In Part 1 of this blog series, we shared a spectacular success story that popularized supply chain collaboration back in the 1980s, and laid out the path for all retailers and their suppliers to follow.
In Part 2 of the series, we explored a solid roadmap to evolve your supply chain collaboration practices and accelerate the deployment of collaborative best practices on a wider scale.
In Part 3, we will take a closer look at what many companies deem to be state-of-the-art supply chain collaboration. What are the best companies doing today, and what are the main challenges with their approach?
Bridging the Divide Between the Retail and Manufacturing World
A fascinating evolution occurred over the last few years in how more and more advanced types of supply chain collaboration blurred the lines between retail and manufacturing supply chains.
Traditionally, a retailer would accept responsibility for his or her own warehouses and force suppliers to ship into these warehouses based on strict shipment schedules. The manufacturer would ship directly from their warehouse or plant into the retailer’s warehouses. And from that point onwards the retailer would supply its various store formats supported by their logistics models.
Clear boundaries and arrangements between each retailer and their manufacturer existed. The retailer would define the rules of engagement of supply chain collaboration in terms of merchandising, shelf space allocation, replenishment and promotion planning, as well as payment terms and logistics operations.
In order to increase margins and better control their supply chains, retailers started to expand into manufacturing. (See orange arrow in graphic). Private label merchandise and the integration of certain retailers with their private label suppliers are examples of this trend. Similarly, manufacturers started opening new channels and retail outlets for their products (See blue arrow in graphic). Luxury brands and high-tech companies such as Apple and Tesla opening new types of stores are examples of that trend.
This blurring of the borders and breaking up of siloed processes led to a strong need for new collaboration protocols and standards to run these evolving supply chains. One of the most widely adopted and successful of these new protocols and standards that drive retailers and their suppliers to tighter supply chain collaboration is Collaborative Planning, Forecasting and Replenishment (CPFR®).
Addressing the Challenges of CPFR
For the last 25 years, inter-industry committees have been working on standards to harmonize the collaboration of retail with their manufacturing partners. The Voluntary Inter-Industry Commerce Solutions (VICS) committee spearheaded some of these efforts and created and trademarked the widely used VICS CPFR model.
VICS also contributed to numerous other technical and business process innovations such as barcodes and electronic data interchange (EDI), Item Level RFID Initiative (VILRI), and Store Level Distribution Resource Planning (DRP), but CPFR is the process enabling the planning and execution collaboration that retailers and manufacturers have been seeking.
However, there are five main gaps or constraints with CPFR documented in a VICS whitepaper titled The Ultimate Supply Chain Machine. (www.VICS.org) Here is a brief summary of those gaps.
Gap 1: Current store level systems support planning consumer purchases. Since these forecasts cannot be leveraged in upstream demand modeling, however, retail planners often neglect forward planning in favor of planning only short-term product needs or events.
Gap 2: Current store level systems are essentially execution systems, not planning systems. They often have no capability to incorporate a volume forecast of products the store will need beyond the current order, much less next week, next month or next season.
Gap 3: Current retail DC systems forecast what stores will need based on historical shipments to stores. This forecast is completely disconnected from store-level sales forecasts and does not account for variables such as current store sales or inventory.
Gap 4: Because retail DC systems are not based on actual store-level demand, they lack the accuracy to adequately forecast the products and quantities the retail DC will need tomorrow, next week, next month or next season. The only demand information provided to manufacturers is an order, which sometimes comes as a complete surprise.
Gap 5: Currently deployed retail store-level forecasting solutions are not scalable for handling the extremely large computer processing requirements of store-level DRP calculations.
One of the most significant questions about collaboration has been: “How do we scale?” From the beginning, the CPFR model assumed capabilities to share sales and order forecasts. Spreadsheets were often the only medium of sharing, however, even if those spreadsheets were maintained in collaborative software hosted on the web.
More recently, computerized solutions capable of handling these requirements have become available for large-scale implementations. These highly scalable programs have proven that retail DRP systems can be practical and that this approach improves on-shelf availability for consumers and lowers supply chain inventory and operating costs.
In my next post in this series, we will look more in-depth at how these solutions can overcome the limitations of CPFR and scale, before covering how you can accelerate the journey in my last blog post.