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Intentional Upskilling: A Three-Year Roadmap for Manufacturers

Wed, 01 Oct 2025 23:21:14 +0000

Evolving the Manufacturing Workforce

This past week, I participated in RIT's National Council for College of Engineering Technology. The discussions with industry leaders and faculty highlighted a genuine urgency: we must prepare students—and the workforce they will soon join—for the demands of evolving industries. That urgency is equally pressing for today’s manufacturers.

Technology adoption is accelerating in manufacturing, but workforce skills often lag. New automation, analytics, and digital platforms cannot deliver their promised value if people are not equipped to use them. Operators default to old habits, engineers underutilize systems, and ROI takes longer than expected.

Skills investment must run in parallel with technology investment. Without it, digital adoption risks becoming another layer of complexity rather than a source of capability. Skill investment is strategic; it takes time and it takes commitment from the C-suite.

This blog outlines a three-year upskilling roadmap designed for OEMs, ODMs, and capital equipment builders—manufacturers of CNC machines, packaging automation, and factory systems—where workforce readiness is the real bottleneck to realizing value.

Year 1: Build Baseline- Job Roles and Digital Awareness

Goal: Ensure the workforce is familiar with the digital tools already in place.

Updated job descriptions: Redefine roles and skills to reflect future competencies. Industrial associations can play an important role in helping members benchmark and standardize.

Clear role definitions are critical before training begins so employees understand expectations and growth paths.

Vendor-led onboarding: Require OEM and automation vendors to deliver role-specific training for operators, technicians, supervisors, and engineers.
In-house refresher modules: Develop short, practical content for ERP, MES, CAD, or CAM systems.
Microlearning: Introduce 15–20 minute shift-based sessions rather than full-day training.

Metrics: % of workforce completing baseline training, time to competency, reduction in basic operator errors, increase in ERP/MES usage rates

Year 2: Expand Applied Skills and Cross-Training

Goal: Move from awareness to confident application.

Role-based in-house certification: Build structured skill paths such as quality diagnostics, maintenance troubleshooting, or scheduling optimization.
Digital twin training: Use simulations to train operators on scenarios such as CNC machine jams or packaging line bottlenecks without interrupting production.
Cross-training: Enable line leads to interpret downtime dashboards and planners to handle dynamic scheduling.

Metrics: Reduction in downtime tied to operator error, shorter onboarding cycles for new employees, measurable OEE and throughput improvement.

Year 3: Embed Advanced Skills and Career Growth

Goal: Develop predictive and decision-support capabilities while improving retention.

Analytics literacy: Train supervisors and engineers to act on predictive maintenance data, throughput analytics, and scheduling recommendations.
Train-the-trainer programs: Build internal champions to sustain programs and reduce vendor dependence.
Career pathways: Link skill acquisition to advancement opportunities, pay scales, and progression into supervisory roles.

Metrics: Increase in ERP/ MES usage rates; reduced root cause analysis cycle time; higher retention of skilled workers.

Integrating Skills with Technology Investments

Every equipment or software investment should include a skills roadmap.

Negotiate structured training programs into vendor contracts.
Pair new systems with defined workforce learning modules.
Measure skills adoption alongside OEE, downtime, and throughput.

Upskilling is not an add-on. It is a direct enabler of ROI.

Retention Through Growth

Workers are more likely to stay when they see growth opportunities. Skills development sends a clear message: we are investing in your future, not just in machines. At MTAB Engineers, quarterly vendor-led training sessions were open to everyone, including shopfloor team members. This approach ensured knowledge-sharing across all levels and gave vendors direct insight into how components were used in practice. The results were tangible: greater efficiency, faster problem-solving, and stronger workforce retention.

Call to Action

If you are planning your next wave of automation, physical or digital, create a three-year workforce roadmap alongside it.

Year 1: Build baseline awareness.
Year 2: Apply and cross-train skills.
Year 3: Advance analytics literacy and career growth.

Technology will continue to evolve. Workforce skills must evolve with it. Intentional upskilling is a strategic necessity and the surest way to secure ROI and workforce stability.

Habits-First Approach to Digital Readiness

Tue, 09 Sep 2025 06:20:19 +0000

Evolving the Manufacturing Workforce

Last week, I was in a conversation with two industry veterans—strategic leaders who have been in the thick of digitization and delivered across industrial verticals. We debated why manufacturers delay digitization. The answer: most leaders are immersed in daily firefighting and cost control rather than planning for the capabilities they will need 12 to 18 months from now. We agreed on this: manufacturers need an expert such as Chief Digital Officer (fractional or full-time) to create visibility, build capabilities, and set a roadmap for capacity and workforce evolution.

