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International Journal of Forecasting 19 (2003) 525www.elsevier.com/ locate / ijforecast

C onducting a sales forecasting audit

*Mark A. Moon , John T. Mentzer, Carlo D. SmithDepartment of Marketing, Logistics and Transportation, 301 Stokely Management Center, The University of Tennessee,

Knoxville, TN 37996-0530, USA

Abstract

Continuous improvement in sales forecasting is a worthy goal for any organization. This paper describes a methodology for conducting asales forecasting audit, the goal of which is to help a company understand the status of its sales forecasting processes and identify ways toimprove those processes. The methodology described here has been developed over a 5-year period, involving multiple auditors, and hasbeen implemented (to date) at 16 organizations. This methodology revolves around three distinct phases: the as-is phase, in which the auditteam seeks to understand fully a companys current forecasting process; the should-be phase, in which the audit team presents a vision ofwhat world-class forecasting should look like at the audited company, and the way-forward phase, in which the audit team presents aroadmap of how the company can change its forecasting processes to achieve world-class levels. Those companies that have respondedpositively to the audit process have experienced significant improvement in their forecasting performance. The paper concludes bypresenting lessons from audits conducted to date, as well as implications for management practice and future research. 2002 International Institute of Forecasters. Published by Elsevier Science B.V. All rights reserved.

Keywords: Forecasting practice; Audit; Forecasting management; Performance measurement; Forecasting systems; Supply chain

1 . Introduction reduce inventory investment, eliminate product ob-solescence, improve distribution operations, schedule

Forecasting has been consistently recognized as an more efficient production, and anticipate futureimportant capability for business planning and man- financial and capital requirements (Galfond,agement (Armstrong, 1987; Cox, 1987, 1989; Fildes Ronayne, & Winkler, 1996; McIntyre, Archabal, && Hastings, 1994; Makridakis & Wheelwright, 1977; Miller, 1993).Mentzer & Gomes, 1994; Sanders & Manrodt, 1994; To improve forecasting, companies increasinglyWright, 1988). Regardless of industry, or whether the take advantage of computer and information systemcompany is a manufacturer, wholesaler, retailer, or technologies. Point of sale (POS) data collection isservice provider, effective demand forecasting helps gathering near-real-time sales movement at a stockorganizations identify market opportunities, enhance keeping unit by location (SKUL) level of detailchannel relationships, increase customer satisfaction, (Smart, 1995). Electronic data interchange (EDI) is

used to transmit detailed sales information through-out various marketing channels to product dis-

*Corresponding author. Tel.: 11-865-974-8062; fax: 11-865-tributors and manufacturers (Mentzer & Kahn,974-1932.

E-mail address: [email protected] (M.A. Moon). 1997). Forecasting systems that were once housed on

0169-2070/02/$ see front matter 2002 International Institute of Forecasters. Published by Elsevier Science B.V. All rights reserved.PI I : S0169-2070( 02 )00032-8

6 M.A. Moon et al. / International Journal of Forecasting 19 (2003) 525

large central mainframes are now capable of running Pharmavite, Smith and Nephew, Union Pacific Rail-on desktop computers and in client server environ- road, and WilliamsonDickie.)ments (Mentzer & Kahn, 1997; Mentzer & Schroe- Section 2 of this paper discusses the relevantter, 1993, 1994; Mentzer & Kent, 1999). Legacy research in forecasting management. In Section 3, asystems, which have historically been limited to a standard against which companies can compare theirsingle forecasting technique for all products and forecasting management practices is discussed. Thisservices, are being replaced by systems which select standard provides the basis of the sales forecastingfrom a series of alternative forecasting techniques or audit process, which is then discussed in detail.employ a combination of techniques to analyze Sections 4 and 5 discuss research and managerialdemand and related information in an effort to implications of this forecasting management re-improve forecasting accuracy (Mentzer & Kahn, search.1997; Mentzer & Schroeter, 1993, 1994; Mentzer &Kent, 1999; Wright, 1988).

Yet, despite these advances, forecasting sophistica- 2 . Forecasting management researchtion and performance have improved little at eventhe more successful companies (Mentzer & Kahn, In a 1977 review of forecasting literature, Mak-1995). While forecasting research continues to pur- ridakis and Wheelwright presented three areas wheresue improvements in systems and techniques (Men- forecasting posed issues and challenges for manage-tzer, 1988; Mentzer & Gomes, 1994; Smith, ment: (1) the range of alternative forecasting meth-McIntyre, & Achabal, 1994), recent studies and ods; (2) the selection of forecasting methods inreviews have identified gaps in our understanding of practice, and (3) organizational and behavioral fac-the relationships between systems and techniques tors affecting the forecasting environment. Whileused for forecasting, and the behavioral factors they recognized the need to continue research toassociated with the management of forecasting in develop alternative forecasting techniques, they em-organizations (Armstrong, 1987; Fildes & Hastings, phasized a need to focus more on the problem-1994; Mentzer, Bienstock, & Kahn, 1999; Wink- oriented or application side of forecasting (1977, p.lhofer, Diamantopoulos, & Witt, 1996). As Fildes 36). Such a focus, they indicated, would lead to aand Hastings (1994) summarized, most of that stronger base on which management can effectivelyresearch and almost all of the text books have use forecasting knowledge (1977, p. 36).concentrated on only one aspect of the problem: how A considerable amount of subsequent forecastingto develop appropriate forecasting methods. research has focused on the development and selec-

To focus some future forecasting research less on tion of forecasting methods. A review of researchmethods and more on management practice, the published in a variety of business journalsinclud-purpose of this paper is to describe a methodology ing those in forecasting, marketing, logistics, opera-for conducting a sales forecasting audit that has been tions management, and management scienceindi-tested in 16 companies to: (1) understand the current cates a relatively limited number of efforts to answerstatus of their forecasting management practices (the Makridakis and Wheelwrights (1977) call to in-as-is state); (2) visualize the goals they should be corporate more applications oriented and behavioralstriving to reach in the various dimensions of research. Since the purpose of this paper is to focusforecasting management (the should-be state), and on forecasting management, the following discussion(3) develop a roadmap for achieving their goals (the will address this forecasting management research.way-forward process). (At the time of acceptance The few articles that discuss the area of forecast-of this manuscript (August 2001), the following ing system implementation and administration typi-companies had participated in the sales forecasting cally propose an implementation process and presentaudit research: Allied Signal, Avery Denison, a case study to illustrate the process and describeConAgra, Corning, DuPont, Eastman Chemical, results. Examples of such studies include ArmstrongEthicon, Exxon, Hershey Foods USA, Lucent Tech- (1987), Schultz (1984), Closs, Oaks, and Wisdonologies, Michelin North America, Motorola, (1989), Fildes and Hastings (1994), Mentzer (1999),

