Skepticism Stifles More Progress Than Failure Ever Does!

Much of what I have written about lately deal directly or indirectly with the general confusion around the topics of digital transformation in the manufacturing industry. I try to bring clarity to many topics such as Industry 4.0, digital transformation, IIoT, etc. and I am seeing a significant change in the industry especially in the last 6 months. Yet, skepticism about the ongoing paradigm change driven by digital technology is still rampant. 

Digital transformation is the engine that propels businesses forward in today's dynamic world.  Companies that leverage new technologies to automate operational activities, improve operator productivity, improve efficiencies, and manage quality are poised to outpace their competitors.  However, lurking in the shadows of this exciting shift is a potential innovation killer - skepticism.  Unfounded negativity towards digital initiatives can create a culture of resistance, stifle groundbreaking ideas, and ultimately hinder progress. Its understandable that new technologies need to be evaluated, and that without proper change management digital transformation can fail. However by being a skeptic you are robbing your organization of potential productivity gains. 

Writing off emerging technologies too soon is a centuries-old practice. New technologies often seem to inspire equal - and often counteracting - surges of enthusiasm and skepticism. 

Its still about people!

Is it technology or people that are driving digital transformation? Both I suppose, its people that can make this change and transformation, but they are also the ones blocking it sometimes. I was  reading the article "Why Most Digital Transformations Will Fail" and speculated why we may be surprised that the key to transformation is people. It is in nearly every single article about digital transformation and also a central component of Pharma 4.0.

The article states "...such digital transformations are far from trivial to undertake, in great part because it requires changing both infrastructure and culture within an organization". This is no revelation, its not the first or last transformation in history and this statement is universally applicable.  What is astounding is that, we see it as a challenge unique to the digital transformation. Let's not re-invent anything here and see how we have dealt with it in the past. There are so many examples and to sum them all up, if that is possible, I would say it takes leadership!

In order to drive transformation people need to believe the change is good, they need to understand that it will bring improvements and that they can have a hand in making the change. Therefore the first question to ask is why is it so important to digitally transform? Is it because we need to keep with the times - no its the promise of increased productivity, the promise of being able to do more with less, to do it smarter. I have for many years pondered this topic - hence the name of my blog "Intelligence in Manufacturing". When I was doing research the theme was Intelligent Manufacturing and we would joke that what we did until then was unintelligent manufacturing. Are we becoming more intelligent? Well I hope so in general and we are in fact continuously learning and with that improving. This time around we are doing it smarter, hence Smart Manufacturing.

Back to the topic of people, it obvious that without us non of this would work and yes it is us driving the change, us the people. The article I mentioned goes in length to describe the hesitation that people have to change. It is the same problem that we face any is a revolution (or change, or big change...) like the manufacturing digital transformation aka Industry 4.0. Hesitancy and resistance to change is always there, in every corner of an organization. Every time I present a new technology to manufacturing organizations, it rears its ugly head, Oh no its new technology hide! However I believe that this transformation introduces technologies that are focused on us the people, not automating processes but helping, augmenting, supporting us in how we work. Instead of year long implementations with weeks of training and months of ramp up it will be as simple as using an app - you know like the ones on your mobile phone. That is why its revolutionary.

The change monster :-)

The 5 Pillars of Composability

I am seeing the industry converge on the term Composability to identify and explain the application of digital technologies that can effectively foster digital transformation. For digital transformation to happen, agility, flexibility, and human-centricity are a vital component that increase productivity in operations - the expected outcome. This is where the concept of composability emerges as the collective transformative paradigm. Let's also make it clear that the opposite of composable is monolithic and contrary to monolithic systems, Composable solutions empower manufacturers to adapt quickly, focus on the needs of their operators, and drive continuous improvement. 

Composable solutions are a critical ingredient in digital transformation because they empower manufacturers to enhance productivity by embracing flexibility, agility, and human-centric design. By focusing on the needs of operators and utilizing real-time data, digital tools enable rapid adaptation to changing conditions, boosting efficiency. This approach accelerates time-to-value, enhances collaboration, and supports sustained operational excellence, ultimately leading to higher productivity​.

The Composability Model for Digital Transformation

Let’s dive into the five key pillars that make composability such a powerful approach: Bottom-Up, Agility, Democratization, Human-Centric, and Compliance.

1. Bottom-Up: Building from the Ground Up

In contrast to the rigid, top-down structure of monolithic solutions, composable systems thrive on a bottom-up approach. This allows organizations to build solutions that are tailored to specific processes, activities, and operations. Composability starts at the operational level, focusing on solving problems at the frontline, rather than imposing broad, generic solutions from the top.

By empowering frontline operators and citizen developers to build apps that address their unique challenges, organizations can capture granular data about each activity. This leads to faster problem-solving, more efficient processes, and solutions that are adaptable to rapid changes​. The bottom-up approach is essential for increasing productivity and maintaining agility in a constantly evolving operational environment.

An interesting phenomena is that the bottom-up approach fosters an emergent design, where solutions are built iteratively, from the operational level up. This means frontline workers, who are closest to the challenges, contribute to the system’s development. By decentralizing control, emergent designs allows for rapid adjustments and iterations, ensuring that solutions evolve in real-time, in response to actual needs. This approach significantly reduces the time-to-value, as it enables immediate deployment and incremental improvements, accelerating innovation and aligning solutions with real-world demands​

2. Agility: Embracing Change through Lean and Continuous Improvement

Agility in composable solutions is crucial because it inherently supports Lean principles, which emphasize continuous improvement, waste reduction, and efficiency. Composability takes Lean further by bringing in adoption of digital technologies as a key enablers. Its the reunion of Lean and Agile, allowing for rapid cycles of innovation, quick iterations, and on-demand changes, which are essential for staying responsive in fast-paced environments.

