Health Assessment of Inventory Records at Assembly Line through Data Analytics
Ladda ner
Typ
Examensarbete för masterexamen
Program
Supply chain management (MPSCM), MSc
Publicerad
2022
Författare
Göthberg, Victor
Wickström, Jonathan
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Big-data and data analytics are today seen by many industry experts and researchers
as key in creating competitive advantage. Insights once hidden in vast amount of data
are through digital tools now becoming available. Traditional manufacturers are today
realising the necessity of data-driven decision-making, there is however a lack of knowledge
of viable use cases. Inventory record inaccuracy (IRI), the mismatch between the recorded
inventory and the physical inventory, is a common issue for manufacturers. The literature
have concluded that there are multiple causes to the problem, but there is a lack of
research on the impact of manufacturers. The characteristics of the problem of IRI makes
it highly suitable for utilising the tools of data analytics in order to better understand
the issue. However, to our knowledge, there is a gap in the literature on how to utilise
data analytics to tackle such a problem. Data-driven decision-making heavily relies on
the available data for reliable and valuable output. Organisations are therefore further
challenged to find ways of assessing their data’s quality to ensure the correct output.
This thesis aims to investigate the impact of IRI at a manufacturing company, and analyse
the extent of the problem through data analytics. Additionally, the thesis aims to propose
how data quality in organisations should be assessed to facilitate future data analytics
projects. A mix of quantitative and qualitative methods were used to generate the results.
Interviews, observations, and data from existing databases of the company were used as the
primary sources for data collection. The findings indicate that the impact of IRI is severe
and affect multiple functions of the investigated company. Further on, IRI is identified
to have direct and indirect consequences, where the latter are found to have the greatest
impact on the company. Data analytics is demonstrated to facilitate quantifying the
extent of IRI, furthermore, the comparative deviation demonstrates a strong foundation
for further categorisation of inventory record deviations. To facilitate future data analytics
projects, organisations should centre their assessment of data quality around the data
consumer, and through frequent reviews, aim to constantly strive for better alignment
between their data and the data consumers’ needs.
Beskrivning
Ämne/nyckelord
Inventory record inaccuracy , Data quality , Data analytics , Digitalisation , Production logistics , Inventory control , Data-driven decision-making