Friday, May 17, 2013

SAP SCM Solution Roadmap 2013


SAP SCM Solution Roadmap


MAIN PROCESS: Demand Planning is often the starting point of the entire Supply Chain Planning process and delivers the anticipated customer demand on a finished product level. This can be used by following planning and execution scenarios. Demand Planning is basically a toolkit consisting of statistical forecasting techniques, life cycle management, promotion planning, data anaysis and calculation tools, and gives visibility to all levels of detail.

Demand Planning & Forecasting

Statistical or univariate forecasting predicts future demand based on historical data. Unlike causal forecasting, other factors are not taken into account. 
Univariate forecasting provides methods that recognize the basic time series patterns as a basis for the forecast:
  1. Constant: demand varies very little from a stable mean value.
  2. Trend: demand falls or rises constantly over a long period of time with only occasional deviations.
  3. Seasonal: demand shows periodically recurring peaks that differ significantly from a stable mean value.
  4. Seasonal-trend: demand shows periodically recurring peaks, but with a continual increase or decrease in the mean value.
  5. Intermittent: demand occurs only in some periods.
The system can automatically identify the optimal method for any item to be forecasted. Different error measures are calculated by the system and alert planners if user-defined limits are exceeded.

Multiple linear regression (MLR) enables you to include causal variables (such as climatic conditions, price, and advertising) in the forecasting process. MLR investigates the historical influence of these variables on demand to produce a forecast. You can set up different scenarios for causal variables to simulate possible developments and thus identify possible risks and opportunities.

The underlying objective is to take advantage of the strengths of each method to create a single "one number" forecast. By combining the forecasts, the business analyst aims to develop the best forecast possible. The composite forecasts of several methods have been proven to out-perform the individual forecasts of any of those methods used to generate the composite.
However, the planner can also let the system automatically select the individual forecast that delivers the lowest statistical error.

A product's life cycle consists of different phases: launch, growth, maturity, and discontinuation. 
You can represent the launch, growth, and discontinuation phases by using so-called phase-in and phase-out profiles. A phase-in profile mimics the upward sales curve that you expect the product to display during its launch and growth phases, whereas a phase-out profile mimics the downward sales curve that you expect the product to display during its discontinuation phase.
For new products, it is proven practice to use historical data of corresponding products (such as the predecessors) as the basis for forecasting. This can be done using what is known as like-modeling.
Using the central maintenance instance for intechangeability relationships, the above profiles can be generated and assigned automatically. Life cycle planning is taken into consideration during statistical forecasting and works on detailed and aggregated level.

In Demand Planning, you can plan promotions or other special events separately.

You can use promotion planning to record either one-off events such as the millennium, or repeated events such as quarterly advertising campaigns. Other examples of promotions are trade fairs, trade discounts, dealer allowances, product displays, coupons, contests, free-standing inserts, as well as non-sales-related events such as competitors' activities, market intelligence, upward/downward economic trends, strikes, and hurricanes.

Demand Planning should include all available information about historical sales, budgets, strategic company plans, or sales targets. This data can come from different sources and can be transferred from any source to InfoCubes in SAP Business Intelligence (SAP BI). From there, the data can be read directly or transferred first to the liveCache to improve performance.

All Demand Planning data is available on the Web to include internal or external partners in the planning process. This ensures that all partners agree on the defined quantities, horizons and conditions.

Macros enable any kind of calculation on the planning grid. Planners can define them using a simple macro language in the macro builder, which has an easy-to-use interface.

Macros can be executed during background processing and on the planning grid. In particular, they are used to combine different types of information, derive dependent measures, or calculate alerts based on any check. More sophisticated macros can even add new planning logic. This increases the flexibility and strength of the application.

As well as planning demand for a product, you can also forecast dependent demand at different planning levels by exploding bills of material. This is of importance in situations where you need to plan the demand for a bundle of products that is sold, in a promotion activity, for example.

