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VMI potentsiaalne tulu ja nõudlusprognoosi täpsus Nefab Packaging OÜ näitel

Tamm, Aune (2018) VMI potentsiaalne tulu ja nõudlusprognoosi täpsus Nefab Packaging OÜ näitel. [thesis] [en] The Potential Profit of the Vendor Managed Inventory and Customer Demand Forecast Accuracy in Nefab Packaging OÜ.

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Abstract

Varude juhtimise ja omamise kontseptsioonid on viimastel aastakümnetel läbinud suure muutuse. Traditsiooniliste varude juhtimise meetodite kõrvale on tulnud kaasaegsed, infovahetusel ja koostööl põhinevad meetodid, mille seast ettevõtted valivad sobivaima ja kuluefektiivsema. VMI on üks neist kaasaegsetest tarneahelas varude juhtimise meetoditest, mis põhineb koostööl ja annab tarnijale õiguse aga ka kohustuse kliendi varude ees. Antud lõputöös arvutati VMI rakendamisest saadav potentsiaalne tulu tarneaukude ja laovarude taseme alanemisest tarnijale Nefab Packaging OÜ-le ning analüüsiti selle tulu saavutamise eelduseks oleva kliendi X nõudlusprognoosi täpsust. Autor uuris erialakirjanduses VMI rakendamise kasusid, mida võib jaotada tarnija, ostja ja ühisteks kasudeks. VMI ühised eelised on parem kättesaadavus ja vähem tarneauke, mis tähendab suuremat tulu ning väiksem laovarude tase, mis tähendab vabanevat käibekapitali. Tarnija eeliseks on peamiselt tootmise parem planeerimine ja suurem kliendilojaalsus. Kliendi eelisteks on madalamad tellimiskulud ja kõrgem klienditeeninduse tase. VMI rakendamisest saab suuremat tulu tarneahel ise, milles väheneb varude tase. Erialakirjandusest leidis autor tulemuse võtmemõõdikud, mis said aluseks potentsiaalse tulu leidmisel. Kaheks enamlevinud ja mainitud võtmemõõdikuks on tarneaugud ja varude piisavus päevades, mis on ühised tegevusmõõdikud tarnijale ja kliendile. Tarneaukude vähenemisest tuleneva potentsiaalse tulu arvutamise aluseks on perioodi 01.01.– 30.04.2018 jooksul registreeritud reklamatsioonid, mille põhjuseks oli kauba osaline või täielik puudumine. Autor võttis tulu arvutamisel arvesse, et reklamatsiooni saanud toodete müük toimus aga hilinemisega, mis tõi kaasa kiirtranspordi kasutamisega seotud kulu ja tööaja kulu. Kulude hulka ei arvestatud kliendi rahulolematust ehk emotsionaalset kulu, millele on arvulist väärtust väga raske anda. Varude vähenemisest tuleneva potentsiaalse tulu arvutamisel on vaadeldud kuu keskmist laovarude taset ja maksimaalse laotaseme erinevust. Autor peab üleliigseks varuks iga toodet, mis on üle maksimaalse määratud laotaseme. Arvutused näitasid, et ettevõte hoiab oma laos keskmiselt 11235 euro väärtuses üleliigset laovaru, ehk siis tooteid, mis ületavad kindlaks määratud maksimaalset laovarude taset. Potentsiaalse laovarude alanemisest saadava tulu arvutamisel võetakse arvesse, et see tulu tuleb vabanevast käibekapitalist. Võttes raha hinnaks 10% laovarude väärtusest, siis on võimalik tulu 1124 eurot. Arvutatud potentsiaalse tulu teenimise tingimuseks on täpne kliendi X poolt saadetav nõudluseprognoos. Nõudlusprognoosi täpsust on kontrollitud pikaajalises perioodis, milleks on 03.01.2018 kliendi poolt saadetud prognoos, millest analüüsitakse nelja esimest kuud. Lisaks uuritakse kliendi poolt saadetava iganädalase korrigeeritud nõudlusprognoosi täpsust. Statistilist andmetöötlust kasutades leitakse prognoosi keskmine viga, keskmine absoluutviga ja keskmine suhteline viga. Arvutused näitasid, et pika perioodi ennustus on oodatult lühiperioodi omast ebatäpsem. Pikaajalise prognoosi keskmine suhteline viga oli korrigeeritud prognoosi omast suurem, vastavalt 84% ja 67%. Nõudlusprognoosi analüüsist selgus, et 16-st registreeritud OOS-i olukorrast 11 on tingitud kliendi valest prognoosist. Nõudlusprognoosi teise astme kliendi põhisest analüüsist selgus, et paremini prognoosib nõudlust klient X7, kelle korrigeeritud prognoosi MAPE oli 33% ning ebatäpsemalt klient X9, kelle keskmine suhteline viga oli 122%. Autor soovitab tarnijal pöörata kliendi tähelepanu prognoosi täpsuse parendamisele, mis võimaldaks tarnijal oma kliendile paremat teenust pakkuda ja tarneauke vältida või vähendada. Autor soovitab tarnija ja kliendi koostöös viia läbi VMI prooviperiood. See võimaldab hinnata ettevõtte valmisolekut meetodi täismahuliseks rakendamiseks, kontrollida ja parendada protsesse ning kokku leppida tegevuse võtmenäitajates ja nende väärtustes. Lõppkokkuvõttes võib hästi rakendatud VMI kasu tuua mõlemale tarneahela partnerile.