In manufacturing, continuous improvement is key and agility is non-negotiable. Composable solutions, by design, are highly adaptable and enable organizations to iterate quickly. Unlike monolithic systems that lock you into predefined processes, composable systems allow for short test-fail-learn cycles that drive faster innovation. This agility extends to everything from software updates to operational adjustments, ensuring that you can stay ahead of challenges and capitalize on new opportunities. Agility also allows for faster implementation and a reduced time-to-value, meaning that benefits can be realized almost immediately after deployment​.

Augmented Lean represents this evolution of Lean, where digital tools and real-time data empower frontline workers to make immediate, informed decisions, maximizing efficiency and productivity in ways traditional Lean couldn’t achieve.

3. Democratization: Empowering Citizen Developers

The democratization of technology is another cornerstone of composability. This is where no-code and low-code platforms come in, they enable citizen developers - the people close to the operations, such as engineers, technicians, or operators - to create, modify, and maintain apps without needing deep IT or coding expertise.

This critically reduces dependency on a software skills, centralized IT and specialized OT departments - it speeds up the development of solutions that directly address operational challenges. As more people within the organization are empowered to contribute to solution development, it fosters a culture of innovation, encourages experimentation, and accelerates digital transformation​.

Democratization in composable solutions means empowering the people who know the process best, frontline workers and engineers, to create content. When those closest to the operations develop solutions, the results are more accurate, relevant, and effective. This drastically reduces development time because it eliminates communication gaps between IT and operations. With a no-code platform, these citizen developers can quickly build, test, and deploy apps that meet specific operational needs, accelerating time-to-value and promoting continuous innovation​

4. Human-Centric: Augmenting Human Capabilities

In a composable system, technology is designed to serve operators, rather than the other way around. In traditional monolithic systems, operators must conform to rigid workflows dictated by the system, limiting their ability to adapt and innovate. With composable solutions, however, operators are empowered by tools that assist them in performing tasks more efficiently, providing real-time insights, and reducing manual effort. This human-centric approach leverages the unique skills of workers, driving productivity increases by augmenting human decision-making and capabilities​

Therefore composability at its core is human-centric. It is built around augmenting human activity rather than replacing them, automating processes where it makes sense but still including them, ie "human in the loop". In a composable system, the technology is there to serve the operator, providing tools that digitize manual tasks, streamline workflows, and offer real-time data insights.

This focus on human-centric apps leads to more intuitive user experiences, reduced error rates, and improved operator efficiency. By connecting operators with their environment through digital tools, sensors, and IIoT devices, composable systems elevate the performance of the workforce, ensuring that technology acts as a productivity enabler.

5. Compliance: Built-In Validation

In the regulated industries, such as life sciences among others, compliance is a critical pillar and probably needs a deeper dive in a future blog post. Composable solutions, especially frontline operations platforms, must be designed with compliance in mind. They have to allow organizations to build and validate solutions iteratively while maintaining compliance. Digital data has to be captured and available to document all the required aspects such as: version control, audit trails, and automated validation processes.

With compliance built into the system from the ground up, organizations can ensure that their solutions are always aligned with regulatory requirements without stalling innovation. Continuous improvements and app iterations can be made seamlessly while keeping operations compliant​ with automatically captured digital data as evidence. 

Validation 4.0 is an essential component of composable solutions and is part of the Pharma 4.0 operational model. It applies a risk-based approach to testing, ensuring that apps are validated for their intended use without lengthy delays. This iterative process allows for continuous updates and improvements while maintaining compliance. Validation 4.0 integrates seamlessly into the digital transformation, supporting rapid deployment and constant change, enabling businesses to innovate faster without compromising regulatory standards. This agility is critical for modern operations to thrive in evolving environments​.

In Summary

Composable solutions represent a fundamental shift in how manufacturing operations are structured and executed. By embracing the principles of Bottom-Up, Agility, Democratization, Human-Centricity, and Compliance, organizations can achieve faster time-to-value, greater productivity, and enhanced operational flexibility. The future of manufacturing lies in building systems that are as dynamic and adaptable as the challenges they address.

Composability as defined here and if applied correctly can give your manufacturing operations a massive jump on your digital transformation. Interestingly it can also serve to sift through the hype and ambiguity in the different so called "digital" technologies. By simply asking the technology vendors how the implement and satisfy the 5 pillars you can effectively qualify any technology as being in or our of the new paradigm. Remember clear objectives and strategy are still the most crucial part of your digital strategy. These objectives have to clearly define how productivity is increased in your operation and clarity around the composability drivers is an excellent strategy.

Digital Maturity Embracing the Paradigm Shift with Composability

In my last post, The 5 Pillars of Composability, I broke down how composable systems have to be bottom-up, agile, democratized, human centric and compliant to enable a resilient digital  manufacturing environment. However, these pillars don't standalone and you may have noticed that the graphic drew the pillars within a structure, i.e. a house. Yeah a bit cliche but its a simple way to drive the point - the foundations is connectivity and data integrity while the roof is digital maturity. Without connectivity to reliable data and a high level of digital maturity, the benefits of composability can be diminished. 

• Data integrity ensures that the digital solutions operate on accurate, consistent, and trustworthy data, preventing breakdowns in decision-making or system performance. High-quality, accurate data is essential for making informed, evidence-based decisions
• Digital maturity enables organizations to effectively adopt composable architectures, ensuring they have the technical capabilities, culture, and processes in place to take full advantage of modular solutions. 

