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Solving the Digital Workforce Problem for Manufacturing

Posted by Barry Kaufman + Zaki Mohammad on Sep 9, 2019 5:13:56 PM

TLDR: Want to digitally transform your manufacturing business? Start with your people! Data and technology are secondary!

As the world becomes increasingly connected, we are beyond automation and AI being disruptors; they are becoming table-stakes technologies. On paper, manufacturers across the globe should all be embarking on their Digital Transformation journey where old factories are outfitted for the future of production, leveraging the technology advancements in AI and IoT. However, the reality is that manufacturers are facing many challenges that are slowing down and even halting their digital transformation journey.

At the heart of this challenge is a fundamental understanding of a ‘Digital Transformation’. What does it mean? Is it integrating data, AI, IoT or a combination of these into the key workflows of a typical manufacturer? How can the traditionally silo-ed data from the factory floor generate actionable insights at the operational and corporate level for an incumbent manufacturer?

Lots of things to unpack here, but let’s just simply agree, ‘Digital Transformation’ or colloquially known as ‘DX’ is a term so buzzy that no-one can quite pin it down. I feel like our industry needs fewer terms like DX, not more.

Put simply, DX is the evolution of an organization and its incumbent business model when it leverages and incorporates new advances in Cloud, Mobility, Big Data (or data for short), AI, IoT, and Blockchain (the list could go on, but you get the point!). For simplicity sakes, let’s collectively bundle Data, AI, IoT, Blockchain, and reality technologies (e.g. Virtual Reality, Augmented Reality, Mixed Reality etc.) into the term DX technologies.

However, here is the eye-opener: Most organizations and the market in general talk about DX being 80% technology and 20% human. This is far from the truth! Being at the ground floor of numerous Digital Transformation organization pivots from Fortune 500 to mid-sized enterprises over the last 15 years, it is probably 80% human and 20% technology. Without the right person or workforce, there will be nobody to ‘push the ON button’ on any fancy new IoT-enabled machinery generating insight-rich data that’s being crunched by the latest and greatest deep learning algorithm.  In the future, someone still has to push the proverbial ‘ON button’ in an autonomous factory!

This is the first in a series of blogs, where we tackle the DX talent challenges in each major vertical and industry that put the brakes on successfully adopting AI and IoT. We are, of course, starting with Manufacturing, as it is predicted to generate the lion’s share of the economic value and impact to society and businesses.


So how does one empower, equip and ultimately transform a typical manufacturer’s ‘workforce of today’ into the ‘workforce of tomorrow’?


When I started writing this blog, I thought about providing a specific roadmap – a description of how companies and their leaders should approach this transformative opportunity. But the more I thought about it, the more prescribing a specific approach seemed like ‘fool’s gold’. Even if the approach is a good one and followed to a T, it’s unlikely that any company would have the intended results or even identical results as another.

Why? Because methods are situational. In the manufacturers I have worked with, there are a few golden rules, but there are ALSO powerful leadership and regional dynamics that underlie each manufacturing organization’s methods. Those dynamics have an oversized influence on the incumbent manufacturer’s successes – or lack thereof and likely would overpower any bolt-on prescribed methodology. So instead, I will provide some guiding principles (based on lessons learned) – a common set of principles that are more likely to lead a manufacturer to success than failure. Principles have vision. Principles adapt to more situations and simplify the ‘beautiful complexity’ and provide clarity when it comes to transforming the workforce. In fact, principles can inspire and more importantly principles are durable.


Every organization’s DX journey, especially manufacturers starts with two main ingredients: people and  data. All of this lead to our five key principles:

