Computers and software can make excellent allies in business and supply chain management. However, while certain progress is being made into the realm of artificial intelligence, for the present—at least—the computers we employ for most of our business functions (in ERP, MRP, MRP II, and similar) are not really thinking machines. They don’t think, at all. They compute, and that’s why they are called “computers.”
The following is a piece of correspondence I recently sent to a company who has engaged us to help them with automation around their manufacturing and supply chain. The focus of the letter was high-level information gathering. But, I want you to pay particular attention to the highlighted portions of the letter because end-to-end dependencies can be a stem weakness.
I would like to start with some high-level questions that, will help guide us toward the best possible outcomes for you—including a rapid return on your investments. If you are looking at multiple ERP solutions I suggest you do this for each solution, because they don’t all have the same features and functionality.
- What is(are) your chief business goal(s) in seeking to implement and use ERP’s Advance Manufacturing capabilities in your business?
- Please list the top 5 business challenges you face, and hope to address, in the deployment of ERP Advanced Manufacturing.
- What average percent of your present capacity is being consumed by your market today?
- Lead Times:
- What is the typical lead (PO release to receipt of goods) time range for your raw materials?
- What is your typical production cycle time (release to manufacture to completion) for intermediate components?
- What is your typical customer tolerance lead time (order placement to delivery) for your finished goods?
- SKU-Locations (SKULs):
- How many SKU-locations do you presently manage (g., a SKU stocked at three different points in your supply chain and under your management is equal to three SKULs)
- Are all of your SKULs managed, presently, in [ERP system name – redacted], or by other systems (including custom applications or Excel workbooks)
- What Reorder Method is presently assigned to the majority of your SKULs in [New technology – redacted]?
- What Cost/Valuation Method is presently assigned to the majority of your Items in [New technology – redacted]?
- How do you presently manage inventory and replenishment today?
- How do you presently determine the strategic size of your stock buffers?
- How do you presently determine the strategic positioning of your stock buffers in your supply chain?
- How do you presently drive manufacturing execution? That is, what factor(s) trigger a manufacturing work order?
- What determines the quantity of units to be produced on a work order?
- What determines when a work order is to be released to the shop floor?
- How are manufacturing batch sizes determined (if used)?
- Describe in a paragraph or two your existing S&OP processes and cycle.
- How do you, or will you, define “work centers” for manufacturing purposes? Why have you chosen that approach?
- Are your manufacturing times known and in control? (Note: A process is in control when variation within the process can be attributed to random variation, whereas a process is not in control when variations are large and are not clustered around a statistical mean.)
- Do you know (or have you calculated) your typical manufacturing (work center cycle) times for all production steps to be included in your routings? These would include (where applicable) ….
- Queue time – the average time a production unit (or job) spends waiting for processing at the work center, or to be moved to the next work center
- Setup time – the average time a production unit (or job) spends waiting for the work center to be setup for processing the unit (or job)
- Move time – the average time a production unit (or job) spends being moved from the previous work center to the current work center in a routing
- Process time – the average time a production unit (or job) spends actually being processed by the work center
- Wait times
- Wait–to-batch time – the average time a production unit (or job) spends waiting to form a batch for either simultaneous processing or moving
- Wait–in-batch time – the average time a production unit (or job) spends waiting in a process batch for its actual processing
Wait–to-match time – the average time a production unit (or job) spends waiting for other components for an assembly operation.
NOTE: These get recorded in the Routing Labor Steps by Work Center and, in turn, are used by the scheduling component for calculating capable to promise times, and other scheduling parameters. If they are not known, not correct, or not in control, the scheduling and CTP outputs will be invalid.
There are formulas available to calculate expected queue length and/or average cycle times at a work center or line, but other factors may need to be known or calculated to perform these calculations.
One of the things of which I often warn clients when implementing an advance manufacturing environment is this:
Setting up an advanced manufacturing environment requires a very large amount of data (see above), and many companies do not really have all the data they require, and some even are uncertain as to how to gather it. As a result, they populate their manufacturing system with averages and best guesses.
At the other end, an advanced manufacturing systems puts out a huge volume of data, in great detail.
The problem is, the people using the systems frequently forget that the output is based on their input. Even though they may have populated their system with guesses and averages, they will tend to actually believe the outputs as being 100 percent correct. If the system tells them that it cost $187.1655 per unit to manufacture an item, they will believe it. If the system tells them that a CTP (capable to promise) date is 27 days from today, they will tend to believe it, without remembering the guesses and averages that went into those calculations.
Where they do notice is when MRP (material requirements planning) or APS (advanced planning and scheduling) outputs simply don’t make sense. So, as a result, they return to managing execution by the seat of their pants and Excel workbooks (or even whiteboards), and leave just the “accounting” to their manufacturing system.
I mention this in the context of supply chain management, especially because, it seems, that there is some considerable thought being given to the concept that ever more complex systems and increasing complex computing algorithms will ultimately lead us to the Nirvana of supply chain excellence.
But, I beg you to check with those companies that have sought solace (and, improved profits) by spending on more and more complex systems. Ask them what their real ROI (return on investment) has been? Many will probably tell you: “We don’t really have any yet, but we still hoping for some in the future.”
The concept of inherent simplicity tells us that the more complex a problem appears to be, the simpler the effective solution must be.
As George Gilder writes, “Predictability and information operate in opposite directions.” By this statement, he is highlighting the fact that “[I]nformation itself is best defined as surprise–that we cannot predict rather than what we can.”*
Think about this: what the effective supply chain manager needs mostly to be aware of what he or she cannot predict, and to know just how well his or her buffers are likely to protect against the “surprise” in the flow of relevant data. What can be predicted should already be covered and protected.
Finding inherently simple methods to protect and promote FLOW in the supply chain is the way to reach the real optimal state for your supply chain.
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