Win the Retail race by sharing data

Written by:

Fouad Talaouit-Mockli

Charlotte Ledoux

Reading duration:5 min


Guess what, the bullwhip effect is back… At all levels of the supply chain, each actor - customers, suppliers, manufacturers, and retailers – have an impact on the final response to demand. As these different parties try to respond to demand fluctuations which are now high due to customers changing habits or unpredictable events, they create the bullwhip effect where each party gradually escalates its orders due to an initial variation in demand. If parties were sharing more to each other the data they have on demand and capacity, this would not happen.

A complex and global supply chain involves thousands of suppliers, logisticians, distributors and generates indeed huge volumes of data at various points of the supply chain:

  • Point of sale data: products sold with prices, store stock management, demand forecasts.
  • Supplier data: supplier risk, price negotiations, stock.
  • Production data: real-time monitoring of production and equipment maintenance, bottlenecks.
  • GPS data: real-time stock location, lead time reduction.
  • RFID data: real-time stock quantity, automatic supply, automatic stock movements.
  • Exogenous data: weather, local events.

The whole supply chain could be more efficient if each party knew what’s going on at the other end. So how come retail actors are not already sharing their data with their supply chain partners at least?

Why it’s scary to share data

- Enterprise mindset: switch from asset ownership to asset sharing

There is a gap between retailers who have the knowledge from their point of sales but don’t have the visibility on what’s going on at their suppliers. And this gap is voluntarily kept because the price negotiations are tough on both side of the barrier. And above that, there is also the fear from retailers of giving away valuable assets to the competition.

- Lack of technology for compliance and security

It is extremely difficult to integrate the data across different sources, partners, and locations as there is no single source of data that can connect the multiple stakeholders of a supply chain. And this central store must be GDPR compliant and secure, but most actors are still using Excel sheets and struggling with the setup of a datalake or cloud migration.

- Lack of analytics / data science skills

With no surprise, data science and analytics are skills that are still rare on the market even though there are many online courses on the subject. And an AI project require different set of skills that cannot be supported by the data scientist alone: ML Ops, DevOps, Architecture, Data Engineering, Product Management… Retailers need to recruit all these professions or train / raise awareness internally to understand the value that can come from sharing data and doing AI collaboration.

- Monetization instead

Many retailers and suppliers think the monetization of their data would help them to generate more revenue. But when it comes to defining a price, it is complicated… and who would want its business to rely on buying data monthly? What if the price doubles in the next months?


What’s to win?

Predict demand with collaborative sales forecasting

To better match supply and demand what better way than to share information in real-time between supply chain partners? Collaborative forecasting is a very efficient way to share POS data, sell-in, exogenous data (weather, events, etc) to create more accurate sales forecasting models. Real-time manipulation between retailers and supply chain partners not only saves time in the realization of models but also ensures the quality of the data used.

Increase suppliers and retailers sales performance

Retailers have the downstream vision of sales with the finest grain: sales per channel (store, website, direct…), per category, per promotion, per customer segment. These insights if shared with suppliers, could enable more revenues through personalization, co-branded marketing campaigns or new products.

Create valuable partnerships in the ecosystem

Sharing data on trends or specific insights can improve partnerships in the ecosystem. It could be a great way to build a common strategy across retailers and CPGs with transparency, to deliver new shopper experiences or sell through other channels for example.

Optimize inventory and resources

A complete view of suppliers, storage and distribution capacity compared against predicted demand enriched with weather and social-economic disruption could help ensure that inventory stays stocked. A shared vision of cross channel demand would also allow for a supplier to play a larger role in shipping their products directly to consumers in small packages instead of sending truckloads to a regional retail distribution center.

Know your customer and improve its experience

Retailers have launched initiatives to build Customer Data Platform to centralize customer data for all touchpoints from pre-purchase to point-of-sale to post-purchase customer care. The idea here is to enrich this pot of data with data from all channels and from other sources (social media, ad partners, etc) to get a 360° view of each customer. Retailers and ad partners can then orchestrate together customer journeys with targeted and personalized communication.

Improve satisfaction through better loyalty programs

Loyalty programs are a tool for retailer to increase customer engagement and get more insights on them. But for the customer, it must be consistent across channels. And this can rely on a cross-channel loyalty platform shared with suppliers to centralize and aggregate consumer behavior, type of offer and performance metrics in a single source of truth. Suppliers could improve their promotions plan and choose the right promotional tool for each target. You can check out Sainsbury’s example here.

Define and monitor common KPIs on sustainability / CSR

Retailers and suppliers are setting up objectives towards zero-carbon emissions and on a larger scope on their CSR. To consolidate KPIs and track progress for the whole supply chain, they need to share data related to emissions, packaging composition, transport etc. It would be also a great way to define incentives for all stakeholders involved.


Forward-thinking retailers have already understood that their data alone has poor value. They are eagerly seeking new ways to share data and knowledge to gain a 360-view of the entire supply chain that drives more sales, minimizes time-on-shelf, and protects against out-of-stock or excessively overstocking. What we see today is that this type of collaboration project is initiated by the retailer who imposes its conditions of access to the data, which does not encourage suppliers to participate.

So during these data & AI collaborations, privacy of data shared must be maintained, either by aggregating data or using anonymization policies before sharing. And sharing data doesn’t mean a security breach will happen. Retailers and suppliers need to learn how they can move past security concerns by coming to an agreement on which individuals or entities are allowed to view and access the data being shared.

Good news is that these obstacles can easily be overcome as solutions are available: we’ll tell you more about ours next time, stay tuned!