Integrated Supply Chain Planning and Execution: Connecting the Retail Store to the Factory Door
8 March 2005
Andrew White   Jeff Woods   John Davison   

Source:  Gartner
Note Number:  G00123696

As foundational technologies such as radio frequency identification, global data synchronization and basic computing power evolve, new business practices are emerging that will fundamentally change the way that retail value chains plan and respond to consumers.

What You Need to Know 

Integrated demand and replenishment planning is a new response to an old problem — the integration of store-to-factory planning for a demand-driven supply chain. Innovative retailers are beginning to look at this area once again to secure the significant step-change in retail/supply chain performance, and to fuel collaboration with partners. Suppliers should look at IDRP when they seek to offer elevated levels of customer support and inventory utilization to retailers, and when asked to take over the responsibility by dominant partners. Retailers can use this opportunity to improve their in-store replenishment business process, paying particular attention to managing tasks that bring the product from the back door of the store onto the shelf.

Strategic Planning Assumption(s) 

Through 2006, 10 percent of the Global Fortune 100 retail operations will transform their demand and replenishment systems into demand-driven value chains to increase competitive advantage (0.7 probability).

Through 2008, 20 percent of the Global Fortune 100 retail operations will cite integrated demand and replenishment as key to revenue growth and improved customer service (0.8 probability).

Analysis 

Planning for and meeting consumer demand at the store level is a problem in supply chain management. Retailers and their suppliers have evolved many techniques and initiatives to enable faster planning and more-intelligent execution to eliminate out-of-stock shelves. Many of the world's largest retailers still use outdated, legacy or basic inventory planning approaches to attempt to maintain the appropriate level of inventory on the shelf. Each year, numerous initiatives promise incremental benefits in terms of out-of-stock reduction, but the core business processes of how consumer demand is used in forecasting and replenishment throughout the value chain have remained consistent. This is about to change.

Disintegrated Retail/Supplier Replenishment Today

Retail store forecasting and replenishment is a notoriously problematic business process because:

• Computer power has never been cost-effective or available to support the volume of data required to determine what needs to be ordered and when.
• Most retailers have developed and deployed different application solutions for a wide range of business processes that were interfaced but not integrated in the form of a single business process; for example, store ordering, allocation, merchandising, category management and replenishment buying.
• The science of forecasting and replenishment has not advanced significantly since the 1970s; regression and causal engines have only limited use; coping with spare data at the store level and allocation routines have evolved little.

The largest retailers struggle the most with dated methodologies and practices, and typically collect information about sales and inventory on a daily basis. Some segments, such as grocery, lack perpetual inventory control systems. Typically, the largest retailers use variants on reorder-point solutions (such as minimum/maximum, order up-to, optimized order quantity) at the store level for short-term reactive planning. These retailers then apply real planning processes centrally at the corporate level. At the warehouse level, statistical forecasting is applied to aggregated point-of-sale (POS) data, and forecasts or profiles are defined by store formats or groupings. In other words, there is no real-time-phased dependence on supply and demand between the store and the rest of the value chain — it is as if the entire chain is "headless." Slight variations in demand at the store level are notorious for creating tidal waves of activity across an entire value chain as each dependent layer tries to interpret trends with little coordination with the other tiers of the chain. Consequently, retailers struggle to make effective planning decisions at the store level (such as promotions and local category and assortment changes) and, through the store-profiling allocation, actively insert forecast error into the process (see Figure 1).

Figure 1.
Current Retail Supply Chain Best Practices

Source: Gartner Research (March 2005)

Based on our research, the typical business characteristics associated with current best practices are:

• Push-based demand-planning processes
• Pull-based replenishment process
• A lack of demand visibility in replenishment models
• A lack of replenishment opportunities or conditions in demand-planning models
• A growing emphasis on better execution (deployment, allocation) because "planning" is always out of date

This leads to a disconnected value chain that generates excess inventory across the entire chain.