M.A. Moon et al. / International Journal of Forecasting 19 (2003) 525 7

Mentzer and Kent (1999), and Mentzer and Schroe- forecasting management, and the use of case com-ter (1994). These articles suggest that forecasting panies to test the model.implementation entails more than the application of In the third article, Schultz (1984) discussedmore accurate forecasting techniques and that effec- managerial issues surrounding the successful im-tive forecasting management, as with effective sys- plementation of new forecasting models. He outlinedtem implementation, may lead to improved operating 12 implementation profile factors which he summa-and business performance. rized from his own and other forecasting manage-

Three exemplary articles from this stream of ment research. These factors include top manage-research bear elaboration. The first (Armstrong, ment support, the relationship between forecast users1987) presented an idealized forecasting case study and model designers, goal congruence, implementa-and, from this case, derived 16 pitfalls in forecast- tion strategy and resources, and costbenefit justifi-ing. From these pitfalls, Armstrong developed a cation. The importance of the Schultz (1984) paperforecasting audit checklist for companies to review is its explicit recognition that even the best forecast-their own management processes. This audit in- ing models will not affect overall corporate per-cluded the steps: (1) assess the methods without the formance without attention to managing organiza-forecasts, (2) assess the assumptions and data used in tional change processes.the forecast, (3) assess the uncertainty of the fore- While these studies have provided valuable in-cast, and (4) assess the costs of the forecast. Al- formation and insight into forecasting management,though not based upon an actual company, this paper they have not offered a generalizable framework thatdid establish the importance of auditing company may be used as a prescriptive tool to improveforecasting processes instead of just methods. forecasting management. As Armstrong (1988)

The second paper (Fildes & Hastings, 1994) drew pointed out, a key area where researchers have yet toupon the organizational behavior and diffusion litera- provide assistance to practitioners is in implementa-ture to develop a theoretical model of a marketing tion. In other words, how can practising forecastersforecasting system. From this model, a series of take the knowledge that has been developed abouttheoretical statements were derived in the areas of forecasting, and put it into action to improve fore-(1) the forecaster and the decision maker, (2) casting in their particular organization? It is thisinformation flows, and (3) technical characteristics question that the remainder of this paper addresses.of the forecast. The authors then tested their theoret-ical statements in a case study of a company with 10separate divisions and concluded that: 3 . Conducting a forecasting audit

The purpose of the research described here was techniques and forecasting software should meet

the development of a process by which companiesthe needs of the forecaster;

could review their sales forecasting processes and with limited time and technical expertise, im- practices to improve sales forecasting performance.plementation will also critically depend on the An important aspect of the process is its applicabilitydatabase system and the supporting organization

to organizations of different sizes, structures, anddesign; industries. The findings presented in this section are without accountability for forecast improvements based on in-depth research conducted at 16 com-

and adequate time and resources, little will hap- panies.pen; and forecast improvement depends on organizational 3 .1. The role of auditingdesign.

An audit has been defined as a formal evaluationThe importance of Fildes and Hastings (1994) of performance to predetermined standards and theresearch to this paper is the establishment of a use of that evaluation to induce improved perform-theoretical basis from which to develop a model of ance (Arter, 1989). While auditing is typically


thought of in relation to preparation of financial whether or not their organizations forecasting pro-statements, other areas of business use auditing as a cesses are good or bad, it is useful to have a standardway to arrive at an unbiased assessment of current against which those processes can be compared.performance, as well as identify areas of needed Armstrong (1987) provided such a standard with hisimprovement. Examples include marketing audits 16-point forecasting audit checklist. This checklist(Tybout & Hauser, 1981), sales management audits was divided into the dimensions of forecasting(Churchill, Ford, & Walker, 1993), human resource methods, assumptions and data, uncertainty, andmanagement audits (Hussey, 1995), and quality costs and benefits (see Table 1).audits (Dew, 1994). Fildes and Hastings (1994) utilized organizational

One of the characteristics of a successful audit behavior and diffusion theory to present a normativeemphasized by each of these authors is the unbiased- model of the Marketing Forecasting System. Basedness of the auditors themselves. Each author encour- upon this model, the authors suggested evaluatingages engagement of credible experts from outside the the forecaster and the decision maker, informationorganization to both collect and analyze the data. flows, and the technical characteristics of the forecastThere are three reasons for this. Firstly, outside (see Table 1).experts have knowledge of accepted standards Mentzer et al. (1999) based their four-dimensionalagainst which current management practice can be framework on the work of Armstrong (1987), Fildescompared. As Fildes and Ranyard (1997) point out, and Hastings (1994), and Schultz (1984), and theexternal consultants have a wide knowledge of findings from a 15-year, three-phase research pro-business practices across a range of organizations, as gram in forecasting management. Phases one (Men-well as relevant knowledge of competitor operations. tzer and Cox, 1984a) and two (Mentzer and Kahn,They may also have specialist knowledge and skills 1995) were based upon two large survey-basedwhich few in-house groups can sustain (p. 339). quantitative analyses of sales forecasting practices.Secondly, individuals from outside the organization Phase three involved a benchmark study of thehave no incentive to overlook areas that might prove forecasting practices at 20 leading companies repre-sensitive or embarrassing to current management. senting a variety of industries. Based on in-depthThirdly, data collection, particularly when such data analyses of company processes and documents, ascollection involves interviews with individuals cur- well as interviews with both users and developers ofrently involved in a management process, can be forecasts, Mentzer et al. (1999) proposed that, inmore successful when those collecting the data are order to adequately understand the overall manage-from outside the organization. Individuals tend to be ment of the forecasting process in a company, thatmore willing to share their true experiences with process must be investigated along the followingunbiased, outside experts, particularly with assur- four dimensions.ances of confidentiality. Or, as Fildes and Ranyard(1997) point out, for an internal project or audit 1. Functional integration, concerned with the role ofteam, confidentiality may be perceived as more collaboration, communication, and coordinationproblematic compared to an external consultancy (p. of forecasting management with the other busi-339). ness functional areas of marketing, sales, finance,

As mentioned above, an audit can be seen as a production, and logistics.formal evaluation of performance to predetermined 2. Approach, concerned with which products andstandards. Thus, before a description of the sales services are forecast, the forecasting techniquesforecasting audit process can begin, we turn to a used, and the relationship between forecasting anddiscussion of relevant predetermined standards for planning.sales forecasting management. 3. Systems, addressing the evaluation and selection

of hardware and software combinations to support3 .2. Best practices in sales forecasting the sales forecasting function as well as themanagement integration of forecasting systems with other

planning and management systems in the organi-Before practising forecasting managers can know zation.

