The research examines the relevance of the data economy for the consumer goods sector and aims to derive a winning model of value creation. A major structural barrier in this sector restricting the direct relationship of brands and consumers has been the intermediary role of retailers. The retailers use extensive consumer data in terms of personal information and purchasing behaviours. However, due to access problems, brands are not able to implement such strategies. Therefore, the winning model should try to eliminate this barrier and create direct links between the brands and consumers. This research conducts quantitative data analysis using macroeconomic data for the case of the UK, along with a qualitative analysis of the literature to arrive at a model. The quantitative analysis shows that in the UK, the consumer goods sector displayed a growth rate very close to the GDP growth. However, there have been significant differences between sub-categories. Clothing and footwear displayed very large growth rates, while the size of the alcohol and tobacco sector declined in the last two decades. The correlation and regression analyses showed that GDP and consumer confidence affected the sector positively, whereas the unemployment rate affected it negatively. Then, the qualitative discussions showed that two strategies of servitisation of the consumer products and the establishment of big data analytics are the most feasible strategies to create value for the sector and brands.