The other evening I was giving my grandchildren (aka the munchkins) a bath, when my granddaughter (Reagan age four in December) asked about my cell phone (better described as a personal device) and I tried to explain about “real phones” – those items that were connected to wires and were only used for voice communication. The explanation didn’t get very far, but it struck me how the term “phone” had stayed in the language. When phones replaced telegraphs (the original view was telephones would simply replace telegraphs to reduce communication errors), the “tele” part stayed in the language for a long time. Yes, I am old enough to have regularly used phones and watch the Superman TV series where Clark Kent used phone booths to change into Superman.
I then read the recent blog “RCCP versus MPS – Can They Be Connected?” it struck me whether this question represents the current best in class or do they represent old terms as well as an old way of thinking that should not be the end goal of an organization any more when it comes to supply chain planning.
Where did the terms RCCP and MPS come from?
In the beginning of time organizations had to work around two major limitations in doing their planning
- Computational limitations – the ability to program and execute extensive calculations and collect, store, and use critical data elements
- Organizational cognitive limitations – what we might refer to coordinated processes
Organizations still needed to plan, to compensate they divided the planning task into loosely coupled tasks often called the alphabet soup (RCCP, MRP, MSP, …) where the task had two sides (business function and supporting software). The best single description of the alphabet soup is done by Prof. Reha Uzsoy in a class he does for his graduate students. Additionally, firms relied on “slack” (see Jay Galbraith Designing Complex Organizations, 1973) to compensate for the twin limitations. Galbraith remains as relevant today as in the 1970s.
Read More: Lessons from IBM: Supply Chain Efficiency & Smart Planning Engines
In its time the alphabet soup represented best in class planning, however beginning in the mid- 1990s two trends emerged
- Folks aware of the limitations took the next step in the journey to master or central planning
- The old ways became institutionalized and were followed without thought
What are the two critical business questions that relate to matching assets with demand (MAD)
- Given a set of assets (materials and capacity) and a set of prioritized demands, how best can the firm meet demand while aligning with business policy and objectives? What we might refer to as “best can do” (BCD).
- Given a set of assets and demand, what additional assets are needed to meet demand on time and align with business policies?
Best in class central or master plans have the following characteristics:
- A model or digital representation (to use a new fancy term) that captures the flow of activities and business policies across the demand-supply network (DSN) which is personalized for various uses simply with a change of input data
- This “representation” typically comes on one of two forms (An Example of When Optimization Is Helpful in Supply or Central Planning) equations as in mixed-integer linear programming (aka optimization) or programming constructs in your programming tool of choice (example Arkieva Replenishment Planner).
- A repository (DataMart) that has the critical information, the ability to dynamically update from transaction systems and user input
- A flexible reporting environment
Additional details for central planning can be found in
- Planning Production and Inventories in the Extended Enterprise: A State-Of-The-Art Handbook, Volume 2, chapter 14
- Central Planning Engines: Lessons from Leibniz
- Tips for Optimizing Your Entire Supply Chain Planning Process
Where the tooling to support capacity has peculiar complexities, there is an associated “tool or capacity planner” that has more detailed representation of these complexities. Examples:
- Campaigns or Trains: where setup times are sequence-dependent and substantial, this drives a need for campaigns
- Reentrant flow: where a toolset is visited multiple times in the production process
- Deployment – in theory, all tools in a toolset can handle all manufacturing activities (operations) in practice each tool can only handle a subset of the operations
- Robotic characteristics of the tools
Matching Assets with Demand in Supply-Chain Management at IBM Microelectronics
As we noted earlier there are twin limitations any organization has to overcome to best in class planning for MAD. As Stu Reed, then IBM VP of Integrated Supply-Chain noted in his 1999 Edelman presentation – to move an organization along its planning journey requires a synergy between better planning tools and process transformation. At that time Mr. Reed had transformed the IBM central planning process that took 21 days using alphabet soup tools in 1997 to a one day process using central or master planning by 1998. One of the learnings was that it is a lot easier to overcome the computational limitations compared to the organizational limitations. It does take a lot longer for the organization to complete this transformation. Hence, it is understandable that these terms still remain very popular in web searches. Companies would, however, do well by aiming higher and move towards the best in class central planning quickly and decisively.
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