M.A

.Moon

etal

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InternationalJournal

ofForecasting

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Table 1Forecasting management frameworks

Armstrong (1987) Fildes and Hastings (1994) Mentzer et al. (1999)Forecasting methods The forecaster and the decision maker Functional integration1. Forecasting independent of top management? 1. Forecasters managerial style 1. Degree of communication, coordination, and2. Forecast used objective methods? 2. Forecasters training collaboration between forecasting group and3. Structured techniques used to obtain judgments? 3. Link between formal forecast and users decision other functional areas4. Least expensive experts used? 2. Organizational location of the forecasting group5. More than one method used to obtain forecasts? Information flows 3. Existence and form of consensus forecasting6. Users understand the forecasting methods? 4. Information flow from the environment meetings7. Forecasts free of judgmental revisions? 5. Intraorganizational information flows and loss 4. Recognition of forecasting needs of various8. Separate documents prepared for plans and forecasts? of information functional areas

6. IT support for information flows 5. Accountability /performance rewards for personnelAssumptions and data involved in developing the forecasts

9. Ample budget for analysis and presentation of data? Technical characteristics of the forecast10. Central data bank exists? 7. Accuracy and bias Approach11. Least expensive macroeconomic forecasts used? 8. Responsiveness and speed 6. Relationship between forecasts and plans

9. Uncertainty estimation 7. Orientation of the forecasting approach (top-downUncertainty or bottom-up)12. Upper and lower bounds provided? 8. What is forecast in the supply chain?13. Quantitative analysis of previous accuracy provided? 9. Forecasting segmentation of products by importance14. Forecasts prepared for alternative futures? 10. Use of quantitative and qualitative forecasting15. Arguments listed against each forecast? techniques

11. Training in technique usageCosts and benefits16. Amount spent on forecasting reasonable? Systems

12. Intracompany and supply chain electronic links13. Information availability (reports and performance

metrics)14. Degree of systems knowledge in the organizationPerformance measurement15. Measurement and use of accuracy16. Recognition of the impact of external factors on

accuracy17. Measurement and use of other performance measures

(costs and customer service)


4. Performance measurement, considering the met- frameworks, we can make several observations.rics used to measure sales forecasting effective- Armstrong (1987) concentrated more on the methodsness and its impact on business operations. aspect of forecasting and, thus, provided more

evaluative detail on forecasting methods than theIn addition to identifying these four dimensions of other two frameworks. The Armstrong (1987) frame-

forecasting management, Mentzer et al. (1999) ar- work can be largely subsumed under the Fildes andticulated four stages of effectiveness within each Hastings (1994) category of technical characteristicsdimension (see Figs. 14). Their article provided a of the forecast, and the Mentzer et al. (1999)detailed description of the characteristics that can be category of approach. The Fildes and Hastingsfound at each of the four stages of effectiveness (1994) framework provides a more comprehensivewithin each of the four dimensions. From the Table 1 framework than Armstrong (1987), with many of thecomparison of the Armstrong (1987), Fildes and same evaluative criteria as Mentzer et al. (1999): theHastings (1994), and Mentzer et al. (1999) criteria under the forecaster and the decision maker

Fig. 1. Forecasting benchmark stages: functional integration.


Fig. 2. Forecasting benchmark stages: approach.

correspond to similar criteria under functional inte- Further analysis of these three studies revealsgration; information flows correspond to both certain key themes in sales forecasting managementfunctional integration and systems; and technical (Table 2). Table 2 takes the numbers of the keycharacteristics of the forecast correspond to much in elements of each study articulated in Table 1 andthe approach category. categorizes them under 24 exemplars of key themes.


Fig. 3. Forecasting benchmark stages: systems.

These key sales forecasting management themes, (reasons for forecast uncertainty explored, variableswhich run across all three studies, pay attention to: forecast and lead time, and forecasters style) that arethe organization, information, technical issues, the not specifically addressed by Mentzer et al. (1999).forecaster and users, and costs and benefits of Since it was the purpose of this auditing research notforecasting effectiveness. to refine any particular framework but rather to select

Perhaps due to the benefit of the existence of the one that could be used as a standard against whichArmstrong (1987) and Fildes and Hastings (1994) company processes could be compared, the combina-frameworks and the fact that the Mentzer et al. tion of these 24 exemplars into one more comprehen-(1999) framework was based on the evaluation of a sive framework is left to future research.broad set of companies, the Mentzer et al. (1999) Therefore, since the Mentzer et al. (1999) frame-dimensions and stages appear to provide the most work was the most comprehensive, it was adopteddetailed and comprehensive comparison standard. for this study. Since the forecasting audit processHowever, several exemplars were addressed by that we describe below adopted this framework, theArmstrong (assumptions explicit, reasons for forecast details of the stages in each of the Mentzer et al.uncertainty explored, users knowledge, and re- dimensions are reproduced here in Figs. 14. Rathersources available) and/or Fildes and Hastings than directly reproduce the figures from the Mentzer


Fig. 4. Forecasting benchmark stages: performance measurement.

et al. (1999) article, we have substituted actual have participated to date in the audit research. Whilefigures from four different forecasting audits as these organizations are diverse in terms of productsexemplars of audit findings. Each of the four figures and services they offer, one important commonalityis taken from a different audit. The bullet points in they all shared was a realization that their forecastingbold, italic type represent the audit teams assess- practices were in need of improvement. Each of thement of that particular companys status on that 16 organizations agreed to participate because theyparticular dimension of forecasting management. felt the audit could help them identify and rectifyThese bolded, italicized bullet points will be ex- fundamental problems with their forecasting prac-plained in more detail later in the paper. tices. As a result, while it is impossible easily to

characterize the typical company that has partici-3 .3. The audit processdata collection pated in the audit research to date, one characteriza-

tion is that, on each of the four dimensions ofThe audit process developed in this research was forecasting management discussed above, the typi-

used to assess practices and recommend actions to cal company is in stages one or two on all fourimprove forecasting management performance at 16 dimensions. It is in this way that this researchlarge and diverse organizations. Table 3 is provided diverges from Mentzer et al. (1999). Where Mentzerto show the diverse nature of the organizations that et al. developed their dimensions while investigating


Table 2aThemes across sales forecasting management frameworks

Themes Exemplars MBK F&H Armstrong

Organization Communications 1Coordination 1Location 2Interaction 3Link to planning and 4, 5, 6 3 1, 8decisions

