Have you ever tried playing billiards on a boat? No? Well, let me paint you a picture. Imagine setting up a perfect shot, lining up the cue stick, taking aim… and just as you strike, a wave rolls in. The table tilts, the balls scatter in unpredictable directions, and your carefully planned shot becomes a chaotic mess.
That’s exactly what managing processes without data feels like.
Companies Want to Optimize Processes—But Are They Set Up for Success?
Every company wants to optimize its processes. It makes sense—you want to be efficient, save money, and deliver products on time. But here’s the catch: You can’t optimize what you don’t understand. And if your data is scattered across disconnected systems, trying to optimize processes is no different from playing billiards on that unstable boat.
So, what are the top three things you actually need to get it right?
1. Product Data (What You Build and Sell)
Your product data is your foundation. It includes everything about what you’re making—CAD models, BOMs, revisions, configurations, and documentation. If this data is disorganized, incomplete, or outdated, your process is already sinking before it even sets sail.
2. Dependencies (Contractors and Suppliers)
No company operates in isolation. You rely on suppliers, manufacturers, and contractors to build your product. But where is that information stored? If supplier details, component availability, and vendor relationships are locked away in different systems (or worse, Excel sheets floating around in email attachments), your ability to manage dependencies is weak at best.
3. Prices and Schedules (How to Plan)
You need to know how much things cost and when they will be available. This includes raw materials, outsourced work, lead times, and delivery schedules. Without accurate pricing and timeline data, your financial forecasts and production schedules are based on guesswork—like aiming at a moving billiard ball.
The Reality Check: Your Data is Scattered
Now, let’s be honest—most companies don’t have all three of these things neatly organized in one place. Instead, the data is trapped in various siloed systems:
- Engineering teams have their data in CAD and PDM + lot of spreadsheets.
- Procurement works from supplier portals, spreadsheets and some ERP systems too.
- Manufacturing relies on spreadsheets, emails, and whatever MES like system happens to be in use that day.
So when someone tries to optimize a process, they’re forced to jump between systems, manually reconcile information, and make assumptions based on incomplete data. And that’s exactly why things fall apart.
What is my conclusion?
If you want to have a great future you have to think about it in the present, because when the future’s here you won’t have the time. Same with processes – if you want to optimize processes without the chaos, the solution isn’t to just “improve the process”—you need to fix the data first. This is where you should go first.
- Make sure your product data is organized, connected and accessible.
- Establish a clear link between your design, engineering data, supply chain, and pricing information.
- Stop relying on spreadsheets and disconnected datasets—organize systems that can connect data and bring all the information together.
When your data is structured, reliable, and connected, optimizing processes becomes a whole different game. It’s like playing billiards on solid ground—you can actually plan your shots, predict outcomes, and win. And… most importantly, you can do it in a repeatable way many times.
So, before you invest time and resources into optimizing your operations, ask yourself: Am I playing billiards on a boat? If your data is shaky, it’s time to fix that first.
Just my thoughts…
Best, Oleg
Disclaimer: I’m the co-founder and CEO of OpenBOM, a digital-thread platform providing Collaborative Workspace with PDM, PLM, and ERP capabilities. With extensive experience in federated CAD-PDM and PLM architecture, I’m advocates for agile, open product models and cloud technologies in manufacturing. My opinion can be unintentionally biased.
