Are You Solving a Problem, or Solving Problems?

Industry 4.0 and problem solving

Industrial IoT and Industry 4.0 digital products on the market today tout flashy ideas and slogans such as "seamless integration to the cloud" or "visualisations of sensor data for performance metrics and predictive maintenance". Many of these products are pushed by people and companies that come from IT backgrounds, motivated by the idea they are "saving" manufacturing and Operational Technology (OT) by bringing them new and exciting technologies that they otherwise wouldn't have. This simplistic mindset is a grave misconception, and one that misses the point of Industry 4.0. The way forward is not determined by any one specific problem being solved or a collection thereof; it is about reinventing your business to have the capability to solve many problems at pace. Before going further with this, let's rewind the clock a little...


Every industrial revolution, from 1 to 4, has had the same high-level goal - improvement. To be better today than we were yesterday. The difference between each revolution is simply the characteristics of the technology used to gain that next step in that improvement (mechanisation and steam in the first, electricity in the second, the transistor and automation in the third, and of course internet and connectivity in the fourth). It is also probably important to note here (and it may be obvious to most) that each "revolution" is really just an arbitrary cluster of common characteristics on what is a continuous evolution. It's not like we went to sleep one night in Industry 2.0 world, and then woke up the next morning in Industry 3.0. In any case, with each "revolution" we seem to be experiencing more avenues to which we can apply the given technology. When we invented the steam engine, we had a way to make big things move in a simple motion (smaller movements for smaller objects were not at all worth the cost). When we had electricity, we could make many more things move, but we could also do other things like work in the dark or make machines that were portable. When the computer popped up, the possible avenues of improvement became even more abundant - we could program motion with robots, create Human Machine Interfaces, collect and analyse data, have statistical process control on production lines, simulate things, use computers for general business use, etc. (the list could really go on for this one). And now we reach the 4th Industrial Revolution where the key characteristic is connectivity - more connections at higher speeds between people, machines, systems, devices, and many other "things". Not only can we enhance and improve on a lot of the solutions from the previous revolution, but people from every domain across the business are coming up with all sorts of ideas on how this next level of connectivity can benefit them.


The fact that there is now much more opportunity for improvement is a great thing; the downside, however, is this increase in activity has created a lot of "noise". For as many "good" solutions on the market we find as many, if not more, "bad" solutions; a "bad" solution is one that either does not provide return on investment (ROI), has an opportunity cost greater than the benefit it provides, or is not future-proof and scalable.

So how can we determine what is "good" and what is "bad"? What is Industry 4.0 technology, and what is just technology for the sake of technology? Thred has developed a framework, SMARTA™, for profiling a piece of technology and answering these exact questions. However, the point I want to make in this post is that in order to fully realise Industry 4.0, we first need to be asking a different question entirely. We need much more than discrete pieces of technology solving discrete problems – instead, we need a way/method/framework to be able to rapidly solve problems with technology, over and over again. Everybody is familiar with the proverb “Give a man a fish and you feed him for a day. Teach a man to fish and you can feed him for a lifetime.” Solving a problem in a non-repeatable way, is the equivalent to receiving the single fish. In order to improve a business with efficiency, ease, and momentum, we must learn how to fish. We must be able to solve problems.

The act of turning data into a business insight shouldn't be a project or investment, it should be business as usual.

In order to solve problems, we must be able to ask and answer questions about the business – continuously. And in order to be this inquisitive, we need limitless access to reliable information and knowledge. At the heart of information and knowledge is data. Without data, this chain of continuous improvement will never get off the ground. So, the question is this – does your business have a framework of which you can ask almost any critical question and then receive a verified and reliable answer in a timely manner without any major cost? In order to fulfil the vision of Industry 4.0, you must be able to answer yes to this question. The act of turning data into a business insight shouldn't be a project or investment, it should be business as usual.

With all of this in mind, we can now refer back to the issue I highlighted in the first paragraph. What floods the market and headlines today are technology solutions to solve a single problem or set of problems, which despite what newcomers to the industry believe, really isn't ground-breaking. What businesses need to truly make this decade different to the last one is technology to solve many problems; repeatedly, and in a timely manner.