Together, data integrity and digital maturity complete the story of composability by ensuring that organizations can both build and sustain these flexible, adaptive systems in a reliable and future-proof manner. In this post I want to dive deeper into these concepts as they are foundational concept that propels us forward in the digital paradigm shift to reshape manufacturing operations.

Digital Maturity, Connectivity & Data Integrity complete the composability model

What is Digital Maturity?

Digital maturity represents an organization’s capacity to leverage digital tools and processes effectively based on their strategy with the objectives of significant increases in productivity. It's not a simple matter of capabilities related to adoption or implementation new technologies but rather about integrating them strategically to align with long-term goals. As companies mature digitally, they move beyond basic digital adoption to foster seamless connectivity across systems, data transparency, an empowered workforce and with that comes order of magnitude productivity improvements - the ultimate goal for transformation.

A digitally mature organization is one where digital tools support real-time decision-making, democratized technology access, and predictive insights - aligning perfectly with the benefits of composable principles. This is also what the Pharma 4.0 operational model prescribes, that manufacturers need to do more than automate - they need to integrate everything from operations to compliance in a way that’s seamless, agile, and deeply data-driven.

What is Connectivity & Data Integrity?

Its not news that data must be accurate, accessible, and trustworthy across all systems for true digital maturity. It must be connected, collected, contextualized and stored to ensure that data collected from production lines, suppliers, and product design all feed into a single, reliable source, creating actionable insights and reducing costly errors. Yet surprisingly it still is very much a challenge in many solutions that I encounter. Mostly in legacy situation, implementation of monolithic system, but also if not considered appropriately in newer digital technologies.

Connectivity in manufacturing is all about creating a seamless flow of data across systems, devices, and people. Imagine every machine, sensor, and workstation talking to each other and feeding data into a single network that anyone can access in real time. When systems are connected, it’s like moving from an isolated set of puzzle pieces to seeing the whole picture. Connectivity enables manufacturers to understand what’s happening on the production floor instantly, respond to issues faster, and improve coordination across departments. For example, in a highly connected factory, when a machine experiences a slowdown, that data can flow directly to maintenance teams and operators, letting them address the issue right away.

But connectivity is only as useful as the quality of data being shared, which brings us to data integrity. Data integrity is about making sure that information is accurate, reliable, and complete across its entire lifecycle. It’s not just about having data; it’s about having good data you can actually trust. In the Pharma 4.0 model, where data integrity is critical, maintaining high-quality data is a must, especially for meeting strict regulatory standards. This means putting practices in place to ensure that data isn’t duplicated, corrupted, or altered improperly, so everyone—from operators to auditors—can make decisions with confidence.

Together, connectivity and data integrity are the backbone of any digitally mature operation. They enable real-time visibility, reliable decision-making, and the flexibility to adapt to change. Without them, even the best technology can fall flat. So, as manufacturers embrace digital maturity and composability, focusing on solid connectivity and data integrity will be crucial for a smooth, resilient operation.

The journey from Technology Adoption to Strategic Transformation

Many manufacturers today are adopting digital tools, but there's a significant difference between early digitalization and achieving digital maturity. A mature digital approach emphasizes:

1. Strategic Data Utilization: Digital maturity involves a shift from collecting data in isolated pockets to having unified, actionable insights. For manufacturers, this means no longer relying on static, siloed data but leveraging real-time insights that span from the shop floor to the boardroom. Yes, this in a way nothing new and really dates to Industry 3.0 concepts - however with new digital tools this has become and achievable reality.

2. IIoT & Interoperability: Digitally mature systems don’t merely integrate; they interoperate, embodying the composable principle of Bottom Up where IIoT components are autonomous and collaborative. Composable architectures are inherently emergent in both design and control - the manufacturing solution is required to evolve with minimal friction.

3. Human-Centric Technology: In a departure from an automation focus, the current paradigm shift places people at the center of the digital equation. Technology becomes an enabler for employees, from line operators to managers, allowing them to respond dynamically to changes and resolve issues swiftly.

4. Resilient and Adaptive Workflows: A composable manufacturing ecosystem relies on digitally mature workflows that can adapt to disruptions, whether due to supply chain variances or unexpected equipment breakdowns. A digitally mature manufacturer leverages their digital capabilities to enable resilience, be predictive and adaptive.

The digital transformation journey towards order of magnitude productivity improvements

The path to digital maturity requires a tailored, strategic approach that elevates an organization from a technological upgrade to a business transformation—one that enables agility, resilience, and sustainable growth. The first step in this journey is to assess and align digital initiatives with overarching business goals. Defining what a mature digital state means for each organization—whether it's minimizing downtime, improving product traceability, or streamlining supply chain management—is critical. Aligning digital initiatives with operational excellence or lean initiatives by implementing data-driven approaches to cut down production waste and achieve near-real-time optimization are critical. Drive value by prioritizing areas where digital maturity will have the most impact on operational outcomes.

A characteristic of digitally maturity is how well your organization is equipped to handle the ever-evolving challenges and capitalize on new opportunities. Embracing composability allows your organization to not only keep pace with the current demands but to thrive in the future - thrive with the accelerated pace of digital innovation. Digital transformation should be more that mere adoption of new technology - it is embedding it deeply in your operational fabric, enabling sustainable growth and resilience in the face of change.

4 Questions As a Guide Towards True Digital Transformation

Most people that have heard me talk about digital transformation are probably sick of hearing me talk about the "order of magnitude" productivity gain that is promised by the ongoing digital industrial revolution. But here again it is a key principle that can be used to understand transformation and navigate through the existing maze of confusion of what is and is not digital technology. Simply put digital technology is a technology that can directly impact industrial or manufacturing operations to bring about an order of magnitude productivity increase. 