For example, this can be used for a kit that consists of several finished products (that can also be sold separately). Planning demand for the kit generates dependent demand that can be combined with the independent demand for the single products. The overall demand by product can then be used for supply, production, and procurement planning.

In SAP APO Demand Planning, you can create a forecast based on the characteristics of configurable end products. For example, in the case of a car, you can plan the characteristics color, engine, and air-conditioning. Moreover, you can forecast the demand for a combination of several characteristics, and thus take into account the mutual interdependency of the demand for these characteristics.

The final consensus demand plan can be transferred to subseqeuent planning or execution processes:
       to SAP BI for reporting and archiving, or integation to any other systems
       to supply or production planning in SAP APO
       to SAP R/3 or SAP ERP for e.g. Materials Requirement Planning (MRP)

Customer Forecast management is used to receive and analyze incoming customer forecast data and make the necessary adjustments before releasing it to Demand Planning for downstream planning. An analysis of forecasts enables the vendor to sense tendencies and changes in customer demand and integrate this information into replenishment planning. Customer Forecast Management ensures higher responsiveness to fluctuations in demand and also contributes to the prevention of stock-outs. 

Inventory Management


Safety stock is the quantity of additional stock procured and/or held to satisfy unexpectedly high demand. Safety stock planning within Supply Network Planning allows you to meet a service level while creating a minimum amount of safety stock throughout your entire supply chain for all intermediate and finished products at their respective locations.
Increasing Revenue
·   Improve order fill rate
Lowering Working Capital
·   Improve capacity utilization
·   Increase inventory turns
·   Lower work-in-process inventory
Managing Fixed Assets & Resources
·   Improve physical inventory process
The easiest safety stock planning method is to define a fixed safety stock or the safety dayssupply required in any stocking location for a material. The system applies these settings in a static or time-dependent way, and calculates the resulting safety stock automatically. The safety stock is then considered during subsequent planning runs.

Advanced safety stock methods can calculate and consider the variability on the demand and supply sides. Furthermore, simulations of the service level and the forecast error can be performed. The service level can be defined in two ways: 
1. As the share of periods with complete deliveries compared to all periods (alpha service level) 
2. As the share of quantity delivered in time compared to overall requested quantities (beta service level) 
Furthermore, the system supports the reorder cycle (that is, reorders can be placed in special periods only, for example, every 4 weeks) and reorder point (that is, reorders are placed if stock falls below a minimum level) strategies.

SAP Enterprise Inventory Optimization by SmartOps is a solution that enables companies to pursue perfect product availability while significantly reducing inventory and working capital.  The solution provides a comprehensive, enterprise-scale process for optimizing, managing, and monitoring inventory stocking levels for every finished product and raw material component at every stocking location in a multi-tier distribution or manufacturing supply chain.
Features include the following:
·         Multistage modeling approach calculates the relationships among inventories, service levels, capacity, and costs across all stocking locations and stages across different types of supply chains within organizations
·         Coordinates capacity, inventory, demand, lead time, and product availability variables to calculate how much inventory should be carried by item, location and time period
·         Planners can set and manage targets such as safety stocks more frequently at granular level, supporting lean processes
·         Customers can realize savings from improved customer service levels, lower inventory and working capital reduction
·         Accurately tracks and streamlines inventory positions throughout order to cash value chain, using advanced algorithms



Supply Network Planning integrates purchasing, production, distribution (of demands), and transportation so that comprehensive mid-term to long-term tactical planning and sourcing decisions can be simulated and performed on the basis of a single, global consistent model.

The heuristic is used as part of a repair-based planning process consisting of the heuristic, capacity leveling, and deployment. The heuristic process considers each planning location sequentially and determines sourcing requirements. It sums up all requirements for a given material in the location into one requirement for the period. The heuristic determines the valid sources of supply and quantities based on pre-defined percentages for each source of supply (quota arrangements).

