Author: David Dehne

Weathering the Next Recession

The global economic recession that started in 2007/2008 hit the manufacturing sector hard. In February of 2009, The Economist even published a piece called The Collapse of Manufacturing. If you recall, this was right about the time the automotive manufacturer bailouts kicked in because they, like the larger financial institutions, were deemed too important to the US economy to fail. It felt like we were on the verge of an economic collapse.

Whether they supported that bailout or not, most people recognized that it was a short-term solution to a long-term problem. The auto industry, like many other manufacturing sectors, was awash in excess capacity. When consumer demand dropped due to the recession, this excess capacity could no longer be ignored because it led to mountains of unsold inventory and raw materials sitting in the supply chain.

Many companies didn’t survive the recession, at least not in their current state. In 2010, Harvard Business Review said that 17% of the companies they were following in a post-recession study had gone bankrupt, were acquired or went private. Opinion makers and pundits differ as to whether the recession actually ended in 2010, so that finding might have been a bit premature.

Things are looking up

While there are still plenty of naysayers who can find the cloud surrounding every silver lining, many economists agree that indicators are improving as we approach the end of 2017. The MAPI Foundation predicts a pretty substantial growth in manufacturing output at least through 2020.

As I write this, unemployment has fallen to 4.1%, a 17-year low, with manufacturing being one of the primary beneficiaries. According to MarketWatch, so far in 2017, manufacturing jobs have increased by 138,000 after falling by 34,000 in the first 10 months of 2016.

Learning lessons from the past

Let’s assume (and hope) these predictions are accurate and the positive trends continue. Now is not the time to get complacent. Unfortunately, recessions are like earthquakes. You know they will happen. You can even monitor for signs of an impending quake. But it is almost impossible to predict when and where they will strike and how much damage they will do. The MAPI Foundation’s growth in output levels off in 2020 because they are allowing for the possibility of another recession. They don’t go so far as to predict one, but they know it will eventually happen.

Clearly, pulling back and not investing in anything isn’t the answer. Instead, the key to surviving the next recession is to avoid making the same mistakes. Demand-Driven Manufacturing can help.

Understand your true capacity – One of the key principles behind Demand-Driven Manufacturing is the Theory of Constraints (TOC). In TOC, there is always one resource that limits the factory’s ability to meet demand. For example, it might be a work station that has a constant backlog, impacting all downstream operations. In Demand-Driven Manufacturing, that constraint becomes the pacemaker for production, keeping work flowing at a constant rate, or load (e.g., CONLOAD) Watch this short demo of CONLOAD to see what that looks like.

Many manufacturers using CONLOAD (part of SyncManufacturing) find that this process actually helps them to increase capacity; because constraints are managed, work continuously flows.

Avoiding excess inventory – In Demand-Driven Manufacturing, production scheduling is based on actual orders; nothing is produced until it is needed. For example, a manufacturer may believe there is going to be an uptick in orders for a particular widget. They might even add capacity in terms of more modern equipment or higher-skilled operators. But that widget will not be produced until an order is actually received. Likewise, the components that go into the final product will not be produced either, lowering both finished goods and WIP inventory.

December 4, 2017
3 Prerequisites to a Modern Demand-Driven Supply Chain

In 2010, Gartner estimated that manufacturers outsourced about 70% of the products they make to other manufacturers. I haven’t seen a recent statistic, but that still feels about right.

So, it only makes sense that, for most manufacturers, implementing modern demand-driven or pull-manufacturing techniques will require collaboration with many partners across the entire supply chain.

Before you can collaborate with your supply chain partners, you need to get your own house in order. Here are three things you need to do:

#1 Digitize. The demand-driven supply chain runs on data—the right data in the hands of the right people at the right time. Before you can make this happen, you may need to address a few data issues in your own operations. It’s not unusual for us to work with companies that have two or three ERP systems, especially if they’ve grown through acquisition, in addition to several point solutions for things like maintenance, scheduling, time management and so on.

For those of you who have been in the industry a while, the idea of a data standardization and consolidation project may send you reaching for the Tylenol bottle. You’ll be glad to know that with the right technology, you can get through this relatively headache-free. For example, we helped Orbital ATK, an aerospace manufacturer of custom composite parts, connect over 100 individual data sources to collect data from more than 61,000 tags. At a recent conference, Paul Hardy, Application Architect at Orbital ATK, gave a fascinating presentation on how they use this data to improve operations. You can access his talk on our YouTube page here.