Information From environmental 12 4Within supply chain 8 4Intra-organization 12 5Availability 13Information systems 14 6 10

Technical issues Top-down/bottom-up 7Techniques 10 2, 3, 4, 5, 7, 11Product segmentation 9Assumptions explicit 15Measurement of accuracy 15 7 13Impact of external factors 16 14Reasons for forecast 9 12uncertainty exploredVariables forecast and 8lead time

The forecaster Training 11 2and users Incorporation of judgement 10

Forecasters style 1Users knowledge 6

Costs and Resources available 9benefits Value (perceived and actual) 17 3 16

to organizationa The authors wish to thank Professor Robert Fildes for the original idea and guidance to develop this table.

companies possessing a wide range of forecasting coordinate the details of the audit, as well as chooseproficiency on each of the four dimensions, the the individuals to be interviewed in the data collec-purpose of this research was to focus on companies tion phase.with a recognizable deficiency in one or more of the The next step is an analysis of all relevantdimensions. Our purpose was to see if these dimen- documentation. Prior to on-site data collection, it issions could serve as a diagnostic tool to help useful for the audit team to become familiar with thecompanies improve their forecasting performance. forecasting process as it is currently understood by

The process used to conduct a forecasting audit is those responsible for forecasting. Thus, any writtengraphically depicted in Fig. 5. This process begins documentation that describes information flows,with identification of the liaison person within the reports that are available to forecasters or users,company. Because the companies that agree to organization charts, hardware and software systemsparticipate in the audit research are companies that descriptions and documentation, historical accuracyrecognize their own deficiencies, this individual is figures and reports, and uses of the forecasts arethe person who has been charged with initiating a analyzed by the audit team.forecasting re-engineering effort. The liaison helps Of the 16 companies that have been audited, there


Table 3Characteristics of audited companies

Company Consumer? Business Primarily Primarilyto business? direct sales through

sales? distributors?

Allied Signal X XAvery Denison X XConAgra X XCorning X XDuPont X XEastman Chemical X XEthicon X XExxon X XHershey USA X XLucent Technologies X X

aMichelin North America X X X XbMotorola X X X X

Pharmavite X XSmith & Nephew X XUnion Pacific RR X XWilliamsonDickie X X

Totals 8 (50%) 10 (63%) 6 (38%) 12 (75%)a Michelins business is divided between OEM and replacement tire.b Motorolas business involved wireless and pager business to consumers and business customers.

has been considerable variance in the quality and k.edu/ forecasting.) The sponsor typically providescompleteness of the documentation provided before copies of this protocol to the interview participants tothe on-site visit. At one extreme was a 5-inch-thick help them prepare for their interviews. The protocolbinder containing an extremely comprehensive de- is designed to help those who are to be interviewedscription of the current systemincluding detailed understand the type of information that the auditdescriptions of what happens during each month and team is trying to collect. It is never the case that anythroughout the fiscal year of the forecasting pro- single individual is able to answer all the questionscessalong with hundreds of pages of reports that posed in the protocol. Rather, the protocol is meantcan be generated on demand by the forecasting to guide the audit team through the entire datasystem. At the other extreme was a photocopy of the collection process, and provide those interviewedsoftware manual for the forecasting system that was with guidance to reflect on issues in preparing for theinstalled, but never used, and no documentation of interviews. In other words, by the completion of theprocesses. on-site visit, the audit teams objective is to have

In addition to receiving information from the answers to all the various items in the protocol fromcompany being audited, the audit team provides a the combined interview responses.detailed, eight-page interview protocol to the audit Although it is the responsibility of the sponsor tosponsor. This protocol presents detailed questions on select the individuals to be interviewed, the auditthe four dimensions suggested by Mentzer et al. team should communicate the critical importance to(1999), i.e. how forecasts are prepared, the systems the success of the audit that an appropriate range ofthat are used to support forecasting, the techniques individuals be included on the interview list. Thethat are employed, what (if any) approaches are participant list needs to be both broad and deep.taken to measuring forecasting performance, and Broad means adequate representation from all thehow the forecasts are used. (Copies of the detailed different functions in the company that are involvedprotocol are available on the web site, http: / /bus.ut- in developing or using the sales forecasts. It is


Fig. 5. Forecast audit data collection process.

important that at least three different groups are work. At the same time, if only workers arerepresented: those who provide input to the sales included, there is the danger interviews will becomeforecast (e.g. the sales and marketing organization), little more than complaint sessions, and the auditthose who actually prepare the sales forecast (i.e. the team may be left with an insufficient understandingsales forecasting group), and those who are custom- of the strategic issues surrounding the sales forecast-ers of the sales forecast (e.g. purchasing, production ing process. Therefore, it is up to the audit sponsorplanning, logistics planning, and finance). carefully to select and schedule the right individuals

The participant list also needs to be deep in the to participate in the interviews.sense that it includes various levels of the organiza- Following this preparation is the on-site visit,tional hierarchy. If only senior level managers are conducted by a team of four auditors. The team ofinterviewed, there is a danger they will have in- four auditors splits into two sub-teams so that twoadequate understanding of the detailed issues and auditors are present for each interview, providing theproblems faced by the people who actually do the ability to assess inter-rater reliability, a crucial


component of validity and reliability in interview- the current status of the companys forecastingbased research (Armstrong, Gosling, & Weinman, practices (the as-is). As each member of the audit1997; Griggs, 1987; Hughes & Garrett, 1990; team analyzes the data, two primary objectives areKurasaki, 2000). Each interview is audiotaped so any foremost. Firstly, the companys position on each ofdifferences in interpretation can be resolved at the the four dimensions of sales forecasting manage-time of data analysis. Interviews typically include mentfunctional integration, approach, systems, andone subject and two auditors, although occasionally performance measurementis assessed. Eachtwo or more subjects are present during a single member of the audit team identifies characteristics ofinterview. the company being audited, and compares those

