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6thInternational Scientific Conference

May 1314, 2010, Vilnius, Lithuania

BUSINESS AND MANAGEMENT 2010

Selected papers. Vilnius, 2010

ISSN 2029-4441 print / ISSN 2029-428X CD

doi:10.3846/bm.2010.151

http://www.vgtu.lt/en/editions/proceedings Vilnius Gediminas Technical University, 2010

1119

ROLE OF DEMAND PLANNING IN BUSINESS PROCESS MANAGEMENT

Vladimira Vlckova1, Michal Patak

2

University of Pardubice, Studentsk 95, CR-53210 Pardubice, Czech RepublicE-mail: [email protected], [email protected]

Abstract.Only these enterprises which are able not only to identify customers needs and requirementsbut also flexibly respond on them can succeed in present very quickly varying business environment.From this resulting customers pressures on time compression needed for orders fulfilment and simultane-ously requests of management on reduction of locked-up capital in inventory create environment in whichsystems controlled by demand begin to assert. Knowledge of demand and sales derived on the base offorecast and their sharing play significant role. Therefore this article deals with the question of changingrelevance of demand forecasting and particularly with the forecast utilization in the demand planning fromthe enterprise point of view. The methodology of the demand planning and its integration with other busi-ness processes is also described here.Keywords:demand forecasting, demand planning, business process management.

1. Introduction

At present, the substantial survival ability of thecompany rests in adaptability to constant changes ofthe environment. The success is seen by the compa-nies not only able to reveal customers wishes butrather capable of flexible reactions to their require-ments. If the company wants to stand up to compe-tition, it must accelerate and make more efficientnot only the partial internal company processes butalso the management of tangible and intangible in-formation flows within the whole supply chain.The growing pressure of the supply chain customerson accelerated reaction of suppliers enforces short-ening time periods for processing orders. It is, how-ever, often possible to carry it out only at the ex-pense of enormous effort of the productioncompany and leads to non-economical rise of costs.That is why management seeks the ways of elimi-nating or reducing the costs. It creates the environ-ment in which the systems controlled by the de-mand are applied. The systems controlled in such a

way are an essential prerequisite for the creationand setting of the production and all related proc-esses that are to maximum degree balanced and si-multaneously adaptable.

There are a number of principles and method-ologies for management of production, stock, hu-man resources etc. However, the rapid developmentof information technologies during the last decademoved these theoretical procedures to an entirelydifferent level. The information systems play a keyrole mainly in operative planning and management.Many companies cannot nowadays imagine running

the business without accessing relevant informationfrom ERP (Enterprise Resource Planning) systems.The concept of ERP does not relate merely the

planning methods but is rather a synonym for agroup of complex information systems, designedfor the management of internal company processes.

In consequence of more efficient informationuse through ERP, the partial planning methods asMRP II (Manufaturing Resource Planning), Salesand Operations Planning (S&OP) or APS (Ad-

vanced Planning and Scheduling) are developed.All these methodologies of planning and man-agement and their software support have some-

thing in common. They enable optimization ofcompany processes in a short time providing the

volume of real sales of particular customers par-ticular products is known, well in advance.However, where to get the information if the cus-tomer service lead time is often a far smaller in-terval than the lead time required by the organiza-tion to produce or distribute the product? In thesecases the expertise in demand and sales prognosisplay a significant role.

The research carried out in numerous produc-tion companies, primarily of chemical and food

processing industry in the Czech Repub-lic (Hamblkov 2009; Patk 2009; Rohov2009), however, showed the changing andstrengthening role of the demand and sales fore-cast is often underestimated by management andthus it is not paid an adequate attention.

The aim of this paper is to demonstrate thesignificance of the demand and sales forecastingfor the production company and support the useof these forecasts via the demand planning. It de-scribes the demand planning methodology and itsintegration within other company processes.

The research methods were a method of struc-tured literature research and a method of in-depth

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interview with managers of selected chemical andfood processing companies.

2. Significance of demand forecasting

The forecasting is a process in course of which

possible future variants of a phenomenon or ob-ject, maybe even variant solutions of ways leadingto future situations are formulated. The forecast-ing creates a basis for planning company processes(Johnson 2009). It enables managers to plan futureneeds and consequently make rational decisions.Forecasting is a continuous process that requiresproduct managers to think about markets and un-derstand those (Haines 2008).