  • Principle 1: Every DX Journey starts with people. Yes, there are two main ingredients for any DX journey: people & data. The focus in this blog is to start with people who will eventually point you to the right data. (P.S. if you are interested in the data side, let us know in the comments section; we are always looking for ideas for future blog posts).
  • Principle 2: Identify the right people aka “Personas”? Identify the relevant ‘Personas’ or categories of job roles that are key to the bringing the workforce of tomorrow to a manufacturer. Start with leadership personas and finish with “front-line” personas.
  • Principle 3: Understand your Point A: Perform a deep discovery on the ‘Current state’ of the DX-relevant knowledge, skills and abilities of your current workforce, collectively referred to as ‘DX acumen’ for short. This is a journey for your workforce and every journey has a starting point (Point A) and a destination (Point B). This helps draw out a simple relationship:
  • Point A = Current state of DX acumen for the manufacturer’s workforce
  • Point B = Future state of the DX acumen for the manufacturer’s workforce
  • Principle: Where exactly is Point B? Develop a ‘Future state’ for DX Acumen for the workforce. This is less looking into a ‘crystal ball’ and more an application of logic and reasoning based on where the market and industry is trending (remember trend is your friend!) and corporate aspirations.
  • Principle 5: Establish a Plan to get from you Point A to Point B through a skills development program for all relevant personas. This would incorporate at a bare minimum, learning paths (e.g. training curriculum, resources, certifications, etc.) for each of the persona. Remember “what gets measured gets done”.


Let’s dive into each of these points:

Principle 1: Why start with People instead of Data

At first this may seem like a chicken-and-egg problem (do I start with people or data?), but it’s really not. The “right Data” do not magically show up at our door nor do they produce insights once you start collecting the data. In fact, today we have too much data and are starved for insights. Manufacturers can attest to this, as their factory floor data today to a large part are siloed. Migrating that to an Enterprise ‘data lake’ is easier said than done without involving the right workforce! Furthermore between 70% to 90% of the work effort in any DX project is identifying the right data, cleaning them and finally integrating the data to train various pipelines, models, agents and algorithms. Here is the real kicker, even if you go through the above endeavor and you start collecting insights that deliver decision intelligence and visibility around your business, you will probably realize you were barking up the wrong tree after all. We continue to see organizations fall into this trap: we already have the data we need, or we know where the right data reside. If we had a dime every time we heard this story …


But guess who really knows where the proverbial pot goes gold (insight-rich data in this case) is at the end of the rainbow. It’s your people of course, specifically, the folks in your workforce that are the front-line product development, engineering, production floor staff, customer service and sales folks. They already have a deep acumen of what the problems of the business are and are deeply involved with a manufacturers’ customers. They already have the domain knowledge of how a manufacturer’s products and services create value for the customer. Ultimately, they are the end-users and primary consumers of DX technologies (outputs from any manufacturer’s DX projects) within the incumbent organization. However, there is a failure today to engage, enroll and empower the front-line workforce for manufacturers in their DX journey. One of the goals of this blog post is to shed some light on this.


Bottom-line: Start with your existing workforce. What they lack is the acumen and the notional understanding in the ‘art of the possible’ with DX technologies. They don’t have the right literacy around DX technologies to start with. The answer is to augment their acumen and capabilities on DX technologies. This is a learning gap issue: either you know it or you don’t. The first step for manufacturers is for their Leadership to acknowledge this, and then act by providing the necessary skills development infrastructure, resources and mindsets for their broader workforce to further augment their acumen on DX technologies. Eventually the organizational culture will shift and follow suit.


Principle 2: Enabling the right Personas:

I am going to skip the research and go right to the goods: there are four key persona categories that are critical to ensuring a successful transition to the ‘workforce of tomorrow’ for any manufacturer: Senior leadership, front-line managers, front-line operational & production staff, and IT & analytics staff.


Persona Categories

Importance to Digital Transformation of the Workforce

Senior Leadership

Without the buy-in, guidance, and support of Senior Leadership, any DX enterprise initiative is doomed to fail. Every transformation journey starts with transforming the Leadership, period. Target job roles: CEO, CHRO, Head of Manufacturing, or Plant General Manager.