Abstract [en]

The methods and attitudes of inventory management and possession have gone through large changes over the last couple of decades. Modern inventory management methods, which have concepts based on the exchange of information and cooperation, have appeared alongside traditional ones. One modern cooperation based inventory management method is VMI. The profits from implementing VMI have been studied in specialist literature, mostly from the viewpoint of buyer and in retail trade. Less research has gone into profits from the viewpoint of the vendor and the processing industry sector, where both parties involved are production companies. The relevance of the research is increased by the fact that the author analyses, within the framework of a case study, the relationship between potential profit and demand forecast, which are usually observed through different studies. The aim of the thesis is to identify the potential profit to the vendor by implementing VMI to reduce out of stock inventory and stock level decrease and analyse the accuracy of the customer demand forecast, which is a prerequisite for gaining profit. The following research tasks have been set in order to reach the goal: • provide an overview of the theory on inventory management and VMI strategy, • discover the profits of VMI implementation and find out the importance of the demand forecast when using VMI strategy, • find result indicators from theoretical sources, which are suitable for calculating potential profits and demand forecast analysis, • synthesise the theory and analysis, and provide recommendations to the company for inventory management. The work consists of two chapters. The first part provides an overview of the theoretical handling of inventory management and the VMI concept in academic literature, and the theoretical profit gained by different parties through its implementation. Key performance indicators are found that can be used to discover potential profits. The importance of the demand forecast is explained and indicators for the accuracy of the forecast are presented. The second chapter describes the research strategy used to fulfil the research goal, provides a short overview on the company this research is based on, and explains the principles of compiling samples. The accuracy of the demand forecast is calculated as well as the potential profits to the vendor when the method is implemented. VMI has several definitions in specialised literature. The definition from the ECR VMI handbook is the basis here, which states: “Vendor Managed Inventory is a replenishment strategy where the traditional ordering process is eliminated and the supplier has the right and responsibility to make stock replenishment decisions based on regular automatic inventory and/or sales data demand forecast from buyer [4]” The sample of the case study includes 45 products and the observation period is 01.01.2018–30.04.2018. The key indicators (KPIs) used to calculate the potential profits of implementing VMI are the number of out of stock inventory and surplus stock. Complaints registered by customer X due to the partial or complete lack of goods are the basis for calculating the potential profits from the reduction of out of stock inventory. When calculating profits, it must be taken into account that the sale of products that received a complaint was delayed, which led to an increase in express transport and labour costs. Customer dissatisfaction i.e. the emotional cost is not calculated among the costs because it is quite difficult to assign it a numerical value. In calculating the potential profit gained from decreasing stock, the month's average stock level and the fixed maximum stock level differences are observed, while also taking into account the customer's demand. Calculations showed that the company keeps surplus stock in its warehouse valued to 11235 euros, that is, products that exceed the maximum stock amount. When calculating the potential profit gained from decreasing stock, it is taken into account that the profit comes from freed up working capital. By valuing money as 10% of stock value, the possible profit becomes 1124 euros. The requirement for earning the calculated potential profit is an accurate demand forecast sent by the customer. The accuracy of the demand forecast has been checked in the long term, which is a four month demand sent by the customer on 03.01.2018. Additionally, the accuracy of the customer provided weekly adjusted demand forecast is being studied. The forecast's mean average error, mean absolute deviation and mean absolute percent error are found by using statistical data processing. Calculations showed that the long term prediction was expectedly more inaccurate than the short term prediction, mean absolute deviation and mean absolute percent error of the forecast were both larger. Demand forecast analysis suggests that out of the 16 registered OOS reports, 11 can be considered caused by the customer’s false forecasts. The author recommends that the vendor direct the customer’s attention to the accuracy of the forecast, which, when improved, would allow the vendor to provide a better service to the customer and avoid or reduce the OOSs. The author recommends that the vendor and customer cooperate and carry out a VMI trial period. This allows us to determine the company’s readiness for full-scale implementation of the method, to check and improve the processes and agree on key performance indicators and their values. In the end, a well implemented VMI profits both partners in the supply chain.

Item Type: thesis
Advisor: Kati Nõuakas
Subjects: Transport > Logistics > Logistics and supply chain management > Inventory managment
Divisions: Institute of Logistics > Transport and Logistics
Depositing User: Aune Tamm
Date Deposited: 12 Jun 2018 07:11
Last Modified: 12 Jun 2018 07:11
URI: http://eprints.tktk.ee/id/eprint/3705

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