I have compiled 4 critical elements that can help you sort through the maze of different technologies that are touted as digital, Industry 4.0 or Smart Manufacturing technologies based on this principle. These 4 elements can be framed as question that guide evaluation and selection of technologies:

Is it adopted and implemented in a "Bottom Up" manner?

Adoption and implementation are performed in an agile method, starting small in an iterative manner and building on outcome of each iteration. Agile approaches are an inherent part of the digital transformation and advocate a way to learn faster by short and rapid test-fail-learn cycles. The overall manufacturing systems solution is built from the bottom up in an iterative manner. 

This is in stark contrast to the traditional system approaches, including MES, where top down hierarchical processes are used to provide a solution that fits within specific constraints that is hard to change. There should be no "gap assessments", the technology is adapted to the process in contrast to fitting the process to the solution. It also removes the difficulties associated with adhering to complicated standards and systems. It frees engineers to focus on building solutions rapidly that fit the process and increases the rate of implementation by an order of magnitude (here I go again...). There are some interesting implications to this approach one of which is that Industry 3.0 standards such as ISA-95 becomes less relevant in this context.

Does it inherently support and enable Continuous Improvement?

Lean principles are still the most effective way to achieve productivity increases in an industrial operation and therefore the technology should be a tool to implement these operational improvements. The adoption of the technology should be done in a methodical PDCA or DMAIC cycle with each improvement supporting the next. Changes and modifications to a solution are easy and support iterative and constant improvement. The technology solutions are targeted at improvement areas with clear and quantified goals.   

It should be no surprise that regardless of the paradigm shift that is going on Lean and the principles of TPS are still real and valid. There is a close connection between the continuous improvement process and agile (bottom up) development approach of using the technology/solution. Th technology should be a Lean tool that allows engineers to rapidly iterate thru solutions to problem building digital content to an effective solution. 

Does it offer a Democratized approach and how does it enable "Citizen Developers"?

Users and implementors of the technology do not need to have unique and specific skills that are common for software, IT or automation engineers. Engineers and SMEs can rapidly adopt the technology to develop solution for the operations. The technology is so easy to use and learn that it is effectively accessible to most people with a basic level of technical aptitude. This allows the people that are closest to the process to craft solutions that are focused on solving a problem or provide an improvement. The technology should be adopted by people from within the operation rather than implemented by external parties.

Democratization and the citizen developer is an important aspect of the digital transformation. With modern digital technology we all can become builders of digital content. We already do this when using office tools such as Word and Excel and now we can even easily program our IoT door to open automatically when we get within range so we don’t have to take our key out. This is a big change compared to the high level of skills and expertise needed to build even simple automation tasks in traditional systems. No-Code/Low-Code is a key enabler of Democratization, it allows people with no programming or IT skills to build content that automates manufacturing processes in a simple and intuitive way. 

I find that for bigger organizations citizen development may be alarming, i.e. they feel it is akin to "arming the rebels". However there is no way around it, the benefits far outweigh the risks in this case and democratization of technology is key element of the new digital age. At the same time most of the new platform technologies provide accessible and transparent control and management of content being created and consumed. 

Is the technology able to provide Human Centric solutions?

The use of the technology should result in solution that serve humans or specifically frontline operators. It has to be intuitive, simple, easy to understand and easy to use. It has to serve the frontline operator by making him more productive, the operator is the key to the productivity gains promised by digital technologies in I4.0  

Modern digital technologies and tools are built on the principle of supporting human activity, that is what makes them so effective and so widely adopted. People are the key to unlocking productivity gains from digital technologies, that therefore have to focus on supporting human activity. The premise is that in order to increase productivity technology needs to support the human operator. In the new digital age manufacturing needs to enable the connected worker whose tasks are monitored and supported by a larger network of digital tools. In addition the technology should be used to capture additional digital data streams such as instrumentation of the human activity, the data that human operators collect, input they can provide about the process, and more. 

In conclusion, if a technology is not able to impact your operations in this significant way then its not digital technology - simply drop it from the list. Let's take a simple example: SaaS MES that is purportedly in the cloud and requires experts with specific skills set to configure and use with a 6+ months implementation time frame. This is not and example of digital technology. You should be seeing quantifiable productivity increase results within weeks of adopting any technology.  Another example is if the technology implementation requires a waterfall/phased method that requires design of the substantial parts of the solution upfront then it is not a digital technology!  

You can watch me talk about these topics on the Manufacturing IT Podcast with Daniel Langley.

Maybe this will also nudge the skeptics out there since speed, effort and real world double and triple productivity gains are becoming real and undeniable. Charlie Chaplin once said "if you look down, you will not see the rainbow".

The Waste of not having Digital Data

My team started using Monday.com around a year ago. We needed a project management tool and Monday.com was our tool of choice. When I looked at it initially it seemed like any other project management tool, albeit cloud based and much more user friendly. Some may even consider it a glorified (or maybe more appropriately specialized) spreadsheet.   

I didn't think about it much, it was a PM tool and its use included the typical interaction as a project team member and for operational oversight. After a few month the team started showing graphs and charts based on the data that it captured. We could now easily see how long tasks take, how many project were over time, hours logged on projects, and more. As time progressed we had more and more data about our project execution and delivery operation. With that we started making better and more informed decisions such as optimizing teams, identifying risky projects, how many projects we are able to effectively run simultaneously, resource balancing, and much more. Then the team started putting in alerts, e.g. projects overdue, risk not being mitigated, and proactive actions. A year into using the tool we have now a services operations that is predictive and adaptable (this is a reference to the Industry 4.0 maturity model below) all on the merit of real time granular data that we is being captured just from us doing our job - without any extra or special effort in data collection.  

