Solving the data dilemma or how to extract more value from PLM?

Solving the data dilemma or how to extract more value from PLM?

I’m getting ready for PLMx in Chicago just in few weeks. Haven’t heard about PLMx? There is still time to meet me in Chicago. I took part of my session topic as a title and a question for today’s blog. So, how to extract more value from PLM?

For starters, let’s talk about PLM value? The old joke in PLM community says that it is easier to implement PLM then explain the value of PLM. There is something into this statement. PLM is  a team journey. A journey of organization towards changes, transformation and optimization. Therefore, the value of PLM is different depends on whom you ask about it. For engineering, it can be automation of lifecycle process. For manufacturing it can be a collaboration with engineering and for procurement lower cost of BOM. For c-level execs it is control and and how to put everyone of the same page in the organization. Therefore the most common value of PLM sold to all manufacturing organization is so called single version of truth.

And therefore, when I think about extracting more value from PLM, I’m actually thinking about how to improve data management. This is very generic statement. For IT, improvement in data management means lower cost databases and improvement in DB maintenance. In the past a very traditional way to think about PLM and data management was thinking about “data control”. If PLM system is controlling data, then we can insure that everyone is getting an appropriate access to the information.

Manufacturing company view on data assets is changing these days. From being a “controllable asset”, data is very fast becoming source of strategic intelligence and insight. Such transformation can actually change the role of organization creating and managing these data assets. In my earlier article, I covered the power of networks and how it can be realized in the future of PLM.

How to turn data into intelligent information asset? Let me talk about solving the data dilemma. Data is growing. The amount of data is skyrocketing. Even smallest organization today is running towards processing of their data assets and extracting value out of it in the way of analytics, machine learning and connecting silos. And this is exactly what data networks supposed to do.

The challenge from an enterprise perspective is coming from the ability to efficiently manage and control multiple islands of data. Simply keeping track of all these data islands doesn’t solve the problem. The data in the enterprise is meaningfully connected and can be delivered to everybody in the way of intelligent platform, which PLM has a chance to become one day.

I’m saying, has a chance, because PLM is not the only platform who is planning to take care of these challenges and opportunities. The simplest step in the future intelligent data networks is to capture communication and data transfers that often represented by a flow of Excel files departments and individuals are sending. After the initial step is done, more advanced algorithms can be brought to process and analyze the data.

The dream of everyone in the organization is to have one integrated view of everything, through one pane of glass, to manage their enterprise silos and ecosystem as simply as possible. New data management can go a long way towards helping manufacturing to unlock the future value of data. IT trams would have full visibility into what is going on every single axis of data management and focusing on how to maximize the value of data that being collected and analyzed in enterprise organization.

What is my conclusion? Can PLM infrastructure to deliver the next generation of data management? This is a question we all have to answer. During my last week blogging I asked the question of what PLM vendors are selling these days – (1) low total cost of ownership and (2) short time to value. I didn’t find an agreement about it. A combination of everything, but it brings many question how to extract value of data by using new generation of data management platforms. Data brings more data and more value, but extracting of these values aren’t simple process. Just my thoughts…

Best, Oleg

Disclaimer: I’m co-founder and CEO of OpenBOM developing cloud based bill of materials and inventory management tool for manufacturing companies, hardware startups and supply chain. My opinion can be unintentionally biased


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