In the last week or so, a couple more articles popped up thanks to the magic elves in the Twitter Box.

From DemandCaster: Whatever happened to JIT?

…The dominant term was JIT. But, JIT and Lean were bandied about interchangeably. There was no different save for the marketing spin of one author or consulting firm over another. But that has changed. The change resulted because the manufacturing base moved, mostly, to Asia. This was contrary to the principle of reducing lead times so central to JIT. The lead time for goods from Asia dramatically increased to four, five, six, or more weeks. Just-in-Time simply did not fit.No matter what the lead times, one could be “lean” by taking the slack out of the lead times. But as the overall lead times increased so much that planning was once again based on forecasts.

Not to mention the additional inventory in the supply chain pipeline thanks to the longer lead times.

From @chrischip: Just in Time Just Isn’t

…But don’t pull your hair out over inventory. Your customers won’t wait for you to ramp up to fulfill their order, and your forecast won’t save you because it isn’t correct. The answer is a buffer. What I hear time and time again is that the cost of a buffer is well worth eating when you can promise delivery from stock. Without that assurance, you may well lose the order, and that’s a heavier price to pay in terms of dollars and reputation.

Buffers are consistent with, and I would argue REQUIRED, to lower inventory investment. Several weeks ago I revealed my personal view with regard to maximizing inventory turnover:

The secret: The fastest way to reduce  on-hand inventory balances is to ship it.

Many supply chain professionals are penny-wise and pound-foolish: They focus on reducing inventory investment by slowing the delivery of component inventory and insist on sticking to corporate strategies, goals, and metrics with regard to ordering and stocking policies. This is the domain of ivory tower academics and corporate theorists. I work in a Manufacturing Plant, where we Build Things Customers Pay For.

It is far better to grasp the universe as it really is than to persist in delusion, however satisfying and reassuring.
~ Carl Sagan

If the sales exist to consume the finished goods, the proper strategy is to ensure 100% order fulfillment. Unless your forecast is perfect (it’s not), your inventory accuracy is 100% (it’s not), your suppliers deliver exactly what you need exactly when you need it with no quality rejects (they don’t), your machines have 100% up-time (they don’t), and you have 100% yield (you don’t), then you have to be honest with yourself as a material planning professional and do the right thing: Buffer.

Better never than late.
~ George Bernard Shaw

That doesn’t mean you start writing blank checks, however. At the risk of sounding arrogant (too late, I know! ), this is the domain of Smart People. Data-oriented decision-making. Bounded risk. Iterative modeling. Yeah, I can spew the buzzwords with the best corporate policy wonk. If you don’t have robust simulation tools, buy them. If you can’t buy them, build them. They won’t be perfect starting out. Probably won’t be right, either. But the second iteration will be better than the first. You’ll do it faster, too. Same with the third, fourth, fifth, sixth… Models will never be perfect, but like a good spouse they get better with age.

When strategies, tactics, and actions are set, execute in the real world using proven, time-tested material management techniques.

How?

Use inventory stratification and manage by exception. Remember ABCs? Remember Exception Reports? Classical stuff. Material Planning 101. APICS Basics of Supply Chain Management.

I don’t worry about C-items. Period. I want tons of C-items. If I go line-down because a penny-part wasn’t in stock, that’s not the cost of doing business – that’s a DISASTER: Shipments are missed, Revenue goals aren’t met, and all of the on-hand inventory associated with the assemblies that now can’t be built will just sit on your books, festering. I watch B-items to the extent that I don’t buy excess but I try to buffer with time; instead of coming in just-in-time, I try to pick up extra days/weeks whenever I can. Finally, I focus completely on A-items. I have a number of homegrown tools I developed to track the supply/demand of A-items over time and any volatility is ruthlessly drilled to root cause and strategies developed to balance the supply with the demand.

Better three hours too soon than a minute too late.
~ William Shakespeare

Most importantly, I am disciplined about reviewing data versus plan and taking action with a sense of urgency. You can’t set up your plans and walk away expecting your great plan will be executed flawlessly. You have to constantly check, double-check, triple-check. Plan and re-plan. This is where Exception Reports are worth their weight in gold. In most companies where bills-of-material are complex and just plain LONG, it’s impossible to do a top-down or bottom-up material analysis on any kind of cycle that permits rapid decision-making. Exception reports separate the wheat from the chaff. By definition, the A-items consistent of ~80-90% of your inventory investment dollars. Planning and re-planning ~5-10% of your components offers an increased likelihood of successfully managing 80% of the dollars, rather than attempting to manage 100% of the component investment with no likelihood of success.