Industry 4.0 Maturity Model

Here is a tool that on first glance seems like just another PM tool. However since its a modern digital tool it instruments the project tracking and management process, capturing detailed data about every tasks and making that data intuitively available for all to use. That is the power of digitations, we see in all digital tools but it sometimes is lost on us when we reflect on something that we have done forever. For example Google, Facebook, Amazon all do this inherently - they capture granular data of everything. and with that data they are able to learn, improve and act.  This is what happens when you instrument your operation with a digital tool.

So if we take this as an example and reflect on any manufacturing operation it means that as a start we have to instrument and digitize. However the way this is approached in most manufacturing shop floors that I have experienced is by complicated data capture systems that require not only a immense effort in implementation but also constant battles from the frontline to use. Inputting data by the operator is typically an additional task they have to do, its not serving them any, it does it provide value to them and is essentially a form of waste. This results and data silos, or as how I like to call them "data puddles" that really do not provide much more than some isolated metrics. 

That of course is if there is any data capture at all! Many manufacturing operation are still operating with manual data and information in the form of paper, performance whiteboards, isolated spreadsheets, visual boards, etc. 

A compilation of photos from different shop floors I have visited.

We have to make the connection here, transforming digitally is not just another IT/OT exercise, its not a project you can execute to implement data capture technology (see post about crossing the digital divide). True digital technology is adopted not implemented, it starts by taking some manual task or operations and instrumenting them like Monday.com does for project execution. The first step in any digital transformation journey is to start to instrument your operation by providing digital tools to your operators that help do their job while at the same time collecting data - not the other way around. 

The interesting thing about doing it this way is that its in fact pretty easy, and at the same time seamless for your operations to adopt. Simply because it helps them do their job, and provide immediate feedback thru data visibility about their operation. It is how they become more productive, and productivity is what digital transformation is all about.  

With that in mind the simple way to start any digital transformation project is to do a Gemba walk to identify the waste of paper or no data. Find the places where instrumenting a process can provide a quick productivity increase. Instrument the process with a digital tool and see experience the boost yourself. Think of PDCA cycle with this level of granular and real time data. That is what digital transformation is all about.

Remember this can only be done by a digital tool that can be adopted (implemented, and used) with no specialized skills (democratized) and fast - within a few hours. Be warned a technology that does not provide these basic requirement, i.e. democratized and fast time-to-value, is not true digital (Industry 4.0) technology.

Don't Be the Last Dinosaur: Your Plant's Digital Evolution Starts Now!

Plant Managers, manufacturing leaders - look around you. The manufacturing world is not just changing; it's undergoing a seismic shift. While you're grappling with daily firefighting, your competitors – the agile, the digitally native, and those strategically investing – are busy building tomorrow's factories. They are not compromising; they are not settling for just automation, they are digitizing every process, they have rich digital data, they are ready to deploy intelligent, agentic systems that learn, adapt, and optimize production with unprecedented speed and accuracy.

The choice before you is stark: Innovate and adopt, or become obsolete.

If you continue to manage your plants with fragmented data, manual processes, and reactive decision-making, you are literally leaving money on the table. You're bleeding efficiency, compromising quality, and surrendering market share. The 'traditional' way of manufacturing is becoming a relic.

Here are the critical decisions and actions you must undertake RIGHT NOW to avoid being left in the dust:

1. Stop analyzing and planning- Start digitizing today: Your operations are awash in data, but is it usable? Is it real-time? Is it connected? The foundation of every advanced manufacturing system—from IIoT to agentic AI—is clean, contextualized data. 

ACTION: Invest immediately in robust digital data infrastructure. This means connecting your machines, sensors, and systems (OT and IT convergence is non-negotiable). If your data is trapped in silos, you are blind, and your plant will suffocate under its own inefficiency. This is simply critical - not having digital data is a waste, like other wastes in manufacturing!

2. Embrace the Power of Composability: Shift your thinking beyond overarching automation or top-down systems to digitize plant processes. The "lights-out factory" is not only outdated, it never truly materialized. Digital transformation isn't about replacing humans but augmenting their capabilities. Composability focuses on empowering your workforce, leading to significant productivity gains. Deploy pilot projects where AI agents can take over mundane, repetitive, or complex analytical tasks. Think predictive maintenance that schedules itself, quality control that detects micro-deviations before they become defects or failures, and production dispatching that dynamically adjusts to supply chain disruptions. 

ACTION: Identify one critical bottleneck in your plant that could be addressed by a digital solution - yes “Kaizen”, start bottom up and iterate. Adopt technology, find a partner and just start. There are some impactful digital technology platforms (I recommend starting with Tulip of course) and launch a focused pilot. Show your team and leadership the tangible benefits.

3. Future-Proof Your Workforce – Invest in Upskilling, Not Just Training: Your people are your greatest asset. They need to evolve from procedure followers to orchestrators, data interpreters, and system managers. This isn't just about technical skills; it's about fostering a culture of continuous learning and adaptability. And with democratization that digital technologies offer this quickly can create a ground swell, a movement within your organization. 

ACTION: Develop a strategic plan for workforce transformation. Enhance your operational excellence with augmented lean principles and identify critical future roles and necessary skill sets. Empower your team to embrace these new technologies and strike down any skepticism or technology fears.

4. Demand Agility from Your Systems – Ditch the Rigidity: The era of monolithic, inflexible manufacturing systems is over. Your plant needs to be agile, able to pivot production lines, incorporate new products, and respond to market shifts with unprecedented speed. This means moving towards composable, interoperable platforms that can readily empower your operations with the new digital capabilities including critically AI. 