Forecasting methods were developed since the1950s for business forecasting and at the sametime for econometric purposes. The application in

software modules makes it possible to forecast fora lot of items in a few seconds (Stadtler 2008).Accurate demand forecasts are an important inputto decision models used in APS. Forecast errorsare directly related to required safety stocks, whilefrequent adjustments of demand forecasts can leadto dramatic changes in plans (Stadtler 2005).

If the company wants to maximize the effectof accessible methods for internal company proc-esses, it must build on objective and evaluateddemand forecasts. The choice of optimum fore-casting procedures and following use of obtainedforecasts may become a competitive advantage.Together with other modern methods it acceleratesother company processes, reduces the costs andincreases the value for the customer.

The demand forecast determines the volumeof products, place and time horizon in which theywill be needed. In relation with the demand fore-cast it is necessary to deal not only with the quan-titative aspect of the needs (the volume demandedby customers) but also their qualitative aspect (thetype of customers needs). The accurate demand

forecast is thus important for the production anddistribution management but also for e. g. areas ofmarketing (distribution of sales forces, communi-cation, promotion and planning of new products),finance (current need of money, budgets and cal-culations), investment designs (production facili-ties, workshops and warehouses), research anddevelopment (innovations) and human resources(structure and labour force volume planning, train-ing).

It is important to accept the process of fore-casting as a part of company planning. A lot of

small and middle-size businesses neglect this ac-tivity or avoids it on purpose as it evokes feelingsof vanity with most practitioners (indel 2009).

The future is always stochastic. In case of marketturbulences it is even more valid. The forecastthus, based on its character, cannot ever be consid-ered entirely reliable. The opportunity for the fore-cast use, nevertheless, does not depend only on theconfidence level. Every evaluated forecast repre-

sents an efficient instrument for decision makingas every decision issues from a particular futureforecast. It is not then surprising that in the recent

years we have been meeting the concept of de-mand planning more and more often.

3. Demand planning

Demand planning represents a set of methodolo-gies and information technologies for the use ofdemand forecasts in the process of planning. Theaim is to accelerate the flow of raw materials, ma-

terials and services beginning with the suppliersthrough transforming to products in the companyand to their distribution to their final consumers.

The demand planning process is done to helpthe business understand profit potential. Indirectlyit sets the stage for capacity, financing, and stake-holder confidence (Sheldon 2006). The implemen-tation of the demand planning enables to deter-mine the closest possible forecast to the planninghorizon and decide the volume of production,stock and sources capacity distribution among par-ticular products to maximize the profits of thewhole company.

The key requirement for efficient companymanagement is sharing the mutual forecast. How-ever, the research carried in production companiesshowed individual departments of the company insome cases draw up forecasts on their own andthus they base their planning on different figures.This provokes conflicts among the resulting activi-ties of in-company plans (Gros, Grosov 2004).The same situation happens also in case when thecompany prefers approved financial plan which

does not correspond with the updated forecast re-sults.The forecasting should always be the process

which is essential and determining for other com-pany processes, including financial planning. Thefinancial plan, however, often represents the mainmotivation source for company managers as it re-flects requirements of the company top manage-ment and main strategic company goals.

While managing processes via the demandplanning the managers should not be assessed ac-cording to their meeting the financial plan but

rather according to their ability to predict the fu-ture development of both the demand and demandcontrol so that the main strategic goals are

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achieved by economically the most advantageousway.

It is evident the demand planning does notrepresent only one of many tools of managing thecompany processes. It is a whole philosophy ofcompany planning and decision making on strate-

gic, tactic and operative levels. With regard to thecurrent turbulent environment escalating require-ments on a prompt company response to custom-ers orders, especially the pressure put on readyoperative decision making.

