Efficient Production Planning Using SKU Groups with the SNP Optimizer

  • by Srinivas Krishnamoorthy, Principal APO Consultant, SCM Practice, Infosys
  • May 1, 2014
Find out how to overcome the limitations of Supply Network Planning’s aggregate and block planning capabilities.
Learning Objectives

Reading this article you will learn how to:

  • Elevate the planning object in a supply chain to a SKU group level, in lieu of a granular SKU-Location level
  • Apply the concept of SKU Group Planning specifically in the context of production resources common across multiple locations
Key Concept
Aggregate planning is a feature in Supply Network Planning (SNP) whereby net requirements calculation from medium to long term can be executed at a product group level using aggregate objects such as SKU groups, location groups, resource groups, and production data structure (PDS) groups. The plans generated at higher levels are disaggregated to actual SKU-location levels using predefined quotas or demand at that level. Block planning is a feature in SNP that comes up with recommended sequence of planned order execution within a planning bucket based on changeovers. Both these features attempt to make the transition into short-term production planning zone more efficient and executionable at the shop-floor.

In the context of verticals such as consumer packaged goods, the consumers of such goods have a wide variety of SKUs to choose from in any given product category. These SKUs may have minor variations in terms of ingredients or packaging. For example, a nutrition bar with the same basic content or ingredients could be sold with different flavors such as almond, chocolate, or vanilla. Another example is a chocolate pudding snack with sugar-free variation that otherwise has the same set of ingredients as a regular pudding. Furthermore, in a private-label business specifically, different retailers sell the same exact product wrapped in different packaging custom to that retail organization. Although from a customer’s point of view, such a wide variety of choices is a benefit, from a production planning point of view, accurately planning production so that SKUs that are similar in content are produced together is a challenge.

Thus, in a context where a production planner has to plan for a wide variety of SKUs characterized by dissimilarities and similarities in various attributes, such as flavor, size, or any other parameters specific to the SKU, the production planner has two choices. One is to plan and produce the SKUs in an order closely representing the demand. However, that might require significant changeover costs to change the flavor of the SKU being produced. The second choice is to group the demand of like SKUs together in a production cycle reducing changeovers. In such instances, production planners usually earmark certain weeks in a month for producing certain kinds of flavors that they would like to see planned in a logical group. This is similar to block planning with the planner wanting the planning tool to work with prespecified dates for production of certain SKUs in a group. Although planning in blocks of time earmarked for a certain SKU group by itself may not be very efficient because it is not demand driven per se, it brings a whole lot of predictability into the production plan model. Predictability is something that everyone on a shop floor wants.

When the production plant level limitations or guidelines in terms of the blocks are taken into consideration up front in SNP for medium- to long-term planning, these plans roll over into the short-term Production Planning and Detailed Scheduling (PP-DS) horizon, making the transition fairly smooth with minimal manual touches and interventions.

I discuss some of the SAP offerings and limitations for SKU group planning that you can implement.


Srinivas Krishnamoorthy

Srinivas Krishnamoorthy is a mechanical engineer from IIT Delhi. He holds a master’s of business administration degree from IIM Lucknow (India). He has more than 13 years of experience in supply chain planning applications and has executed several end-to-end Demand Planning, Supply Network Planning, and Global Available-to-Promise projects. He has contributed to the APO forum in SDN and has also written several blogs and papers on supply chain topics. 

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