Structuring Data for Reuse and Establishing Repeatable Processes
Look at the diagram below, a generic data structure that highlights that part and product data are comprised of numerous components.
What’s not shown are the ongoing changes that occur. Parts change along with associated documentation, specifications, calculations, and so on. Hence, there are revisions and rolled up versions. In reality, this should be a three-dimensional image that reflects changes over time.
Now think about your company’s environment. We would bet donuts-to-dollars that most data components are stored in file folders, spreadsheets, Access databases, emails and even sticky notes. Part number, project, or some other tribal conventions known to a handful of folks in the shop miraculously connect them. So, HOW IN THE WORLD DO YOU MANAGE THE DATA?
You assign staff to walk through the quoting process (you know who you are!). Those individuals are the workflow process… it’s like pushing a shopping cart around the office. You have folks dedicated to tracking customer orders. Or, you don’t worry about until it comes to shipping and know that the delivery team will pull it all together. These are mitigating efforts and typically reactionary processes.
It begs the questions … without hiring more people, can you turn around quotes faster, get to a 100% accurate bill sooner, reduce scrap and rework, or continue to meet customer delivery commitments?
As you can probably sense, this is fundamentally not sustainable, especially if you want to double the size of the business. It’s simply not scalable.
If your company already has a PLM system, then something is not working. As Peter Schroer, president of Aras mentioned in his PLM Underground blog earlier this year, these systems “were never deployed.”
If PLM is not in place, then that’s the significant opportunity. The ROI is often no more than a year. And, in the following years, the PLM investment returns multiples through shorter sales cycles that drive incremental revenues, reduced cost of goods and greater operating efficiencies.