Integrated Retail/Supplier Replenishment in the Future

However, a combination of several technological threads — which we call integrated demand and replenishment planning (IDRP) — is about to provide an opportunity to remedy the retail supply chain dilemma. This process is built on distribution requirements planning (DRP), a concept founded by Andre Martin in the early 1980s that has been used effectively by distribution-intensive manufacturers. It is a process by which all nodes of a network — factories, warehouses, distribution centers — are connected such that independent supply and demand is replaced by dependent relationships. For retailers, DRP is a new term and a new idea. However, the combination of the following capabilities is enabling innovative retailers and their partners to rethink their entire value chain model.

• Triggering item/location-level activities
• Automating (through net change, perpetual or event-driven processing) which items are demand- or replenishment-planned
• Integrating store-level space constraints and requirements (back-room fulfillment) with entire supply chain replenishment
• Integrating event-driven and message-based execution systems with smarter, more-selective (net-change or perpetual planning) engines for localized or "as needed" re-evaluation of decision making
• Integrating task management systems to monitor the in-store business process from back-door receiving to shelf replenishment

The scope of retail planning will expand from forecasting and replenishment to full supply chain resource management, including transportation, space planning, labor planning and financial planning. IDRP results in a single, integrated set of plans that are shared across a retail organization and among organizations in the supply chain, such as suppliers, freight companies and third-party logistics. This may not necessarily be achieved through one single data model or application, although this would simplify initial implementation. As integration across the entire value chain increases, a new level of granularity will emerge in which decisions to restock shelves will be analyzed using variables such as cost and profit, rather than just service. This will herald a more-universal interest in factory gate pricing. This is the demand-driven, performance-focused supply chain (Figure 2).

Figure 2.
Future "Next Practice" Retail Value Chain

Source: Gartner Research (March 2005)

What Changes Must Be Made to Achieve IDRP?

IDRP is not a panacea. Several changes or enhancements to the classic DRP process will be necessary.

• More work will be needed in forecasting slow-moving products using aggregate data (so that the aggregation of demand at the store-level does not result in an aggregation of error), and altering the classic DRP replenishment logic for slow-moving products. The use of net-change combined with perpetual (in-memory) planning will be needed to handle the wide range of demand and replenishment planning cycles that products exhibit. This will be achieved by DRP-type engines that embed business-activity-monitoring technologies.
• Integration of retail planning systems (merchandise, category and promotion planning, as well as store-level inventory and space management) will need to change because all the planning data is no longer stored corporately with assumptions about store and consumer-based demographic behavior. In the new model, actual stores and actual consumer responses will be modeled, rather than assumptions. This will replace one set of errors (man-made by retailers) for a real set of errors derived from the forecasting and replenishment process at the store level that was previously overlooked by the assumptions that retailers made in their store models.
• Integration of retail planning systems (merchandise, category, promotion planning and space management) will deepen and the process will span these traditional silos. It is inefficient to have a separate forecasting system in the planogram system, another in the category management system, and so on. A single forecasting system will be used to drive these other systems, providing retailers with a single integrated set of numbers for the first time.
• Changes in the integration points between planning and execution will be required so that execution is more "network-aware" and, hence, more able to provide intelligent decision support (profit-driven allocation, re-allocation, cross-docking and back-room fulfillment from inventory needs on the shelf).
• Changes in collaborative business processes will enable the retailer and supplier to synchronize two time-phased plans, as buyers and sellers are exposed to high levels of automation of analysis of the time-phased data.

Benefits

An integrated approach to demand and replenishment connecting store to factory door is likely to yield benefits in the same way as synchronized (lean) distribution and DRP did to older, reorder point-based environments. Cost structured to provide the service will ultimately fall, inventory levels will fall and competitive advantage will accrue to early adopters. Benefits will include:

• Lower inventory levels
• Altered inventory ownership, as control of inventory will shift from retail to suppliers via more achievable scan-based trading programs that can be implemented in an IDRP-like solution, particularly in North America
• Faster cycle times, which are important for fashion, perishables and other short life-cycle categories
• Improved customer service/lower out-of-stocks (cutting out-of-stock measurements by as much as 50 percent)
• Reduced transportation and distribution center labor costs

Our research showed that when DRP replaced reorder-point methodologies in the past, savings in terms of inventory for some implementations exceeded 40 percent, cycle times fell as much as 30 percent, and costs from unbalanced inventory and excess/obsolescence fell by as much as 80 percent. These numbers are high level and not specific to an industry, but it is clear that the adoption of IDRP by retailers has the potential to achieve great savings.

