Tag: TOC

Fast Results Using TOC for Demand-Driven Manufacturing – Part Two
Manufacturers use constraints management first to gain the most demand-driven change

Last time, we talked about focusing on enterprise improvements rather than local efficiencies using constraints management (TOC). We discussed that continuous improvement tools such as TOC, Lean and Six Sigma work like “sandpaper” on an organization’s processes, smoothing various stages of their demand-driven journey.

I likened TOC to the “coarse” grit of sandpaper—the one to use first to get the best results–faster. Before discussing the other tools (which I’ll address in future articles), I wanted to share how the TOC principles we discussed last time have brought real results to two manufacturers.

Constraints management improves throughput, on-time delivery, more

My first example, a discrete manufacturer of test equipment for semi-conductors, decided that they could do better and that TOC was going to be the philosophy they utilized to do it. They had a lot of difficulty in production and in meeting their client requirements. They began by implementing drum buffer rope (DBR) scheduling. As part of this, they identified a drum for the organization and began managing it as the constraint. It is important to note that TOC people do not regard constraints as bad things per se, instead, they look at them as leverage or control points that allow you to simplify management of your system. There are many people that I come across who think TOC is about identifying and eliminating constraints. However, Goldratt viewed constraints as a positive item in that in an interconnected environment, the constraints provided the leverage points that greatly simplified management of the system. Goldratt once told me that the constraint within an organization should not move any more than once every two to three years.

Once the drum was identified, the next steps were to exploit the constraint and subordinate all other resources to the constraint. As part of this, the company identified a number of policy and process changes. First, they changed what they did when a constraint resource needed a first-article inspection before continuing to run. They began moving the parts requiring inspection to the front of the queue and, in some cases, removing parts from the test equipment in the middle of the test, in order to service the constraint faster. Soon, the team carried this first-in-line mentality throughout the organization with a laser-like focus on clearing anything that got in the way of the constraint producing to current customer demand. Here are their results:
- Increased constraint throughput by 120%.
- Increased on-time delivery from low 70% to 95%+.
- Cut cycle time and lead-time in half.
Before this change, the company was outsourcing 50% of the work for the constraint. They have since brought it all in house where the yields were much higher, plus, they added another 20% of throughput.

All of this was accomplished within four months and without making one physical alteration to production. No 5S, no kaizen events, no SMED, no value-stream maps, no re-laying out of the production process, no Six-Sigma projects. Also, no additional people or capital equipment were needed. The tools of Lean and Six-Sigma were critical to continuous improvement and refinement of the process, but Constraints Management (harkening back to the sandpaper analogy) served as the coarse sandpaper, taking a rough board and making the dramatic change of smoothing it out.

60% on-time delivery to 90+

Another example – During my work with a discrete manufacturer of capital equipment, with hundreds of parts needed to move through a spaghetti-type flow and meet up in final assembly. Chaos and stress reigned throughout this organization, with the head of final assembly serving as chief expediter. Our aim was to increase their on-time delivery rate which was in the low 60% range and their replacement part fill rate which was less than 50%.

We turned it around by focusing on synchronization and the pacemakers of production. We began by “choking work” into production at the rate the system could handle and subordinated all other resources to the constraints and to final assembly. Soon parts were delivered on time to final assembly, and, ultimately the customer. The results?
- On-time delivery up to 95%+
- Increased fill rate to the upper 90% range
- Returned profitability to the organization for first time in four years
- The head of assembly spent time managing assembly rather than expediting parts.
All of this happened in less than six months. Again, not a resource was added, not a single resource was moved; the physical flow of material was unaltered– yet these were the results.

In both of these cases, it was still critical to employ the tools of Lean and Six Sigma to continue the path of continuous improvement, and we’ll talk about that the next time I write to you. However, these cases prove that nothing gets results as fast as the use of Constraints Management. The board will never get as smooth as when Lean and Six Sigma are used after TOC– but to take a really coarse board and make it relatively smooth quickly and efficiently, you need the coarse sandpaper (TOC) –and then the medium (Lean) –and then the fine (Six Sigma)– to make it as smooth as glass.

