that it was not risky at all on aparticular attribute it could be scored 1. Together with a low weighting, thiswould result in little impact on the overall score, but with the assurance thatthis aspect of the project profile had been considered.

It is suggested that the emerging framework has parallels in terms of theconcepts being applied with SIA techniques used in the not-for-profit sector.

TABLE 2

Weighting of risk attributes

WEIGHTINGS

TYPE 1 TYPE 2EXTERNAL CLIENT INFRASTRUCTURE

RISK ATTRIBUTES weight % weight %

CORPORATE FACTORS:Strategic fit 20 3 10 1Expertise 100 14 80 12Image 20 3 20 3PROJECT OPPORTUNITY:Size 85 12 70 11Complexity 90 13 20 3Planning timescale 20 3 20 3EXTERNAL/MARKET FACTORS:Cultural fit of parties 45 6 10 2Quality of information 85 12 80 12Demands of customer(s) 70 10 80 12Environmental (PEST) 30 4 100 15COMPETITIVE POSITION:Negotiating strength 70 9 80 12Proposed contract terms 80 11 90 14TOTAL 715 100 660 100

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The concept behind cost benefit analysis (CBA) is that projects withoutmarketed outputs, that is, no associated sales revenue, often have manynon-financial benefits to be evaluated. Any minor income or cost savingsare usually netted off against project costs, leaving a non-financial value tobe placed upon the remaining benefits. This technique was developed innot-for-profit organizations, for example, government departments, whichhad finite cash resources and numerous potential projects competing forthose resources.

It gives a framework for quantifying ‘stakeholders’ perceptions of thebenefits they would anticipate to flow from a particular project. Multi-attribute utility theory (MAUT) was developed in the Social Servicessector in the United States to aid CBA. It is a mathematical modelused to measure the preference for an alternative expressed by a numberof people, representing those who may be expected to benefit from theproject. The key elements of the model are the measurement of preferencesin utils against a number of attributes of unequal importance, for eachalternative which may be chosen. The additive MAUT model is illustratedby Huber (1980).

Whilst used for managerial decisions involving non-marketed outputs,MAUT is usually applied where the costs are financial and the benefitsnon-financial. In many strategic investment decisions in business, it is thebenefits that are expressed in financial terms, as net cash inflows, and therisks which may be expressed in non-financial terms. In this study theconcept of weighting essentially non-financial factors was applied to the riskattributes of a project, in a similar way.

Other SIA models have used a scheme of weightings, for example Wissema(1985) for assessing non-financial factors such as strategic and societalaspects. Though overall, Wissema’s model seemed to prove too complexfor practitioners to adopt. Others include Lefley (1997), Gup & Norwood(1982), and Morgan & Pugh (1997).

Table 3 shows the assessment of a type 1 project by team 1 in the UKindustrial division. It shows that whilst the project was fairly low risk overall,its size (relative to the existing business of the division), complexity andproposed contract terms, followed by the quality of information available,are the factors which contribute the most (each over 10%) to the ultimateweighted risk score. The implication here is that should the project go ahead,these four key factors deserve more management attention to implementthe project successfully.

On reflection, the use of a 1 to 100 scheme of weighting caused someunnecessary problems, with the first team to apply it, and for the secondteam to agree it. An alternative scheme of weighting was eventually tested inthe second team, using three levels of importance (equating to weightingsof 30, 60 or 90). This scheme has not yet been formally adopted but it islikely to feature in the ultimate user guide after further consultation.


TABLE 3

Project risk assessment grid

GROUP RESULT TYPE 1 EXAMPLE

RAW WEIGHT WEIGHTEDSCORE SCORE

RISK ATTRIBUTES score x % w wx

CORPORATE FACTORSStrategic fit 1 3 3Expertise 1 14 14Image 1 3 3PROJECT OPPORTUNITYSize 3 12 36Complexity 2 13 26Planning timescale 3 3 9EXTERNAL/MARKET FACTORSCultural fit of parties 1 6 6Quality of information 2 12 24Demands of customer(s) 2 10 20Envoronmental (PEST) 3 4 12COMPETITIVE POSITIONNegotiating strength 2 9 18Proposed contract terms 3 11 33TOTAL wx/100 24 100 2Ð04

Timing of risk assessment

The timing of the project risk assessment was thought to be a key issue, asthe extent and understanding of relevant information which the managershave, as the basis for such assessment, changes over the project planningand initial implementation stages. The grid was designed to be used at thedecision point, with the information or base assumptions reflected in thecash flow forecast in the project proposal paper (stage 2 below). However,the managers felt they could benefit from using the grid much earlier, withrough forecasts, to avoid spending time on potentially high risk projectproposals which they would not get funded. It was also suggested that therisk could be reassessed with hindsight at the post-audit stage, as part of thelearning process.