3.1. Methodics of demand planning

Methodics of the company demand planning(Formnek 2004) can be divided into six steps:

understand essential forecast principles; integrate systems for forecasting and planning; identify key factors influencing the demandlevel; identify and understand customer segments; select appropriate forecasting techniques; build a system for measuring performance and

error rate of forecasts.Every forecasting process should start with

making aims and purposes of the resulting forecastclear. The company should precisely define thearea of the future demand, the volume of which ittries to estimate. In this phase it simultaneouslydetermines the time horizon of forecast defined as

a time gap between the point, for which the fore-cast is carried out, and the point, when it is carriedout. These decisions should correspond with theneeds of other company processes for the resultingforecasts to be used efficiently both at the strate-gic, tactic and operative levels. Though, for theirdecision making the partial company departmentsrequire forecasts of different aggregations andforecast horizons, the forecasts should not be per-formed at the level of individual company depart-ments. The only one central unit should be incharge of final demand forecasts. This is the onlyway for the company to ensure the creation of anintegrated demand forecast issuing from the sameinformation and sheltering all the company proc-esses.

If the company wants to acquire the most pre-cise and reliable demand forecasts, it should utilizeall information about future jobs it may get. Itshould be aware of what customers it will producefor and what distribution ways will be used toserve them. It should also identify their needs,wishes, requirements and determine factors that

could significantly influence the demand volume.At the same time it should know the reliability ofthis information and systematically collect the in-

formation necessary for the chosen forecastingmethods. While collecting and classifying this in-formation it is adequate to use all available seg-mentation techniques and methods of clusteranalysis (Bottomley, Nairn 2004). When applyingthe procedures in the right way, there is an oppor-

tunity to reduce considerably the number of fore-casts of the whole production portfolio to forecastsof the product categories (e. g. product lines) inparticular customer segments.

In connection with in previous paragraphmentioned the term Hierarchical Demand Planning(HDP) can be found in the literature. HDP is basedon the assumption of independence among vari-ables, and this allows for simple and easy aggrega-tion and separation of plans and data (Nielsen,Steger-Jensen 2008).

A variety of modeling techniques are avail-

able for producing forecasts. Based on data pat-terns, forecasting horizon, data availability andbusiness requirements the choice of technique dif-fers (Voudouris, Owusu, Dorne, Lesaint 2008).Viaappropriate combining of the forecasting tech-niques it is possible to estimate quantitative influ-ences of the identified factors and set the demandforecast (Lehmann, Winer 2005).

The most frequently used statistical forecast-ing method is the time series technique. It useshistorical data sequenced by time and projects fu-ture demand by the same time sequence (Crum,Palmatier 2003). POS data is rich in informationfor building forecast models. Building a goodforecasting model with POS data is demonstratedin many case studies (Andres 2008; Gallucci,McCarthy 2008).

While a quality forecast is a good basis for ademand plan, the forecast needs to be modified forexternal activities that will have an impact on thedemand for the product being forecasted. The im-pact of promotional events needs to be integratedinto the forecast and demand plan so that the accu-

racy of both is improved (Gattornaet al.

2003).As soon as the forecast is elaborated in detailinto individual product forecasts geographicallyallotted along a time period, it is labelled salesforecast, which is a more unambiguous term es-pecially for the sales management. It is an objec-tive and evaluated forecast of sales that the com-pany is capable of carrying out in the future.

To make the forecasts objective, the practiceintegrates numerous unbiased experts for obtainingrequired forecasts. Another way of making theforecasts objective rests in using several methods

for forecasting the same phenomenon and the ob-tained results are finally mutually compared. Asevery forecast is preconditioned by a complex of

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external and internal factors, this fact should bereflected in the alternatives of the potential futuredevelopment. That is why the forecasts should bealways drawn up in variants.

The evaluation of the variant forecast is car-ried out in terms its credibility and confidence.

The credibility of the forecast can be understoodas a degree of its true value, i. e. as the approach-ing of the model future image to the reality. Theconfidence of the forecast is determined by theprobability with which it is likely to expect theindividual forecasts variants to come true.

Though the forecast cannot ever be consideredentirely reliable, the company should arrive at anagreement over the final forecast and its reflectionin all the company plans. Only this way leads tofulfilling the basic concept of the demand plan-ning, i. e. the company should not for example

accept decisions on production based on its wishesbut only on the set forecasts.

The forecast, or as the case may be, the salesplan set on its basis is necessary to be comparedwith the real sales. The discrepancy between theforecast and the real sales value in the forecast pe-riod is the forecast error. Its value should issue incorrection activities of the company.