This is part two of a three-part series. Here are the links to the entire series.
- Part 1, What Sandpaper Will You Use?
- Part 2, Fast Results Using TOC for Demand-Driven Manufacturing
- Coming soon
-John Maher

John’s passion for demand-driven manufacturing is equal to his interest in how this method improves the lives of employees within these environments. “I’m here to help, not to judge” comments John whose posts reflect why demand-driven matters and are based on his experience working in manufacturing environments and expertise in ERP, MRP, APS, supply chain, manufacturing planning and scheduling systems and constraints management.
April 23, 2018
What Sandpaper Will You Use? – Part One
What to Use to Get the Most of Your Demand-Driven Changes

Demand-driven manufacturing leaders are always refining their tools and tactics to ensure they’re spending their time wisely. This blog marks the first in a three-part series about using the tools of TOC, Six Sigma and Lean to help manufacturing leaders gain the most benefit from their demand-driven transformation.

Three in One

TOC, Lean, and Six-Sigma should all be part of the continuous improvement (CI) journey at your company – and knowing which tools are right for the job will help you realize your CI goals faster. And even though these three methodologies are not the end all, be all of continuous improvement, they offer proven frameworks and tool sets that are very effective at improving organizations.

During this discussion, I want to explain how the methodologies of TOC, Lean, and Six-Sigma work like sandpaper. TOC is the coarse, Lean is the medium, and Six-Sigma is the fine-grit sandpaper. The company is the board –or piece of wood in a particular state of roughness – and you have to know which paper to use, based on the state of the board. At Synchrono, we use all of these methodologies together—leveraging the right tools at the right time —and apply them strategically in our customers’ demand-driven transformation.

TOC to Start

I have never seen a more effective approach when you are just starting out than TOC. The methodology is all about understanding the entirety of the system and based on that, knowing where the leverage points are in the organization that, if affected, will bring about a rapid change to the entire system. It recognizes the interconnectedness and cause and effect of organizations, their people, resources, processes, and most important, policies.

When you first start a continuous improvement journey, the opportunities for improvement are great. They are everywhere within the organization and once the workers in the system have approval and the tools to change the system; they will do so with great effort. However, if we want to get the most out of these efforts, we need to focus these improvement efforts on the constraints/ leverage points of the organization to yield global results, not just localized effects. Said differently, we need to focus on the areas inhibiting enterprise performance, and I have not seen a more effective approach at doing this – and doing this quickly – than the TOC methodology.

Next time, I’ll talk about how to use TOC to pinpoint the changes necessary to get the most out of your continuous improvement efforts. Then, I’ll address the role of kaizen events and drill down into how Six Sigma – the finest grit of sandpaper – can refine your process change and ensure that each moving part works harmoniously together. Like many jobs, having the right tools makes all the difference in the world. The right methodologies, along with ongoing refinement, will steer your demand-driven environment towards embodying the best in form and function.

This is part one of a three-part series. Here are the links to the entire series.
- Part 1, What Sandpaper Will You Use?
- Part 2, Fast Results Using TOC for Demand-Driven Manufacturing
- Coming soon
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-John Maher

John’s passion for demand-driven manufacturing is equal to his interest in how this method improves the lives of employees within these environments. “I’m here to help, not to judge” comments John whose posts reflect why demand-driven matters and are based on his experience working in manufacturing environments and expertise in ERP, MRP, APS, supply chain, manufacturing planning and scheduling systems and constraints management.
April 9, 2018
Efficiency vs. Productivity: Metrics that Matter…Until They Don’t

Measure efficiency and productivity against your REAL goal

I keep seeing the word efficiency in the manufacturing media. For someone who is a Constraints Management person, this is the equivalent of saying “Ni” to the Knights Who Say Ni (Monty Python reference, okay?) or like scratching your fingernails across a blackboard. It is one of those words that I think we should remove from the English language.

When we look at the organizations of today, words like efficiency and productivity get thrown around with little understanding of what is required to improve one of these measurements (metrics). If I change to improve efficiency, what are the positive results, and what are the negative results? Also unknown is the outcome to the organization as a whole. Let’s discuss why an efficiency metric is usually not the right metric and what a Lean manufacturing expert does when measuring true value in the supply chain.