The interview typically begins with one member characteristics to the bullet points in Figs. 14.of the audit team briefly describing the audits Initially, each research team member does thispurpose, giving assurances of confidentiality, and work independently, and then all members meet toobtaining permission to audiotape the conversation. compare the results of their analyses. When disagree-The auditors then ask the subject to describe his or ments arise, the analysts talk through their reasonsher role in the forecasting process. Probes include for highlighting a particular bullet point on one ofquestions such as what do you do with that in- the four dimensions, citing evidence from the docu-formation?, where do you obtain that informa- mentation and/or the interview notes. If necessary,tion?, and is the information you obtain from that the audiotapes of the interviews are replayed forsource credible and complete? While a considerable clarification, and consensus is reached. The results ofportion of the interview is spent gaining an under- this process are a version of Figs. 14, with variousstanding of the subjects formal role and responsibili- bullet points, or portions of bullet points, highlightedty with regard to the forecasts, the auditors also to identify characteristics of the audited company onprobe to obtain insights as to the subjects satisfac- each of the four dimensions of forecasting manage-tion with the sales forecasts and the sales forecasting ment. As mentioned previously, Figs. 14 giveprocess. Focus is placed on understanding any actual examples from audits that have been con-frustrations or problems the subject has with the ducted to date. Examination of these figures showsforecasting process and his or her role in that how different bullet points have been highlighted,process. Each interview ends with a wish-list identifying the as-is state of that particular com-question, where one of the auditors asks the subject pany on each of the four dimensions.to describe what he or she would do to make the It is important to note that during the analysis it isforecasting process more effective. Interviews typi- common to identify characteristics consistent withcally last 45 min to an hour. multiple stages of sophistication along a forecasting

At the 16 companies audited to date, the number dimension. For example, examination of Fig. 1of interviews has ranged from 22 to 64, with an reveals that on the functional integration dimen-average of 32 per company. Following completion of sion, this particular company exhibited one worldthe interviews, the auditors combine all interview class, stage four characteristicexistence of fore-notes, then distribute those notes to all audit team casting as a separate functional areawhile alsomembers. With data collection completed, data anal- exhibiting several stage one and stage two charac-ysis begins. teristics. The insight revealed here is that while well

positioned organizationally to achieve a high level of3 .4. The as-is status functional integration, lack of a forecasting champ-

ion (Mentzer, Moon, Kent, & Smith, 1997) hasThe purpose of the sales forecasting audit is to prevented this company from taking advantage of

articulate for the audited company its as-is status, a this organizational strength.vision of its should-be position, and a description Similarly, Fig. 2 shows a company that, on theof the way-forward process that will help the approach dimension, has four stage one characteris-company improve its sales forecasting practices. The tics, three stage two characteristics, and one stagefirst step is for the research team to understand fully three characteristic. In other words, some areas of the


approach dimension have great opportunities for these organizations are creating forecasts basedimprovement, other areas have lesser opportunities upon plans or sales targets, rather than their bestfor improvement, and still other areas on the ap- judgments about future customer demand.proach dimension are managed quite well. As will Limited commitment to sales forecasting (10 ofbe discussed in the next section (the should-be 16 companies)this theme was manifested by astate), this articulation of characteristics at different number of different situations at audited com-stages of sophistication helps a company identify and panies, including: insufficient commitment ofprioritize areas where improvement can take place. resources to training, documentation, systemsThe audit process is not concerned with classifying support, or reward and recognition programs;the company solely within a single discrete stage of relegating the forecasting function to relativelysophistication as much as understanding the relation- low levels in the organizational hierarchy; unwil-ships among the stage characteristics and the impli- lingness to designate a forecasting champion, andcations for improving performance. lack of accountability throughout the organization

The second objective of analyzing the interview for forecast accuracy. At one company, this themenotes is to identify strategic themes that emerge was manifested by the failure to fill an openfrom the data. These strategic themes are issues that director-level forecasting position for over a year.cut across multiple dimensions of forecasting man- Because of this lack of leadership, the companysagement, and which are so pervasive or which cause forecasting improvement efforts were unfocusedsuch wide-ranging problems that they demand spe- and unsupported by other constituent organiza-cial attention and discussion. Following is a discus- tions in the company.sion of those strategic themes that emerged at a Islands of analysis (nine of 16 companies)this ismajority of the companies. the situation where a company has non-standard,

non-interfacing systems or procedures for per- Limited performance measurement and lack of forming similar tasks, or forecasting systems that

performance evaluation (12 of 16 companies) fail to connect with other enterprise systems likewhile this characteristic is discussed at length in production planning or finance. These islandsthe dimension on performance measurement, it can range from each forecasting analyst havingis such a pervasive characteristic that at most his or her own home-made spreadsheet withcompanies it has warranted special discussion as a unique characteristics and assumptions, to sepa-strategic theme. One clear lesson learned as a rate forecasting systems installed and operating inresult of this research is companies do not seem different departments of the company, to theto measure adequately forecasting performance, manual transfer of data either into or out of atie that forecasting performance to the evaluation forecasting system. An extreme example of thisof individuals, and then reward individuals for phenomenon occurred at one audited company,excellence in forecasting. where three separate forecasting systems had been

Blurred distinction between forecasts, plans, and installed over time: a mainframe-based legacygoals (11 of 16 companies)this is a situation system, which was the official forecasting sys-where a company does not recognize that fore- tem, an AS/400-based system installed by pro-casts are a projection into the future of expected duction planning, and a PC-based system installeddemand, given a stated set of environmental by logistics. These latter two were described asconditions, while plans are managerial actions black market forecasting systems, and wereproposed by the organization to capture and installed because the forecast user organizationssupply as much of the forecasted demand as did not trust the integrity of the official forecast,possible (Mentzer & Bienstock, 1998). Evidence and so created their own forecasting systems.of this theme can be found in these actualstatements from audits: we forecast up to plan, From these two sources (dimensions and strategicor it would be suicide for me to forecast anything themes), the portrayal of the audited companys as-different than the plan. Such statements indicate is state of forecasting management practices is


complete. The second stage of the audit process is tics, and forecasting). In this more detailed way, athe description of the should-be state of sales company can see where it should be going in each offorecasting management practices for the company. the four dimensions of forecasting.

Mentzer et al. (1999) asserted that stage fourtargets in each of the dimensions provide a bench-

3 .5. The should-be state mark to which the company should ultimately strive,while other, lower dimensions provide intermediate

