top of page
hector-j-rivas-1FxMET2U5dU-unsplash (1).jpg

Our Thought Provoking Insights

Leveraging Data Science to Thrive Sustainably in Retail

Sustainability in retail encompasses everything from environmental impact to delivering long-term value to customers with high-quality products. It includes the materials used within product development, the transportation of goods, factory labour conditions and waste practices, amongst many more, and to satisfy an increasing cohort of environmentally conscious consumers, retailers must adopt a sustainable lens to strategize accordingly. However, it's important to understand what customers' sustainability expectations are and what is workable in a reactive retail environment.

It’s never been so challenging to understand what consumers genuinely believe about the whole issue of sustainability. Retailers need to figure out whether their customers are willing to pay extra to adhere to legislation and whether they are willing to wait longer for delivery to reduce emissions. They appear to have progressively more elevated expectations, but often their purchasing behaviour would suggest otherwise.

Fast fashion continues to drive more volume globally, regardless of flawed practices and the tremendous waste produced. Consumers claim they will support sustainable efforts, and with cancel culture rising, any brands found guilty of bad practices are being widely shamed.

Therefore, achieving a sustainable approach without alienating customers and supporting a convenient, positive shopping experience is crucial to encompass. But how best can these AI and science-led initiatives be used to reduce the impact on customers while tackling a sustainable-led supply chain?

Undertake the developing role of data science and AI for sustainable processes

Utilising and understanding customer data should be the first step in achieving a positive impact on profit, people, and the planet without sacrificing convenience. Looking at how your supply chain operates could be a great entry point for establishing a solution to this wider issue. In these efforts to be profitable and sustainable, retailers can leverage data science and AI technology to meet customer standards and sustainable goals. These AI capabilities can be used for more accurate demand forecasting, minimising the risk of excess inventory, and predictive pricing. Consequently, there’s value in educating the consumer about what sustainability looks like in retail and understanding why there may be higher costs of products due to the processes involved, and communicating these efforts through generative marketing, could see further rewards.

Working towards a satisfied conscious consumer

Improving allocation practices will give your customers what they want when they want it. Exploring an integrated planning ecosystem can improve decision-making, gaining increased satisfied customers through a sustainable data-led approach for a transparent supply chain. Combining these powerful data science capabilities to futureproof a conscious retail state needs reliable data.

Reliable data is the first step in implementing a science-led approach to planning. Transparency, visibility, and associated reporting can enhance decision-making at the supplier or manufacturer level. It sets up trust among suppliers and customers, leading to environmental stability for the future of retailing.

Understanding customer demand and improving allocation practices, an integrated planning strategy will transform how you manage your inventory. TPC can support adopting innovative technologies, from selecting systems providers to implementation and integration. We understand both retail and tech and work in the space in between, advising on which solutions to adopt and how best to integrate them, often developing customised bolt-on tools to operationalise to maximum effect.



Want to receive exclusive invitations to our events, expert industry analysis reports and exciting updates about our services?

Join our mailing list today! You can unsubscribe at any time.

bottom of page