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What's Missing From Asset-Heavy Digitalization?

What's Missing From Asset-Heavy Digitalization?

Your initial reaction, facing digitization, is to focus on the data, sensors, and equipment in an effort to enable machine learning. What's most often missed is the user.

There’s been a shift happening and it has a name. You definitely know it and have probably used it already. Depending on your point of view, this name strikes fear or excitement - digitization.

You’re tasked with the digitization of your assets and systems to reduce costs, increase efficiency, reduce unplanned downtime, and connect to the industrial internet of things (IIoT). But how? How do you take sensor data to accomplish the goals set by executives? Or if you’re an executive, how do you enable those under you to achieve these tasks? Here’s the secret.


This is important. Your initial reaction, facing digitization, is to focus on the data, sensors, and equipment in an effort to enable machine learning. It’s not your fault, it’s part of the name "digital"-ization. What's most often missed is the user - they are the variable that can have the most impact.


Many of us know about the industrial revolution and for those that don’t know, our current economy and wealth owe everything to the it. It propelled us from farms to cities, gave us cars, fabricated houses, easier access to products and goods, and ultimately brought about globalization and increased trade.

We’re much better off having gone through this revolution. This was a revolution built on assembly lines and systems. It required someone to stand and do a task repeatedly as the product moved down the line. As our technology grew, we slowly added machines to automate to reduce the number of actual human beings required to do repeated tasks.

Leaving the holistic thinking of farm and rural life, people specialized and started to get really good at one thing. We needed more engineers to build more machines, production lines, and systems. Then we needed more people to fix specific problems that arose.

The focus left us as humans and went to the line and equipment. Questions arose, "how do we keep things working longer?" People became cogs, line-items, extensions of the equipment, and we developed systems to keep our "human" equipment functioning properly (enter the Human Resources Department).

Then the internet came into the picture. Suddenly we had connections and communication that we didn’t think were possible. The internet thrust us unknowingly into the Knowledge Revolution.

With the Knowledge Revolution, we discovered that things optimized for an industrial mindset wouldn’t work as efficiently. It required people to think holistically and through complex problems; much like rural life before the Industrial Revolution, we needed to be able to see a system and our contribution to that system.


Why users? Industrial mindset principles won’t work when applying Knowledge Mindset Principles, such as Systems Thinking and Mulitple Intelligences Theory. Focusing on the user allows you to use the Industrial Mindset as a tool to apply a Knowledge Mindset.

Industrial analytics is the next step in our journey and allows humans involved to see a bigger picture. This will give them the opportunity to have a full impact on the system. The goals of decreasing unplanned downtime, pull greater efficiencies and find solutions faster will all naturally fall out of a user-focused approach through industrial analytics.

Machine learning, industrial analytics, sensors, and data are all tools to enable the users; the humans. These tools aren’t the digital solution - your equipment operator, maintenance engineer, and reliability engineer are that digital solution.


A user-focused solution is hard and feels counter-intuitive. An industrial mindset is easy. You focus on one problem at a time. The problem is specific, the solution is most often easy to see. There are no emotions to get in the way, it either works or doesn’t.

The user-centered approach is messy. You’re dealing with people, emotions, complexity, systems, decisions - the list goes on. How do you do it? How do you focus on the user?

Lucky for us, a whole discipline around user-centricity has developed with a wealth of knowledge. User-Experience Design is more than making something look nice, highly developed, or an addictive digital consumer product.

It asks the necessary questions:

  • What's my user doing?
  • What are their goals?
  • What tools do they currently use to solve their problems?
  • How will my product influence their work?
  • Are they able to reach their goals easier with my product’s help?
  • What are other points of friction my product can help within this process or system?

The questions can be unending and tactically may not help you immediately. Here are a few things you can do right now to be more user-centered:

  1. Put the equipment aside for a moment and dig into the "jobs to be done" and the motivations of your users.
  2. Develop a visual of the system in which the user interacts. User Experience Designers call this a Journey Map and involve making a visual representation of the user's decisions, interactions, and impacts.
  3. Compare the "jobs to be done" and the system to see where you need to improve. These improvements may not always be a "digital" solution.
  4. Repeat - in design, we call this iteration.


You’ll be tempted by your colleagues to focus on the equipment only. Challenge this, don’t give in to the industrial mindset and always bring the user back into the picture. When you find yourself around users, talk to them. Make sure to record their quotes and insights. Use them as fuel in conversations to show how something would work better.

Ultimately your goal is to put analytics into the hands of the users. You do that by knowing your user first.

Learn more

How to Start Thinking About Architecture for Data-Driven Solutions

Rapid IoT Projects in Industry - Where Should You Focus?

The Journey to Predictive Equipment Maintenance