Table 1 Research design overview Study... | Emerald Publishing

Table 1

Research design overview

	Study 1: quantitative study	Study 2: qualitative study
Research purpose	Evaluate the value of retail data integration in terms of forecast accuracy	Explore the value of retail data sharing in terms of demand planning alignment
Research questions	Does sharing of POS data increase the forecast accuracy of a CPG Manufacturer?	How does retail data sharing increase demand planning alignment?
Research study	Quantitative study: addition of POS data as an explanatory variable in forecasting models of 4 CPG companies	Qualitative study: semi-structured interviews with two manufacturers, three retail chains and experts from a solution provider company
Data	Order rates, POS and other retail data of four CPG companies. Background information of case companies’ products and operations and observations on decision making and feedback for the pilot	10 semi-structured interviews exploring practices, use cases and benefits of data sharing
Analysis	Comparison of forecasts generated with and without POS data using a Bayesian approach	Thematic analysis of practices, challenges and benefits of retail data sharing

	Study 1: quantitative study	Study 2: qualitative study
Research purpose	Evaluate the value of retail data integration in terms of forecast accuracy	Explore the value of retail data sharing in terms of demand planning alignment
Research questions	Does sharing of POS data increase the forecast accuracy of a CPG Manufacturer?	How does retail data sharing increase demand planning alignment?
Research study	Quantitative study: addition of POS data as an explanatory variable in forecasting models of 4 CPG companies	Qualitative study: semi-structured interviews with two manufacturers, three retail chains and experts from a solution provider company
Data	Order rates, POS and other retail data of four CPG companies. Background information of case companies’ products and operations and observations on decision making and feedback for the pilot	10 semi-structured interviews exploring practices, use cases and benefits of data sharing
Analysis	Comparison of forecasts generated with and without POS data using a Bayesian approach	Thematic analysis of practices, challenges and benefits of retail data sharing

Source(s): Created by authors