Cost vs. Throughput

Let’s start by looking at how people usually define productivity and efficiency in practice (from the TOC-ICO Dictionary). There’s a big difference between managing efficiency and productivity using traditional thinking and using Constraints Management thinking. If you are an Operations Manager, you “feel the heat” on these two competing deliverables every day.

Cost-world paradigm (page 35): The view that a system consists of a series of independent components, and the cost of the system is equal to the summation of the cost of all the sub-systems. This view focuses on reducing costs and judges actions and decisions by their local impact. Cost allocation is commonly used to quantify local impact.

Usage: In the cost-world paradigm, global impact is believed to be the sum of all local impacts.

Perspective: This paradigm is in conflict with the throughput-world paradigm, which claims that global improvement is NOT the sum of local improvement and that the use of cost allocation often results in incorrect decisions.

Throughput-world paradigm (page 123): The view that a system consists of a series of dependent variables that must work together to achieve the goal and whose ability to do so is limited by some system constraint. The unavoidable conclusion is that global improvement is the direct result of improvement at the constraint, and cost allocation is unnecessary and misleading. This paradigm conflicts with the cost-world paradigm.

Here’s how the terms efficiency and productivity set up a conflict for an Operations Manager:

Operations manager core conflict (page 86): The conflict is between judging the Operations Manager‘s performance according to the local impact of decisions and judging the manager‘s performance according to the global impact of the manager‘s actions. The operations manager is under constant pressure to reduce waste and the biggest waste in operations is viewed as idle time on a resource (person or equipment). In figure 1 below, the assumption on the B-D side is: A resource standing idle is a waste. Therefore, local efficiency is used to measure resources. The operations manager then looks for work (even if it‘s not needed now) to keep the resource busy. When work is increased on the shop floor, local efficiencies go up and top management is satisfied. BUT maximizing efficiencies results in increased work-in-process, which increases lead times and inhibits flow, thereby jeopardizing sales.

Figure 1 (Adapted from TOC-ICO Dictionary, Page 87)

Productivity vs. Efficiency

Sam Ashe-Edmunds of Demand Media explained this conundrum perfectly in his Small Business Chronicle blog post:

“Increased efficiency can hinder productivity and vice versa. In its simplest form, an explanation of productivity versus efficiency is the difference between quantity and quality. It’s not always possible to achieve 100 percent quality at maximum productivity levels. Finding the right combination of productivity and efficiency helps you optimize your output while minimizing losses.”

He goes on to say that “businesses often measure productivity by output during comparable time periods. For example, if you produce 1,000 units one week and 1,100 units the next, you are more productive the second week.” This example is a cost-world example. The demand is not factored into the evaluation of productivity. It is only productive if it turns into sales. Since most machines and processes are decoupled from actual demand, the Operations Manager builds to the plan provided by the ERP System, because they have nothing else to tell them otherwise. Unless they have been managing for some time, and they have built a level of intuition that is better than the formal system.

In this case, if the actual demand is 900, the Operations Manager would be thinking that they were doing GREAT! However, they are actually creating waste; as in one month they had 100 units of excess production, in the next month they had 200 units of excess production, or 300 units in excess inventory.

Since inventory is considered an asset on the company financial statements, the balance sheet looks good to the CFO, CEO and stockholders. However, an opportunity is lost during this scenario, especially if there are some other products that were not meeting their demand requirements. This is so important, but is not a traditional measurement that companies use. This “lost opportunity metric” is now something that Lean manufacturing experts try to keep at the top of the list.

In other cases, businesses measure productivity by comparing employees, locations or distribution methods. If Bob sells $10,000 worth of business during the month while Joe sells $9,000, Bob is more productive. If Bob sold $12,000 the month before, he’s still more productive than Joe this month, but less productive this month than he was last month. True, but this does not have any relationship between if the company is closer to the goal, or further from the goal. Something is missing.

The Efficiency Effect

Efficiency relates to the quality of your work, which might include creating output with less waste, using fewer resources or spending less money. If Bob sold $10,000 in May but spent $3,000 on travel expenses, while Joe sold $9,000 in May but did so over the phone, Joe is more efficient and creates a larger profit. This is a case in which increased efficiency justifies decreased productivity. True, but this does not have any relationship between if the company is closer to the goal, or further from the goal. Something is STILL missing. Many other unmeasured factors are not addressed, like if Bob is new to the company, and needs to build his clientele, or one of Bob’s customers is looking for help on a possible business expansion that requires input from Bob. Month-to-month measurements often hide some of the overall processes or factors not included in the number being measured. Maybe the next term will shed some new light?

