The Power of Downstream Data for Sensing Demand
Lora Cecere, CEO of Supply Chain Insights, has released a useful new report entitled “The Power of Downstream Data” which describes previously undocumented benefits for collecting and analyzing downstream supply chain data. Downstream data is the demand data that powers a market-driven, “outside-in” supply chain. It translates demand streams into a demand signal for each Stock Keeping Unit (SKU)-Location for a reliable forecast.
Cecere defines downstream data broadly, as “data that comes from the channel, offering insight on demand and buying patterns. It includes 3rd-party syndicated data, direct store-level point of sale [POS] data, store-level inventory data, and retailer or distributor warehouse withdrawal data.”
She says that downstream data “makes a substantial difference in retail execution, inventory management, and improving on-shelf availability.” At this point, those benefits have been well documented in previous studies from various sources. But this new report offers three additional benefits for leveraging channel data in a consumer-facing supply chain:
- Improved demand sensing and replenishment for long-tail products – A Supply Chain Insights simulation shows that exploiting data at the point of sale for long-tail products improves replenishment by 60-70%, with fewer out-of-stocks. This is because long-tail products are particularly susceptible to demand latency that creeps in when you don’t take advantage of POS or retail warehouse withdrawal information.
- Sell-In for new product launches – Cecere reports that new products have a demand error of 70%. “As a result, the product forecast is a poor indicator of what will sell. Initial shipments are also not a good signal. The reason is simple. Initial shipments represent pipeline fill. Without a good forecast, or a good signal of historic shipments, POS data aligns the organization on new product launch fulfillment.”
- Improved localized assortments – Downstream demand data can be used to create assortments that capitalize on localized consumer behaviors better than historic demand averages that do not capture regional geographic demand patterns (see chart at top of page).
The biggest challenge for many organizations can be getting the data in the first place. Organizational silos stymie the use of downstream data in supply chain. Supply chain teams may be focused on order and shipment data; sales is working with downstream data for reporting, assortment planning and category management, and retail execution; marketing may use 3rd party syndicated data that is weeks old.
A Demand Signal Repository (DSR) can help to synchronize all this demand data in a centralized database that integrates demand data from various points of sale, wholesalers, warehouses, and stock movement and promotions. We also have seen success at vertically integrated retailers, like Costa Coffee and Amplifon (aka “Miracle Ear”), who have access to much of their POS data.
Cecere reports that the firms that have leveraged this data have achieved up to 50-70% improvements to on-shelf availability, fewer stock write-offs and improved organizational alignment. In a separate analysis, published in her Supply Chain Shaman blog, Cecere says, “… companies find that the use of downstream data pays for itself in less than six weeks, every six weeks, and companies that were good at the use of downstream data and sensing channel demand aligned and transformed their supply chains 5X faster than competition.”
Cecere thinks downstream data is a key to future supply chain planning. She concludes, “As markets become more complex, the use of channel data will differentiate leaders from laggards.”
Click below to read more on the benefits of downstream data for sensing demand.