Watching the validity and accuracy of the par-tial forecasting methods may then help with theselection of appropriate methods, specific in rela-tion to a particular situation.

It is important to realize the demand planninguse in practice is not a mere creation of a perfectsystem for carrying out the demand and sales fore-cast (Blanchard 2008). The objective of forecast-ing is to predict demand whilst the aim of demandplanning is to shape the demand and produce a

resource requirements plan (Voudouris et al.2008). Without the right forecast - planning sys-tem integration it is not possible to use efficientlythe information provided in the forecasts.

3.2. Forecasting and planning system integration

First and foremost the company should perceivethe demand planning as an instrument of the mar-keting management of the company. Every mar-keting oriented company needs to integrate thecompany plans with forecasts as these forecasts as

such more or less represent a real view of the fu-ture requirements and wishes of the customers towhich the company should efficiently adapt.

However, there is a feedback between themarketing and demand planning. The informationsystem aimed to support the demand planningshould save, classify and process also informationabout the influence of the marketing managementon the future sales volumes. Via assessing theseinfluences it is possible to control the demand effi-ciently to achieve optimum management of theother company processes.

Fig. 1.Scheme flow of information in processes planning

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This feedback can be demonstrated by the fol-lowing example. The forecasting result of the pro-motion influence on the sales might be a future de-mand for products the company is not able toproduce in time e. g. due to the capacity limits inproduction. If, however, they consider more mar-

keting strategies, they will certainly find the onethat supports the strategic company goals and si-multaneously reflects the production capacity po-tential.

The right applying of the demand planning inpractice should involve also the demand controlwhich will lead to such sales forecasts in which allthe company sources are utilized to the maximumdegree.

If the forecast is to be used in all the companyprocesses, the relation of these processes with fore-casting must be assured in such a way for the fore-

cast to be the essential initial information for othercompany planning. Also the company processesfeedback to the forecasting itself must be assured inthe same way. This cannot be achieved without thesupport of integrated in-company information sys-tems. That is why the demand planning is often per-ceived as a superstructure of the ERP systems. Thescheme flow of individual processes is depicted inthe Fig. 1.

There are numerous applicable modern analyti-cal instruments which due to new technologies en-able real time planning and large information vol-umes processing as detailed as possible, e. g. salesof individual customers or sales categorized accord-ing to delivery locations (Formnek 2007). Thesoftware products for the demand planning, tradedin the current market, use advance statistical func-tions combined with expert estimations of the givenmarket situation and development, gained frominternal and external collaborators (Knolmayer etal.2009). As a rule they provide a unified platformfor creating a quality demand forecast that can beshared in real time by all company departments.

In an operational setting, software now permitsautomatic forecasting and the integration of fore-casts into planning. But large numbers of series arestill being forecast by the crude methods containedin planning systems while opportunities to applymore sophisticated and precise techniques are notoffered. So there is still much room to apply ad-

vances in statistical forecasting to current businessprocesses (Kusters et al.2006).

3.3. Demand planning as instrument of business

processes management

The result of the demand planning process is theestablishment of independent requirements which

will trigger the planning activities as distribution,production and procurement planning (Dickers-bach 2009).

Frequent situation which is solved in moni-tored companies is that the period which is re-quired for realization of all activities from pur-

chase, through production up to distribution islonger than is acceptable for customer. If all theforecasts represent credible quantitative estimatesof the future sales, the company could efficientlycontrol all the company processes even in thesesituations. It could be labelled as managing theprocesses by the real demand known to the com-pany well in advance, which means before themoment when the real product demand comesinto existence. It is obviously a purely hypotheti-cal situation which does not happen in practice.

Every forecast should be, however, variant

and evaluated by the confidence. Every sales fore-cast can be thus generally determined in terms ofthe forecast confidence interval when the forecastconfidence is understood as the probability, underwhich the company carries out the future sales inthe volume complying with the given value inter-

val. In forecasting by using statistical methods thelimits of the production confidence interval can beexactly determinated. While exploiting the qualita-tive forecasting methods (expertise, intuition), thepessimistic variant of the forecast can be the lowerlimit and the optimistic variant can be the upperlimit of the interval (Fig. 2).

The knowledge of the forecast confidence in-terval can be used e. g. while planning the pro-duction of cycle and safety stock of the finalproducts in the production company.