Efficient Productivity

Some businesses measure productivity by including only quality output. For example, if a production plant produces 10,000 units in March and only 9,000 units in April, productivity in March is not necessarily higher. If the 10,000 units produced in March included 1,000 that were defective and couldn’t be sold and another 1,000 that came back for service, the productivity for the production plant in March is 8,000 units. If only 500 of April’s units were defective or returned, productivity in April is 8,500. Still true, but this does not have any relationship between if the company is closer to the goal, or further from the goal. These measurements have very little to do with how the company is really doing. They are only incomplete pieces, which are hidden from the people in the system who make the decisions –day-in and day-out. Only if the measure of input is related to the actual output will the measurements make logical sense. As long as part of the system measures in one way, and other areas measure in another way, these will create conflict and confusion.

Balancing Productivity with Efficiency

When you emphasize the quantity aspect of productivity, such as by paying bonuses on amounts produced or sold, you might encourage employees to be less careful. “If you tell me how you measure me, and you have a misleading measurement, what will you expect from me?”

This might not be a bad thing if your increased quality output outweighs the number of problems you have. For example, a production plant’s rush to increase output may increase defects and returns by 10 percent. However, working at that speed might allow the plant to increase quality units by 30 percent. When you put a premium on efficiency, and try to eliminate all problems, you might scare workers into slowing down enough to negate the incremental increase in quality you get with an exponential decrease in the quantity of work produced.

So, what should you measure when you’re deciding how productive your plant is and how efficient it can be? See Aligning Metrics to Strategy to read about how to get closer to your goals and next time, we’ll address metrics you can take immediate action on to improve performance.

March 26, 2018
How the Internet of Things Can Shorten Lead Times

A new study in Modern Materials Handling reports that 86% of industrial organizations are currently adopting IoT (Internet of Things) solutions, and 84% believe those solutions are very or extremely effective. Manufacturers lagged behind the industrial segment as a whole, with only 77% of manufacturers implementing IoT in their facilities.

So, what is holding manufacturers back? Anecdotally, I can share that many of the manufacturers I talk to intend to implement the IoT in their facilities or have already started a project. But, they are less sure about their results than the respondents to the study.

In this series of posts, our goal is to break through the hype and the uncertainty around the IIoT (Industrial Internet of Things) by focusing on projects you can execute and for which you can achieve a measurable ROI in 2018.

In the first post, we looked at how the IIoT can help manufacturers lower inventory levels. (Read the full post here.) We also shared how one of our customers was able to reduce inventory by as much as 55% in one factory, while at the same time reducing lead times from twelve weeks to two.

Some of the customers I talk to are initially skeptical that they can both reduce inventory AND reduce lead times. Achieving these results at the same time seems counter-intuitive because they think they need to keep high levels of inventory on hand and in process to meet customer demand. In today’s post, I want to unpack that by focusing on how the IIoT and Demand-Driven Manufacturing (DDM) can help you achieve both objectives in your facility by implementing one specific manufacturing philosophy.

The IIoT in action: TOC

Today’s IIoT project leverages the Theory of Constraints (TOC) or constraints management principles. Like the Kanban project we talked about (see How the IoT Can Help You Lower Inventory Levels), TOC isn’t inherently an IIoT project. You can implement TOC manually, but when IIoT data-sharing technologies are leveraged, your TOC efforts are turbocharged for even greater benefit to your bottom line.

Many of you are, no doubt, familiar with TOC, but let’s quickly cover what it is so we’re all on the same page. TOC says that, in any given manufacturing environment, there are a small number of constraints that limit the throughput of the factory. Increasing productivity at any other point in the system will not increase overall productivity because the constraint cannot keep up.

For more details on the four types of constraints, refer to my recent post: It’s Time to Revisit Your Constraints.

