Supply Chain Lessons: Having Our Cake and Eating it, Too

Black_Forest_gateau 400x300Truth to be told, I think the biggest lesson learned from my experience in supply chain management is that managing trade-offs is a sure fire way to limit the potential of the supply chain as a driver of business performance.

Yes, I said it. The most depended-upon framework for managing supply chains for decades: choosing between cost or quality, efficiency or flexibility and innovation or production at scale may have produced the lowest cost supply chain or the most efficient supply chain. What it hasn’t done is enable rapid, sure-fire innovation, a demand-driven supply chain or sustained competitive advantage.

We didn’t get here through stupidity or because we intentionally wanted to limit our potential. We got to this point because those priorities were what we believed were important. As Peter Drucker said decades ago, “what get’s measured, gets done,”

Now, having learned the lesson, it’s time to change the way we manage the supply chain. We couldn’t ask for a better time to embrace the power of “and” – pursuing cost and quality, efficiency and innovation. The timing is perfect because today’s technology innovations are able to support the transformation. The advances we’re seeing break down the focus on limitations and allow us to do more, do it better and push the boundaries of excellence.

Like what, you ask? 3-D printing is one example. It used to be just for prototyping. But now the technology is available for some volume production. The fidget-spinner is a perfect example of how 3-D printing enabled the movement from idea to product to the hottest gadget in just a few weeks. Capturing the demand – and the sales – once would have taken months or even a year. Now, it’s weeks and sometimes even days.

Some might say that the fidget spinner example isn’t one of real, industrial manufacturing. Regardless, we can’t ignore the fact is that the cost curves for 3D parts are continuing to come down, making more and more traditional manufacturing fabrications technologies candidates for 3D alternatives. Entirely new business opportunities are being created as a result of low cost and rapid, iterative design.

Collaborative robots represent another innovation that will transform supply chains. Once a tool solely for productivity and efficiency in production, robots now are able to do more tasks, provide insight into ways to improve the performance of those tasks and free people up to do more critical thinking. They will ultimately tighten the links in the supply chain between demand and delivery, allowing manufacturers to improve agility and capture greater results in shortened market cycles.

Nascent, but something I think with real potential for improving supply chain performance is blockchain technology. The applications for facilitating peer-to-peer collaboration offer real promise in bringing all stakeholders in the supply chain together in a trusted, credential-enabled way. Better, faster collaboration with key partners and lower risk. Efficiency and agility and innovation.

It’s an exciting idea, isn’t it? After all, who doesn’t want to have cake and eat it, too? Now, we can get closer to that. I’d welcome your thoughts on the trade-off you most want to see knocked down. How do you think innovation will make that possible? Reach me here @jim_lawton.

Originally published on Beet Fusion.

Robots Know Things: Put Them to Work for You

EngineerI recently presented at an event where leaders of several of the world’s largest manufacturers gathered. Everyone agreed that manufacturing is undergoing transformational change. No one agreed though how, when and where to get started and what it will take to achieve the promise of Industry 4.0 – where machines are connected and smart, efficiency and productivity are optimized, and manufacturing sets the new standard for best practices in harnessing innovation.

As leaders develop their strategic roadmaps and dig into pilot projects, robots are playing a key role in bringing together man and machine. Today’s smart, collaborative robots are so much more than machines for increasing the productivity of repetitive tasks and doing jobs too dangerous for people. These robots are engines for process innovation, quality improvement and the agility needed to accelerate the journey to successful implementation of the Industry 4.0 vision.

When Robots Think More Like Humans, Everything Changes

I’ve written about the ways in which robots are able to sense and respond like we do and how robots are moving more toward dealing with variability like we do. Where robots are heading now is toward the ability to engage with their environments, tasks, and people in the same ways the people do.

Several innovations are shaping up to move robots from simply working for humans to actually working with them. It’s an important distinction. Think about what a person needs to be able to do in order to perform their job in a manufacturing operation. Broadly speaking it comes down to having the answers to four questions:

  • What do you want me to do?
  • How am I doing?
  • How can I do better?
  • How can I help improve how we perform the task?

Advances in software enable robots to act on the answers to these questions – just as a human would – constantly working to figure out what is going on, what is wanted, and make smart recommendations seamlessly to modify what they are doing so they can do it better.