In common practice of the demand planningthe company would generate such stock reservesthat would cover the sales as far as reaching thelower confidence interval limit of forecast whilecovering uncertain sales belonging into the fore-cast confidence interval would cover the safety

stock. This, however, would be still relativelyhigh in relation to the whole volume of sales.The sales forecast for fast-moving products

is usually well predictable by means of extrapola-tion of the last sales time lines. The highest prob-ability density in these cases will appear in themiddle of the confidence interval. It is possibleto prove the high speed of product moving wouldcause the safety stock to get constantly renewedon average in the volume of half the interval.That is why it is useless to consider this produc-tion to be the safety stock production but it can be

a part of the common cycle stock production.Thus there comes to the decrease of the safetystock (Fig 3a).

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When the product moving decreases (Fig3b), it is more efficient to reduce the safety stockby means of adapting the production processes sothat they are controlled by the real demand, i. e.by orders. One of the possibilities rests in aprompter response to customers requirements

not only in the company but along the entire sup-ply chain (Christopher 2005).

Fig. 2. Limits of the forecast confidence interval

This way of planning the production obvi-ously means the width of the forecast confidenceinterval will remarkably influence the volume ofthe safety stock and the requirements on thechange of the company processes. Though boththe facts will assure a high reliability of meetingall the future customers requirements, they bringthe company costs related to the capital locked-upin stock, to maintaining stock and changing proc-esses. The demand planning partial target thusshould also be the effort seeking the ways to con-stant decreasing of the width of the production

confidence interval.The suggested way of utilizing the knowledge

of the forecast confidence interval allows not onlymore efficient mass flow management in the com-pany, but they can be generalized for the manage-ment of all activities of all but to using it generallyfor managing all the company processes.

Demand planning processes provide the toolsfor understanding, projecting, and managing de-mand in the supply chain network (Sehgal 2009).Since a supply chain involves the synchronisationof a series of inter-related but different stages ofbusiness processes influencing multiple tradingpartners, its demand planning and forecasting can-

not rely on a single, stand-alone forecasting tool(Min, Yu 2008).

Fig. 3. Cycle and safety stock planning focused onutilization of the forecast confidence interval

4. Conclusions

All the supply chain links nowadays face a heavypressure from the part of the customers, which isto make them shorten the process time of their or-ders. A significant role is played by the develop-ment of the information technologies. Especiallywithin the operative planning there comes to thedevelopment of partial planning methods such asMRP II, S&OP, APS. However, a frequent prob-lem of the production companies rests in the issueof how to get, i. e. well in advance to predict cor-rectly and precisely the initial information on the

sales volumes of individual products with individ-ual customers.

Our research in numerous companies showedif the companies do not use systems controlled bythe forecast, whether for they do not trust the finalforecasts or for they are not able/willing to workwith them, they must seek other ways of compen-sating this insufficiency in the reliable forecastcreation competence. The production companiesmust then often face very unbalanced utilizationsof all the capacities and solve these situations onlyat with great effort leading often to inadequate rise

of costs, e. g. by raising the stock of finished prod-ucts, extraordinary shifts, hiring large numbers of

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contemporary staff at the expense of the regularstaff.

In such cases demand planning can be startingpoint for companies which exploits forecastingmethods and effectively interconnect them withother business processes. Investigations realized in

recent years indicate that key factor for successfulimplementation of demand planning in companiesis very forecasting and planning integration. Wealso pointed out on the basic principals of this in-tegration.

Software products for the demand planningenable flow of planning the company processes onindividual forecasts. Using them, managementhowever does not have exploited always possibili-ties to manage company processes on the base ofall information, which each forecast provides. Aswe have pointed out the knowledge of the forecast,

its accuracy and confidence enables more efficientdeciding on whether in the given case it is mean-ingful to manage the company processes accordingto the forecast or adapt them to the control of thereal demand.

The demand planning is a significant instru-ment for creating the forecast, its integration withthe in-company plans and business processes man-agement. It is a whole philosophy of companyplanning and decision making on strategic, tacticand operative level.

References

Andres, F. 2008. Demand planning and Forecastingwith POS Data: A Case Study, Journal of BusinessForecasting27(4): 2932.

