Exceli Power BI põhise planeerimistööriista juurutamine Saku Õlletehas AS näitel

Sepp, Henrik (2020) Exceli Power BI põhise planeerimistööriista juurutamine Saku Õlletehas AS näitel. [thesis] [en] Implementation of Excel Power-BI Based Planning Tool on the Example of Saku Õlletehas AS (Saku Brewery).

[thumbnail of digidoc] Other (digidoc) - Published Version
Restricted to Registered users only

Download (1MB)
[thumbnail of lihtlitsents - digidoc] Other (lihtlitsents - digidoc) - Other
Restricted to Registered users only

Download (252kB)

Abstract

Müügiprognoosimine on tarneahelas väga oluline tegevus. Nimelt, planeerimise käigus püütakse eelnenud perioodide müügiajaloo ja turu nõudlust mõjutavate tegurite tundmise pealt planeerida eelseisvate perioodide müüke. Seda tehakse kas kogemuslikult või arvutusmeetodite abil. Nõudluse planeerimise väljund on otsene sisend tootmise planeerimisele ning selletõttu on prognoositäpsus vägagi oluline faktor kogu ettevõtte kasumlikkusele. Lõputöö eesmärk oli analüüsida uue rakendatava tööriista tulemuslikkust - prognoositäpsust. Töö autor leidis vastused kõikidele püstitatud küsimustele. Lõputöö fookusettevõtteks oli Saku Õlletehas AS. Analüüsi tegemiseks rakendas autor uut tööriista paralleelselt kasutusel olnud lahendusega testperioodil. Rakendusobjekti testiti nelja nädala vältel, kasutades selleks iga joogikategooria erinevaid tooteid. Nädalate vältel võrreldi kahte erinevat prognoosimisviisi. Üheks oli juurutamises olev planeerimistööriist ning teiseks aastaid kasutusel olnud protsess. Saadud tulemusi võrreldi ja analüüsiti kategooriate kaupa. Testperioodile lisas raskust samaaegselt ülemaailmselt kestnud COVID19 pandeemia. Lõputöö tulemusena leiti, et autori poolt valitud testmeetod osutus selles suhtes edukaks, et tootmisplaneerimisele ja müükidele valitud viis lisakomplikatsioone ei valmistanud. Küll, aga autori enda päevad olid testperioodil väga kiired, sest kahte täiesti erinevat viisi prognoosimine võtab palju aega. Eriti olukorras, mil valitses turul üleüldine eriolukord ning klientide tavapärane ostumuster oli muutunud.. Juurutatud tööriista prognoositäpsuse tulemus oli piisavalt rahuldav, et pärast testperioodi üle minna täielikult uuele protsessile. Tulemuste vahed olid küllaltki väiksed ning suuremad anomaaliad seletatavad ning edaspidi ära hoitavad. Lisaks, vabastab parendatud protsess suure osa müügiplaneerija ajast, mida saab planeerija kasutada müügiplaanile lisandväärtuse loomiseks. Kokkuvõtteks võib öelda, et uurimustöö täitis oma eesmärgi ning rakendusobjekt sai edukalt juurutatud. Antud töö tulem on kasulik Saku Õlletehasele, sest täpsemad müügiplaanid võimaldavad ettevõttel olla paindlikumad ning läbi selle ka kasumlikumad.

Abstract [en]

The following thesis Implementation of Excel Power-BI based planning tool on the example of Saku Õlletehas AS (Saku Brewery) is written by Henrik Sepp. The length of the work is 34 pages long and includes 28 blueprints and 7 different tables. Sales forecasting plays a substantial role in the supply chain. Namely, during the planning process, enterprises try to plan the sale of forthcoming periods, taking into account the sales history of previous periods and the factors influencing the market demand. This is done either on the basis of experience or by using calculation methods. The output of demand planning is the direct input for production planning and thus is the forecast accuracy an essential factor in terms of the profitability of the enterprise. The aim of this final paper was to analyse the cost-effectiveness of a new tool – its forecast accuracy. The author of the paper found answers to all the questions set at the beginning. The focus enterprise of this final paper was Saku Õlletehas AS (Saku Brewery). To carry out the analysis, the author applied, during the test period, the new tool in parallel with the solution previously in use. The new tool was tested during four weeks with different products of each category of beverages. During those weeks, two different forecast methods were compared. One of them was the planning tool that was being implemented, the other was the process that had previously been in use for many years. The results were compared and analysed by categories. The test period was aggravated by the concurrent global COVID-19 pandemic. As a result of the final paper it was identified that the test method chosen by the author was successful in terms of not causing additional complications to production planning and sales. For the author, the test period was extremely busy and demanding as forecasting with two different methods was very time-consuming. This was further complicated by the overall emergency situation on the market which had changed the usual buying pattern of the customers. The forecast accuracy of the new tested tool was sufficiently satisfactory to be fully implemented after the test period. The differencies in results were relatively small, major irregularities were explainable and would be avoidable in the future. Along with that, the improved process enables the sales officer to save considerable time that can be used to create added value to the sales plan. To sum up – the research achieved its objective and the new tool could be successfully implemented. The results of this final paper are beneficial to the Saku Brewery as more accurate sales plans enable the enterprise to be more flexible and thus also more profitable.

Item Type: thesis
Advisor: Lea Murumaa
Subjects: Economy and Management > Production Management
Divisions: Institute of Technology and Circular Economy > Production and Production Management
Depositing User: Henrik Sepp
Date Deposited: 25 Aug 2020 11:38
Last Modified: 25 Aug 2020 11:38
URI: https://eprints.tktk.ee/id/eprint/5623

Actions (login required)

View Item View Item