The Supply Network Planning (SNP) module in SAP Advanced Planning and Optimization (APO) technology allows organizations to plan for sourcing, production, distribution, and purchasing. Use the SNP Capable-to-Match (CTM) planning tool to maintain inventory levels across the supply chain and to eliminate procurement shortfalls.
Key Concept
The Capable-to-Match (CTM) planning algorithm in SNP supports rule- based supply chain planning to propose a feasible solution for demand fulfillment. A search strategy with existing stocks and planned receipts matches demand elements with supply elements. CTM uses constraint-based heuristics to conduct multi- site checks of production capacities, procurement priorities, and transportation capabilities based on predefined supply categories and demand priorities.
My client uses SAP APO with an R/3 execution system to address its global demand planning, logistics, and
order management processes. The system meets the demands of a globalized supply chain by accommodating cyclical business
trends and multiple partners, avoiding excess inventory levels and liabilities, eliminating gross profit erosion, and
being ever-vigilant of the competitive landscape.
SAP technology provides my client with so-called "what-if" planning capabilities. This allows users to
source from different vendors as needed, move material from different plants, and use existing inventory before
procurement across the supply chain. The APO CTM planning algorithm available in the SNP module allows the client to
maintain
inventory levels and create strategic plans that minimize supply outages while maximizing the advantages
economies of scale provide with vendors.
CTM supports rules-based supply chain planning and allows for tactical adjustments such as making product
and location substitutions when needed. Let's look at how CTM is used for global, regional, and local demand planning and
how supply aggregations match existing inventories with current needs while remaining in line with supply network
constraints.
SAP Landscape
Before discussing the CTM functionality, I'll show you the IT landscape and a high-level data flow across
my client's systems (Figure 1). The data flow is little different than a typical SAP landscape with
respect to receiving customer forecasts and how they are massaged in the different SAP systems — R/3, BW, and APO.
Customer forecasting data is received in R/3 via a standard EDI interface. After validation checks are performed in R/3,
data is loaded into the BW system and used to run decision support queries.

Figure 1
High-level data flow in SAP landscape
The BW system feeds forecast data to the APO system. Data at the customer part number level is sent to the
APO Demand Planning (DP) module and exploded into manufacturer/supplier part numbers using the system's bill of materials
(BOM)
functionality. This unconstrained forecast data is then passed to the SNP module in APO, which applies the CTM
algorithm. After the CTM processing, purchase requisitions are transferred to R/3 for further processing.
Business Requirements
With plants across the globe in three main regions (Figure 2), my client relies on the
CTM planning algorithm to monitor plants and administer strategic replenishment. It allows the company to satisfy the
customer forecast demands first at the local plant level, then for regional hubs.

Figure 2
Local plants rely on hubs, which are supplied from vendors and from each other
Each region uses a hub to supply local plants and vendors furnish materials to two of the three regional
hubs. The Asia hub is replenished from the EU hub, which is able to negotiate cheaper volume-based prices, and does not
purchase from vendors. Materials can be moved among the hubs as needed to meet customer forecast demands. Hubs from other
regions are tapped to provide inventory when the main regional hub cannot supply its local plants.
The hub and spoke relationship allows inventories to be used first at the local plant level, then at the
hub level. Local plants keep 21 days of supplies on hand to avoid stock outages and inventories at the hubs must be
exhausted before orders are placed with the vendors.
Alternate products are available across the supply chain when the original
products are not. If a substitute item is needed, the system first looks to the original local plant to see
if the alternate is in stock, then to the regional hubs. If an external procurement is required, the material is sourced
from the region where my client has the cheapest agreement with its vendors. Purchase orders are guaranteed in the R/3
system and reviewed before being cut.
The demand from all local plants and regional hubs is aggregated and purchase orders reflect this
aggregated demand so that the client can benefit from the lower costs offered by economies of scale. Product demand can be
prioritized
according to specified criteria including availability date, sales orders, and customer forecasts.
Figure 3 details the flow in my client's planning scenario. It addresses all the
relevant planning needs I just explained.