Industry 4.0: Robots that Know Things

Robots know things today. Tomorrow they will know more.

Today, smart collaborative robots are able to tackle different tasks with ease when a person accesses the stored parameters for the work in order for the robot to move on to the next task. Soon, with advanced vision systems, robot-generated insight shared through cloud robotics, object and application recognition, robots will be able to enter a workspace and know – based on the equipment present – what needs to be done. Using its own experience and calling on the experiences of robot “colleagues”, these robots will begin the task without human intervention. Just as a person who has been trained would do.

One way to think about this robot knowledge is as the common understanding that humans bring to their world every day. Just as a human recognizes a screwdriver and knows how to use it based on that recognition, so too will robots “know” what a tool is and how to use it. A robot “watching” a human pack a box, will recognize the task. Tapping into its own experiences with the task or perhaps the shared experience of others, the robot will know how to perform the task. Ultimately, the robot will be able to make recommendations based on that ‘common’ sense of how to improve the performance of the task.

For their manufacturing employers, these robots will provide metrics for world-class manufacturing operations such as efficiency and productivity of a work cell, error reporting, quality reporting and basic analysis. They will make it possible for manufacturers to be more adaptive to changing market conditions and improve performance in the work cell and at the facility level. Ultimately, robots will improve global operations with the ability to leverage robot-generated insight at scale.

When we talk with manufacturers about Industry 4.0, they are excited by the vision – automation that can move operations toward more agility and responsiveness. It’s time to capture that energy and act as the pace of innovation picks up. Manufacturers who don’t move quickly to put that asset to work will be left behind.

What is your business doing to move your operation toward the model? Tweet me @jim_lawton.

Originally published on Forbes.


Smart Machines: Closing the Supply Chain Gap Between Demand and Delivery

Robotic arm playing chess, artwork

I recently spoke at a conference in Chicago for MIT’s Leaders for Global Operations program. Gathered there to learn about the latest innovations in advanced manufacturing were executives from some of the world’s largest manufacturers. Artificial intelligence, 3-D printing, the Industrial Internet of Things and robotics were among the topics and it was clear that everyone there is aware that manufacturing is at an inflection point and big changes are needed to make the pivot. How, when, what and why were the biggest questions.

I can’t remember the first time I heard or read Lora’s description of the “demand-driven supply chain”, but while at the conference it struck a chord in my mind. The concept is a heady one – especially when we think about manufacturing and the ease of comparing driving change in the field to turning a battleship. That is to say slow and methodical. The idea that supply chains can be designed, built and managed to meet demand where it falls – up, down, in new markets around the corner or around the globe – is exciting and initially, daunting. Now, though I see technological breakthroughs that will, in fact, bring us closer to the vision, maybe sooner than we think.

The ability of the supply chain to “sense and respond” to fluctuations in demand is at the heart of the demand-driven supply chain and I’d say that manufacturers are doing much more to find ways to get closer to the customer. The next hurdle is to find ways to tighten the window between product design and delivery so that the “respond” side of the equation can be executed flawlessly.

The radical transformation of automation will speed this along. Advances in hardware and software are moving machines into a role where they can make meaningful and measurable contributions to manufacturers’ ability to adapt the supply chain as demand and market conditions fluctuate. This smarter automation includes

  • Sensors that collect data in ways similar to humans – seeing, touching, engaging
  • Behavior-based artificial intelligence – innovation in intelligence is making it possible for robots to integrate and interpret the information gathered by the sensors and then formulate and direct the appropriate action, overcoming the limitations set by “programmed-only” responses.
  • Actuators that can execute the required action – advances in the hardware take shape as robot hands and arms that work much more like human appendages – more flexible, dexterous and sensitive to the environment and the situation

With machines that can do more than perform a single task over and over and over, manufacturers and supply chains will become nimble. The responsiveness articulated by the concept of a demand-driven supply chain will move from a vision to a real-world model and become the standard by which world-class performance is measured.

Originally published on Beet Fusion.

Losing Sleep over Your Digital Manufacturing Strategy? You’re Not the First

Business technology conceptRobots, digitization, manufacturing.

