The Cognitive Factory: It's Not About Technology
Dr. Martin Landherr, Director Industrial Services, Festool GmbH
Dr. Martin Landherr, Director Industrial Services, Festool GmbH
First, the level to which we will automate decisions is difficult to predict. Most examples I see in production nowadays are automating easy and repetitive tasks like the mapping between available capacity and the predefined production plan using an Excel file that grew over the last years or even decades. But as soon as there is any short-term deviation from this plan, there is always a strong involvement of humans in the process of deciding for a reaction. That is the reason that makes the reaction slow. To accelerate these reactions, we will see that these Excel files will continue to grow. But will there be a point at which you hand over the whole production planning and control including the decision-making sovereignty to any possible deviation to a machine, to software using learning algorithms? I think we will discover something in between but I try to be prepared for this artificial intelligence utopia.
Second, the world and the technology at hand is changing at an unprecedented speed. That makes it hard to predict what is coming up next and even impossible to say when it comes. So, what is the “Digital Transformation” if it is not possible to see the end. Consequently, it is no transformation we need to master. It is a transformation that will never end. Thus, we must adapt to a new way of working, innovating and living for an unknown future in an accelerating transition. Here are some aspects to think about and discuss:
For me, learning is the key principle for this VUCA world. On the one hand, the competencies we need now are very rare. For example, the whole discussion about the interface between IT and OT shows that there are several challenges without a solution yet. Or in the context of the hype topic of artificial intelligence in production, two worlds collide, where no wellestablished course or training is covering both disciplines. Additionally, these mandatory competencies will change in a way, I am not able to predict. And now imagine an organization that never makes a mistake twice (what is far away from reality). As a basis, we need to recognize every mistake immediately. That will be more likely while raising the transparency using software in almost all areas of the organization. But we must put the focus on the characterization of patterns that certain mistakes describe to recognize them from the ocean of data, we can create in seconds. And we must get rid of hiding our own mistakes. That is a question of failure management and corporate culture. In the end, it is all about the people, being creative and flexible with the freedom they need to learn and evolve faster than ever before.
But what is even more important than learning and anything else in the world? Yes, it’s money. And digitization costs a lot of money, where we can see the revenue very late. I am not talking about the pilots and prototypes of I4.0- projects. I am talking about implementing a Manufacturing Execution System or closing the gap between master data from the development department (PDM) and sales (ERP/ CRM). How can you even measure the financial benefit of initiatives like these? What is the financial value of Microsoft Office or Google G Suite or whatever you use in your office? That is hard to calculate or even estimate. Thus, the top management needs to believe that it is crucial for future success to go the way of digitization. And we need new indicators for measuring the success of certain software implementations. For example, you could think about capturing the number of people, working on the same document when implementing a new collaboration platform. This is based on the belief that it is better to work on the same file instead of creating local copies. But what is the financial benefit of reducing the source of errors that come along with manually copied and integrated files?
I hope I could support you with my thoughts. If you face similar challenges, please feel free to contact me via LinkedIn for further discussion.
For me, learning is the key principle for this VUCA world. On the one hand, the competencies we need now are very rare. For example, the whole discussion about the interface between IT and OT shows that there are several challenges without a solution yet. Or in the context of the hype topic of artificial intelligence in production, two worlds collide, where no wellestablished course or training is covering both disciplines. Additionally, these mandatory competencies will change in a way, I am not able to predict. And now imagine an organization that never makes a mistake twice (what is far away from reality). As a basis, we need to recognize every mistake immediately. That will be more likely while raising the transparency using software in almost all areas of the organization. But we must put the focus on the characterization of patterns that certain mistakes describe to recognize them from the ocean of data, we can create in seconds. And we must get rid of hiding our own mistakes. That is a question of failure management and corporate culture. In the end, it is all about the people, being creative and flexible with the freedom they need to learn and evolve faster than ever before.
But what is even more important than learning and anything else in the world? Yes, it’s money. And digitization costs a lot of money, where we can see the revenue very late. I am not talking about the pilots and prototypes of I4.0- projects. I am talking about implementing a Manufacturing Execution System or closing the gap between master data from the development department (PDM) and sales (ERP/ CRM). How can you even measure the financial benefit of initiatives like these? What is the financial value of Microsoft Office or Google G Suite or whatever you use in your office? That is hard to calculate or even estimate. Thus, the top management needs to believe that it is crucial for future success to go the way of digitization. And we need new indicators for measuring the success of certain software implementations. For example, you could think about capturing the number of people, working on the same document when implementing a new collaboration platform. This is based on the belief that it is better to work on the same file instead of creating local copies. But what is the financial benefit of reducing the source of errors that come along with manually copied and integrated files?
I hope I could support you with my thoughts. If you face similar challenges, please feel free to contact me via LinkedIn for further discussion.
