This document explains how stepwise planning is conducted in M3 SCP. This includes adjusting the Scoreboard, solving infeasible demands and iterative evaluation of the final supply chain plan until it is ready for final approval.
The process results in a supply chain plan that is ready for approval.
The plan can be used to update M3 Business Engine.
The outcome of this process does not effect other parts of M3. The subsequent approval and incorporation of the supply chain plan, however, will effect M3 BE.
In order to make the analysis and problem-solving tasks easier it is necessary to adjust the Scoreboard to make it reflect the current situation as closely as possible. Scoreboard adjustments can involve the following actions.
Various types of Scoreboard records help the user gain focus on different performance indicators, for example related to resource utilization and costs, consolidated into easily comprehended data sets. The user-defined records provide quick access to the exact information needed for taking the necessary actions to resolve problems in the supply chain model.
The same Scoreboard records can be used in different simulation versions of the plan. Similar Scoreboard records used in different versions (for example, using different optimization strategies) can be compared directly in the Version Compare List panel. (This panel contains one line per Scoreboard record per plan version. The list shows scores in absolute numbers). It can also be done in the Compareboard panel. (This panel is used to compare the differences between two plan versions. The list shows the number of dissimilar records).
Solve Infeasible Demand Fulfillment
The main purpose of supply chain planning is to meet as many demands as possible. Sometimes all demands can not be met even though all required resources are available. This situation may occur if lead times are too long or if you have long lead times in combination with low inventory levels.
In order to prepare the plan for solving these demand problems the preset optimization strategy Infinite is used. This strategy is based on the assumption that all required resources are available. In this way demands that can not be met under any circumstances will be uncovered. When they are uncovered, changes can be made in order to solve this kind of problem.
The process of solving demands that can not be met at all takes place prior to the detailed plan analysis. This is because these demand problems should be solved first so that focus is on the conditions that are actually constraining the flow through the supply chain.
The following ways are available to solve infeasible demands in this case:
Changing demands means changing either the demand date (that is, moving some or all demand to a later time bucket) or the quantity of the demand. Change of demand can be made in the Data Generator or in the Demand and Delivery report. This report is accessed from the Navigation Menu under Material Flow/Quantities.
The start inventories are used to show the inventory levels for item groups (at network nodes) at the beginning of the optimization period. The start inventories of the current plan are shown in the Start Inventory report. This report can also be used to adjust the start inventories. The report is accessed from the Navigation Menu under Material Flow/Quantities.
Simulate and Evaluate Plan
When the Scoreboard is adjusted and infeasible demands have been rectified the plan is ready for simulations and consequence analyses of different solutions. It is during this process that the plan is evaluated and optimized towards the final solution that meets as many demands as possible at the lowest possible cost (or at highest possible profit).
Various reports and profiles can be used to show aggregated and detailed data with focus on capacity/utilization, material flow/quantities or economics (cost and revenue). These reports can also be used to make changes. This way the decision-making is conducted directly in the M3 SCP reports.
Each simulation activity is based on a specific optimization strategy. Optimization strategies can be both system-defined and user-defined. Usually, it is necessary to add some user-defined strategies to the standard strategy because the stepwise and iterative planning process consists of several discrete steps.
The process of solving capacity constraints takes its starting point from the infinite plan that is based on the system-defined optimization strategy Infinite. The next standard strategy is Finite where all resources are planned using finite capacities. It may be necessary to create some user-defined strategies to be used in-between in order to be able to solve the capacity constraints in the appropriate order according to the principle of Theory of Constraints (that is, to find and resolve the most important constraints first).
A new optimized plan is created after each simulation. The user evaluates the plan and decides what decisions still need to be made before the plan is ready for approval. The user is in charge of the process all the way, and therefore also decides when the plan is good enough to be accepted and exported (if needed).