The digitization of manufacturing is a pretty big topic these days. The vision for an information-driven model that touches nearly every aspect of the product transformation process is pretty exciting. It can also be – for those in the midst of it – a pretty heavy mix of anticipation, excitement, skepticism and trepidation. Finding little examples of how things in our lives have changed for the better with digitization can provide some comfort: how we pay for things from our phones, how recommendations for our next great read appear magically when we visit Amazon or how navigating an unfamiliar city is a snap. But what about wholesale transformation? Is there an industry that has some lessons for manufacturers? I don’t think you have to look too much further than marketing.

That’s right. I think there are lessons that can be learned from the experience that marketing has undergone since the first clickable banner ad appeared in 1993. Yes, manufacturing is very, very different from marketing (capital intensity and scale come to mind in a big way), but there are a few parallels that can be drawn.

Data Becomes Knowledge, and Knowledge is Power

It once was that marketers broadcast messages widely, expecting that in a sea of ears and eyes, they’d find the one pair that might be looking for what they were selling. Access to information changed all that. Age, race, gender, sex, geographic location and more was just the beginning. More information filled in the lines: where we shop, what we buy, whom we associate with and how we wish to be perceived. All this information increases the level of precision and focus of marketing messages, without a significant increase in cost or resources. In fact, costs can come down. More importantly though, it produces better results.

Now, manufacturers are ready to embrace data-driven models. Recently, manufacturers shared that they plan to use the data captured by sensors to improve performance in several ways

  • 81% will use the data to drive product innovation
  • 64% will use the data to improve the customer experience
  • 47% plan to use the data to sell add-on solutions

The Market Speaks, You Listen

Manufacturers need to look no further than the evolutionary path that marketing has taken to see what is coming in terms of consumer expectations about products, services and engagement.

  • Dawn of marketing to 1950: marketers pushed messages to the market and consumers
  • 1950-2010: marketers pushed messages to customers and to markets at large
  • 2010-present: marketers collaborate with customers and partners to create and sustain value

For manufacturers, this last period, the one we are in now that has the biggest impact on their thinking and what’s driving the move toward digitization. The move has been emerging for decades actually and primarily taken hold in the electronics sector, where consumers quickly bought into a model where they could configure the latest gadget – computer, cell phone or today, cars – to their specifications. The result is factories that no longer produce in volume but continuously narrow lot sizes, cognizant of the fickle nature of consumers. One-to-one manufacturing may not be realistic, but every step that brings manufacturers and customers closer is one in the right direction.

Shifting Skill Sets

Early on marketing was the domain where creative thinkers thrived. Artists, writers, designers were the drivers behind the effort. As digitization took hold, creative minds were still important to the process, but so too became analytical skills. Fifteen years ago, who’d ever heard of a social media manager? Now, who’s heard of a company that doesn’t have or partner to get one?

The reverse seems to be true in manufacturing. As process-intensive as manufacturing is, with the need for exactitude, analytical minds have filled the ranks. Now, again, technology is driving a change. The combination of interconnected machines and artificial intelligence will mean that people will do less of the heavy lifting. To work in the factory of the future, creative people will become a critical asset for problem-solving, innovation and yes, customer engagement.

I’m not simplifying the learning curve that manufacturers have to overcome. I do think that in many ways the transformation will be easier, simply because manufacturers have always been good at measurement and they are pragmatic when it comes to sweeping changes.

Are there other digital transformation stories that can shed some light on what manufacturers need to do? What changes in manufacturing you think will be made be possible by digital technology? Tweet me @jim_lawton.

Originally published on Forbes.

Democratizing Manufacturing: Smart, Collaborative Robots Bring Automation Benefits to All

Acorn1Every morning, I read yet another article or blog or tweet about the resurgence – or not – of US manufacturing and the potential – or not – for good jobs to be won by the same. It’s ok, because as I’ve said before, I love manufacturing. And I’ll say it again, I love manufacturing.

As I travel around the country visiting our customers, more and more, I realize that I really love manufacturers who are considered small- to mid-sized businesses by the measure of number of employees. That’s likely to be because, in the U.S., more than 250,000 manufacturers have fewer than 500 employees. A big reason for my sentiment is because in spite of all the challenges these companies face – from labor shortages to lack of access to capital to help them scale, acquire new technology or even just repair worn-out equipment, they keep at it. Call it grit, call it optimism, call it good old American stick-to-it-iveness, they’ve got it and they keep going.