Early pilots and implementations of this process are now under way in the United States and Europe by giant retailers such as Argos, Cole National, J.C. Penney, Kroger and Sears. A full scorecard and analysis of results will be as important to the early adopters as it will be to the fast followers and vendors of this technology. These initial results will drive much of the hype associated with this initiative (see "Hype Cycle for Retail Technologies, 2004"). However, reviewing data from distribution-intensive environments where classic DRP has long been in place will provide deeper insights as to the potential scale of benefits.

What Are the Characteristics of IDRP?

The core element of an IDRP system is its ability to model the entire physical and virtual network — all with one business process.

An IDRP system includes the ability to:

• Model the entire physical and virtual network, including store locations, retailer storage locations, supplier storage locations, and suppliers or factory shipping locations
• Plan all items at all locations for demand and replenishment evaluations on a timely basis (perpetually available to replan based on priority, although real-time replanning for all items is not actually needed) for the entire network
• Apply independent forecasting techniques at the store level for extended planning periods (up to more than a year)
• Apply independent forecasting and dependent planning at all other levels of the network
• Model varying levels of constraints across the entire network
• Provide item/location planning cycles on a daily (or more frequent) basis, or more frequently for perishable items
• Periodically classify item/locations for more-efficient processing
• Integrate with the supply chain execution systems of the supplier and the retailer to support dynamic allocation or deployment, whereby previously published plans are revised locally, based on new data
• Use various methods to trigger consumption and replanning/execution, such as bar code, POS and radio frequency identification devices
• Integrate multilevel replenishment signals, from shelf-based or inventory-based messages to the store's back room for floor replenishment to networkwide messages for the supplier to initiate replenishment to retailer warehouses (scan-based trading or direct store delivery)
• Net inventory and lead time from store-level planning to roll up to a dependent forecast at the distribution center and warehouse levels
• Support direct store delivery models by enabling independent forecast models at any level of the network
• Support scan-based trading, factory gate pricing and vendor-managed inventory models using the same data architecture
• Integrate with accounting systems to indicate changing ownership of inventory (for scan-based trading)
• Integrate with collaborative planning, forecasting and replenishment; and with other collaboration processes to enable comparison of independently calculated demand streams (where applicable)
• Model shelf space constraints and networkwide movement and logistics constraints
• Integrate or model sufficient logistics and storage constraints, or support interactive communication models with transportation management systems

IDRP is not a new concept. However, a single offering that can be deployed and supported in such a fashion does not yet exist. Several vendors are active in multiple areas, although none actually supports the entire model (see Note 1).

Integrated systems are just beginning to appear in pilots in the United States and Europe. Small and specialty retailers have been fortunate that their data volumes have enabled them to implement regular DRP systems in a store environment. New solutions are enabling larger retailers to enjoy the same benefits. Additional industry efforts will offer the ability to implement IDRP or to leverage high levels of integrated planning and execution. Global data synchronization will help ensure that the data needed by such business processes are kept clean and in synch across the value chain; and radio frequency identification will assist in making replenishment systems more responsive to actual inventory consumption.

Key Issues 

Which emerging technologies will have the most impact on software users, vendors or markets?

Note 1

IDRP Vendors

• i2 Technologies, with its new releases of Demand Planner and Replenishment Planner
• Tomax, through a partnership with Retail Pipeline Integration
• Manugistics, through its experience in DRP systems for distributors and manufacturers
• Teradata, a division of NCR, through its acquisition of the Stirling Douglas Group; now called Teradata Demand Chain Management 
• SAP, through its original equipment manufacturer partnership with SAF AG
• Blue Agave, Vision Chain and VMT, which offer "POS/analytics-based replenishment" for retail value chains from the "store to the distribution center"

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