Most manufacturers still rely on experienced supervisors to interpret production data, while operators rarely engage with digital systems, let alone AI. Yet as experienced staff retire and roles evolve, this model becomes unsustainable. Digital-native (AI-native) means every role, from operator to planner, interacting with digital information meaningfully, giving it real-time context.

But the truth is, all factories are not created equal. Workforce skills, infrastructure maturity, and tool availability vary dramatically. This blog reframes AI readiness as a stepwise progression—with practical, habit-first changes that build toward Digital/ AI-native behaviors without requiring high upfront investment or perfect systems. A diverse perspective + domain expertise greatly helps in defining the journey. It is useful to hire a Chief Digital Officer (CDO), part-time or full-time, to guide the leaders and their people through this journey.

Step-Up Maturity Ladder for Manufacturers

Change is hardest among the manufacturing workforce, who physically build products. Change here encompasses physical and digital. They are required to deliver efficiently, at quality, within the cost and time boundaries, while juggling internal and external variables, ensuring safety and compliance is maintained. This does not give them much time to build digital fluency skills unless organizations are intentional. This five-level ladder helps factories take actionable steps based on their starting point. Each level builds from the previous one—embedding habits, visibility, and tools at their pace, without judgment.

Level 1: Tribal Knowledge + Paper Systems

Reality: Verbal guidance, paper logs, operator memory.
Actions: Use end-of-shift whiteboards for operators to note issues. Assign a supervisor or intern to digitize them weekly.
Tools: Whiteboards, sticky notes, spreadsheets.
Indicative ROI: Cultural shift in how problems are surfaced. Minimal cost. Builds engagement.

Level 2: Routine Digitization of Observations

Reality: Supervisors collect observations but storage is informal.
Actions: Set up structured Google Forms or Excel templates. Categorize top recurring problems.
Tools: Shared drives, Google Forms, Excel with macros.
Indicative ROI: Early pattern visibility. Supports better maintenance planning.

Level 3: Shared Visibility for All Roles

Reality: Dashboards exist but only management sees them.
Actions: 80/20 Rule—Display heatmaps of delays, progress and success in shopfloor spaces.
Tools: Current ERP dashboards, Power BI (read-only), Tableau.
Indicative ROI: Cross-role alignment. Downtime reduction through proactive responses.

Level 4: Micro-Decisions and Role-Based Prompts

Reality: Leads rely on experience, no digital triggers.
Actions: 80/20 Rule—Create “if-this-then-that” cards or digital guides. Run post-shift reviews comparing decisions vs. outcomes.
Tools: Co-Pilot, SOPs, Decision Trees (Process Shepherd, Tulip).
Indicative ROI: Increases first-time-right. Improves supervisor effectiveness.

Level 5: AI-Augmented Roles

Reality: Some engineering or planning staff adopt AI suggestions.
Actions: Introduce guided root cause analysis tools, build-sequence optimizers, and delay impact simulators. These help planners and engineers test “what-if” changes and quantify downstream impacts—without touching production.
New Tools: Phantasma for scheduling & planning and integrates with multiple ERPs, Quarter20 for collaboration between design engineers and manufacturing/ assembly, DeepSight Realite for factory onboarding, Augmentir for connected worker knowledge management.
Indicative ROI: Faster RCA. Improved planning resilience. Scenario planning capacity. Knowledge retention, transfer and addition.

Two Frameworks to Measure Workforce Digital Fluency

For the curious mind, here are a couple of available frameworks that can be used to assess maturity of roles and job transformation.

Assess and Improve Digital Literacy in Manufacturing through SIRI

Skills and competencies to be acquired to improve maturity
https://incit.org/thought-leadership/why-assessing-your-teams-digital-literacy-is-the-key-to-unlocking-innovation/

World Economic Forum’s Global Skills Taxonomy Adoption Toolkit

Aligns job transformation with tech evolution.
https://reports.weforum.org/docs/WEF_Global_Skills_Taxonomy_Adoption_Toolkit_2025.pdf

Final Thoughts: Pragmatism over Perfection

AI-native is not a destination. It is a journey of building decision intelligence, one observation, one dashboard, one behavior at a time.

Start with what your team knows. Visualize what is happening. Add just enough structure to turn experience into action.

Turn daily habits into future-proof capabilities—starting where you are, with what you have and identifying what you need to add.