The grid is therefore being used at three stages in a project’s life:

1. Project definition or initial screening stage (Figure 1, stage 3)2. Decision point for the project proposal to go to the group board (Figure 1,

stage 5)3. Post-audit stage, 6 to 12 months after the project start date (Figure 1,

stage 7)

364 ELAINE HARRIS

For some projects with long lead times, they may be assessed at each ofthe three stages, to collect data on how the project risk assessment changesover time. Further research work aims to focus attention on this timingissue. At present most data has been collected at or around the decisionpoint. A few projects have been through an early screening assessment usingthis technique, before the divisional board decides whether to proceed to afull project proposal.

Risk assessment at the post-audit stage is now incorporated into thelearning process in an established post-audit procedure. Previously, actualcash flows were compared with estimated returns and reasons for variancesdiscussed. Now, any changes in the risk profile of the project are alsodiscussed. This usually involves the divisional MD, FD and project manager,as a subset of the decision-making team.

Changes in the risk score over time which might impact on the outcomeof the decision or on project management will be analysed in more detaillater in the study. The decision on a project where an early assessment isclassified as too risky (say between 3Ð5 and 4Ð5), could result in delayinguntil the uncertainty is reduced. Type 2 (infrastructure) projects could bemore easily delayed, as they were generally more controllable.

There may be a real or opportunity cost involved in delaying the decision,which is mirrored by the price variation in an option to buy shares in optionpricing theory (Busby & Pitts, 1998). From the discussions with participantson this issue, they felt that opportunities to delay projects of types 1 or 3were so limited in their competitive marketplace, that any benefits would beoutweighed by the increased risk of losing the contract to their competitors.Type 2 (infrastructure) projects occurred less frequently. Further analysisusing option pricing theory may be applied to a future type 2 projects laterin this study.

Use of group repertory grids in SIA

Results from the first four projects assessed in the UK ranged from weightedscores of 1Ð45 to 4Ð34. The highest risk project assessed at 4Ð34 had not goneahead, whereas the other three had (all assessed at under 3). In continentalEurope the first three projects assessed ranged from 2Ð97 to 3Ð81, and hadall gone ahead, with the highest risk project presenting management withthe most problems in terms of implementation.

The team 2 managers were quite concerned that their projects maybe more inherently risky than those experienced in the UK. One of thestrategies which the group board could adopt to reflect this would be risk-adjusted hurdle rates, though not recommended (Reimann 1990). This riskassessment technique avoids the need for divisions to be given differentialhurdle rates, thus keeping the managers on a level playing field within theorganization.


A user guide was developed to enable the managers in the divisions tocontinue to experiment with their grids without the researcher present,and test ways of relating the risk score obtained to the required return forprojects. A decision matrix has subsequently been developed and testedwhich assists management in the interpretation of risk scores and theformulation of suitable management responses.

Over the implementation phase the researcher has been working with alldivisional management teams and with the group board on the developmentof the user guide. The draft version has undergone several revisions to takeaccount of the broader range of views expressed. The organization hasproved to have a remarkably coherent construction of risk across nationalboundaries, such that the ‘final product’ of a definitive user guide may havebeen similar if research had begun in any of its divisional teams.

One important aspect of the group repertory grid technique, is thecohesiveness of the team, which may not be found so easily if natural teamshad not been used, as in the case of Grundy & Johnson, whose teams werein a structured learning situation rather than their natural organizationalsettings. For Kelly’s corollories to apply in a group situation, a commonrange of relevant experiences is required, in order to elicit group constructs.

Also, it is helpful if management teams are experienced or have receivedguidance on a consensus-seeking process, as in this study, such thatconstructs and risk scores are agreed by the team, and are not dominated byone person’s views. Team behaviour is important, as the process by whicheach project is dicussed is designed as an information sharing exercise, withclear rationales required to support the suggested risk scores. The role of thefacilitator in managing this process, was guided by Hall’s (1971), principlesof consensus building.

CONCLUDING REMARKS

The results demonstrate how an action research approach to the studyof strategic investment appraisal can provide insights into how managersperceive the riskiness of projects. Furthermore, repertory grid techniquesdesigned for research in behavioural science can not only be applied tomanagement research, but also be utilized by organizations as part of theirown strategic analysis techniques.

The risk constructs elicited using repertory grids in this study bearquite close resemblance to risk drivers identified by Chapman & Ward(1997), but also contain some context specific constructs. In an alternativeorganizational setting, one might expect to find some similar genericconstructs and some different contextual ones.

Some constructs may be specific to the type of project, whilst othersmay just be differently weighted according to project type. This type ofrisk assessment may lend itself more to some project types than others.

366 ELAINE HARRIS

The transferability of the framework to other organizational settings maybe better in business services industries, where business is conducted in asimilar way to logistics, than in manufacturing or retailing.

The participants involved in the research have welcomed the addition ofa project risk assessment process to their investment appraisal procedures.This study has resulted in the project risk assessment grids being usedcompany wide. Following presentation at the Company Conference in1997, the perceived benefits recognized by the organization include:

ž Extra confidence in decisions madež Minimizing time spent on planning ‘reject’ proposalsž Identification of key factors for control of projectsž Extra efficiency of resource allocationž Shared understanding of managers’ views on projects proposed/undertakenž Capturing and sharpening of managerial judgement exercised in decision-

making

The importance of ownership and understanding of SIA techniques by themanagers involved in project definition, evaluation and implementation forSIA to be a meaningful and successful activity makes this type of cognitiveframework potentially invaluable.