A good plan violently executed now is better than a perfect plan executed next week.
~ George S. Patton

I’ve been involved early in the sales pursuit process several times, as well as had products/programs “thrown over the transom” as they say. I have a simple process I follow to manage the material planning function on those programs where I’ve been involved early. I follow the same process on those “over the transom” programs to place the challenge into perspective for management and the program team so recovery decisions can be made as appropriate. Here it is in a simplified flow chart:

If your company has a formal S&OP process, each of these steps is probably documented in excruciating detail and the ability to drive component orders on forecast is defined through bounded risk calculations. If your company does not have a formal process, as a material professional you can’t just sit on your hands and wait for someone to hand you the approval to buy material before you start developing your availability analysis. A professional reaches out to the rest of organization, uncovers these “hidden demands” and gets to work.

I am considering a series of posts that describes how I go through each of these steps; we’ll see if the response to this post warrants the effort.

photo credit: AMagill

# Supplier may deliver their product late or not at all
# The warehouse may be on strike
# A number of items at the warehouse may be of poor quality and replacements are still on order
# A competitor may be sold out on a product, which is increasing the demand for your products
# Random demand (in reality, random events occur)
# Machinery Breakdown
# Unexpected increase in demand

There are many reasons and methods for calculating safety stock, and one of the more common reasons I’ve seen in the world of complex electronic assemblies is Test Yield. As electronic assemblies get more complex due to smaller component packages and denser placement on the board, as well as tougher requirements for the boards themselves, there will always be issues with yield. Couple this with complex testing requirements for certain high-reliability electronic assemblies, and yield issues begin to multiply. While zero defects is the goal we all strive for through continuous improvement programs, the real world has to take defects into account. Along with the actual defect comes accounting for the turnaround time to troubleshoot and repair boards, and finally, accounting for the loss of irreparable assemblies.

It might be easy to say “Well, I’ll just take whatever my first-pass fall-out is and release that many more in each work order”. But, releasing extra quantities in each work order isn’t safety stock; safety stock is the quantity of units required in your supply chain to account for VARIANCE and achieve your target service levels to the demands from your customer. While there are statistical formulae to determine order quantities and safety stock, if you understand your planning factors and your processes, you should be able to model your order quantities while achieving inventory and service goals.

Depending how the planning factors are set in your materials requirement planning (MRP) module, you won’t be releasing the same quantity in each work order. Most MRP systems will “see” those defective units unless they are immediately placed in an inventory status that “blocks” MRP. If your processes allow for defective units to sit in WIP through the next MRP cycle, your planned orders will be reduced accordingly.

For the example below, I assumed a first-pass yield of 97% and a scrap rate of 0.5%. Another factor that is important in the cycle below is that the test occurs on Day 5 of a 5-day cycle and it takes 2 days to troubleshoot and repair the units, which means the units show in WIP at the time of the next order release. See this example:

Manufacturing Lead Time (days)	5
Weekly Demand	100
Historical First-Pass Yield	97%
Historical Final Yield	99.50%
Historical Troubleshoot & Repair Time (days)	2
Day Test Occurs	5
Initial Order Qty + Safety Stock	103

	Wk 1	Wk 2	Wk 3	Wk 4	Wk 5	Wk 6	Wk 7	Wk 8	Wk 9	Wk 10
Demand	100	100	100	100	100	100	100	100	100	100
Order Release	103	100	101	100	101	100	101	100	101	100
Order Shipment	100	100	100	100	100	100	100	100	100	100
Fallout/Scrap		1		1		1		1		1
Balance in Troubleshoot WIP	3	2	3	2	3	2	3	2	3	2

As you can see, the quantity of units in WIP from one cycle to the next fluctuates between 2 and 3 units – 2%-3%.

There will be some in your organization (for instance, the production supervisor ) suggesting you should always release 103 units in each work order. Not only are they wrong, doing so will actually drive up your work-in-process (WIP) inventory – a cerain percentage of your first-pass defects will go through a troubleshoot-and-repair cycle, making them available for finished good shipments. If you continue to release “X” extra in each work order, WIP inventory builds according to this formula:

(Units released) + (Units Repaired) – (Shipments)

In the example above, watch what happens to your WIP inventory:

	Wk 1	Wk 2	Wk 3	Wk 4	Wk 5	Wk 6	Wk 7	Wk 8	Wk 9	Wk 10
Demand	100	100	100	100	100	100	100	100	100	100
Order Release	103	103	103	103	103	103	103	103	103	103
Order Shipment	100	100	100	100	100	100	100	100	100	100
Fallout/Scrap		1		1		1		1		1
Balance in Troubleshoot WIP	3	5	8	10	13	15	18	20	23	25

As you can see, your inventory will build to infinity unless some undefined variable consumes these units. Obviously, this is not a satisfactory solution in any organization due to the impact his has on cash flow.

