Although it was first introduced with SCM 4.0, few users have leveraged SAP Inventory Collaboration Hub (SAP ICH) to take control of large inventories in numerous locations. Those in retail and other industries with such requirements will find they can manage large operations more easily.
Key Concept
SAP ICH is heralded as SAP's strategic supply chain collaboration platform. Requirements of the magnitude retail operations demand often compromise APO performance or server cost significantly, due to APO's dependence on liveCache memory. Prior to ICH, retail companies had to consider implementing non-optimal solution designs, including interfacing legacy non-SAP tools with an R/3 execution backbone to handle such sizing challenges. SAP Inventory Collaboration Hub (SAP ICH) was first available with SCM version 4.0, and it remains one of the more novel products in 4.1, the latest SCM offering. SAP ICH is tailored for the significant sizing requirements of retail and other industries with large product-location combination environments. Later, I'll describe how the scalability challenges of a well-known retail apparel conglomerate were met using an SAP solution based on SAP ICH and APO. Given the relative newness of the SAP ICH offering, I'll begin with a general introduction to SAP ICH.
Note
The SCM 4.1 software bundle consists of the APO technology that has been available since 1998 (Demand Planning [DP], Supply Network Planning [SNP], Production Planning and Detailed Scheduling [PP/DS], Transportation Planning/ Vehicle Scheduling [TP/VS], and Global Available to Promise [GATP]) and the newer SAP ICH and Event Management (SCM EM) components. SAP ICH and SCM EM were first introduced with verson 4.0 in late 2003 and were greatly enhanced for the current 4.1 release.
ICH Overview
SAP ICH is positioned in the "collaboration" quadrant of SAP's latest SCM 4.1 suite offering. Besides SAP ICH, SCM 4.1 includes SAP APO, SCM EM, and various logistics execution components. SAP ICH is, however, a much newer and less mature product than APO.
SAP ICH was first introduced with SCM 4.0 and greatly extends the functionality and scalability of the base vendor-managed inventory (VMI) function available previously within the R/3 and APO SNP solutions. The SAP ICH platform is much less dependent on liveCache memory than APO. This new architecture allows SAP ICH to scale up to the huge sizing requirements of the retail, consumer products, and other industries effectively, where APO alone cannot. APO, R/3, and SAP Business Information Warehouse (BW) act as back-end complements to SAP ICH.
SAP ICH is a transactional engine offering both customer- and supplier-facing collaborative features. It also provides both a Web-based user interface, via SAP Enterprise Portal, and an advanced message processing capability, which is built on SAP's NetWeaver Exchange Infrastructure (XI) technology. When combined with APO and R/3, ICH provides for the evolution from standard VMI to true collaborative planning, forecasting, and replenishment functionality.
The SAP ICH platform can handle several different collaborative viewpoints and business processes. In its Supplier Managed Inventory (SMI) or Supplier Collaboration adaptation, it is essentially a VMI application hosted by the customer for the use and the cobenefit of its various suppliers. For example, a large retail company would recommend that its suppliers use its SAP ICH SMI infrastructure to manage its retail store inventory levels and replenishment in a standardized manner.
SAP ICH SMI provides several functional blocks for managing the supplier-customer collaboration process. The Inventory Monitor is a portal for visualizing inventory levels and managing replenishment to established minimum and maximum levels. The spreadsheet-like appearance of the portal is representative of all tabular SAP ICH screens. The Demand Monitor provides a vehicle for comparing customer demand plans with vendor supply plans, along with planned and confirmed replenishment orders. Functional views for managing purchase orders, releases from scheduling agreements, and exception alerting are also available.
The other main application of SAP ICH is the more traditional, customer-facing VMI or Customer Collaboration adaptation hosted on the vendor's infrastructure. SAP ICH VMI functionality is the focus of the retail customer implementation example described later. SAP offers two variations of an SAP ICH VMI solution. Which to use depends on the type of back-end R/3 execution system to which it is interfaced and the industry in which it is applied.
The Forecasting and Replenishment solution is provided for retail industry environments running R/3 IS Retail as their execution system. The Responsive Replenishment solution is provided for use in standard R/3 environments in various industries, such as consumer products, pharmaceuticals, high tech, and chemicals.
The Forecasting and Replenishment and Responsive Replenishment solutions are similar in that they address the same "pull" replenishment process requirements characteristic of VMI applications. Both of the solutions access customer retail store sales, inventory, and promotion projections; calculate forecasts; make replenishment decisions; and optimize replenishment orders.