#2 Synchronize. The next prerequisite is to synchronize everything (people, processes, materials, machines and data) at the order level. If production flow isn’t aligned to customer orders inside your own facilities, you can’t deliver the right data to your supply chain partners.

This synchronization alone can have a dramatic impact on performance. We worked with GIW Materials, a manufacturer of heavy-duty centrifugal slurry pumps, to help them lower cycle times and improve on-time performance. The crux of the solution was to optimize product flow and control cycle time by synchronizing everything to orders: pattern information, flasks, combination equipment, engineering revisions and capacity. The impact was so noticeable to their customers that GIW doubled their revenues in two and a half years. You can access their case study here.

#3 Visualize. Once you’ve digitized your data and synchronized production flow to customer orders, you need to put the right data into the hands of the right people. These days, there is almost no limit to the amount of data we can collect. In the demand-driven supply chain, more is not necessarily better because you can easily overwhelm people. Here are the three areas where you should focus your efforts:

Demand and supply – visibility and synchronization of the demand signal, material and resource availability to drive uninterrupted production flow.

Production flow indicators – visibility into stock buffer levels, constraints, shop floor events, etc.

Priorities – adapting to demand and communicating changes across the supply chain.

Pulling it all together

If the products you manufacture are heavily reliant on outsourced components or services, you may not have the luxury of waiting long before you roll out your demand-driven manufacturing approach to the rest of your supply chain. This was the case with a microchip manufacturer we recently worked with.

A growing part of this manufacturer’s business was to receive parts from OEMs and supply them to contract manufacturers. Both the OEMs and the contract manufacturers gave the manufacturer forecasts, but the formats were different, and like all forecasts, not always reliable. As a result, they were constantly in reactive mode, manually standardizing data from multiple sources in spreadsheets while juggling variances in supply and demand. We worked with them to consolidate the data into a single screen view that showed real-time, aggregated replenishment, inventory, and order status information. We also created a platform that allowed them to provide similar views to their OEM and contract manufacturing partners.

Related resource: White paper: E2E Supply Chain Visibility Technology is Here

November 20, 2017
A New Way of Looking at Manufacturing Metrics

Most experts agree. The metrics you use to manage your manufacturing operations need to matter, and they need to be actionable. We concur. For a detailed review of the operational metrics we recommend in a demand-driven manufacturing environment, refer to our Metrics for Action Guide.

Conventional wisdom also says to keep the number of metrics you measure to a minimum. This advice is based on well-established research that shows that the human brain just can’t focus on more than five to seven things at a time. Trying to measure too many things at once has long been a recipe for never getting anything done.

Besides, many manufacturers are still calculating metrics by hand (or spreadsheet) from information that is gathered manually, often with considerable effort. By the time they get the information they’re looking for, it’s already obsolete. Measuring more than a select handful of metrics may not be realistic.

But, maybe it’s time to take another look at the way we think about metrics in manufacturing.

It’s time to let go of conventional wisdom.

Today’s technologies have solved the problem of outdated data. Metrics can be calculated in real-time and refreshed almost instantly. Tools are even available to gather data from the most antiquated of ERP systems, standardize it, and combine it with data from the increasingly extensive sources enabling the Internet of Things (IoT) that exist in almost every manufacturing environment.

Technology also gives you the power to create a set of role-specific metrics that are accessible through dashboards from any device. A plant floor manager can see the metrics that matter at the plant level in Peoria using a tablet, while the COO can see the metrics that matter across the entire operations using a smartphone while waiting for a flight in Singapore.

Modern technology collects and analyzes data from multiple sources, providing real-time visibility to metrics you can quickly take action on to improve.

Of course, technology hasn’t yet changed our ability to concentrate on more than half a dozen things at once. (Regardless of how much we may try.) However, with the right applications, we don’t need to.

For example, plant floor managers no longer need to comb through every metric and compare it to acceptable norms or historical data to identify problem areas. Nor do they need to walk the plant floor hoping to spot possible problems, which savvy factory workers are often adept at covering up. With the right software, dashboards can be as sophisticated as a visual representation of the shop floor with color-coded indicators showing problem areas. The plant manager can measure metrics like queue turns at every single workstation in their domain, but they only need to pay attention to those workstations where queue turns are outside of the acceptable range.