These examples are simple and focus only on one variable – Yield. In a robust safety stock model one would account for other sources of supply and demand variance – forecast accuracy, supplier performance, additional quality yields, etc. But the examples do demonstrate how one can easily get to a safety stock determination through logical thinking, an understanding of their internal processes, and simple math.

I would love to see other examples of how to account for variance in the supply chain, so please leave me a comment if you care to continue the conversation.

photo credit: dan paluska

Good piece, as far as it goes.

Uh-oh…

For instance, you might expand on the effect the long cycle time has on the ability of the manufacturer to implement “changes” or respond to a customer’s request for expedite or change that they want implemented.

and…

I don’t know how important it is to quote a 5% year over year labor reduction…perhaps a more general approximation of labor savings or even just mentioning that there are some short lived labor savings (labor being less than 10% of the cost of most products might also be mentioned). You make a good point about trading off labor savings for reduced ability to serve the customer might not be in a company’s best interests.

Also, developing a model to address the ideas in your last paragraph might be interesting…or…I imagine someone already has and, if so, it might be good to find out and possibly incorporate it into the argument.

That’s what you get when your father is a retired electronics manufacturing CEO with domestic (US) and global contract manufacturing experience.

Key points from his feedback:

1. Labor is less than 10% of product cost. If you had any production/operations management classes in college, you know this to be true. As products grow more complex and require more automated manufacturing tools, direct labor goes down even more, but indirect labor may go up as these tools require skilled engineers to set up and maintain the programs and equipment.
2. The effects of increased cycle time on the ability to respond to customer changes: While many electronics manufacturers have an objective to reduce manufacturing batch sizes to the smallest quantity possible, intercontinental shipping of most products is more cost-efficient as batch size goes up. This means the entire supply chain is holding more inventory, especially more finished goods, so engineering changes can’t be incorporated, a direct “violation” of Lean principles.
3. A model that incorporates the cost of cycle time in offshore outsourcing: It would be intriguing to develop this, but I have to believe one already exists. Can anyone point me in the right direction? If not, I might take a stab at this (with a little help… ahem…).

Anyone else have any thoughts?

I’m actually getting into this discussion a bit and doing some research (what can I say, I’m a geek when it comes to SCM and competitive advantage), so I’ll have a few more posts on this subject, I’m sure.

The item that appears to be least understood by OEMs, from my perspective, are increased cycle times. Unfortunately, current financial practices require only that inventories are measured while in the legal possession of the OEM. So, each company is optimizing around their local process. If OEMs considered throughput and turns for the entire supply chain, if there was a true partnership between these companies to optimize the entire supply chain, I believe the geographical solutions would be vastly different.

Ironically, many of these same companies tout their operations as being “Lean”. The increased cycle time associated with offshore manufacturing is the exact opposite of the Lean mantra. Unfortunately, the elements affecting decision-making go much deeper than the dollars-and-cents; there are cultural and compensation issues in play as well.
As long as OEM supply chain, finance, and program managers receive incentives to provide year-over-year labor savings, they will chase wages around the globe. OEMs chase low wages from the US, where they may do prototyping, to Mexico, to China, to India, to Russia. Each year, the product moves to a cheaper country, and the OEM manager receives a 5% labor reduction for each of the five years, but his supply chain and cycle time grows. However, the manager has achieved his objective: he reduced labor costs, and earned his bonus.

Unless enlighted managers “dollar-ize” the effect of the integrated cycle time – and there are hard- and soft-dollar impacts associated with going from one week to four weeks, or one month to three months – manufacturing will continue to be performed where wages are lowest. It is the challenge of the regional contract manufacturer to educate and inform the customer, and develop financial models to highlight the true bottom-line impact of offshore manufacturing. Global contract manufacturers provide geographic migration plans as a standard piece of their proposals. Regional contract manufacturers must not be afraid to aggressively present these models and make the case for domestic manufacturing.

So, I am currently UNDERemployed in a company with stagnant growth. In fact, I have little work to do during a typical day. I yearn for challenges that will allow me to showcase my management, analytical, and problem-solving abilities. I would love to stay in manufacturing, but I believe my talents work well in other industries and the challenge of proving my case would be most welcome.

My specific experience includes:

• Market Research, Analysis, & Communications for major electronics manufacturers in the Aerospace & Defense industry.
• Supply Chain Management, Materials Management, Inventory Analysis & Control, and Production Control for electronics manufacturers.
• Direct sales experience at the retail and consulting levels.

Please see my Resumes page for html and pdf versions of my resume. Any job leads would be appreciated.