For too long, robots and the benefits they bring to manufacturing have been out of the reach of these manufacturers. Price was one barrier. Complexity – and the need for highly specialized expertise, another. With those obstacles out of the way, manufacturing has been democratized. Now, manufacturers of all shapes and sizes can put robots to work in their operations. They are, for many different reasons, and to do many different kinds of tasks.

With equal access to smart, collaborative robots companies like Standby Screw and Vanguard Plastics gain a fast path to exploiting automation to improve productivity and lower cost. They are tackling repetitive tasks, lowering error rates and reducing the likelihood of an injury to a person. For many customers, these robots allow them to “staff” positions that have been left unfilled for weeks or months with stability. They are also working alongside people, giving them opportunities to do more strategic work.

Perhaps, though, what I like best about working with these companies is the curiosity and optimism they bring to engaging with a robot. There’s a focus on the possibility that all too often seems limited at large manufacturers who are stuck in the old way of thinking about robots and automation. They are fearless when it comes to trying new applications and undaunted by trial-and-error. And our team learns a lot from them.

When you consider that studies show that smaller manufacturers produce more innovation per employee than large manufacturers, the potential for the next great thing to come from one of these is that much higher, as employees won’t be stuck doing work best suited for robots. So, no matter what tomorrow’s headlines say, I believe that “small” is where it’s when we look for big changes in manufacturing. What kinds of things do you think robots can do for “small” manufacturing? Tweet me @jim_lawton.

Originally published in Forbes.

Stories from the Trenches

One thing I came away with from last fall’s Summit was clear agreement that the race to digital manufacturing is on. The second takeaway was that there are a lot of questions about how and where to get started.

Industry 4.0 promises to bring about a revolution, built on information-driven operations that optimize efficiency, capacity, and innovation. The waves of innovation are coming faster and faster so it’s no wonder that for many of our customers, the excitement is tempered by pragmatism.

It’s only been a few years since the arrival of smart, collaborative robots that are able to bring automation to the 90 percent of tasks that were out of reach to traditional robots. Now, these robots are well-positioned to play a big role in accelerating the journey to the digital factory for manufacturers large and small.

In just the past few months, two companies that could not be any more different in size and scope of work have built models for testing and demonstrating scalable approaches to using robots in a factory of the future.

The first, Fla.-based Tuthill Plastics Group, never thought robots would be a viable solution for their needs. The work it does is highly customized, intensely repetitive, has a very low tolerance for variance and is often quick-turn. The company was not in a position to reconfigure lines, bring in integration experts and experiment with automation solutions that might or might not work. Now, with software-driven robots that are up and running in less than a week, Tuthill has deployed a solution that communicates with the equipment it is operating and provides feedback on performance. By starting on a single task, in a single cell, Tuthill is able to test, measure and refine its approach. The company will build its digital factory with success built one work cell at a time.

The second company, MS Schramberg, based in Germany, is no stranger to large-scale traditional automation. In it highly automated operation, the magnet manufacturer now uses three pairs of robots working as pairs in three work cells on complex logic tasks. In these cells, one robot selecting parts from an array of grid patterns and loading the part into the machine, while a second robot removes the part from the machine and loads the part into a tray.

Both scenarios illustrate the way that robots will contribute to the digital pivot – one task and one work cell at a time. For companies ready to dig in, this approach offers a digestible path to success that won’t leave them choking on the promise.

Originally published on Beet Fusion.

Artificial Intelligence-Driven Robots: More Brains than Brawn

Geek and body builder playing chess

Automation and robots for manufacturing have come a long way since Unimate was introduced in the 1960’s. The machines that manufacturers are using today are smaller, safer and able to perform more than a single task without expensive programming. While these innovations have significantly increased the value that automation brings to manufacturing, what’s coming online now will transform the industry in ways that we’ve not seen since the first industrial revolution.

The 4th industrial revolution or Industry 4.0 will be built on robots that are more brains than brawn. These robots integrate physical and cognitive ability to do more than heavy, highly repetitive tasks. In the sophisticated, highly automated environments where manufacturing takes place, these behavior-based robots – fueled by new innovations in artificial intelligence (AI) – are changing the way factories are organized, operate and perform.

