I had a chance to visit The Art of Brick exhibition in Boston’s Faneuil Hall Museum few days ago. If you following me on social media websites, there is a chance you noticed few pictures. Afterwards, I read more about LEGO artist Nathan Sawaya. What impressed me is a power of “simple LEGO brick”. A simple plastic brick and huge amount of imagination is allowing to create such an incredible models.
You can ask me – how is that connected to engineering, manufacturing and product lifecycle management? Here is the thing… It made me think about ways PLM systems are implemented these days. I’m sure you are familiar with the “best practices” approach. The topic isn’t new. I found my old post - PLM best practices torpedo. After five years, I still like my conclusion – PLM best practices are good to show what PLM technology and software are capable to do. However, for real implementation, it is not very useful. You have to come back to a “simple bricks” of PLM technology – data models, documents, lifecycle statuses, bill of materials, processes.
I captured a bit different perspective about PLM best practices. Navigate to PLM cultural change blog – PLM design patterns. It took me back into thinking about best practices. How to define implementation patterns and make a real PLM implementation much easier? The article speaks about general way of PLM implementation can be done, organizational transformation and change. Read the article. I found the following few passages interesting:
In general you can setup all required supporting procedures in using the PLM design patterns. Even for specific supporting procedures of a business process pattern like Engineer to Order (ETO) you can derive patterns, which consists of a framework of general PLM design patterns and are adapted to the specific business needs. There is enough freedom to derive based on these patterns supporting procedures to fulfill specific business needs.
If some organizations would have implemented supporting procedures based on patterns already, then consultants in introducing PLM to an organization could refer to “state of the art” implementation examples of these organizations. The target is to convince an organization, that the decision for a new practice requesting organizational change is required and works. Only then the organization can enable the full potential of the PLM methodology without remaining stuck in the current practice.
Instead of inventing a Ping-Pong table “from scratch” with a cabinetmaker we can make a clear decision based on all the options available, fulfilling and probably exceeding our originally perceived needs (with a safe and easy-to-use folding mechanism). And we can afford it, because a stock table is cheaper than a custom built one.
The time saved in avoiding the endless discussions and continual redesign of processes because of paradigm paralysis, based on current methods, could be better used in a well-planned, strategic deployment of the new processes leading to an improved business solution.
The idea and vision of configurable patterns and best practice is interesting. In my view, it was invented earlier as PLM toolkits, flexible data models and process templates. The key problem here is not related to technology- software does what it does. The problem is related to people and organization. Remember, technology is simple, but people are really hard. What called “to convince people” is actually a process that takes organization and people to understand their business and product development patterns. Without that understanding the chances of successful PLM implementation are very low and probability of PLM project failure is high.
So, what could be 21st century solution for that problem?
My attention today caught by a new startup – The Grid. The tagline states – AI websites that design themselves. The vision of The Grid is to change the paradigm of website building. The idea of self-building websites driven by artificial intelligence and data analysis is something worth to think about. Watch the video.
Now let me back to manufacturing companies and PLM implementations. All manufacturing organizations are different. The approach most of PLM vendors are taking these days is to classify companies by size (small, medium, large), industry (aero, auto, industrial equipment, etc), manufacturing model (mass production, configured to order, engineering to order, etc.) and many others such as locations, supply chain, existing enterprise systems (ERP, SCM, etc.). The decision matrix is huge. To make analysis of existing manufacturing company, processes, existing systems, requirements – this is what takes time and money during PLM implementation.
What is my conclusion? The opportunity we have today is coming from new way to process data. Call it cloud computing, big data, whatever. Facebook is reporting about a capability to index trillion posts. Would it be possible to capture data from an existing manufacturing company and ask PLM system to build itself? Is it a dream or a future of PLM? Just my thoughts…