Plant level view with indicators showing the status of key metrics at each workstation.

We’re not suggesting you go wild with managing metrics. Remember, they still need to matter, and in demand-driven manufacturing, there are generally fewer metrics that do. However, we are saying that if there is a metric that matters to you, why be held back by conventional wisdom from the 20^th century?

To learn more about how technology can help you manage – and visualize – the metrics that matter, join us online for our on-demand webinar Visualizing Metrics in the Factory of the Future.

November 13, 2017
FAQ: Is Demand-Driven Manufacturing the Same Thing as Lean?

Many of our customers don’t start out looking to implement Demand-Driven Manufacturing per se. Often, they’re focused on Lean Manufacturing or at least some element of it. In fact, customers often find out about us as they search for an eKanban or production scheduling solution that will work with their current ERP system.

However, at some point in the conversation, they will inevitably ask, “Is Demand-Driven Manufacturing the same thing as Lean Manufacturing?”

Demand-Driven Manufacturing isn’t synonymous with Lean or other related initiatives such as Theory of Constraints. Instead, it supports and is supported by them. To understand that, let’s look at basic definitions of each of these philosophies, including Demand-Driven Manufacturing, to see how they are related.

Demand-Driven Manufacturing enables a synchronized, closed loop between customer orders, production scheduling and manufacturing execution.

Demand-Driven Manufacturing is a manufacturing method that enables a synchronized, closed loop between customer orders, production scheduling and manufacturing execution – all while synchronizing the flow of materials and resources across the supply chain.

Another term commonly used for Demand-Driven Manufacturing is pull-based or demand-pull manufacturing. Instead of producing to what you think will happen (forecasts) or to maximize an efficiency metric like asset utilization, the only variable is actual demand, and all production is synchronized to it.

Both Lean Manufacturing and Theory of Constraints emphasize managing variability as part of a continuous improvement effort.

Lean Manufacturing focuses on the removal of waste from the production system; waste being defined as anything the customer isn’t willing to pay for. Pull manufacturing isn’t the same thing as Lean, but it is one of the five principles of Lean as defined by Womack and Jones in their landmark book Lean Thinking. So, at some point in your Lean journey, you should be replacing your push-based production scheduling approach with one that is pull- or demand-based.

On a side note, going from push to pull is almost impossible to do when your schedule is reliant on the push-based logic found in most ERP systems. (Most notably MRP and APS.) That’s why we developed Synchrono software, including SyncManufacturing, as web-based applications that can be easily used with your existing systems. For a more thorough discussion on push vs. pull, download our white paper The Next Generation of Planning and Scheduling Solutions.

Demand-Driven manufacturing is also one of the easiest and quickest elements of Lean Manufacturing to implement. Even though it’s number four on the list of five principles of Lean, you don’t have to get through numbers one through three before you can start realizing benefits such as reduced lead times and lower inventory levels.

Theory of Constraints (TOC) emphasizes increasing throughput. Be careful though. In the vernacular of TOC, throughput does not refer to production. Instead, throughput is the rate at which the organization generates money by producing finished goods that are sold. Excess inventory sitting in the warehouse is not counted. That tightly matches Lean philosophy in that Lean defines waste as anything the customer is not willing to pay for. Excess inventory and the storage and handling of it certainly falls into that category.

A constraint is defined as anything that limits throughput. Inside the facility, that is often a work center. Instead of managing the production capacity of every work center, TOC focuses on synchronizing production to the constraint. This is a vital component of Demand-Driven Manufacturing as well, and you can see how this works in this excerpt from one of our recent webinars.

I hope this discussion not only helped clarify the differences between these common manufacturing philosophies, but also highlighted how Demand-Driven Manufacturing can help you reach your goals regardless of which philosophy drives your organizational thinking. As always, we welcome your comments – and I’d be happy to answer any specific questions you might have. Just submit them below.

November 6, 2017
Guest Blog: Real-world Advice for Getting Started on eKanban
by Jim Shore

Through this guest blog series, I’d like to share some of my experiences implementing supplier quality and Lean manufacturing initiatives by focusing on eKanban systems. This first entry offers advice for planning an eKanban rollout – suggestions that can also be applied across any Lean manufacturing project.

