Implementing Time-Series-Based Supply Planning with SAP IBP

The Supply Review phase is a crucial part of the Sales and Operations Planning (S&OP) process of managing supply chain operations. Understood in relation to the Demand Review phase, which examines anticipated demand based on the Consensus Demand Plan, the Supply Review proceeds to balance this projected need with available or projected supply.

This phase makes use of heuristic methods and optimizers that consider both Constrained and Unconstrained Demand Plans. Working on the analysis of anticipated demand, these tools help to evaluate just how effectively the current or planned supply will suffice to meet it. They provide a comprehensive overview of the supply chain, allowing teams to identify any gaps between supply and demand.

While the Demand Review forms the foundation for the planning process with its focus on potential demand, the Supply Review builds on that by evaluating the current supply situation.

Upon completion of these two initial steps, companies can move to the reconciliation phase, which aligns the analyzed demand and supply plans to ensure consistency with departmental goals and objectives.

The insights collected during these stages of the S&OP process prove invaluable during the final stage: Management Business Review. This step involves conducting an in-depth examination of the Final Consensus Demand Plan, incorporating findings from previous steps, including those from the Supply Review, to help strategize better and improve overall supply chain efficiency.

In this lesson, we explored the critical Supply Review phase within the Sales and Operations Planning (S&OP) process, which is essential for managing supply chain operations. The Supply Review phase follows the Demand Review phase, which assesses anticipated demand based on the Consensus Demand Plan. The primary goal of the Supply Review is to balance this projected demand with available or projected supply, utilizing heuristic methods and optimizers that consider both Constrained and Unconstrained Demand Plans.

These tools help evaluate how effectively the current or planned supply can meet anticipated demand and provide a comprehensive overview of the supply chain, identifying gaps between supply and demand. The insights from the Demand and Supply Review phases feed into the Reconciliation phase, aligning analyzed demand and supply plans with departmental goals and objectives.

Finally, the lesson highlighted the Management Business Review, the concluding stage of the S&OP process, where an in-depth examination of the Final Consensus Demand Plan and previous findings is conducted to strategize and enhance overall supply chain efficiency.

Planning operators in SAP Integrated Business Planning (IBP) for Supply Chain execute large-scale calculations and run background jobs efficiently. These operators utilize the SAP HANA library to execute algorithms, the behavior of which can be modified by specifying associated parameters.

These planning operators can be scheduled within SAP IBP, through Microsoft Excel add-in, or via the web user interface.

S&OP Operator Profiles is an application that configures various algorithms used in time-series-based supply planning. For efficient use of these algorithms in the SAP IBP Excel User Interface, each algorithm needs an S&OP operator profile defined. This profile can be accessed and run in Excel under the Application Jobs menu. It includes different settings to control the algorithm's behavior during a planning run.

Video Summary

Explore the key algorithms that support effective supply chain management in this video. Learn about supply planning heuristics, finite heuristics, supply propagation, shelf life planning, and supply planning optimization.

These profiles cater to various algorithm types like TS-Based Supply Heuristics, TS-Based Supply Optimizer, TS-Based Forecast Consumption, Check Mode, Local Updates, and Compute Quotas. TS-Based Supply Heuristics includes Infinite Without Shortages, Finite Heuristics, and Supply Propagation.

Common settings across all the profiles include the algorithm's name and description displayed in SAP IBP, add-in for Microsoft Excel, allowed processing modes, the designated planning area of the algorithm, and the level of time granularity for the algorithm execution. By defining these parameters, you can customize the algorithm to operate outside the storage level defined for supply planning key figures.

You also make algorithm-specific settings that control the behavior of the algorithm with respect to planning features such as quota checks, source validity, and lead-time horizon. For the optimizer only, you set parameters for discretization, fair-share distribution, time-independent penalty costs, and global cost factors.

We will focus on the algorithms that apply to Time-Series Based Supply Heuristics Planning and the parameters that apply to all algorithms. The algorithms for the time-series-based supply optimizer are covered in a separate course.

The table, Algorithm Types, describes the main algorithm types in supply planning.