Both solutions also have common architecture, including use of Time Series Data Management and Order Data Management for data storage, the Logistics Inventory Management Engine (SCM-ECT-LIM) for inventory modeling, SCM master data and customization with enhancements, and XI as the integration technology. Both Forecasting and Replenishment and Responsive Replenishment also provide tabular planning views. Figure 1 provides an example of the Responsive Replenishment short-term planning view.

Figure 1
Short-term Forecasting view in SAP ICH Responsive Replenishment
Forecasting and Replenishment and Responsive Replenishment have significant differences in functionality. Forecasting and Replenishment primarily serves retailers by facilitating planning for store replenishment from DCs as well as replenishment of these DCs from manufacturers. Responsive Replenishment, on the other hand, primarily serves manufacturers by planning for replenishment of DCs and not usually the replenishment of retail stores.
The strength of Forecasting and Replenishment is its forecasting capability inherited from SAP's partnership with another German software company, SAF. The forecasting algorithm used takes into account demand influencing factors (DIFs) that are critical to retail forecasting accuracy. The solution also provides for consideration of store shelf restrictions and uses a new exceptions management tool specific to Forecasting and Replenishment. Forecasting and Replenishment provides for temporarily active products and locations and interfaces with point-of-sale (POS) systems — e.g., PIPE. The solution currently uses Remote Function Call (RFC) technology to interface with R/3 IS Retail master data and uses SAPGUI as a user interface. Architectural improvements in this area are expected as the Forecasting and Replenishment product evolves and matures.
Differentiating features of Responsive Replenishment include external data handling capability via the Data Import Controller, extensive promotions handling, transport load building, and the ability to plan on a subdaily level. The solution also uses the full suite of APO forecast algorithms and utilizes the Core Interface (CIF) to interface to R/3 master data. Responsive Replenishment also uses the standard SCM alert framework and monitor for exception management and provides a Web-user interface.
Both of the SAP ICH VMI solutions are designed to overcome tough performance challenges due to the huge planning environments found in the retail, consumer products, and similar industries. Current scalability goals for Forecasting and Replenishment are: 40,000,000 location-product combinations, 200,000 master data changes/day, 6,000,000 POS transactions/day, 2,200,000 order line items/day, and 600,000 inventory changes/day. The sizing goal for Responsive Replenishment is 12,000,000 location-product combinations to be planned weekly. SAP continues to make progress toward these scalability goals by working with key pilot customers as these offerings evolve.
Retail Implementation Case Study
Now that I've described SAP ICH, let's take a brief look at a retail implementation example. The company is a large, well-known apparel company based in the US that operates about 5,000 retail stores across multiple apparel retail brands. It is heavily dependent on its Asian apparel subcontractors and, thus, has a critical need to optimize its use of overseas supplier capacity.
Also, in the retail fashion business, products have long development cycles and relatively quick obsolescence, requiring both long- and short-term demand and supply planning. This company's retail stores must also be replenished effectively on a day-to-day basis to take full advantage of customer buying trends and to avoid stock outs. Therefore, this company's functional planning requirements span the whole spectrum: prepositioning capacity with subcontractors years in advance, seasonal fashion inventory deployments, and immediate retail replenishment of in-store items. These functional requirements are tough for any single supply chain solution to meet.
The company specified the following key business goals for the SAP implementation: optimize sourcing of contract manufacturing capacity and use of component materials, establish long-range planning based on available data, provide for more planning iterations per year, and optimize inventory levels and positioning through improved demand forecasting and supply network planning. Benefits for this implementation were estimated to be about $300 million, to be gained primarily from sales revenue uplift, inventory reduction, and improved subcontractor capacity utilization.
The original solution footprint was quite broad, as was expected given the functional requirements. It included the R/3 Apparel and Footwear solution (AFS), R/3 IS Retail, APO DP and SNP, and two non-SAP legacy advanced planning tools. The R/3 AFS system was to be used to manage apparel sourcing and subcontract manufacturing, while the IS Retail system was intended strictly for retail store inventory management and replenishment. APO DP and SNP were added to facilitate advance subcontractor modeling, capacity planning, and optimal demand-supply balancing.
With no prior experience with SAP ICH and knowing the scaling limitations of APO, the project team had originally advocated using a legacy tool for retail store planning. In addition, another non-SAP tool was to be used for specialized fashions and basics demand planning.