While understanding the current status of sales targets. In addition to their benchmark, the benefitsforecasting management (the as-is state) is im- of achieving a stage four level of sophisticationportant, managers cannot take steps toward excel- along each dimension receives support from researchlence without guidance on the directions to take. For in forecasting technique development and applica-this reason, it is important to provide a clear picture tion, systems design and implementation, and man-of the should-be state of forecasting management in agement. The functional integration characteristicsthe company. This should-be picture can be found of communication, coordination, and collaborationin Figs. 14 in two different ways. The first is to reflect the benefits associated with team-based fore-provide broad targets at which managers can aim. casting (Kahn & Mentzer, 1994), and are identifiedExamination of stage four in each of the four as one of seven keys to better forecasting (Moon,dimensions describes the most advanced level of Mentzer, Smith, & Garver, 1998). Maintaining aforecasting excellence uncovered in the sales fore- separate forecasting function is suggested as a meanscasting benchmark research. Therefore, a best prac- to reduce bias and support forecast processes (Fildestices company would operate at stage four on all & Hastings, 1994). Providing forecasts in formatsfour dimensions. Stage four characteristics provide that match the requirements of user functions helpsmanagers with a long-term target toward which they improve understanding and input (Mentzer & Bien-can strive. However, since few companies have stock, 1998; Marien, 1999; Fliedner, 2001; Mentzerachieved a level of excellence near stage four, it is & Schroeter, 1994). Forecast development is alsoimportant that intermediate targets be set to move viewed as a consensus building process, acknowl-toward stage four. If, for example, a companys edging the relationship between unconstrained mar-as-is status is primarily in stage one, then stage two ket forecasts and the constraints associated withcharacteristics can be seen as intermediate targets operating capabilities or requirements (Fildes &that will improve forecasting effectiveness, and Hastings, 1994; Waddell & Sohal, 1994). Schultzbegin the company on the path to the excellence (1992) emphasizes the need for multidimensionalfound in stage four. performance metrics noting that, we must go

The second way that Figs. 14 provide the beyond measures of accuracy and look to objectiveshould-be picture is in a more detailed, tactical performance measures such as sales, costs, andsense. Careful examination of Figs. 14 reveals that profits (p. 410).for many of the bullet points found in each dimen- Reviewing characteristics associated with a stagesion, there is a natural progression from stage one four level of approach, top down/bottom up fore-(low level of forecasting sophistication) to stage four cast development has been identified as a means to(high level of forecasting excellence). In Fig. 1, for improve forecast performance over either approachexample, which describes the dimension of func- separately (Kahn, 1998; Fliedner, 2001). The needtional integration, the first bullet under stage one for forecast reconciliation between sales and opera-describes a state where major disconnects exist tions (Fildes & Hastings, 1994; Waddell & Sohal,between marketing, finance, sales, production, logis- 1994; Nelson, 1987), and an understanding of thetics, and forecasting. For one company that found its impact of sales force gaming (Galfond et al., 1996),current as-is state described by this bullet, the whether internally or from customers, are also pro-immediate should-be target was found in the first posed to impact forecast accuracy. Forecast educa-bullet of stage two (coordination (formal meetings) tion that goes beyond technique development (Men-between marketing, finance, sales, production, logis- tzer & Cox, 1984b) and top management support


(Miller, 1985; Schultz, 1984) are also recognized as current status of their forecasting practices, thesekey elements of forecast success. recommendations usually fall into four categories.

Characteristics associated with a stage four level Two of these categories, systems and performanceof sophistication along the systems dimension measurement, directly match the dimensions previ-reflect findings from case studies involving system ously discussed. The other two categories, processdevelopment and implementation (Mentzer & and training, are designed to help companies in bothSchroeter, 1993, 1994; Mentzer & Kent, 1999). functional integration and approach.Mentzer and Kent (1999) outlined the development Process recommendations refer to the way fore-and implementation of new processes and systems casts are created and used. One company, forthat helped The Longaberger Company establish a example, was at stage one on the dimension ofsystem-centric approach to forecast development. functional integration, so process recommendationsTheir discussion addressed the need for companies included instituting a consensus forecasting process,considering forecasting systems to make the tool fit where different people from different parts of thethe problem. Kahn and Mentzer (1996) discussed company work together in a forum characterized bythe benefits of incorporating EDI as a means to open information-sharing to create a consensus fore-integrate supply chain demand information to im- cast. On the other hand, another companys forecast-prove data availability and accuracy, and subsequent- ing practices were at stage one on the approachly reduce inventory costs. Their propositions are dimension, and statistical tools were not used effec-supported by studies evaluating the impact of fore- tively to uncover patterns in historical demand data.casting information availability on variability in the Thus, the process recommendations included im-supply chain (Chen, Drezner, Ryan, & Simchi-Levi, plementation of a process where baseline forecasts1999). Chen et al. (1999) quantified the improve- are generated statistically, then distributed to know-ment in supply chain forecasting and inventory ledgeable experts, such as sales or marketing people,performance resulting from a shift in information for adjustment.availability from a decentralized to centralized Training recommendations refer to specific situa-model. tions where company personnel who are involved in

Performance measurement characteristics were forecasting have inadequate skills or knowledge tosupported by Fildes and Hastings (1994), who perform their forecasting tasks effectively. For exam-recognized that environmental factors influence fore- ple, salespeople are usually in a position to providecasting practices and performance. Calling on mana- forecasting intelligence, but in only one of the 16gers to make forecasting important and to measure, companies in our database did salespeople have anymeasure, measure, Moon et al. (1998) emphasized training on why forecasting is important (functionalthe need to implement measures of forecasting integration), or how to make qualitative adjustmentsperformance based on accuracy and its impact on to baseline forecasts (approach). Thus, in almost alloperating performance. companies that constitute the audit database, such

While an understanding of the should-be state is training programs targeted at problems in functionalcritically important to the continuous improvement integration and approach were recommended.process, it is not very useful without an understand- Similarly and surprisingly, in 13 of the auditeding of how to get to that should-be state. For that companies the people in the forecasting group hadreason, we now turn to the third purpose of the received no training on how time series and regres-forecast audit: the description of the way-forward. sion analysis can be used to create baseline forecasts,

so training programs targeted at this deficiency in the3 .6. The way-forward approach dimension were recommended.

System recommendations refer to the way com-The audit process provides the audited company puter and communication systems can be enhanced

with a way-forward roadmap through a series of to develop and communicate forecasting informationconcrete recommendations. While the recommenda- more effectively. For example, the as-is status oftions are unique for each company, based on the one company showed forecasting systems were not


closely integrated with other corporate systems, in panies in this category tend to bog down in assigningthis case finance and MRP systems, resulting in blame rather than in pursuing solutions. Companiesmanual transfers of data. Therefore, the system in the why should I care? category tend to viewrecommendations included creating electronic link- forecasting as an unimportant activity. In theseages that allow data transfers between systems. Also, companies, there is no understanding at the seniorin several companies where island of analysis management level of how forecasting improvementsexisted, characterized by multiple processes or sys- can dramatically enhance the companys key per-tems performing similar tasks, system recommenda- formance indicators.tions included specific procedures designed to elimi- One company in particular provides an excellentnate such islands and standardize on a single set of example of the address the problems response. Thisforecasting processes. organization, which was in stage one on all four