In the Demand-Driven Manufacturing environments we work in, we apply constraints management technology (based on TOC) to constraints in the system. By understanding the constraints – and their capacity – we can set the optimal rate of flow to that constraint (see CONLOAD™ Scheduling Methodology: Set the Right Pace for Production). This reduces congestion and keeps work flowing throughout production. Real-time, IIoT data allows for automated adjustments based on changes in demand, priorities, etc.

So how does synchronizing the pace of production to the constraint in real time lower both lead times and inventory levels? In a traditional make-to-stock manufacturing environment, as much as 90% of cycle time is queue time, that is, a part waiting for its turn on the machine or in the work center. By synchronizing the flow of material to the constraint in the system, material spends less time in queue and cycle times are shorter. And, because less material is in queue, WIP drops as well.

Related Post: It’s Time to Revisit Vendor Managed Inventory

Some of you may be thinking, “Ok, that explains how cycle times and WIP inventory drop, but how does constraints management affect lead times? We measure lead time from the time an order is taken until it is shipped. I still can’t manufacture anything faster than my constraint, and it doesn’t lower lead times if I can’t start the order any faster.”

Good point. But, what we’ve found is that lead time typically drops as well for a variety of reasons such as better prioritization of projects at the constraint and increased capacity. When all work throughout the facility is synchronized to the pace of the constraint, everyone knows what they need to do next, and no time is wasted running orders through the system that aren’t a priority. This is especially impactful in facilities where changeovers take time either because of retooling or a paradigm constraint, such as a focus on productivity at every workstation that slows the overall factory down.

In my last post, I shared the example of Dynisco, a leading manufacturer of materials-testing and extrusion-control instruments that reduced inventory levels by 55% in one of its facilities while at the same time reducing lead time from 12 weeks to 2. Today, I want to tell you about another Synchrono customer that addressed a lead time issue with Demand-Driven Manufacturing.

Rex Materials Group (RMG) manufactures custom vacuum-formed ceramic-fiber products. In the late 1990s, the company implemented TOC and modified its home-grown systems to apply drum-buffer-rope principles. That system worked for a while, but eventually, the company decided they needed something better to feed their continuous improvement efforts.

RMG implemented SyncManufacturing™ synchronized planning, scheduling and execution software from Synchrono® across three separate facilities. The first facility went live in 90 days and the second and third in 45 days each. By accelerating their TOC efforts, RMG went from lead times of three to four weeks, on average, to delivering 30-40% of products within five days of receiving the order. They can even ship some overnight. Read the full case study.

Want to learn more? Here are some related resources that can help you get started on your next IIoT project in 2018:

Video: What is Demand-Driven Manufacturing?

White Paper: Three Key Strategies of Modern Demand-Driven Manufacturing (Watch the video here.)

Video: Manage Manufacturing Constraints and Optimize Production Flow with CONLOAD

February 12, 2018
Time to Revisit Your Constraints

We talk a lot about constraints management in our work with customers who are implementing Demand-Driven Manufacturing (DDM) in their facilities. That’s because constraints management is fundamental for synchronizing the pace of production and keeping the demand (orders) flowing throughout the shop floor. But, our focus is naturally on physical constraints, e.g., that piece of equipment or workstation that is preventing you from delivering on time or offering shorter, more competitive lead times to your customers.

Not Everything is About Production

Those of you who have spent time studying the Theory of Constraints (TOC) in-depth understand that it’s not always all about the production process. Constraints can fall into one of four categories:

Physical – These are the constraints we focus on with technologies like CONLOAD™ that set the pace for production based on the capacity of the physical constraint.

Policy – These constraints dictate how work is performed. Sometimes you can do something about them (e.g., an old company policy that no longer makes sense), and sometimes you can’t (e.g., a regulation that still might not make sense but needs to be followed anyway).

Paradigm – This is a way of thinking that gets in the way of meeting commitments, such as the COO’s resistance to outsourcing processes to other companies even if they can do it faster, better or cheaper than you can.

Market – Put simply, capacity exceeds demand. Remember, TOC emphasizes throughput (The rate at which the system generates “goal units,” Goldratt) and not productivity.

For some manufacturers, the real constraint over the last decade has been their market. Manufacturing production has seen its share of ups and downs in the last ten years. It wasn’t that our facilities couldn’t produce more, many manufacturers just didn’t have the orders to warrant increased production.