Figure 3
Supply planning processes are supported by CTM
CTM Support
CTM is able to accommodate scenarios that call for prioritizing demand according to specified criteria
with all the supply elements categorized in advance. It allows demand elements to be matched with supply elements
according to a search strategy with existing stocks and planned receipts.
Sequential planning runs consider all the customer requirements and product substitutions for local plants
and regional hubs. It creates stock transfer proposals among the regional hubs. Once all the inventories in the hubs are
used, CTM has been configured to create hub-to-vendor aggregated purchase requisitions.
To meet these requirements, CTM uses constraint-based heuristics that conduct multi-site checks of
production capacities, procurement priorities, and transportation capabilities based on predefined supply categories and
demand priorities. The aim of a CTM planning run is to propose a feasible solution for fulfilling the demands.
CTM planning is done using location-by-location procedures, so there is no global demand prioritization
and no global supply categorization across the supply chain. All supply categories and production are taken into account
for each location according to the search strategy specified with CTM planning profiles.
You can also use available-to-promise (ATP) rules in CTM planning for more supply chain control. Match
supply with demand via specific demand attributes such as location and product for forecasts and dependent demand, or
location, product, sales organization, order type, etc. for sales orders.
The standard condition technique that is used in the rules-based availability check offers you the
flexibility to define various conditions to trigger the application of a rule. You can also use the standard
condition technique to define product
substitutions, partial delivery, partial
satisfaction, delayed demand
satisfaction, and early demand satisfaction.
Using the substitution rules for products, CTM searches through the entire available stock of the
requested product as well as of alternative products, in order to cover the demand before production occurs or going for
external procurement.
Engine Sequences
The CTM engine has been configured to meet the exact client business requirements by following four
sequential CTM Planning runs (Figure 4). Let's take a look at each one and see how CTM meets all the
goals.

Figure 4
The CTM engine sequences fulfill the client’s business requirements
The Sequence 1 planning run takes care of the demand for local plants. Because the technology provides for
multiple-site planning, all the local plants and their respective regional hubs are included during this first sequence of
planning runs.
The CTM engine establishes customer demand for a local plant and attempts to reconcile the demand with the
supplies on hand at that local plant or at a hub.
All the alternate products are taken into account along with the 21 days of supply restriction for local
plants. Orders for unsatisfied demands are placed with the respective regional hub for fulfillment. This planning run
sequence ends after all local plant demand is assigned to the regional hubs.
Sequence 2 allows all the unfulfilled demands from Asia to be placed with the European hub for central
procurement in Europe. The CTM engine is configured so that the Asian hub places all the unsatisfied demands orders with
the European hub after all the primary and alternate products supplies in the Asian hub are exhausted. This planning run
ends when all the unfulfilled Asian hub demands are allocated to the European hub.
The planning run for Sequence 3 coordinates the regional hub in the US with the EU hub to meet the
fundamental business requirement of allocating all stock on hand before going to a vendor. This sequence only looks at
stock (original product and alternates) available at the regional hubs to prepare the stock transfer proposals between
them. The aim of this planning run is to completely use any existing inventories. No external procurement proposals are
created for vendors in the third sequence.
External procurement proposals for vendors are generated during the final planning run, Sequence 4. All
the regional hub demand is aggregated and volume-based purchase requisitions are placed with the appropriate vendors.
The CTM plans are integrated into R/3 for execution planning, but some custom functionality is required.
Standard integration of APO into R/3 does not transfer APO product substitution proposals to R/3 for execution. The custom
functionality bridges that gap and transfers the product substitution proposals for successful
execution.
Srinivas Gudipati
Srinivas Gudipati is director of SAP solutions at Falcon Prime Inc., at which he leads SAP SCM solutions (SAP ERP Logistics, SAP APO, and RFID). He implements large scale corporate supply chain projects and deploys the end-to-end supply chain process solutions. Falcon Prime Inc. specializes in SAP products and solutions across the enterprise domain, and provides business and technology consulting services, software implementation, and development. Srinivas has 12 years of SAP experience and more than eight years of experience implementing SAP supply chain solutions.
You may contact the author at srinivas.gudipati@falconprime.com.
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