Finally, performance measurement recommenda- dimensions of forecasting management, respondedtions refer to specific metrics that should be put into by assigning a cross-functional project team first toplace to measure forecasting performance adequate- perform a detailed review of the recommendations,ly. For example, in six companies the salespeople then propose a prioritization scheme, followed by anwere asked to make adjustments to baseline fore- action plan. Three months after the conclusion of thecasts, but the accuracy of those adjustments was not audit, this project team met with the audit team tomeasured and communicated back to the salespeople. review their proposed priorities and action plan, andThis resulted in a recommendation that such a this was followed by a 2-year-long effort to re-measurement and feedback system be implemented. engineer their approach to sales forecasting. As aSimilarly, in the 13 companies that had implemented result of that re-engineering effort, this companysome performance metrics, accuracy was the only now approaches stage four on all four dimensions ofmetric used. Thus, other metrics designed to assess forecasting management, and their supply chain coststhe impact of forecasting accuracy on overall supply have been reduced dramatically. In fact, the companychain costs and customer service were recom- estimates their entire implementation effort cost lessmended. than $1 million, but the savings in raw material

While recommendations have been included in purchasing costs alone (buying more on long-termeach of the 16 audits conducted to date, there has contracts based on accurate forecasts rather thanbeen considerable variance observed in manage- buying at the last minute on the spot market) duringments responses to these recommendations. Man- 1998 were in excess of $7 million. Thus, the returnagement reaction has typically fallen into one of on investment from implementation has been consi-three categories, which we can characterize as either derable. It is important to note that this $7 millionaddress the problems, assign the blame, or why saving was seen by upper management as an accom-should I care?. Companies that fall under the plishment by all departments involved in the fore-address the problems category tend to have an casting effort, not just purchasing.organizational culture oriented toward solutions, Another company provides an example of theregardless of which department is to blame. Com- assign the blame response. At this organization,panies in this category also tend to recognize that which was primarily at stages two and three on tworesponsibility for complex organizational problems of the dimensions and stage one on the other twoare usually shared across functions, and thus look for dimensions, the auditors final presentation to seniorcross-functional solutions. Companies in the assign management degenerated into a heated discussionthe blame category tend to have an organizational between executives over which department was atculture oriented toward identifying the source of fault for the problems identified by the audit team.organizational problems, and when that source is While these executives agreed that problems existed,identified, that department becomes responsible for none were willing to acknowledge that performancesolutions. Since forecasting problems tend to be improvements were needed in their individual de-cross-functional, it is usually impossible to identify a partments. As a result, no consensus could besingle source of forecasting problems. Thus, com- reached on how to effect change, and no re-engineer-


ing effort was carried out. Over the next 18 months, system on managers job performance. This factor isthis company experienced considerable disruption consistent with the Mentzer et al. (1999) frameworkand customer service problems due to an inability to that stage four companies provide performance re-forecast demand hitting their distribution centers. wards to all personnel involved in the forecasting

Finally, at an audited company that exhibited the process. Similarly, Schultz (1984) mentions that goalwhy should I care? response, during the question congruence positively affects implementation suc-and answer portion of the final presentation to senior cess, while Mentzer et al. (1999) encourage commonmanagement, the executive vice president of market- goal setting through communication, coordination,ing rose from his chair and stated that all the and collaboration. Thus, while the Schultz papercompany really needed was a new killer product, provides guidance for successful implementation ofand with such a new product, all this attention to new forecasting models, many of his points are alsoforecasting improvement would not be necessary. At consistent with those companies who have demon-another company, the CEO spent the time during the strated a positive (address the problem) response tofinal presentation to management doing other work forecast audit findings and recommendations.and gazing absently around the conference room. Ata third company, the audit team was told that sincethey had moved to a just-in-time environment,

4 . Implications for practitionersforecasting was no longer important. None of thesecompanies, to date, has made any changes in salesforecasting management and, thus, has not realized One important finding that emerged from thisany of the supply chain cost savings and customer research is the realization thatas with other typesservice benefits achieved at the other companies. of auditsan outside, unbiased analysis is critical to

Schultz (1984) cites a number of factors that the success of the audit. Several companies in theinfluence the success or failure of organizational study had attempted forecast process improvementsefforts to implement new forecasting models. One of on their own, prior to the audit study, and reportedhis findings is that the presence of top management frustration with their inability to effect significantsupport is the top ranked predictor of implementation organizational change. In these companies, the use ofsuccess, and lack of top management support is the external auditors was very helpful both in thetop ranked predictor of implementation failure. In the articulation of the companys true forecasting pro-examples cited above, top management support was cess and in inspiring management action. Individualsclearly present in the address the problems re- who are directly affected by a companys forecastingsponse profile, and top management support was processes will share their experiences and frustra-clearly lacking in the assign the blame and why tions more freely with external auditors whom theyshould I care? responses. Obtaining such top man- perceive to be unburdened with preconceived ideasagement support is one of the key contributions from and free from any political agendas. This perspectivea forecasting champion (Mentzer et al., 1997). helps to uncover elements of the forecasting processConsistent with Schultz, one of our conclusions from that may not be evident to those who are involved inthis auditing research is that the existence of a sales the process day-to-day. This research reinforcesforecasting champion, along with the top manage- Armstrongs (1988) call for the value of salesment support for forecasting improvement such an forecasting auditing. Academics and practitionersindividual can obtain, is critical to long-term organi- should develop the skills and knowledge base neces-zational success in sales forecasting management. sary to conduct such sales forecasting management

Other factors noted by Schultz (1984) that en- audits.hance the successful implementation of forecasting The positive results companies obtained from themodels can also be considered in light of reactions to sales forecasting audits conducted to date provideforecast audit recommendations. For example, encouragement for other companies to follow suit.Schultz cites performance, or the impact of a new The example provided earlier of one company


realizing substantial savings in purchasing costs 5 . Implications for future researchduring the first year as a result of more accurate andcredible forecasts provides an exemplar. Dramatic The process and framework described in thissavings in supply chain costs are typical when the article address an important area of forecastingaudit recommendations are fully implemented. research called for by Armstrong, Brodie, and

From the 16 companies that constitute the data- McIntyre (1987), and followed by Armstrong (1987,base for development of the sales forecasting audit 1988) and Fildes and Hastings (1994). It offers aprocess, there are a number of lessons from which all foundation to direct future investigations of forecast-managers can benefit. Firstly, it is clear from this ing best practices and how the audit described mayresearch that forecasting is a distinct and critical be used to help organizations improve forecasting.management function, and not just an exercise in Figs. 14 offer a framework of benchmark criteriatechnique or software selection. Technique develop- based on an original in-depth study of 20 leadingment and selection have been the focus of much companies. The criteria were validated and the auditresearch, and this literature has made an enormous process developed as a result of subsequent studiescontribution to improving sales forecasting accuracy. with 16 additional organizations. It is important thatHowever, this audit research has demonstrated that researchers continue to evaluate and improve uponcompanies must look beyond techniques and soft- the criteria and process presented. The experienceware, and must pay close attention to overall man- and perspectives of others who use the criteria andagement of the sales forecasting process. process in research settings can help to establish a