ACTION: When evaluating new solutions (like MES, LIMS, CMMS or other systems), prioritize open composable architectures with cloud-native capabilities, IIoT platforms and and in herent AI capabilities that are not an afterthought or “bolt on”. Demand systems that are built for change, not for static operations. These systems have to enable you to transform, they have to provide you a way to implement according to the 5 pillars of composability. Make agile, emergent control a reality with agentic AI.

5. For Regulated Industries: Make GxP a Competitive Advantage, Not a Burden: If you're in Pharma, Biotech, or Med Device, the GxP implications of these technologies are paramount. But don't let compliance be an excuse for stagnation. Modern digital validation approaches and Pharma 4.0 guidances mean you can innovate with compliance. Transformative digital platforms have inherent built in compliance through detailed digital data, audit trails, and transparency to control mechanisms. Democratization means technology is simpler to understand with that comes transparency and self documentation.

ACTION: Engage with experts who understand both cutting-edge digital transformation and the nuances of GxP. Be proactive in defining your digital validation strategies for IIoT and AI, leveraging initiatives like Validation 4.0. This ensures your innovation is robust, secure, and compliant.

The clock is ticking. The question isn't if your plant will undergo this digital transformation, but when and who will lead it. If you hesitate, you risk becoming a case study in industrial obsolescence. Seize this moment, or watch your competition leave you in their digital dust. This is the mindset you need to adopt to thrive in this new era. What's your immediate next step?

How Holonic Dreams are Becoming Manufacturing Realities

Let me tell you, there are few things more thrilling than seeing a concept you poured your heart into decades ago slowly coming to life in ways you barely dared to dream. For me, that feeling hits hard with the incredible capabilities of AI in general, and specifically, Generative AI . These aren't just buzzwords; they're fundamentally reshaping how we think about digital manufacturing (or whatever the latest term is). While Generative AI is phenomenal for creating content, designing new products, or even simulating complex processes, its true power in manufacturing often lies in its ability to empower something even more profound - Multi-Agent systems. This is the realization of Holonic concepts in a composable manner to enable agile manufacturing with Agentic AI .

When I see these advancements I am just mesmerized and my mind goes back to the 1990s. That’s when my journey into this future really began, deeply immersed in the world of Holonic Manufacturing Systems (HMS) and the emerging field of multi-agent systems.

Back then, I was a young researcher PhD working a methodology and architecture for Holonic manufacturing systems in collaboration with other like minded researchers as part of global consortium. It wasn’t just an academic exercise; it was a burning ambition to make manufacturing truly agile and resilient. I envisioned a factory floor that wasn't a rigid, top-down hierarchy, but a vibrant, decentralized network of intelligent, collaborative entities – what we called "holons."

The Holonic Vision: A Glimpse into the Future I Believed In

Imagine a shop floor where every machine, every production cell, every product, wasn't just a passive component but an intelligent "holon" – a self-contained, self-regulating unit. They would have their own smarts, making decisions, talking to each other, and collectively adapting to whatever curveball the market threw at them. Koestler's concept of a "holon" – simultaneously a whole and a part – perfectly captured this idea of distributed intelligence.

The benefits? Oh, they were clear and seemed a world away but yet an eerily anticipatory need of the current political and economic circumstances.

• Agility beyond belief : Reconfiguring production lines in a flash, launching new products on a dime, responding to customer demands with unprecedented speed.
• Built-in resilience : If one holon stumbled, the others would dynamically pick up the slack, re-routing operations to keep things flowing. Downtime issue would be a distant memory.
• Seamless scalability : Adding new machines or processes would be like plugging in a new module, effortlessly integrating into the intelligent network.
• Optimization from within : Local decisions by these smart holons would ripple up to optimize the entire system, far surpassing anything a central, rigid control system could ever hope to achieve.

This wasn't just theory; it was a blueprint for a manufacturing revolution.

We are Still Waiting for a Digital Manufacturing's Breakthrough

The holonic concept was the perfect architectural dream, but the engine to power it, multi-agent systems, was still in its infancy. My research in the 90's focused on how to design these agent systems, how to give them that holonic spirit, but the reality was that our ambition ran ahead of the available technology. We were hitting walls. The computational power needed to run complex agent logic on shop-floor controllers was simply astronomical for the time. Getting a multitude of agents to communicate reliably and securely across a factory? That was a networking nightmare. And then the AI capabilities were nascent, a whisper of potential, compared to the what we wield in our hands today."

Those were exhilarating times for pure research, pushing the theoretical limits of what manufacturing could be. But bringing it to large-scale industrial reality? That was a bridge too far. Until now ...

Today's Reality: AI and Digital Infrastructure can Unleashing the Holonic Dream

Fast forward to today, and the technological landscape has dramatically evolved. The convergence of several critical advancements has not only rendered the holonic vision achievable but has propelled it into operational realms previously unimaginable:

1. Advanced AI and Machine Learning Capabilities : Modern Artificial Intelligence and Machine Learning algorithms now provide the sophisticated analytical and cognitive capabilities for individual software agents. These algorithms enable agents to learn from large-scale industrial datasets, execute robust predictive analytics with high precision, and achieve adaptive process optimization in real-time. This represents a fundamental shift from deterministic, rule-based systems to dynamic, self-optimizing intelligence.
2. The Industrial Internet of Things (IIoT) as the Network of Agents, Powered by Agentic AI : This is where the core holonic vision finds its full realization. The Industrial Internet of Things (IIoT) is not merely a collection of connected devices; it forms the very network of agents. The IIoT nodes themselves are designed as autonomous, intelligent agents . Each smart device, each sensor, each piece of equipment can be made to act as a data acquisition point and, crucially, as a decentralized intelligent entity. The emergence of Agentic AI imbues these IIoT nodes with advanced capabilities for complex task decomposition, strategic planning, execution, and critical self-reflection. This synergy of IIoT as the foundational agent network and Agentic AI providing the cognitive layer directly mirrors the autonomous and cooperative principles fundamental to our original holonic concepts, enabling seamless interoperable collaboration across the manufacturing ecosystem. 

