Enhancing Demand Forecasting Accuracy for Retail Equipment A Quantitative Assessment of Forecasting Methods
Publicerad
Författare
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
In a globalized world with supply chains becoming more and more complex, the
need of being more accurate in predicting future sales becomes essential for com-
panies. In this thesis, the focal company was IKEA Components and the demand
forecasting process of the retail equipment was analyzed. The thesis aimed to an-
swer the question of what are the most suitable forecasting methods and parameters
to accurately predict the demand for the retail equipment at IKEA Components.
The current method used by IKEA Components was compared with 7 proposed
methods and the results showed an accuracy improvement in 87% of the retail
equipment stock keeping units (SKU). For the majority of SKUs with smooth de-
mand, the best-performing forecasting method is Moving Average (MA) followed
by Double Exponential Smoothing (DES) due to the low fluctuations in demand.
For items with erratic demand, the Triple Exponential Smoothing (TES) Additive
method stands out for its ability to closely follow the sharp fluctuations in demand.
Each suggested method yielding the smallest error for at least one SKU, proved
that an one size fits all approach is not suitable for the retail equipment at IKEA
Components.
As a result from the selection of the best-performing forecasting methods, some in-
sights were found. First, demand patterns were identified and the one that involves
the largest portion of SKUs are trend and seasonality occurring simultaneously.
Second, correlation in demand behavior between subcategories of SKUs were iden-
tified. Furthermore, suggestions on how to further enhance forecast accuracy by
applying qualitative assessment were given. Finally, it was theoretically stated that
there are positive economic, environmental and social implications of improving the
forecasting process.
Beskrivning
Ämne/nyckelord
Demand Forecasting, Forecast Accuracy, Quantitative Forecasting, Retail Equipment, Erratic Demand, Smooth Demand, Lumpy Demand