A further lesson this sales forecasting audit re- richer understanding of its applicability in differentsearch can provide managers is that the four dimen- industry and organizational environments, and undersions of forecasting management articulated in Men- different operating conditions. By expanding thetzer et al. (1999) are a useful diagnostic and pre- diversity of conditions under which the audit processscriptive framework to affect sales forecasting im- is tested, researchers will be able to assess better theprovement. A significant portion of the audit meth- generalizability of the current criteria and process,odology described here makes use of this framework, and identify areas for improvement. Research mayand it has been very helpful for characterizing a identify circumstances where characteristics pre-companys current forecasting management status, as sented in the benchmark criteria of Figs. 14 cannotwell as showing managers the should-be state to be assessed or do not have an impact on forecastingwhich they can aspire. performance. There may also be new criteria which

Finally, the benchmarking phases of as-is, can be added to one or more of the four dimensionsshould-be, and way-forward developed by mana- of forecasting that will help lead to improvedgers involved in this auditing research are an excel- performance. In particular, the exemplars of Arm-lent way to examine the process of continuous strong (1987) and Fildes and Hastings (1994) thatimprovement in sales forecasting management. are presented in Table 2 but not included in theThese three phases have provided managers with a Mentzer et al. (1999) framework should be consid-clear, concise way to think about the process of ered for incorporation into future sales forecastingcontinuous improvement, not only in sales forecast- management audit research. The ultimate goal of thising, but also in other business functions and pro- research program should be to develop quantitativecesses. Without both a clear understanding of how a measures of the attributes articulated in Figs. 14.company currently operates (the as-is), and a vision We encourage other researchers to adapt and utilizeof what world-class really is (the should-be), this audit methodology and report the results inchanges to core processes (the way-forward) will future research.be unfocused and ineffective. Further development, Future research must also investigate ways toexplication, and exploration of the characteristics and quantify better the impact of changes in salesnature of these three phases are left to future forecasting practices. As noted by Schultz (1992), toforecasting research. determine if an organization is better off having


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Mentzer, J. T., Moon, M. A., Kent, J. L., & Smith, C. D. (1997).The need for a forecasting champion. Journal of Business Biographies: Mark A. MOON is an Associate Professor at theForecasting, 16, 38, Fall. University of Tennessee, Knoxville. He earned his BA and MBA

Mentzer, J. T., & Schroeter, J. (1993). Multiple forecasting system from the University of Michigan, and his Ph.D. from the Universi-at Brake Parts, Inc. The Journal of Business Forecasting, 12, ty of North Carolina at Chapel Hill. Dr. Moons professional59, Fall.

experience includes positions in sales and marketing with IBMMentzer, J. T., & Schroeter, J. (1994). Integrating logistics

and Xerox. He has published in the Journal of Personal Sellingforecasting techniques, systems, and administration: the multi-

and Sales Management, Business Horizons, Journal of Businessple forecasting system. Journal of Business Logistics, 13(2), Forecasting, Industrial Marketing Management, Journal of Mar-205225. keting Education, Marketing Education Review, and several

Miller, D. M. (1985). Anatomy of a successful forecastingnational conference proceedings. Dr. Moon also serves on the

implementation. International Journal of Forecasting, 1, 69editorial review board of the Journal of Personal Selling and

75. Sales Management.Moon, M. A., Mentzer, J. T., Smith, C. D., & Garver, M. S.

(1998). Seven keys to better forecasting. Business Horizons,John T. (Tom) MENTZER is the Harry J. and Vivienne R.4452, SeptemberOctober.

Bruce Excellence Chair of Business Policy in the Department ofNelson, P. T. (1987). Viewpoint: a forecast is not a sales plan.Marketing, Logistics and Transportation at the University ofJournal of Business Logistics, 8(2), 115122.Tennessee. He has published more than 140 articles and papers inSanders, N. R., & Manrodt, K. B. (1994). Forecasting practices inthe Journal of Forecasting, Journal of Business Logistics, JournalUS corporations: survey results. Interfaces, 24(2), 92100.of Marketing, Journal of Business Research, International Jour-Schultz, R. (1984). The implication of forecasting models. Jour-nal of Physical Distribution and Logistics Management, Trans-nal of Forecasting, 3(1), 4355.portation and Logistics Review, Transportation Journal, JournalSchultz, R. (1992). Fundamental aspects of forecasting in organi-of the Academy of Marketing Science, Columbia Journal of Worldzations. International Journal of Forecasting, 7, 409411.Business, Industrial Marketing Management, Research in Market-Smart, R. (1995). Forecasting: a vision of the future driving theing, Business Horizons, and other journals.supply-chain of today. Logistics Focus, 3(8), 1516.

Smith, S. A., McIntyre, S. H., & Achabal, D. D. (1994). Atwo-stage sales forecasting procedure using discounted least Carlo D. SMITH is an Associate Professor of Marketing at thesquares. Journal of Marketing Research, 31, 4456, February. University of San Diego. He holds a BS and MBA in logistics

Tybout, A. M., & Hauser, J. R. (1981). A marketing audit using a management from the Pennsylvania State University and receivedconceptual model of consumer behavior: application and his Ph.D. in logistics and marketing from the University ofevaluation. Journal of Marketing, 44, 82101, Summer. Tennessee. His articles have appeared in the Journal of Business

Waddell, D., & Sohal, A. S. (1994). Forecasting: the key to Logistics, Journal of Business Forecasting, Business Horizons,managerial decision making. Management Decision, 32(1), and the Journal of Consumer Satisfaction, Dissatisfaction and4149. Complaining Behavior. Before attending to doctoral studies, he

Winklhofer, H., Diamantopoulos, A., & Witt, S. F. (1996). spent 12 years in industry as a logistics consultant, executiveForecasting practice: a review of the empirical literature and an educator, and corporate logistics manager.agenda for future research. International Journal of Forecast-ing, 12, 193221.

Conducting a sales forecasting auditIntroductionForecasting management researchConducting a forecasting auditThe role of auditingBest practices in sales forecasting managementThe audit process-data collectionThe 'as-is' statusThe 'should-be' stateThe 'way-forward'

Implications for practitionersImplications for future researchReferences