Futuristic Use Cases Becoming Reality: Empowering the Digital Twin for Tomorrow's Factory

For all these visions to truly become reality, we needed more than just powerful tech; we needed a concept that can effectively by applied to the realities of a physical operation. Here we can use a Digital Twin approach to represent the reality of the operation and build a foundational model with a set of constructs that aligned perfectly with the holonic principles I’d spent years researching.

This is also where Agentic AI enters the stage, becoming the intelligence that breathes life into this digital replica. My research from the 90s proposed a consistent model for these foundational constructs, embodying them as intelligent Product, Order, and Resource agents (or holons). This was the blueprint for how the real-world manufacturing elements could become autonomous, cooperative entities within the digital twin.

Let's step into this future for a moment, and I’ll paint a picture of what a manufacturing operation truly looks like when its digital twin is powered by these agentic principles, or in other words a next generation paradigm shifting composable manufacturing system . In this world, a work order isn't just data on a screen; it instantly awakens an intelligent Order Agent within the digital twin - or plainly the manufacturing system. This agent immediately gets to work, dynamically negotiating with Resource Agents —the digital representations of machines, tooling, even the specific human expertise required—to secure optimal production slots and materials in the virtual space, which then collaboratively drives actions in the physical factory assisting operators in orchestrating the operation.

As raw materials enter the facility, each component, or even the nascent product itself, manifests as a Product Agent within this digital twin. This agent carries its own unique digital identity and manufacturing instructions, literally guiding operators to route its counterpart through the physical production line. It's constantly communicating its status and needs within the digital twin, ensuring it receives the precise processing at each stage in the real world. If a specific machine (a Resource Agent ) suddenly reports a slight anomaly – say, a bearing starting to warm up – its built-in intelligence within the digital twin instantly flags it. Instead of waiting for a catastrophic failure, the line's collective intelligence, orchestrated by operators using the various software agents operating within this digital twin environment, might subtly re-route the physical Product Agent to an alternative, readily available machine. Or, better yet, the affected Resource Agent might even initiate a precise, self-healing routine or schedule a just-in-time, predictive maintenance intervention, ensuring that the issue is resolved before it impacts production, all while the Order Agent helps ensure deadlines are still met.

Quality control isn't a post-production check; it's baked into every micro-decision. Product Agents and Resource Agents , leveraging their digital twin data, are continuously monitoring parameters, spotting the tiniest deviation, and triggering immediate corrective actions to ensure "right first time". This seamless, autonomous orchestration – where products find their way, orders fulfill themselves, and machines manage their own well-being, all empowered through the precise, real-time fidelity of their digital twins – transforms the factory into a living, breathing, self-optimizing organism. It’s a level of agility, efficiency, and resilience that felt like pure science fiction in the 90s, but is now can become our tangible reality.

This leads us to an operational reality where the use cases that may seem futuristic are in fact possible , for example:

• Self-Optimizing Production Lines : Imagine entire lines monitoring themselves, sniffing out bottlenecks, predicting breakdowns, and then autonomously re-routing production or tweaking parameters to keep output optimal. Empowering human operators with currently unimaginable support in orchestrating operations.
• Dynamic Resource Allocation : Agents negotiating for machines, tools, and materials in real-time, ensuring every asset is utilized perfectly, eliminating idle time. Elevating scheduling and dispatching to unheard of levels of effectiveness and accuracy. 
• Predictive Maintenance and Self-Healing Systems : No more waiting for a breakdown. Agents predict failures with incredible accuracy and can even kick off self-repair routines or proactive maintenance, slashing downtime and costs.
• Enhanced Quality Control : Agents tirelessly monitoring processes and product quality, spotting deviations instantly and triggering immediate corrective actions. This is "right first time" manufacturing, every time.
• Boosted Compliance : Automated data collection, precise procedure execution, immutable digital records – agentic systems dramatically reduce human error and guarantee adherence to the toughest regulations.
• Unparalleled Traceability : Every single action, every decision by an agent, meticulously recorded. Audit trails become pristine, investigations swift and clear.
• Driving "Right First Time" : By minimizing variability and providing real-time feedback, these systems help ensure products meet quality specs from the outset, slashing costly rework.
• Accelerated Innovation : With more efficient, reliable processes, companies can pour more resources into R&D, bringing life-saving drugs or mission-critical components to market faster.

The journey from the elegant theories of holonic manufacturing systems to the practical, jaw-dropping capabilities of Agentic AI has been long, but intensely rewarding. What started as pure academic curiosity, exploring the power of decentralized, intelligent control, has now become the very bedrock of digital transformation in manufacturing. We’re no longer just imagining; we are actively building factories that learn, adapt, and optimize themselves , powered by the incredible, collaborative intelligence of software agents, physical machines, and empowered humans. It's a testament to the enduring power of fundamental research, a strategic commitment to true digital transformation, and the relentless, accelerating pace of technological innovation.

But hold on, not so fast. Here’s where my passion often turns to frustration. We have the technology today, and more is coming fast – innovation is accelerating at an exponential rate! Yet, a fundamental problem persists in manufacturing: so many companies still don't grasp that adopting digital technology demands a profound transformation , not just a simple upgrade.

