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Supporteffektivisering: Undersökning av GDMs supportarbete
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
2021 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [sv]

Det blir allt vanligare med företag som automatiserar sina arbetsuppgifter. GDM i Sundsvall är ett IT-konsultbolag som därför ville veta om de kunde automatisera någon av sina arbetsuppgifter. Målet med detta arbete har därför varit att undersöka hur mycket tid de kan tänkas spara in genom att automatisera en av sina arbetsuppgifter. Målet var också att ge förslag på hur en sådan automatisering skulle se ut samt om det fanns ett användbart sätt att applicera AI, artificiell intelligens, på de uppgifterna med hänsyn på vad det kostar kontra vilken nytta den kan bidra med. Det valdes sedan ut två typer av ärenden som GDM har idag, lösenords- och behörighetsärende. För att kunna utföra en sådan undersök behövs vetskap om hur arbetet fungerar idag. Därför har GDMs arbete studerats och brutits ner i mindre delmoment som sedan har analyserats. För att räkna ut hur mycket tid GDM kan tänkas spara har en uppskattning baserat på hur många operationer en dator behöver göra för att utföra varje delmoment gjorts. De olika delmomenten har även legat i grunden för hur automatiseringen ska se ut. Tiderna som uppskattats har sedan jämförts med tider från ärendena som GDM haft statistik på. Resultatet av undersökningen blev att ärendena skulle bli ungefär 30% snabbare, för lösenordsärende skulle medeltiden bli 12 minuter istället för 17 minuter och för behörighetsärende skulle medeltiden bli 21 minuter istället för 30 minuter.

Abstract [en]

It is becoming increasingly common with companies that automate their duties. GDM in Sundsvall is an IT consultancy company that would like to know if they could automate any of their tasks. The aim of this work has been to investigate how much time they can save by automating one of their tasks. The goal was also to provide suggestions on how such automation would look and if there was a useful way to apply AI, Artificial Intelligence, to those tasks considering what it costs versus the benefit it can contribute. Two types of cases of GDM work were then chosen to perform the study, password and authorisation issues. To carry out such a study, knowledge of how work looks today is necessary. Therefore, GDM's work has been studied and broken down into smaller parts that then were analyzed. To calculate how much time GDM is likely to save has an estimate based on how many operations a computer needs to perform each task been made. The various sections have also been the basis for how the automation will look like. The times estimated have then been compared with times from the cases that GDM had statistics on. The result of the investigation was that the cases would be about 30% faster, for passwords cases the mean time would be 12 minutes instead of 17 minutes and for authorisation cases, the mean time would be 21 minutes instead of 30 minutes.

Place, publisher, year, edition, pages
2021. , p. 47
Keywords [en]
AI, Artificial Intelligence, Support Work, Support Enhancement
Keywords [sv]
AI, Artificiell intelligens, Supportarbete, Supporteffektivisering
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:miun:diva-44097Local ID: DT-V17-G3-009OAI: oai:DiVA.org:miun-44097DiVA, id: diva2:1630826
Subject / course
Computer Engineering DT1
Educational program
Master of Science in Engineering - Computer Engineering TDTEA 300 higher education credits
Supervisors
Examiners
Available from: 2022-01-21 Created: 2022-01-21 Last updated: 2022-01-21Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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