The Supply Network Planning run produces a plan that meets all the demand requirements (for example, sales orders and dependent demand). However, the resulting plan is not necessarily feasible. Capacity leveling enables you to smooth your production schedule either manually or using method-based approaches:
1.        Heuristic-based scheduling
2.        Optimization-based scheduling
3.        Customer-specific scheduling logic
With capacity leveling, you have the opportunity to build up inventory or increase capacity to ensure that you can meet demand without overstocking and to avoid periods of resource overload or underuse.
You can easily analyze alternatives and re-plan, even re-forecast, before putting the plan into production. You can adjust the plan by modifying supply or consumption, or by changing the production and transportation orders manually. You can modify supply by changing the resource master data. You can modify consumption by leveling the capacity on the active resource or by using an alternate resource (shift order from one resource to another manually). You can manually edit production and transportation orders.

The SNP optimizer offers cost-based planning. This means that it searches through all feasible plans to try to find the most cost-effective one.

Total costs refer to the following:
1.     Production, procurement, storage, and transportation costs.
2.     Costs for increasing the production capacity, storage capacity, transportation capacity, and handling capacity.
3.     Costs for falling below the safety stock level.
4.     Costs for delayed delivery.
5.     Stockout (or shortfall quantity) costs.

Capable-To-Match (CTM) planning uses constraint-based heuristics to conduct multi-site checks of production capacities and transportation capabilities based on predefined supply categories and demand priorities. CTM can also consider characteristics during planning which is especially important for industries with customizable products like e.g. Mill or Machinery & Components. Shelf Life restrictions are respected in CTM as well. The aim of the CTM planning run is to propose a feasible solution for fulfilling demands.

The subcontracting process is a kind of outsourcing of manufacturing facilities to a third-party called the subcontractor. The manufacturer provides the subcontractor with components and the subcontractor uses these components and supplies the finished product to the manufacturer.

Subcontracting scheduling agreements can be created as external procurement relationships and you can plan ordered finished products and subcontracting components at the subcontractor (vendor) location for the SNP heuristic as well as for Production Planning and Detailed Scheduling (PP/DS). This gives you access to information about subcontracting stock at subcontractor locations. Third-party order processing can also be used if you want an external supplier to provide you with the components for a finished product that is to be manufactured by a subcontractor, rather than providing the components yourself from your own plant.

Scheduling agreements define a fixed amount of quantity to be delivered from a supplier to a manufacturer over a longer period (for example, a year). The SNP heuristic can use this information (transferred from SAP R/3, for example) to plan the schedule lines and to create the releases. Using collaborative supply planning, the supplier can confirm these quantities before they are transferred to the execution system (for example, SAP R/3).

Aggregated planning can be performed, by defining hierarchies for products and locations to be taken into account by both the SNP heuristic, capacity leveling and optimizer. 
Disaggregation logic ensures that plans are consistent at all levels of aggregation. Extended drilldown options enable an easy displaying of the aggregated planning results. This type of planning will reduce the planning complexity as well as improve the system performance.



The distribution planning process is used to determine which demands can be fulfilled by the existing supply elements. The deployment run generates deployment stock transfers based on the SNP or PP/DS stock transfers that were created during the SNP run. The PP/DS deployment also considers characteristics during planning. The Transport Load Builder (TLB) then uses these deployment stock transfers to create transport loads based on predefined constraints of the means of transports. Responsive Replenishment: You can use this business process to plan responsive replenishment based on the results of the Responsive Demand Planning process. Responsive Replenishment Planning plans the optimal shipments to customer locations. During this process the netting takes place, transport loads are created, and finally the orders are created. Promotion and baseline demands can be planned independently.

The distribution planning process is used to determine which demands can be fulfilled by the existing supply elements. The deployment run generates deployment stock transfers based on the SNP stock transfers that were created during the SNP run. The Transport Load Builder (TLB) then uses these deployment stock transfers to create transport loads based on predefind constrainst of the means of transports.

You can use this business process to plan responsive replenishment based on the results of the Responsive Demand Planning process. Responsive Replenishment Planning plans the optimal shipments to customer locations. During this process the netting takes place, transport loads are created, and finally the orders are created. Promotion and baseline demands can be planned independently.