Of the algorithm types in the supply planning operator in SAP Integrated Business Planning (IBP) for Supply Chain, only the T-S Based Heuristic (all types) and the T-S Based Optimizer algorithms actually plan supply. The other algorithm types have other functionality.

Several parameters control certain functionalities of the SCM planning operators, that is, of the heuristic or optimizer. This means that some of these parameters impact the heuristic only, others might affect the optimizer only, and others are relevant for both.

Infinite Without Shortages Heuristic.

In SAP Integrated Business Planning, two distinct heuristics called Infinite Without Shortages and Finite Heuristic play pivotal roles in demand and supply planning. Infinite Without Shortages heuristic performs an unlimited demand and supply planning with zero shortages. It creates a supply plan that dismisses certain constraints like finite resource capacities, allowing the software to identify any supply issues for a given location product, its nature, and the necessary capacity to meet all demands in due time.

However, it does not consider constraints such as finite resource capacities, minimum supply and resource requirements, maximum values, maximum lot sizes, and aggregated constraints. Situations may arise where the projected stock dips below zero, but it still provides useful insights for efficient supply planning, like identifying bottlenecks in the supply chain network. Exceptions exist when the entire demand for each location cannot be met due to reasons such as undetermined key figure values, undefined supply sources for a location product, or delays in lead times.

Finite Heuristic.

The Finite Heuristic allows you to create a priority-based supply plan, prioritizing demand over costs. Unlike the previous heuristic, it ignores constraints like time-series-dependent features, aggregated constraints, co-production, component and customer production substitution, dynamic periods of supply lot-sizing procedures, and more.

Outcome Calculation: By taking into account input key figure values, it calculates a supply plan, considering certain supply and resource constraints and writes the outcomes into output key figures.

Additional Algorithms.

Local Updates: The local update algorithm allows you to import data from an external system and simulate its impact on a particular location product. You can see how changes affect the projected stock without recalculating the supply plan across the entire supply chain. It limits itself to changing key figures for deficit, shortage, and projected stock without affecting any other location products in the network.

Check Mode: The Check Mode algorithm independently performs a number of checks for master data and key figures and returns messages for violations detected by the checks without changing any data. Regular running of this algorithm, especially after data upload from an external source, is highly recommended.

This section introduces Time-Series-Based Supply Planning using SAP Integrated Business Planning (SAP IBP). This approach allows businesses to develop detailed demand and supply plans using specific time-series-based algorithms.

• Supply Planning Heuristic: Generates an infinite supply plan to meet all demand regardless of current supply, preventing shortages.

• Supply Planning Finite Heuristic: Creates a finite supply plan based on priority, considering available supplies to meet demands.

• Supply Propagation Heuristic: Forms an infinite supply plan by propagating available supplies downstream through the supply chain.

• Shelf Life Planning Heuristic: Focuses on product shelf life to create an infinite supply plan, ensuring no stockouts.

• Supply Planning Optimizer: Develops a cost-effective, finite supply plan.

The algorithms are typically used within a sales and operations (S&OP) business process that we will explain later.

SAP IBP's flexible design allows running these planning algorithms using the Microsoft Excel add-in, either in simulation or batch mode. The Application Jobs app enables easy initiation or scheduling of planning runs.

Upon successful execution, the algorithms provide critical insights about the quantity of each product to be procured, produced, or shipped from each location within the supply chain during the planning horizon. They also identify potential supply chain issues, such as insufficient production capacities or stocks. To address these, SAP IBP offers configurable alerts as an early-warning system for possible disruptions.

The Excel add-in also allows users to explore various problem-solving approaches and share scenarios with the team before finalizing necessary changes.

SAP IBP supports comprehensive modeling and planning, considering various supply-chain-relevant locations and associated production steps. The generated supply plan acts as a quick reference, answering questions related to production volumes, logistics, external procurement needs, and potential bottlenecks in the supply chain.

The supply plan derived from these algorithms helps adapt stock levels as necessary and respond swiftly to market or supply chain developments. This dynamic approach ensures business continuity and efficiency even in volatile circumstances.

The S&OP process includes four essential phases:

1. Demand Review: Based on the Consensus Demand Plan, this step evaluates anticipated demand, forming a robust foundation for further planning (covered in Unit 2).