Building the Industrial Internet of Things from the Bottom Up

Advances in technology have always been the catalyst for transformation in manufacturing, but this time the technology is less about mechanization and physical automation and more about cognition. The Industrial Internet of Things makes it possible for manufacturers to orchestrate the production process in completely new ways. It also will automate – on a large scale – the analysis of mission-critical information in a continuous flow to enable informed, real-time decision making. It’s an exciting time, but it’s also daunting, and manufacturers are not simply going to go whole hog on rolling out an information-driven operation. They are skeptics, remember? The vision of Industry 4.0 will be achieved – in large part – by software-driven robots with innate cognitive abilities.

With AI, robots can work semi-autonomously on a much wider range of tasks. Beginning in the work cell, robots with “smarts” built-in draw from a cloud-based database of “lessons” and information to:

  • Recognize equipment and parts in a work cell and perform applicable behaviors and make “auto-complete” suggestions, e.g. recognize a tool or piece of equipment and be able to use it correctly
  • Use pattern matching to suggest error handling best practices
  • Apply a database of corrective suggestions to help task designers (that would be the robot’s human colleague) find ways to modify a task or work cell in response to a fault
  • Analyze motion profile and behavior against a global fault database to identify opportunities to optimize a task

Just as smartphones and other internet-of-things-enabled devices receive software updates that add new features and functionalities, so too will robots expand their abilities. Optimizing production at the work cell level is only the beginning. Robots will eventually share information and insight that improves performance factory-wide and ultimately, across global operations, with the ability to:

  • Learn from self and others
  • Correct self and others
  • Collect, analyze and share insights from data collected on the factory floor and from robots in other locations

Innovation: Only As Good as the Value it Provides

We’ve all seen the crazy stories about artificial intelligence and its potential to destroy life as we know it. The reality is that there is a significant value that AI-driven robots deliver to manufacturers now, and even more so in the future, such as

  • Drive continuous process improvement and improve quality
  • Reduce costs and improve margins
  • Accelerate the NPI process
  • Build factories that can produce highly customized products at mass market prices

We’re seeing customers rolling out the work cell-based model in their factories with robots at the core. How do you think next-generation AI-driven robots will change manufacturing? What opportunities and challenges do you see? Tweet me @jim_lawton.

Originally published on Forbes.


2016: A Year of Advances and a Few Reality Checks

Reflection in rear view mirror of businesswoman driving car

Before 2016 disappears from view, it’s worth pausing to sum up where all that happened in our fields of interest got us. Sure, there were a lot of stories about robots (killing us, replacing us, filling all kinds of unmet needs for us…) in the past 12 months.

Beyond the hype though, there are some clear takeaways to keep in mind as 2017 kicks into gear.

#1: Robots are forcing us to think about the definition of work. From white collar jobs to farming and customer service we saw robots move into a broader range of categories. Gaining skills, dexterity and the human abilities in touch and sense make it more and more possible for robots to work directly with humans.

Still, the robot workforce is more a novelty than a reality. People are still doing jobs they should not be doing. And while the concept of “guaranteed income” (since we won’t have to work one day) might appeal to some, most of us realize that to be human is to have purpose and for more than not, purpose means work. Navigating the “new” model for work needs to be as much a part of the discussion and investment as is the technological innovation that is forcing us to re-examine who does what.

#2: Artificial intelligence (AI) has been around for decades, but the non-rules-based form of AI is still a very nascent field…at least as far it goes in replacing the human brain with a machine. If you believed the coverage of AI in 2016, you might expect that machines are advanced enough to try legal cases, teach graduate level physics and run the world. More realistically, machines today can be “trained”, for example, to recognize a cat after being shown an image of cat thousands of times – but unlike humans, machines can’t extend that “knowledge” to differentiate between a cat and a penguin until you show it another thousand images of penguins. That means that when presented with an “unknown” scenario – something the machine hasn’t seen before – it can’t determine what action is necessary – which is a very human trait.

So while Google’s AlphaGame won at Go in 2016, when it comes to navigating real-world situations, robots aren’t replacing human cognition yet.

#3 Manufacturing is the new black. Well before the election and its focus on bringing manufacturing jobs to the US as the silver bullet for fixing the economy, expectations were high around the digital transformation of manufacturing. More and more, there’s honest talk about the 300,000+ jobs that are currently unfulfilled and the need for a new model for cultivating the skills needed to work in smart factories. The spotlight on manufacturing isn’t likely to fade, creating a real window of opportunity for the sector’s revitalization.