Besides functionality, sizing was a major challenge for this retail apparel customer, with:
• 5,000 retail stores
• 250,000 finished good materials
• 400,000 component materials
• 15 distribution center locations
• 1,200 vendor factories
• 125 million material/location combinations
At first, the project team was willing to allow significant redundancy, in both hardware and software, to scale effectively in such a huge planning environment and to provide specialized fashions and basics planning functionality. This customer's sizing requirements were clearly at a level that APO alone could not reach. Customer management was justifiably concerned that such redundancy was not an optimal situation, given the implications on total cost of ownership. Maintaining three vendors' planning infrastructures, developing redundant internal advanced planning skills, and developing and maintaining interfaces from legacy systems to SAP R/3 were obviously not desirable undertakings.
Therefore, management was interested in learning how SAP ICH Forecasting and Replenishment, when combined with APO, could effectively handle its scalability requirements. Of equal interest was how it might use the BW-based Merchandise and Assortment Planning (MAP) and Business Planning and Simulation (BW-BPS) tools to provide for fashion planning and basic demand planning. If this SAP-centric approach worked, it would eliminate the need for both legacy infrastructures and significantly reduce total cost of ownership going forward. Figure 2 shows the proposed SAP-based design.

Figure 2
SAP-centric solution for retail apparel customer
The SAP solution architecture was composed of R/3 AFS connected to APO via the SAP APO CIF and ICH Forecasting and Replenishment interfaced to R/3 IS Retail via RFC technology. These two binary execution system installations were then bridged via SAP NetWeaver XI. The R/3 AFS-APO was installed to plan and manage the source and make supply chain processes, i.e., from the subcontractor's vendors to the subcontractor and on to US-based regional DCs.
The R/3 IS Retail ICH Forecasting and Replenishment was installed to plan and manage the deliver and return processes, i.e., from the regional DCs to the local retail DCs, and finally replenishment of the retail stores. SAP BW-based MAP and the associated BW-BPS solution were to be used to carry out the sophisticated fashions and basics apparel deployment planning required.
Since SAP, at the time, did not provide an out-of-box interface between APO and SAP ICH Forecasting and Replenishment, the project team had to design a custom interface using SAP NetWeaver XI technology. Figure 3 depicts how the custom interface was designed. From a conceptual standpoint, the retail side of the customer's supply chain was separated from the wholesale supply side of the supply chain. This was done to divide the huge number of product-location combinations required for demand-supply planning, making the scale more manageable.

Figure 3
Integration between APO and SAP ICH Forecasting and Replenishment
Dummy DCs in APO were used as the logical construct to connect SAP ICH Forecasting and Replenishment to APO. These dummy DCs mirrored the company's regional DCs, which were used to source the local area DCs. These, in turn, were used for replenishment of retail stores. Replenishment demand signals were first netted against existing local DC stocks within Forecasting and Replenishment with overages passed to the regional, i.e., dummy, DCs, and then on to APO. APO DP was used only as a convenient pass-through or input mechanism for Forecasting and Replenishment's replenishment pull demand and BW-based fashion and basics push demand. APO SNP then received and netted the demand at the regional DCs and passed unfulfilled demand to Asian apparel subcontractors.
SNP multilevel, heuristic functionality was used to realize the business goal of optimizing the sourcing of contract manufacturing capacity and raw materials while meeting customer demand. Specifically, the "subcontracting with third-party provision of components" functionality within SNP was used to model interaction with Asian apparel subcontractors and their vendors. This variation of base subcontracting functionality allowed the modeling of the subcontractor's direct procurement of components, as opposed to first going through the customer's enterprise. This approach fit the company's needs and resulted in more efficient transaction processing. See Figure 4 for an example of SNP "subcontracting with third-party provision of components."

Figure 4
SNP "subcontracting with third-party provision of components"
Charlie Bienvenu
Charlie Bienvenu is director of SAP supply chain management at Pragmatek Consulting Group (www.pragmatek.com). Pragmatek helps its clients realize significant productivity gains and increased profitability by applying process improvement techniques and optimizing SAP business systems. The firm's team-centered approach helps clients to diagnose problems and identify improvement opportunities that can reduce cost, increase revenue, and capture value. Charlie was previously with Capgemini as a senior manager in its supply chain management practice. Prior to that, he spent seven years with SAP America as a project manager in its supply chain management practice. He is a member of the Supply Chain Council, participating on its metrics committee, and holds a master's degree in quality management from Loyola University.
You may contact the author at charlie.bienvenu@pragmatek.com.
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