2. Supply Review: Utilizes heuristics and optimizers based on both Unconstrained and Constrained Demand Plans to balance supply with anticipated demands (detailed in Unit 3).

3. Reconciliation Review: Aligns analyzed demand and supply plans, ensuring departmental goals and objectives are consistent.

4. Management Business Review: Formulates and examines the Final Consensus Demand Plan, incorporating insights from previous steps.

1. Real-Time Planning: Enables instant adjustments to changes and challenges in the business environment.

2. Collaboration: Promotes effective communication and input from various team members to create a comprehensive plan.

3. Simulation and Comparison of Multiple Scenarios: Allows running different scenarios, comparing potential outcomes, and selecting the best strategy.

4. Monitor Performance: Tracks real-time performance and progress against set benchmarks.

5. Manage Risks, Assumptions, and Opportunities: Proactively manages potential risks, assumptions, and opportunities to ensure a robust supply chain management plan.

Global configuration is used to maintain application-level defaults. The Global Configuration app is used to change the values of global configuration parameters. This application also allows to visualize the difference between the parameter's default value and the active value and to check the number of revisions.

In the app, the global configuration parameters are organized in the following parameter groups:

Think about a time when you had to manage resources or coordinate a project with multiple moving parts. How did you address the challenges of balancing supply and demand, and ensuring everything ran smoothly? What tools or methods did you use to adapt your plans in response to unexpected changes? Relate your experience to the time-series-based supply planning and capabilities of SAP IBP discussed in the lesson.

In my role as a project manager, I frequently dealt with the challenge of coordinating resources across various departments to meet project deadlines. Balancing resource allocation and ensuring that tasks were completed on time required constant adjustments and communication.

To manage these challenges, I used project management software to track tasks and resource availability. I held regular meetings with team leaders to discuss progress and any issues that arose. When unexpected changes occurred, such as a delay in receiving materials, I had to quickly reallocate resources and adjust timelines to keep the project on track.

With SAP IBP, I could have leveraged time-series-based supply planning algorithms to automate and optimize resource allocation. The Supply Planning Heuristic would ensure all demands are met by generating an infinite supply plan, while the Supply Planning Finite Heuristic could help prioritize available resources more realistically. The Supply Planning Optimizer would assist in creating cost-effective plans, reducing unnecessary expenses.

Real-time scenario planning and "what-if" simulations in SAP IBP would allow me to quickly adapt plans based on current data, enhancing responsiveness to changes. The collaboration tools would improve communication across departments, ensuring alignment and cohesive decision-making.

Comparing my approach to the advanced capabilities of SAP IBP, I can see how the platform's features would significantly improve efficiency, accuracy, and flexibility in managing resources and coordinating complex projects.

This lesson introduced Time-Series-Based Supply Planning with SAP Integrated Business Planning (SAP IBP), highlighting key algorithms like Supply Planning Heuristic, Finite Heuristic, Supply Propagation, Shelf Life Planning, and Supply Planning Optimizer.

SAP IBP's flexible design, real-time insights, configurable alerts, and problem-solving functions enhance supply chain management and support comprehensive modeling across supply-chain locations and production steps, ensuring dynamic and responsive adjustments.

The Sales and Operations Planning (S&OP) process, which includes Demand Review, Supply Review, Reconciliation Review, and Management Business Review, is central to effective planning. SAP IBP's capabilities—real-time planning, collaboration, scenario simulation, performance monitoring, and risk management—ensure efficient, resilient supply chain management.

Furthermore, we explored various algorithm types used in SAP Integrated Business Planning for Supply Chain. Key algorithms include the T-S Based Heuristic and the Finite Heuristic, both essential for creating supply plans, with the former ignoring constraints like finite resource capacities and the latter prioritizing demand while considering some constraints.

Additionally, we discussed the T-S Based Optimizer, which creates cost-optimized plans, and other supportive algorithms like Check Mode and Local Updates, which ensure data consistency and simulate impacts on projected stock. Understanding these algorithms and their parameters is crucial for effective supply chain management in SAP IBP.