While robots and advances in cognitive automation got a fair share of attention in 2016, we’ve got work to do to make the most of the innovation that will continue to evolve. As we roll up our sleeves to work with companies around the world on transforming their operations with smart, collaborative robots in the coming year, we’re looking for ways to make all the promise real. If you’ve got an experience to share about this journey, tweet me @jim_lawton.

Originally published on Forbes.

Making the Digital Pivot: Physical & Cognitive Automation Make it Easier

Rethink-TagTeam-9If last month’s report from Boston Consulting Group about the slow implementation among US manufacturers of the means to achieve the possibilities articulated in the vision of Industry 4.0 hasn’t reached your desk yet, let me summarize the findings. While 90 percent of US manufacturers confirm that their organizations see value in terms of productivity and efficiency in the digitization of their operations, only one in four is looking beyond the incremental improvements to greater opportunities in generating new revenue streams. This short-sightedness limits the scope of transformative strategy and reinforces the industry’s profile of slow to move, rigid and no longer the engine of economic good we all want and need it to be. That’s got to change.

If we agree that the digital pivot is indeed an innovation that manufacturing needs to make, how then, to shift the mindset? Manufacturers tend to be skeptics – the work required to transform raw materials into finished goods isn’t easy – and many have been around implementations that were big on promise and not much more. I’m not saying it’ll be easy to change minds, but it can be done.

I believe that the expansion of automation will be the accelerator of the changes necessary to making the digital pivot. What manufacturers need is a way to test, prove and repeat the innovations. That’s where the smart application of software-driven robots comes into play, offering a way to build the factories of the future from the work cell up and out. The robots will use computer brains to learn new tasks, how to use new tools and be able to share with human colleagues insight into processes that can improve both productivity and quality. As new software is developed, the robots will gain new skills and ultimately shared with robots initially in the same place, and eventually across the entire organization. Ultimately, information from product design and development, marketing and sales will seamlessly be streamed to the robots which will be able to modify production strategies based on the information.

When information and insight flow back and forth between the “front office” and the production floor and can be acted upon in real-time, supply chains are more fluid and adaptive to shifts in conditions. Robots that bridge the physical and cognitive aspects of automation accelerate that flow and make the possibilities of the digital pivot that much easier to attain and valuable.

Originally published on Beet Fusion.

Sense + Think + Act = The Digital Supply Chain

Picture2I think about it like this. The digital supply chain will be a supply chain that adapts. One that’s more agile and less brittle. One that’s self‐configuring and self‐optimizing. And one that’s adaptive and fault tolerant.

How will this finally come about? The technology we’re rolling out today will transform manufacturing and the supply chain with the ability to sense, think and act on real-time information about everything from production and equipment data, market variability, and demand. The Industrial Internet of Things, “Big Data”, the automation of processes with robots, 3D printing, cloud-based sharing and artificial intelligence will combine to break manufacturers free from the constraints of the “planned supply chain.”

It will happen thanks to the advancement of automation of both physical and cognitive tasks – manifested in collaborative robots. Until now the supply chain relied heavily on planning, planning, and more planning. The input into those planning models was always behind and as a result, the supply chain was constantly reacting to variability. Which as we all know is the reality in which we live. It’s like trying to tell someone how to get from Penn Station in Manhattan to the Empire State Building. Sure, you can tell them how many blocks and when to turn right or left and what landmarks they might look for. But your instructions aren’t likely to include the detour required thanks to a water main break or the taxi that’s going to choose to run the red light at 33rd and 6th. In other words, you can tell them how to plan to get there, but they will have to navigate the route based on what’s happening that day, that minute.

Robots will automate more of the factory using rules for known procedures and cognitive computing to adapt to physical changes in the environment. They will use computation at vast scales, deep learning and other forms of AI, and the cloud to process additional data and to share learning with robots in other operations. Ultimately, the information they glean will be used to configure – and re-configure – the supply chain in real-time and build supply chains that are able to respond accordingly.

The vision of the digital supply chain is exciting, no doubt. What’s more exciting to me, though, is the outcome and results of that vision and what the technology and innovation that underlie the digital supply chain will do for manufacturers.

Originally published on Beet Fusion.