If you are looking to bring on an interim or part-time Chief Digital officer or Smart Manufacturing Expert or understanding what you need,t alk to us.

Human Capital Development in Manufacturing

Wed, 09 Apr 2025 00:09:07 +0000

Augmenting Human Potential: Designing the Future with Digital Tools

In today’s rapidly evolving manufacturing landscape, the role of technology is no longer just to automate tasks—it is to augment human potential. That was the core message of my Lightning Talk at the Stealth Summit 2025, where I explored how small and mid-sized manufacturers can thrive by embracing digital tools that enhance—not overwhelm—their people.

The Opportunity in the Chaos

Manufacturing in the U.S. is at an inflection point. The reshoring is creating long term opportunities and exposing unresolved vulnerabilities. Small and mid-sized manufacturers, who form the backbone of our industrial base, are under immense pressure. They face:

Acute labor shortages and succession issues
A deluge of digital transformation and cybersecurity demands
A perception that automation is unaffordable or ill-suited for their size

Unlike large enterprises, these firms don't have the backing of deep IT teams, transformation advisors, and layered implementation support. Yet, they are expected to remain competitive, agile, and compliant in a high-velocity market by their customers and this requires digital capabilities.

Start with a Manufacturing Tech Health Check

Similar to a financial health check, manufacturers must assess their digital fitness- what I call Manufacturing Technology Balance Sheet. Tools like the Smart Industry Readiness Index (SIRI) provide a structured framework to uncover:

Technology debt built over years of tribal knowledge, paper-based workflows, and siloed systems
Efficiency leaks from outdated tools and disconnected processes
Misaligned priorities, where symptoms are mistaken for root causes

For example: At one industrial plastics manufacturer, the management team was receiving signals that their delivery issues stemmed from capacity shortage, requiring investment in equipment and additional workforce. An assessment, however, revealed the true cause: manual process triggers, system fragmentation, and poor data visibility. The assessment shifted their course of action and investment—towards digitization and systematization of critical processes.

Changing the Engine While Flying the Plane

Digital transformation occurs while the business continues running. This is akin to changing the engine while flying the plane—and it requires precision, clarity, and a phased approach.

Here are three ideas to build capability while minimizing disruption and enabling adoption:

1. Connected Worker Platforms: People first

Today’s workforce learns and operates differently. We must replace binders and verbal instruction with digital, role-based, context-aware tools. Connected Worker Platforms aggregate static documents, SOPs, reports, and drawings, and deliver dynamic content via mobile and AR devices—accelerating onboarding, improving safety, and developing human capacity.

2. Process Blueprinting for System-Driven Actions

Many shopfloor activities are still triggered manually, which is unsustainable. To start with, digitally blueprinting and systematizing critical operations enables information flow across functions, triggers cross-functional processes, supports exception-based decision-making, and reduces waste from waiting and miscommunication. I can tell stories when the absence of one person in the manufacturing value chain introduced multi-day delays and disruption.

3. Digital Twins: Utilize this asset.

A digital twin is more than a virtual replica of hardware, process or supply chain. When designed well, it becomes a shared intelligence layer across the enterprise—from sales and planning to production, service, and even the customer. Digital twins allow for:

Scenario testing
Cost and time reduction
Decision support across product lifecycle

When tied to real-time data and operations, digital twins become assets that unlock new business models, such as outcome-based services or predictive maintenance offerings.

Designing Services That Develop Human Capital

The future of manufacturing isn’t just digital—it is human-centered. Many transformation projects will be brownfield, requiring integration with legacy systems and human adaptability. Success depends on designing solutions with the following principles:

Start small, deliver value, scale pragmatically
Small, outcome-driven implementations build confidence and minimize risk.

Adopt flexible, service-based models
Manufacturers are shifting from capital investment to robots and software as a service, giving them agility without long-term lock-in.
Embed learning in the flow of work
Implementation providers must prioritize creation of a knowledge base, skills training, and change management. Connected worker tools and digital learning environments reduce dependency on informal knowledge transfer.
Use data analytics to elevate people, not just performance
For the near future, employees remain at the center of decisions. Dashboards must show how employee interventions—setup changes, quality catches, problem-solving—drive productivity and improvement. This creates visibility, encourages innovation, and builds a strong talent pipeline.

Final Thought

The future of manufacturing is about human capital development. It is about designing systems that amplify their capabilities, scale their strengths, and unlock innovation.

By embracing connected platforms, digital twins, and human-first design, we can create a resilient and inclusive manufacturing ecosystem—one where technology empowers talent.

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