Supply Chain Efficiency through Collaboration
There has been an evolution of initiatives over the years to improve the efficiency of the supply chain. It began with computerized software to help companies manage and control their internal data flows to support larger and more complex manufacturing facilities. This included but was not limited to Material Requirements Planning (MRP), Distribution Resource Planning (DRP), statistical forecasting systems, etc. The emphasis was on low-cost production through economies of scale based on sales forecasts supported by large inventories to ensure high service levels. Integrated plans relied on a Sales and Operations Planning process to ensure the specific goals of the organization were in-sync across functional groups.
Over time companies developed “Best Practices” in which businesses operated in a total “Closed Loop Supply Chain” where demand prompted supply and supply satisfies demand. The goal was to move from a make-to-stock towards a make-to-order environment in which the consumer’s purchase would trigger the production of a replacement unit in the factory and ripple back through the supply chain to the raw material suppliers. The pipeline or supply chain includes the production and movement of raw and packaging materials from vendors to manufacturing sites, the conversion of raw and packaging to finished goods, the movement of finished goods to distribution centers, and the monitoring of finished goods to the ultimate consumers.
Developments such as Electronic Data Interchange (EDI) allowed manufacturers to forge information links with key customers, effectively exchanging information in a timely manner. This customer connectivity further improved the efficiency of the pipeline but in most cases still operated in a make-to-stock business model. Other enablers such as bar coding and Advance Shipping Notices (ASN’s), similarly improved the speed and accuracy of exchanging information and thereby increased the integrity of the data in the pipeline.
Seeking further improvements, end users introduced new business processes such as Just-in Time (JIT) in the automotive industry, Quick Response (QR) for general merchandise, and Efficient Consumer Response (ECR), for grocery distributors and retailers. Continuous replenishment plans such, as Vendor Managed Inventories (VMI) were among the results. The major benefits from all of these programs are reduced inventories, fresher product, reduced stock outs and a quicker, more nimble supply chain. This reduces many of the indirect costs such as damages, aged inventory, and obsolescence, as well as the administration related to each of these activities.
Typically, the process change initiatives have been driven by the end users, as it has been relatively easy for them to achieve immediate results that benefited their bottom line. Suppliers and manufacturers have had a more difficult time obtaining tangible benefits. In many cases the result has been a shift of costs from the end user further back in the supply chain.
Real benefits can be achieved by reducing cycle times and by having a more accurate sales forecast. Many plants were built to support a make-to-stock strategy and to achieve the lowest possible manufacturing costs.
| Real benefits can be achieved by reducing cycle times and by having a more accurate sales forecast. |
They tend to be large inflexible operations that cannot respond quickly to changing demand. Reducing their cycle times and improving speed of throughput requires time and considerable resources to improve their response capabilities.
Even with a make-to-order strategy, considerable reductions in finished goods inventories are possible with accurate sales forecasts. Robust data will allow the internal processes to be optimized, assuming that the organization has the systems and tools to support the use of this information. The key is the accuracy and quality of the forecast. This is the true benefit of Collaborative Planning Forecasting and Replenishment or CPFR. It assumes that this process will result in a superior forecast; keeping supply and demand in greater balance.
Most assume that this requires elaborate systems and technology but this is not always the case. Some industries such as dairies and bakeries that produce products with a short shelf life already have informal collaborative systems in place because of necessity. They already support a make-to-order strategy with flexibility and surge capacity that allows them to make variable production requirements. Some have standing orders by retail location that are modified daily, based on actual consumer off-take. A more formal arrangement may improve the results, but the good performers already have a competitive edge.
Intuitively we all believe that collaboration will improve the forecast. This requires that we are willing to share information, which is not always practised. Some end users, especially retailers, view this data as proprietary. It provides them with a competitive advantage by having superior market intelligence and consumer insight for category management, promotional programs and support for their own private label programs. Another extreme is the largest retailer in the world sharing daily point of sale data by store location.
There is considerable debate over the pros and cons of both positions, but as logistics practitioners we support the elimination of waste wherever it can be achieved in the total pipeline. While it may not be possible to share the potential benefits because of unequal negotiating power, lower costs should ultimately result in lower prices to the end consumer. Staying competitive is the best method of ensuring long term survival.
Collaborative Planning, Forecasting and Replenishment
CPFR is the next stage of supply chain initiatives that has been developed in search of the goal for a seamless pipeline supply. Sharing of information such as sales, inventory levels, promotions etc. allows for co-managing the business processes and integration of the distribution network to meet the shared goals of superior service at the least total cost of operation. The assumption is, like the ripples of the waves that result from throwing a stone in a pond, the closer you are to the center of action, the smaller the chance of turbulence.
Hypothetical Sample Size
Standard Deviation Calculation Directional Relationship to Inventories
B) To relate this data to a degree of safety stock, the average demand (1640.5 / 12), 136.7 cases will be used to define future forecast. |
The primary benefit is the reduction of inventory levels and associated costs throughout the system releasing resources for other investments. Secondary benefits are also substantial and in the long run may even be greater than the inventory reduction, but are not possible without achieving the first goal. Reduced complexity, administration, and improved speed to market are only a benefits. Accurate forecasts are the result of collaboration that makes these benefits possible. Accurate forecasting is the critical factor that is needed to obtain the desired results. Technology is the enabler that has allowed this to occur, by providing the capability to manage the ever-increasing volumes of information linking the total supply chain.