Blanchard, D. 2008. Top 10 Demand Planning Strate-gies,Industry week11(11): 5556.

Bottomley, P.; Nairn, A. 2004. Blinded by Science: TheManagerial Consequences of Inadequately Vali-dated Cluster Analysis Solutions, InternationalJournal of Market Research46(2): 171187.

Christopher, M. 2005.Logistics and Supply Chain

Management: Creating Value-adding Networks.Third Edition. New York: Pearson Education. 305 p.ISBN 0-27-368176-1.

Crum, C.; Palmatier, G. E. 2003. Demand ManagementBest Practices: process, Principles, and Collabora-tion. First Edition. Boca Raton: J. Ross Publishing.239 p. ISBN 1-932159-01-0.

Dickersbach, J. T. 2009. Supply Chain Managementwith APO: Structures, Modelling Approaches andImplementation of SAP SCM 2008. Third Edition.Berlin: Springer. 501 p. ISBN 3-540-92941-3.

Formnek, T. 2004. Demand planning v praxi [Demand

Planning in Practice],IT Systems 5(6): 4041.

Formnek, T. 2007. Efektivn pedpov poptvky azen zsob [Efficient Demand Forecasting and Re-plenishment],IT Systems 8(9): 2021.

Gallucci, J. A.; McCarthy, H. J. 2008. Enhancing theDemand Planning Process with POS Forecasting,Journal of Business Forecasting27(4): 1114.

Gattorna, J.; Ogulin, R.; Reynolds, M. W. 2003. GowerHandbook of Supply Chain Management. Fifth Edi-tion. Aldershot: Gower Publishing. 692 p. ISBN 0-566-08511-9.

Gros, I.; Grosov, S. 2004. Logistika a marketing vdodavatelskch etzcch [Logistics and Marketingin Supply Chains], Logistika [Logistics] 10(78):4849.

Haines, S. 2008. The Product Managers Desk Refer-ence. First Edition. New York: McGraw-Hill Pro-fessional. 744 p. ISBN 0-07-159134-6.

Hamblkov, P. 2009. Proces pedpovdi poptvky aprodej v podniku chemickho prmyslu: diplomov

prce [Demand and Sales Forecasting in ChemicalIndustry Company: Diploma work]. University ofPardubice. Pardubice. 76 p.

Johnson, R. 2009. Sales Planning During an EconomicCrisis, Supply House Times52(5): 8690.

Knomayer, G. F.; Mertens, P.; Zeier, A.; Dickersbach,J. T. 2009. Supply Chain Management Based onSAP Systems: Architecture and Planning Processes.First Edition. Berlin: Springer. 207 p. ISBN 3-540-68737-8.

Kusters, F; McCullough, B. D.; Bell, M. 2006. Fore-casting Software: Past, Present and Future, Interna-

tional Journal of Forecasting2006(22): 599615.Lehmann, D. R.; Winer, R. S. 2005. Analysis for Mar-keting Planning. Sixth Edition New York: McGraw-Hill/Irwin. 256 p. ISBN 0-07-286596-2.

Min, H.; Yu, W. B. 2008. Collaborative Planning, Fore-casting and Replenishment: Demand Planning inSupply Chain Management,International Journal ofInformation technology and Management 1(7): 420. doi:10.1504/IJITM.2008.015886

Nielsen, P.; Steger-Jensen, K. 2008. Demand Planningand Control-Handling Multiple PerspectivesThrough a Holistic Approach to Hierarchical Plan-ning, Lean Business Systems and Beyond 1(257):

5765. doi:10.1007/978-0-387-77249-3_7Patk, M. 2009. Analza procesu pedpovdi poptvky

a prodej ve vybranm podniku: diplomov prce[Analysis of Demand Planning in Chosen Company:Diploma work]. University of Pardubice. Pardubice.94 p.

Rohov, J. 2009. Pedpov poptvky a prodej vevybranm podniku: diplomov prce [Demand andSales Forecasting in Chosen Company: Diplomawork]. University of Pardubice. Pardubice. 60 p.

Sehgal, V. 2009. Enterprise Supply Chain Manage-ment: Integrating Best in Class Processes. First Edi-

tion. New Jersey: John Wiley&Sons. 206 p. ISBN0-470-46545-X.

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