As a result, my hope is that you, too, will experience successful Lean results.

Leadership matters

My training as a U.S. Marine gave me many skills I carried over into civilian life and into my work as a Lean practitioner. First, I gained deep respect for strong leadership; and second, I’ve come to value a pragmatic approach to project execution.

Successful projects start with buy-in from the top and an eKanban initiative is no exception. At a minimum, recruit an executive sponsor to serve as the project spokesperson – someone who will fully support and clearly communicate with all stakeholders the rationale for the project. I know it sounds simple. Even though the benefits to the business are real (e.g., reduced inventory waste and carrying costs and more) asking people to change the way they work is also real. Let your leaders know project success is accelerated through gaining universal buy-in. (If you think about it, this is also a waste-reducing, Lean strategy!)

The reality is that sometimes change is welcomed and other times you may meet resistance. Efficiency programs, whether Lean, Six Sigma or Theory of Constraints (ToC), require that teams understand the impact change can have on an environment. Change management strategies stress over-communication of:
1. What the organization intends to accomplish;
2. Why the organization is undergoing the change;
3. What the change means to each individual;
4. How success will be measured;
5. How accountability will be measured.
From the plant floor to senior management, buy-in starts with a clear rationale and explanation of how the new eKanban process or Lean methodology will add value. Leaders must effectively engage all levels of the team; explaining how the new process is great for them, the company, the customer and suppliers (for those using supplier Kanbans). The last two bullets are extremely important. Ensure it is clear how success will be defined and how everyone will be held accountable for achieving it. In my experience, the best method is tying the annual bonus to the success of the project.

Overcoming barriers to create lasting change vs. “initiative-of-the-month” change

While rare, resistance can manifest as blatant sabotage of the new Lean initiative. More likely, resisters will remain quiet and hope the advocates of the new method will lose enthusiasm and the execution of the Lean project will fade, reverting to the status quo. To reverse this, make them part of the solution.

On an eKanban project I led for a materials testing and extrusion-control instrumentation manufacturer, the rollout of the new software involved multiple sites. Corporate leadership sponsored and evangelized the project, but we still needed buy-in at the local plant level. By involving outspoken resisters in the process, we ended up gaining some real advocates – it also helped that we were able to reduce the replenishment process from 66 to just 6 simple steps.

It goes without saying that for this – and any eKanban project – you achieve success through consistent communication and universal team buy-in. Depending on where your replenishment occurs, this principle extends beyond the four walls of an individual plant or enterprise, to your suppliers. (I’ll provide advice for engaging suppliers in the next post.)

As part of their advocacy for the eKanban initiative – or any modern demand-driven supply chain project – leaders need to distinguish the project as a serious, ongoing operating process, not an initiative of the month.

Drive the planning process with bottom-line facts

A significant part of the planning process is business justification. Automating replenishment with an eKanban system provides some highly quantifiable returns.

There is a real cost of carrying inventory and eliminating this cost frees up accessible cash that can be reinvested into the company. Consider the following:
- The cost of just carrying inventory at a component level adds 10% to the valuation of the actual part – and that valuation increases by 10% for every month the material is not transformed into sellable goods.
- On average, the cost of carrying finished goods is approximately 20% of its cost.
For manufacturers managing materials with expirations, these costs can be compounded through scrap.

These are just some examples of costs I help clients quantify as part of their business case for investing in an eKanban solution. Examine how these cost savings could impact your business. You can see how real-time inventory replenishment with an eKanban system can pay for itself fairly quickly.

In the next post, I’ll cover some best practices for eKanban implementations utilizing Kaizen events and value stream mapping.

Related resources:

Article: Going eKanban – Moving from a Manual to an eKanban system

Case Study: Continuous Improvement Immersion + the Right Tools Proves Profitable for Dynisco

White Paper: Common Barriers to Moving from Push to Pull Manufacturing

Jim Shore is the Principal of Quality Lean Solutions, a Consultant Firm that specializes in Medical Device companies, Supplier Quality and Lean Manufacturing principles. Mr. Shore is co-author of “Proactive Supplier Management in the Medical Device Industry” (2016: Quality Press). Jim has 25 years of quality and supplier management experience in medical devices, semiconductor, aerospace and defense for firms and organizations including Titan Medical, Nypro Healthcare, Boston Scientific, Aspect Medical, Brooks Automation, Raytheon and ACMI Gyrus (now Olympus). He is Six Sigma Black Belt and Quality Manager/Operations Excellence-certified by the American Society for Quality (ASQ), as well as an ASQ-certified Quality Auditor and Mechanical Inspector. A veteran of Operation Desert Storm, he served in the U.S. Marine Corps for more than 15 years.
October 30, 2017
3 Ways to Put Big Data to Work in Your Factory

Is enthusiasm for Big Data wavering?