Incentives for Change
To provide a means to express the CPFR opportunity for the manufacturer, a hypothetical assumption has been made for forecast error on an item over a 12-month horizon.
Obviously, the less accurate the Sales Forecast Accuracy (SFA), the greater the multiplier-effect toward safety stock. In the data shown, a weak performance of 50 percent SFA would reflect in a probable need for 49% of the average demand to be held in safety stock.
Building on the noted wins through improved forecast management, there are additional change agents related to standardized data management and an idealistic amendment in retailer attitude. In data management, the standards for storage and configuration have become much more consistent and generic across varied industries. Today,the eases of data extraction and sharing have literally exploded. With the web as the conduit, global transactions in 2002 could exceed $800 billion with 2003 transactions exceeding one trillion. The influence of reduced cash-to-cash cycles and paperless transactions has become very infectious.
Regarding the retailer, their perspective towards product supply has definitely changed. Carrying a manufacture’s product on shelf is more about selling privilege than selling obligation. Basically, store-shelf ownership lies more with the products’ manufacturer than with the products’ retailer. The manufacturer must take a stronger interest in the final sell-through or face the hardship of retail rationalization.
Clearly the risks and opportunities fuel the decision to get aggressive with collaborative partnering. With CPFR well defined in several channels today, logistics practitioners must take a stronger interest in this methodology and design to remain competitive and efficient for the future. To support this thought, a closer look at the actual process is needed.
Beginning the Process
From the manufacturer’s point-of-view the process begins at the end of the supply chain. It is the final “store-consumer” relationship that the manufacturer must focus on.
Having the point-of-sale (POS) data populating a statistical base forecast, the collaborative element begins to synchronize manufacturers and retailers around true replenishment timing and quantity. To build upon this activity, an event calendar is usually maintained to further ensure maximum supply chain efficiency is exchanged between partners on promotional and trade timings. Once the complete demand picture is defined, the manufacturer applies this against the retailer’s on-hands, lead-times, safeties and potential intransits to net a final replenishment quantity for production.
To illustrate this point, a retailer may have several regional distribution centers (RDCs) to fulfill to store (below). The manufacturer aggregates store level forecasts against store level availability as associated with the supply RDC. This net demand becomes the supplying RDCs forecast, which then is applied against the RDC stock availability. Aggregating the RDCs net demands should provide the manufacturer a final replenishment position and grant several opportunities to view, simulate, plan and grow the directional outcome of their products within the retailers’ supply network.
Populating numbers to the illustration, the final replenishment plan to the manufacturer could be built upon several netting levels along the retailers’ chain. As noted below, a certain item is followed from store level to RDC to manufacturer. Without overcomplicating the process with intransits, safeties and firm production, the logistics practitioner (who has the the correct data) could easily design and trace the complete supply-chain all the way to the final consumer and create a much stronger forecast plan.
Building upon this structure, exception management must be designed to expose potential stock-outs or overages at store. In a stock-out situation the focus likely would be on safety-stock management rather than forecast-adjustment due to the lack of backorder data and risks in trying to compensate for them.
With this general design and supply philosophy, what lies ahead for CPFR? Is this another logistics acronym to gravitate to, or is it a major building block to future development? As one contemplates future supply technologies, CPFR may evolve from data partnering to physical operational-partnering.
A Physical CPFR Model
What are the limits, defined by the scope of direction? CPFR could change the future landscape of supply by actually drawing like businesses together to achieve critical mass at every link.
Imagine the interpretation of forecasts, safety stocks, minimum runs and cycle times changing as links in the total supply chain are continually removed through innovation gained by CPFR. Web-based systems that communicate consumer needs, from the number of eggs in the fridge to how much oil and gas is in your automobile, would create an endless string of demand-feed to the supply hub of your choice.
A hub may be a group of manufacturers with similar trade and consolidation appeal which partner together to capitalize on operational, pack and distribution synergies. As you can imagine, the strengths of this coalition would be powerful. Areas such as mixed order, pallet and case would follow a seamless assembly as consolidated orders by business; brand and customer are all serviced through the same hub. Raw materials and warehousing could all fall under the same synergistic theme where the strengths of the whole overwhelm the sum of the pieces.
As illustrated below, the opportunities of this design are definitely challenging. However, through CPFR, customers, manufacturers and retailers may develop such trust and efficiency that this potential direction is inevitable.
The general philosophy of CPFR definitely is not rocket science. It is an obvious next step in the development of supply chain processes. Every link along the chain benefits from this collaboration and the competitive pressure to get connected is obviously well worth the investment. Failure to connect could slowly cut off the critical data streams needed to connect customers, suppliers, manufacturers and retailers. Success can no longer be measured on exclusivity and guarded data protection.
Supply chain waste and excess are well known facts, and the practitioners of CPFR are at the leading edge to take full advantage of eliminating them.