The Agility Forum , a 1990 initiative to transform manufacturing, proclaimed that we need to thrive in an environment where change is the only constant. In today's volatile business landscape – marked by unprecedented geopolitical shifts, rapid market fluctuations, and increasingly fragile global supply chains – this is not longer a theory; it's the raw truth of survival. While our research in the 90s certainly anticipated a future of greater dynamism and the critical need for manufacturing systems to adapt , even we couldn't have fully foreseen the sheer velocity and breadth of the disruptions we face now.

This intense, continuous flux means leveraging that change, embracing agility itself, as your ultimate competitive advantage. The sheer ability to adapt, to pivot swiftly, and to continuously evolve your operations is precisely what will differentiate leaders from those left behind. In this dynamic landscape, digital transformation is not a static one time event, nor is it a project with a defined end; it is a continuous process of adaptation to changing business and technological environments - hence we need to start talking about Continuous Transformation .

The core issue isn’t the lack of innovative tools; it’s the mental, organizational, and cultural shift required to truly embrace them - yes its still really about people . Real digital manufacturing means rethinking everything – your processes, your workflows, even how you do business. It’s a complete reimagining, and that's precisely why the original holonic concepts, now enabled by modern tech, offer the inspiration for a breakthrough path. Embrace this paradigm shift, or risk being outmaneuvered by those who do. The future of manufacturing is intelligent, interconnected, and increasingly autonomous, built directly on the visionary concepts laid down decades ago.

Are we seeing the return of the Custom MES, or is it something else? (Re-Posted)

The role of MES in the Industry 4.0 reality is a topic of debate and a source of critical misinformation. In general MES belongs to the era of automation and computer integrated manufacturing, i.e. Industry 3.0. MES or MoM came about in the 1990s to solve the challenges of coordinating and executing work on shop floors with the advent of computers. It really is a relic of the previous industrial era.

The challenge of coordinating and executing work on shop floors however has not changed. Manufacturing is increasing in complexity and the need to adapt to changing business requirements is accelerating. At the same time the advancement in computer technologies have ushered a new digital era that we now call Industry 4.0. How do we solve the shop floor operational challenge with these new technologies?

Are these new digital technologies making it attractive and maybe even necessary to develop custom manufacturing systems solutions, or custom MESs? For years we have advocated that companies focus on their core business competencies and leave the software development to expert best in class software companies. There are many horror stories of companies that are stuck supporting custom built software that is running their critical operations, why build and spend millions maintaining in house developed systems?

Yet the need to tailored solutions for shop floor operations is still valid and in fact even more critical as the rate of change to the business environment coupled with operational complexity increases. It seems like a case of history repeating itself since that is how MESs started in the 80s, however technologies have vastly evolved since. With the digital technologies that are now available we are going well past the simple ability to customize. We are taking a very different approach that is operations and human centric. It allows us to rapidly create tailored solutions that increase productivity by supporting frontline operators for each specific operation and activity.

This allows companies to once again opt to develop custom solutions to solve their manufacturing systems needs. Yet this time around they do not look like MES of the past, they are not custom solutions that are unique and require high cost and effort to manage and maintain. In the digital era solutions are built rapidly by the people that are closest to the operations, they are tailored to the frontline operator and help increase their productivity and all of this in a Cloud-Edge infrastructure that allows easy management and governance. There are a number of forces at play that are causing this to happen.

Emerging digital technologies, specifically no-code cloud based SaaS platforms provide user friendly ways to build tailored digital content with very quick ramp-up times. I.e. you don’t need software development skills. There is a real business need to get the promised productivity gains from these digital technologies. In other words organizations have allocated money and people to get things moving in their digital transformation.

The new generation of workforce comes from the digital age (i.e. digital natives) and are used to in simple words, just download an app for that. They are confronted with what they see as antiquated software systems that are not really user friendly and their reaction is to find another app. The new digital technologies aimed at the manufacturing operations space are in general human centered – they aim to solve (and support) what we as people do, whereas traditional MES is developed to automate a process.

Modern cloud and edge technologies provide a rich playing field for integration and capture of digital data to help bridge the digital divide. I.e. start capitalizing on productivity improvements while not having to decommission existing traditional systems.    

The transformational forces at play are unstoppable at this point. The high skill and expertise level required to implement and maintain the current IT/OT owned systems are becoming a thing of the past. The new tailored manufacturing solutions can be built at a unprecedented speeds by people that are closer to the actual manufacturing process. We will not have unique and specific monolithic systems for each department or business function. The future digital factory will be supported by a network of digital components, apps, edge devices and tools will have been composed in a iterative and agile process, ie bottom-up. Solutions will emerge and mature over time based on continuous improvement rather than a top-down design and development process. With that traditional hierarchical thinking and approaches such as ISA-95/88 will become less relevant unless they are adjusted to fit the new digital reality.

Are we then seeing a case of history repeating itself? Will we see a resurgence of home grown MES solutions that we will in a few years pay dearly to maintain or replace? The answer is yes but not what you might expect. There will be some level of custom software being built but at the same time what we will se are tailored solutions that do not carry the burden of the custom system of the past. Modern digital technologies such as no-code platforms are democratizing the manufacturing systems landscape. They are transforming manufacturing systems software development to a process of composing digital content for the shop floor. They are more of an engineering and operations toolset rather than an IT system. Again we might use the term MES but these new solution will really not look like anything that resembles current MESs, they will consist of digital content that support human operations and digitize all activities and process in the plant. They provide unprecedented levels of detail in the form digital data that is easy to use, analyze and interpret. They provide the foundation for digital maturity toward the predictive and adaptable states in Industry 4.0. Companies adopting these platforms will be able to accelerate their maturity and their digital transformation.

This is a reposting of an article in Engineers Outlook and is based on a previous post on this blog The return of custom built manufacturing software.