Front Line Managers & Supervisors

They are responsible for creating and managing high performing teams. Additionally, their support in re-skilling themselves and their teams (front-line operational and production staff) will serve as a catalyst for creating and fostering a DX-enabled culture of continuous learning within the manufacturer and promotes an engaged workforce, reduces attrition and positively impacts manufacturing KPIs and metrics (e.g. OEE and Quality). Target Job roles: Manufacturing & Production Supervisors


Front line Operational and Production Staff

They ultimately are the most affected and vulnerable to advances in automation and AI. They have an innate fear of change that automation and AI will take away their jobs. In fact, the reality is that both the former and latter will bring in a more cognitively fulfilling job role and a better work-life balance for them. This persona often gets overlooked in any Manufacturer’s DX journey but is the key to truly pivoting a Manufacturer DX journey. Example job roles: Operators, Assemblers and Laborers


IT and Analytics teams

Their role is evolving from a back-office cost-center to a truly strategic partner in any manufacturer’s DX journey. It is simply not enough for them to be upskilled and reskilled on the latest Data science, IoT or even AI technical technologies, but also understand how to integrate their workflows with those of two other personas:  Front Line Managers & Supervisors and Front line Operational and Production Staff. Example job roles: Data Analysts, Data Engineers, and Data Scientists


If we really want to screen and pick the minimum number of Personas for any enterprise DX skills development initiative for a Manufacturer, it would be the following:

  • C-suite and Senior Leaders
  • Manufacturing & Production Supervisors
  • Operators, Assemblers and Laborers
  • Data super friends – Data Analyst, Data Engineer and Data Scientist.


Principle 3: Understand current state of your workforce’s DX acumen.

Based on our own work, which is congruent with findings from other analysts, there are five skill categories for a typical manufacturing workforce. These categories form the basis of ‘Point A’, otherwise known as the starting point of a typical manufacturer journey to transform their workforce. Leveraging the roles identified previously, the breakdown of skill categories is displayed in the following graphic:


Principle 4: What is the future state of DX acumen for a manufacturer’s workforce?

With some logic and reasoning and leveraging the graphic from Principle 3, there are significant shifts in workforce skill categories in the automated AI future. For a manufacturer, the biggest changes are:

  • Demand for physical and manual skills as a predominant skill set will continue to decrease. Basically physical & manual and basic cognitive skills will shrink while the proportion of higher cognitive, social & emotional and technological skills will significantly grow;
    • Pervasive automation (e.g. Robotics) will reduce the physical and manual footprint in almost all job roles
    • Basic cognitive functions like visual inspections, simple actions with equipment and tools and remote monitoring will diminish as a result of advances in AI;
  • Technological skills will increase in importance, both in advanced skills such as programming, advanced data analysis, data-driven decision-making and technology aided product design, as well as basic digital skills will become prevalent for all businesses but especially for manufacturers;
  • The AI-enabled automated future will place significant demand on various types of social and emotional skills. These are collectively referred to as “21ST Century business skills” (a blog post for another time but rest assured ‘design thinking mindset’ is there).
  • Manufacturer’s current staff in the job roles described above may or may not have the aptitude to perform the new DX-enabled roles of the future.


Principle 5: Establish a plan to get the workforce from current state to future state

To get to the future state of DX acumen for a manufacturer’s workforce requires a plan or roadmap for a ‘Skills development program’ for all relevant personas. This means establishing Learning paths for each of the Personas. Such a Skills development program would address the learning gaps that exist for each persona to get from their ‘current state’ to their ‘future state’ of DX acumen. It goes without saying that employing the right learning science (aka how humans learn) and approach will ensure positive results and generate both short- and long-term ROI for any manufacturer embarking on this path.



Manufacturers’ have a consistent need to maximize production levels, minimize downtime, improve product quality & safety, reduce production costs, and adapt rapidly to changing production requirements.  DX technologies like data, Cloud, AI and IoT can drive transformational breakthroughs in these areas and more. But to do so requires that each manufacturer equip their leaders and workforce with the kind of skills needed to tap the full potential of what the technology has to offer. Skills development with a focus on re-skilling and up-skilling these target personas is at the heart of the solution.

Manufacturers that invest and execute in skilling their leaders and workforce will accelerate and improve their chances as they embark on their own DX journey. We have proposed five guiding principles herein which serve as catalysts for any manufacturer’s DX journey.

Our last request to the readers: please let us know if the comments section if you found this article helpful and please share your ideas on possible future topics. We are all here to learn from each other!


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