The aim of vendor-managed inventory (VMI) is to integrate key customers in supply chain planning. The customer regularly sends stock and sales data to the vendor, and based on that information, the vendor determines replenishment requirements for the customer. It improves the vendor's access to the actual customer requirements, and also enables the vendor to make informed decisions about how to distribute goods for different customers. This ensures improved customer service, lower transportation costs, less inventory, and lower sales costs.



Service Parts Planning delivers integrated planning capabilities to the service parts supply chain. While it considers the specific aspects of the after-market and provides extended capabilities for handling the large parts volumes present in an after-market supply chain, it also delivers a tight integration of the end-to-end planning process with other processes, such as Supply Network Collaboration, Procurement, Warehousing, and Order Fulfillment.
For detailed information on Service Parts Planning please click here to review SAP Service and Asset Management

Lowering Working Capital
·   Increase inventory turns
·   Reduce material and component obsolescence
·   Reduce out-of-stock situation
Reducing Operating Costs & Increasing Efficiency
·   Reduced service parts inventory levels across the service parts network
Improving Customer Service
·   Better service levels
·   Improve forecast accuracy

Strategic Supply Chain Design includes the definition of all elements of the supply chain.

Parts Demand Planning offers a set of capabilities that allow to capture historical demand, model that demand according to the structure of the service parts supply chain, and perform forecasts for future demand. Demand planning is done in an adaptive fashion which continuously analyses past forecast performance and adjusts forecast models and parameters accordingly. It considers the various stages of the parts life cycle, including parts introduction, parts supersession, and a longterm forecast.

Parts Inventory Planning determines where to stock which product and how much of it - balancing maximum service levels with lowest inventory costs. 

Parts Supply Planning supports tactical net requirements planning based on parts requirements throughout the service network.

Parts Distribution Planning distributes available parts within the network via push or pull deployment and inventory balancing.

Parts Monitoring provides visibility of all planning related processes and includes follow-up activities, e.g. using
- Shortage Management
- Service Parts Planning Cockpit
- Product Detail Information
- Service Parts Planning Alert Monitor



Demand planning has typically been the domain of a small group of highly specialized individuals who manage the planning and forecasting process for an entire organization or its divisions, product groups, or regions. The SAP® Supply Chain Management application (SAP SCM) provides the perfect toolset for these highly skilled and experienced users. Demand-planning software within the application offers a complete range of advanced functions for data analysis, multilevel planning, life-cycle management, forecasting, and promotion planning. In addition, SAP SCM supports collaboration and supply chain partnerships such as vendor-managed inventory and collaborative planning, forecasting, and replenishment. 
Used with a fully configured SAP demand-planning application in the back end, Duet offers a comprehensive array of interactive planning functions for creating, controlling, and modifying demand plans or forecasts. Duet links the advanced demand-planning features of SAP SCM with the familiar and flexible interface of Microsoft Excel. Together, Duet and SAP SCM support usersneeds for comprehensive interactive functions that are flexible, intuitive, and easy to use. In addition, users have the option to work offline allowing, for example, a sales representative to enter forecast data while on the road. 

When working online, planners can use preconfigured planning sheets to load data from SAP SCM, analyze, modify, and add data as required and save the changes back in SAP SCM. They can use the standard spreadsheet functions in Microsoft Excel and additionally an action pane to manage selections or switch between pre-assigned selections in order to navigate to the relevant data.

If users want to work offline  while visiting clients or other business partners, for example  they can load the data into the planning sheet while you are still online and connected to SAP SCM.
Planners can use the standard spreadsheet functions in Microsoft Excel to add rows or columns and carry out calculations. They can use macros and formulas created in Excel to fill out cells in the planning sheet or make calculations and reference data from other worksheets in their calculations.
The next time back online and connected to SAP SCM, planners simply save any changes made while offline to the SAP back-end application.