With today’s dynamic business environment, executives need cost-effective and user-friendly analysis techniques that they can apply easily, butnot mechanically, which are embedded in their everyday thought processes.It is suggested that repertory grids offer this possibility, and that theorganizational learning and development which may result surpasses thelikely benefits of applying much available normative theory.

Further work is being done to link the results of this project risk assessmenttool to the financial analysis undertaken in investment appraisal, to aiddecision-making at both divisional and board levels in this organization. Toextend the research beyond this study, more evidence may be sought tosupport this approach to risk assessment within logistics, with further projecttypes, and to test the framework in alternative organizational settings.

In organizations with an established framework for taking into accounta qualitative analysis of risk and uncertainty in decision-making, taking agrounded theory approach (Glaser & Strauss, 1967) to studying this aspectof SIDs may provide interesting insights. As with repertory grid techniques,grounded theory is still quite rare in management accounting research, butis emerging (for example, Slagmulder, 1997).

Team dynamics may be analysed in detail in a later paper on the roleof consensus in group decision processes of this type. Further researchmight be undertaken to examine whether and how new group processessuch as this change the political behaviour which surrounds SIAs in manyorganizations.


ACKNOWLEDGEMENTS

The author wishes to thank Clive Emmanuel, Robin Jarvis, Mike Page andthe two anonymous referees for their valuable comments on earlier versionsof this paper.

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APPENDIX 1: DEFINITIONS OF PROJECT RISK ATTRIBUTES

Strategic fit: the potential contribution to corporate strategy as stated inpublished documents (e.g. mission statement) and in business plans (e.g.market segment penetration) of the project (1Dgood fit, 5Dpoor fit).

Expertise: the level of knowledge and skill needed for the project to succeedwhich exists in the company. (1Drelevant strength, 5Drelevant weakness).

Image: the potential damage to the company’s reputation or brand imagewhich may derive from the project and related publicity, for example, publicsensitivity to product being carried (1Dinsensitive, 5Dsensitive).

Size: the scale of the project relative to existing business, indicated by capitalexpenditure required, length of contract, and annual revenue predicted(1Dsmall, 5Dlarge).

Complexity: the number of and association between variables or assumptionsinherent in a project, which complicates the company’s ability to predict theoutcome (1Dsimple, 5Dcomplex).

370 ELAINE HARRIS

Planning timescale: the time available to research and develop a projectproposal before a decision must be made and a contract signed to meet therequired deadline for the project to proceed (1Dlong, 5Dshort).

Cultural fit (of parties): the potential match or mismatch in the corporatevalues beliefs and practices of the contracting parties involved in the project(1Dgood fit, 5Dpoor fit).

Quality of information: the reliability, validity and sufficiency of base data andother relevant information available to form the basis for project assumptionsand appraisal (1Dgood, 5Dpoor).

Demands of customer(s): the challenge posed by customer requirements, bybusiness specification, for example, non-standard containers, or level andnature of customer contact for example, frequent communication expectedwith staff having no or low knowledge of logistics (1Dbarely demanding,5Dhighly demanding).

Environmental (PEST factors): the likely impact of Political, Economic,Social and Technological factors on the project, for example, TUPE(1Dlow impact, 5Dhigh impact).

Negotiating strength: the power position of the company relative to theother contracting party(s), for example, due to relative size, reputation, orcompetitive advantage (1Dstrong, 5Dweak).

Proposed contract terms: the evaluation of the likely contract terms, andpotential to pass risk(s) to other contracting party(s) (1D favourable,5Dunfavourable).

APPENDIX 2: FOCUS GROUP MEETINGS AND PARTICIPANTS

Team 1 meetings, UK division

1. Risk constructs elicitation and initial raw scores for three projects.2. Definition of Risk Attributes, Clustering etc.3. Project typology and weightings of risk attributes, plus test on 4th project.4. Timing of risk assessment and relating risk scores to project returns (way

forward), plus test on 5th project.

Team 1 participants

Managing DirectorFinance DirectorOperations Director


Personnel DirectorDirector of Business Development (UK)Director of Business Development (Europe)Network Operations ManagerNetwork Fleet Manager

Team 2 meetings, continental Europe division

1. Presentation of UK research to continental Europe Steering Group anddiscussion of applicability of findings (risk attributes and weightings) toEuropean divisions. (equivalent of UK agendas 2 and part of 1 and 4).

2. Project type 3, weightings and comparison of three test projects(equivalent of UK agenda 3 and part of 1 and 4).

Continental Europe team participants

Chief ExecutiveŁŁ : Group HO, UKManaging Director : FranceManaging Director : GermanyManaging Director : Continental EuropeManaging Director : BeneluxLogistics Manager : Continental EuropeOperations Manager : Continental EuropeBusiness Development Manager : Continental EuropeFinance Manager : Continental EuropeŁŁattended meeting 1 only

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PROJECT RISK ASSESSMENT: A EUROPEAN FIELD STUDY

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