Big data business analytics in supply chain management - The effects on organisational performance

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School of Business | Bachelor's thesis
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Date
2018
Major/Subject
Mcode
Degree programme
Tieto- ja palvelujohtaminen
Language
en
Pages
34+2
Series
Abstract
Big data and analytics have been emerging topics in 2010’s. Applied to supply chain management they can improve organisational performance. Nevertheless, organisations’ capabilities and difficulties to see the benefits that analytics can bring are the major challenges in successful implementation of analytics. This thesis investigates these issues by reviewing literature and creating a research framework that helps to understand how these issues relate to each other. The research objectives of this thesis are 1) to find out what are the needed big data business analytics capabilities and 2) to form a clear picture how big data business analytics, applied to supply chain management, can effect on organisational performance. At first the three main concepts (Big data, supply chain management and business analytics) are defined. This is followed by discussion of the three main organisational capabilities (technological, managerial and analytics personnel). After that this thesis discusses more closely about the connection between analytics and supply chain management. And lastly how analytics effects on organisational performance. The results indicate that all three big data analytics capabilities are important and should be development together. Analytics can bring benefits to all supply chain functions and organisations’ supply chain regardless of their size. Many studies found the positive connection between analytics and organisations’ performance. This is supported by strategic alignment of analytics, business and information system strategy. Lastly this thesis proposes five steps what to consider before making decisions on the use of analytics in supply chain management.
Description
Thesis advisor
Kauppi, Katri
Keywords
analytics, big data, supply chain management, SCOR
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