In 2015, McKinsey Global Institute claimed that the IIoT had the potential to create as much as $3.7 trillion in economic value in the global manufacturing sector by 2025. They also predicted that 80 to 100% of manufacturers will have implemented IIoT applications by then and already be reaping the benefits of data-driven insights into their operations.

When Gartner surveyed manufacturers in 2016, nearly three quarters said that their organization had invested or were planning to invest in Big Data, perhaps putting the manufacturing sector a bit ahead of schedule.

However, the Gartner survey also uncovered signs that Big Data investments may not yet be providing the anticipated returns. A full 85% of projects were still at the pilot stage. And, as further evidence that enthusiasm for Big Data may be wavering, only 11% of those who said they had invested claimed their Big Data investments were at least as important as other IT initiatives.

To drive ROI, begin with a purpose in mind

From our perspective, a large part of the reason Big Data/IIoT projects fizzle out is because team leaders and company executives don’t have a clear vision of the purpose of the initiative. They gather data as though it were a valuable raw material, but then they struggle to make anything useful out of it.

In this post, I’ll cover the three ways you can use Big Data to improve operational performance.

#1 Predictive analytics – The most common benefit espoused by Big Data enthusiasts is gaining insight into what might happen so you can prepare. Bernard Marr, a noted speaker and columnist for Forbes, describes it this way. “Big Data works on the principle that the more you know about anything or any situation, the more reliably you can gain new insights and make predictions about what will happen in the future.”

Predictive maintenance is probably one of the best-known applications of predictive analytics and Big Data. Before the IIoT, manufacturers had to guess how long a piece of equipment would last and when it would need maintenance. Unplanned downtime was common and costly.

Intelligent machines (even if that intelligence is retro-fitted) provide alerts on when the equipment is performing outside of normal parameters, e.g., running at a higher temperature indicating excess friction. And when connected to smart manufacturing tools like SyncOperations™, automated workflows and alerts to maintenance address the issue before it becomes a problem. From a demand-driven manufacturing perspective, this turns unplanned downtime into planned downtime and gives the planner/scheduler time to adjust and optimize flow.

Related resource: How Technology Will Connect Your Enterprise and Create the Demand-Driven Factory of the Future – Today.

#2 Continuous improvement – Continuous improvement is the cornerstone of any Lean initiative and has become a best-practice throughout the industry, even in those organizations that don’t consider themselves Lean. Big Data gives you the data you need to measure what matters and the ability to work with real data as opposed to someone’s best guess about what’s happening on the factory floor.

Of course, it goes without saying that a BigData initiative is only as good as the data the manufacturer has to work with – and if the right data can be accessed by the right people at the right time. In a typical manufacturing operation, data may be stored in dozens of places. Managing issues impacting production is easier with software like SyncManufacturing™ that can leverage its own data in addition to that stored in an ERP or other external system – and use it to make real-time adjustments to ensure production is flowing and resources are synchronized throughout the factory and extended supply chain.

Related resource: Metrics that Drive Action

#3 Real-time responsiveness – Finally, most manufacturing operations can be considered something like “controlled chaos.” Rush orders come in. People get sick. Raw materials shipments are delayed. Scheduling to known constraints is a piece of cake compared to optimizing flow when the unexpected happens. Demand-driven manufacturing can take signals from the shop floor to automatically synchronize production based on what is actually happening in your operations.

Related resource: Set the Right Pace for Production

Just as you wouldn’t buy a piece of equipment without knowing what it’s for, you shouldn’t launch a Big Data initiative without knowing what you want to accomplish. Beginning with a clear idea of what you want to accomplish can help keep enthusiasm high and ensure you see a return on your investment and efforts.

October 16, 2017

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