A lot of companies these days are working hard to turn their big digital archives into more intelligent data. These initiatives usually comes from some kind of digitalization strategy that has been formed to support a vision.
We see it every day, data is power, data can be analyzed, used in different contexts to support end customers, to sell new services or support internal processes in the company.
We see it every day, data is power, data can be analyzed, used in different contexts to support end customers, to sell new services or support internal processes in the company.
However, for this to happen it is not enough so simply store and manage data in digital format. The data must be “connected”, stored in object or information structures that represents the data used in different contexts. Coming from a PLM background, some of the aspects are quite easy to identify. From a product perspective you’ve got a requirements breakdown structure, maybe a model configuration or variant structure, an engineering bill of material that represents the design intent and supporting CAD structures from various design tools. All of the structures mentioned are being managed today as digital information, but very few companies have structured the information and put it all in context of the other information structures to achieve full traceability and change consequence control.
Note, I’ve so far only touched the product design aspect, so when considering the manufacturing intent (the manufacturing bill of material), the manufactured product, the sold product and the installed product the complexity grows, but so does the benefits of managing it all as connected data structures stored in context of each other. This data can be used to sell services to the end customers.
Examples could be a pump manufacturer who has full traceability on all pumps sold to different facilities. The pump manufacturer could offer services for maintenance of the pumps, and if the pump contains different sensors, the manufacturer could also analyze operational data to schedule preventive maintenance. This data could then serve as valuable input to the design processes of new and even better pumps. As a consequence of the fact that all data structures are connected, the pump manufacturer knows the location of all pumps sold, and can offer the new and improved model not only to all customers, but to all customers and all the locations for each customer.
All of a sudden we are touching one of the biggest fashion words these days “the Internet Of Things”, because what would happen if a large portion of the pumps were installed on ships and they contained sensors? The pump manufacturer could set up maintenance offices in large ports. Knowing exactly what pumps would arrive in what ports, at what times and what maintenance need they have would allow the manufacturer or service provider to order the right spare parts just in time and to reduce the maintenance time. This would minimize the risk of fines by the ship owners because the ship had to stay in port longer than scheduled or even worse, having the service personnel performing the service at sea and thereby leaving the service office in the port severely under manned.
This is only one example of the power of “connected data” or digitalization. Quite a few companies have similar business models as our pump manufacturer, but very few have the opportunity to utilize the services by “connected data”. Instead there are a lot of manual work, interpretation and searching for data in different digital archives. This in turn leads to errors, misunderstandings and lost business opportunities.
Some points to ponder
Bjorn Fidjeland
All images used in this post are purchased at dreamstime.com
Note, I’ve so far only touched the product design aspect, so when considering the manufacturing intent (the manufacturing bill of material), the manufactured product, the sold product and the installed product the complexity grows, but so does the benefits of managing it all as connected data structures stored in context of each other. This data can be used to sell services to the end customers.
Examples could be a pump manufacturer who has full traceability on all pumps sold to different facilities. The pump manufacturer could offer services for maintenance of the pumps, and if the pump contains different sensors, the manufacturer could also analyze operational data to schedule preventive maintenance. This data could then serve as valuable input to the design processes of new and even better pumps. As a consequence of the fact that all data structures are connected, the pump manufacturer knows the location of all pumps sold, and can offer the new and improved model not only to all customers, but to all customers and all the locations for each customer.
All of a sudden we are touching one of the biggest fashion words these days “the Internet Of Things”, because what would happen if a large portion of the pumps were installed on ships and they contained sensors? The pump manufacturer could set up maintenance offices in large ports. Knowing exactly what pumps would arrive in what ports, at what times and what maintenance need they have would allow the manufacturer or service provider to order the right spare parts just in time and to reduce the maintenance time. This would minimize the risk of fines by the ship owners because the ship had to stay in port longer than scheduled or even worse, having the service personnel performing the service at sea and thereby leaving the service office in the port severely under manned.
This is only one example of the power of “connected data” or digitalization. Quite a few companies have similar business models as our pump manufacturer, but very few have the opportunity to utilize the services by “connected data”. Instead there are a lot of manual work, interpretation and searching for data in different digital archives. This in turn leads to errors, misunderstandings and lost business opportunities.
Some points to ponder
Bjorn Fidjeland
All images used in this post are purchased at dreamstime.com
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