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  • Writer's pictureBrad Zorn

5 Best Practices to Start Your Agile Factory Initiative: Start Small, Think Big, Go Fast

It’s not hard for manufacturers to think big.

They’re the vanguards of industry, leading the creation of products and services that change the world and lives of their customers. Over my career in manufacturing, I remember a few distinct roles that changed the way I perceived the world. One shop I worked in gave me the ability to see products hard at work in the field and see that same line of products on the assembly line. In another organization, I learned how many products it takes just to make a consumer product, and how the B2B supply chain shaped a huge number of things I saw in the world around me. In another experience, I gained a wealth of understanding on how the energy in products powers all the gadgets I use every day. World-class manufacturing organizations are incredibly astute (and rightfully proud!) of the difference they make in the world.

When it comes to Agile Factory initiatives, it’s also easy to get ahead of yourself with big plans and bigger goals. But the best way to begin is in small, attainable steps that set you on a path to those bigger dreams.

I’m a big fan of the mantra to Start Small, Think Big, and Go Fast. To me, that means creating an effective proof of concept aimed at validating potential real-world production applications. The overall objective of a proof of concept is to validate potential solutions to technical problems, such as how systems can be integrated or how results can be achieved through a specific configuration. Assume some technical debt using low code environments, iterate fast, and most of all, learn and apply that knowledge to the next project.

Agile Factory projects are the perfect space to apply this approach, which I breakdown like this:

  • Think Big. This is the space to tackle those big, high-priority challenges. The long-term focus should be maximizing business value, allowing you in the long run to build a system that can and enable multiple use cases. The important part about this step is providing perspective, focus, and making sure that your investment is something that could scale if successful, not necessarily trying to solve all of that before getting started; have a general plan for what to do when you are successful!

  • Start Small. Tackle those big challenges by starting with a proof of concept that is a manageable size, setting up your team to get immediate traction and results. The most important part about this step is to provide laser-guided focus on exactly what you’re setting out to accomplish. This could even be breaking a project down into smaller steps and tackling what you can.

  • Move Fast. Don't take a couple of years to come up with that perfect strategy before you test something out. Start now with smaller, achievable goals. A big part of moving fast is innovating in a hypothesis/test fashion, without considering disproval of a hypothesis a “failure.” We usually hear “fail fast” as part of this mantra as well, but I often avoid the “failure” term because we should never actually fail or look at it as a failure, it’s a feedback loop to revise your hypothesis and keep going!

So let’s take a look at several best practices and methods to apply this theory to proofs of concept to get you started on creating Agile Factories.

Define the Vision

It’s very easy to get enamored with all the latest shiny new technology. As a society we’re used to getting the latest smartphones, and when they come out, people want to migrate to the tech right away. In manufacturing, we often see software and functionality dangled in front of us and get excited, but we need to remain disciplined in the business goals and objectives first - let that define process and requirements, and then look at technology.

Don’t overlook or underestimate the work and effort upfront to define the vision, realizing there’s a heavy focus on objectives, process, and change management. What is it you're trying to accomplish?

One of the things my teams in industry always did was put a heavy focus up front on LEAN or operational excellence, standard processes, and employee engagement. There’s something uniquely defeating about spending time on digital transformation that simply enables or automates a bad process or creates something that employees and leadership cannot or will not use.

At the end of the day, the project comes down to process, technology, and people; but organizations can’t afford to skip aligning the project vision to the company vision. I often shoot for aligning a project vision to a CxO strategy – e.g. if the CEO of a company is focused on releasing new products quickly, then how does this shop floor project align with rapid development to market?

Cultural Buy-In & Training

Speaking of people, there is a level of intimidation when it comes to implementing modern platforms, new technology, or process changes. Every single person’s performance is suddenly very transparent, and people can feel exposed. Or perhaps it’s a shift in the way they do their jobs. I remember assessing a manufacturing cell for digitization, and the operator telling me how intimidating the new equipment was. This person was an incredible machine operator and knew both the product and the process inside and out, but they didn’t have much experience with technology, computers, or touch screens. Manufactures have to ensure people know the company will invest in them, that the company appreciates their skills and talents, and that the plan is to take great people on the journey together.

It’s important not to overlook the fact that there is a skill set requirement with Agile Factory projects. There are folks that have worked in the factory floor for many years, in the factory office or at corporate office and they're used to functioning a certain way. As you start to introduce new technologies and process changes, there are some skill sets that must be addressed and help people make the journey.

Be as transparent as possible when making changes and keep a focus on the ways these new technologies will improve their performance, streamline operations, bolster bottom lines, and improve customer service.

Model Line Approach

My first point was on foundational work, which is very important. But don't let it slow you down.

In my previous years in industry, one tactic used was the model line approach. The model line approach takes a single value stream or element within an enterprise and develops a full operating system or proof of concept around it. Resources are put in place to ensure the goals of the project are met. By doing this, manufacturers are attentive to the needs and challenges that could arise and ensure the project is given its best chance to succeed and prove its value.

In one instance, we started with a cell of machines with a focus on the foundational needs that were there. We had a modern set of operating equipment coming in to replace aging assets. But after a few weeks into the production runs, the pace wasn’t there – the aging assets were outpacing the automated, modern equipment! We had a specific problem to solve and had a hunch that in the machine data somewhere there was a clue. Sure enough, we were able to connect and start historizing the performance and availability data from that equipment, and quickly realized that a key part of the automation was our prime suspect – the automation had to change arm tooling to do one specific task, and it was doing that task far too often. Within weeks, we had demonstrated the value of collecting and using shop floor data to help the operation, and we were on to our next project.

Finding the Right Place to Start

Don't be intimidated by this step. You really can't pick a “wrong” line or place to start, you just want to make sure you’re going to add value.

Leveraging a partner to help you figure out where the right place to start can also play a role in finding the best area to make improvements within your factory. If you have staff with operational experience, and they’re aligned to a project goal, they can also help find your areas of opportunity. In many cases I was from central corporate, and a reoccurring joke was, “Oh good, corporate is here to help.” That said, being from “outside” became a niche role because it became somewhat easy to find options to provide plant leadership on where to start. Talk to the operations team on where WIP builds up verse where it was designed to, talk to the planning team on where they get the most surprise reschedules, talk to the finance team about where they would like to remove cost, talk to the engineers, talk to the line leads and operators. Sometimes, just learning about the operation from the team on site is enough to consolidate a list of options, do some assessments on which can provide the best effort/benefit ratio, and get started.

Obvious pain points are usually the best place to start.

Image Courtesy of Microsoft.

It Doesn’t Take Large Capital Investment

You shouldn't have to spend a ton of capital to get started. You don't need huge solutions, but you should also never cut corners on foundational elements, like security. I remember one situation where IT was unhappy to find a black box attached to a piece of equipment with a process engineer’s credentials saved as the Guest Wi-Fi connection; needless to say, that generates some churn and slows things down when that kind of thing is surfaced. So, partner with IT to get it compliant from the start!

While many of the technology tools for this offer free product downloads and trials to allow you to start experimenting quickly, don’t be hesitant to stash some seed money into the first project as innovation or business transformation funds that will help the project team be flexible without a lot of corporate overhead.

You're not going to go from a complete paper process to something out of Star Trek in one project. I love the maturity curve image above because once you get through the foundation elements and ending with visualization to conclude phase one, you can do a lot of really great things within the factory just from being able to see that data and be able to expose it more often.

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