Shifting Your Paradigms

Early indications are that many of the market constraints on US manufacturers may be melting away in 2018 through 2020. (Along with a few policy constraints.) Manufacturing GDP is expected to slightly outpace GDP for all industries (2.5%) and grow by 2.8%. (Some analysts are predicting even higher numbers, but like our customers, we prefer to focus on more conservative estimates when doing mid-term forecasting.) The stock market is also at an all-time high, indicating strong investor confidence and more money for investment. Oil prices are expected to remain low, keeping the cost of manufacturing and transportation of goods to market in check.

In other words, it’s time to take your focus off the market constraints you can’t do much about and place it on the constraints that are within your control. If you have outdated policy or paradigm constraints, it’s time to rethink your thinking. If you have physical constraints – leverage them to set the optimal pace for uninterrupted production flow.

Time flies and so do great economies. Don’t let the best market in a decade pass you by without taking advantage of it. If your constraints are physical, here are a few resources that may help:

Video: Manage Manufacturing Constraints and Optimize Production Flow with CONLOAD

White Paper: Metrics That Drive Action

Case Study: GIW Industries

February 5, 2018
FAQ: Can I Use Demand-Driven Manufacturing in a Make-to-Stock Environment?

Demand-Driven Manufacturing seems like it was made for Make/Assemble-to-Order and Engineer-to-Order environments. It’s true that Demand-Driven Manufacturing can be beneficial for manufacturers who already produce goods based on customer demand because it improves their responsiveness to customers and lowers lead and cycle times.

Demand-Driven Manufacturing is a method of manufacturing where production is based on actual customer orders (demand) rather than a forecast.

But what about Make-to-Stock environments? These manufacturers also produce goods based on customer demand, but instead of actual demand, production is typically based on forecasted demand. Considering our definition of Demand-Driven Manufacturing – a method of manufacturing where production is based on actual customer orders rather than a forecast – it seems like that would preclude the Make-to-Stock manufacturer from taking advantage of Demand-Driven Manufacturing principles, right?

Not at all.

The challenge in MTS environments is replenishment lead time.

That is, the lead time provided by the customer is less than the lead time needed to complete the finished good. Given this, MTS Demand-Driven Manufacturers use their forecast to establish a stock buffer. Production execution, however, is based on actual demand. The stock buffer provides just-in-time materials to complete the order, ensuring there are no delays in responding to the demand signal. Here’s how it looks:

MTS manufacturers apply Lean/Demand-Driven strategies to make the stock buffer as small as possible. This reduces carrying costs and the potential for waste. As we’ve covered other posts, eKanban software is a great way to not only reduce lead times, but inventory costs. If considering eKanban, you will want to check out Real-world Advice for Getting Started on eKanban.

Lower lead times are one of the primary benefits we see in manufacturers who implement components of the Synchrono Demand-Driven Manufacturing Platform (see the sidebar for other benefits). For example, Dynisco, an instrumentation manufacturer, reduced their lead times from 12 weeks to 2. Rex Materials Group reduced their lead times from 3-4 weeks to less than five days in some cases. You can read their case studies and those from several more customers on our website.

Other ways MTS manufacturers benefit

As noted in the graphic here, Demand-Driven Manufacturing adds tremendous value to MTS environments in a variety of ways.

For example, one of the strategies of Demand-Driven Manufacturing is constraints management – adapted from the Theory of Constraints (TOC). According to the TOC, there are a limited number of resources in any manufacturing environment that limits the manufacturer’s ability to meet demand (e.g., the constraint(s)). Scheduling production flow to the capacity of the constraint resource(s) improves overall production flow and on-time delivery rates.

To show how we work to manage constraints, we’ve posted a short video on YouTube – Manage Manufacturing Constraints and Optimize Production Flow with CONLOAD.

Here are some additional resources that can help you explore Demand-Driven Manufacturing and what it might mean for your organization. And, as always, reach out to us with any questions you have, or if you’d like to discuss a pilot project.

Website: Why Demand-Driven Manufacturing?

White paper: Demand-Driven Manufacturing—Metrics that Drive Action

Video: What is Demand-Driven Manufacturing?

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January 22, 2018

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