A day in the life of an engineering company
A new customer RFQ arrives. A precision-machined component. STEP model and technical drawing attached. The customer gives eight weeks to manufacture the part — but only 2 or 3 days to decide whether you can.
The clock starts ticking. The engineering team has just a few hours to understand the part, assess manufacturability, estimate cost, identify technical risks, and prepare a competitive quote. Within minutes, engineering, sourcing, manufacturing and commercial teams begin asking questions: Can we manufacture this? Have we made something similar before? Which supplier should we use? Can we confidently commit to the delivery date? What should we quote?
None of these questions are unusual. In fact, most have probably been answered before. That’s the irony. Manufacturers don’t start from zero with every RFQ. They’ve accumulated decades of engineering knowledge through thousands of completed jobs. The real challenge isn’t understanding the drawing. It’s understanding everything your company already knows about that drawing.
What slows RFQ responses
Most people think RFQs slow down because engineers need technical clarification. That’s only half the story. Every RFQ triggers two very different sets of questions.
Engineering questions
These are visible: Can this tolerance be achieved? Is the drawing fully defined? Does the geometry require clarification? Which machining strategy should we use?
These questions often travel back and forth between the customer and the engineering team, costing valuable time. Every day spent waiting for answers is another day your competitors are moving closer to winning the business.
Business questions
Hidden and rarely documented: Have we manufactured something similar before? What did it cost? Did we win or lose that quote? Did we make money? Which fixture already exists? Did this geometry create quality issues? Can we confidently commit to eight weeks?
These aren’t engineering questions. They’re business decisions that depend on engineering knowledge and they determine whether the quote is profitable, competitive and worth pursuing. Unlike engineering questions, nobody usually knows the answers to business questions because information is scattered across enterprise systems, spreadsheets and emails.
Not being able to answer these questions quickly enough are symptoms of two deeper structural problems that affect every manufacturer I’ve worked with — what we call the Human Limit and the Systems Limit.
The Human Limit
Every factory has someone who ‘just knows’. When they’re on leave, in another meeting, or have left the company, that knowledge becomes surprisingly difficult to recover. They remember the difficult machining operation from three years ago, which supplier solved the problem, which tolerance caused unexpected scrap and why a similar quote was lost.
Experience is invaluable. But human memory doesn’t scale. No engineer can remember 3000 drawings, five years of quotations, hundreds of suppliers and thousands of production decisions. Larger the organisation, more valuable is experience — and harder it becomes to access it.
The System Limit
Enterprise systems have the opposite problem. They remember everything. ERP remembers costs, PLM remembers revisions, QMS remembers quality records, MES remembers production, CRM remembers customers. Yet none of them understand that today’s incoming RFQ might represent almost the same engineering problem as something manufactured five years ago under a completely different part number.
Enterprise systems are excellent at storing answers but are remarkably poor at connecting them.
Confidence — the foundation of every winning RFQ
The Human Limit and the System Limit led manufacturers to the same problem: a lack of confidence.
Every incoming RFQ requires manufacturers to make commitments — to customers, to suppliers and to themselves. Those commitments can be made confidently only when engineering knowledge and business intelligence come together.
In practice, every RFQ demands three kinds of confidence.
The confidence to build
Can we build this? Not just in theory but based on evidence from similar geometries, proven processes, and demonstrated manufacturing capability. This is where engineering experience matters.
The confidence to quote
Should we quote this — and at what price? The answer depends on much more than estimating cost. It requires understanding what similar jobs cost, whether they were profitable, what quality issues arose, and whether the business succeeded at that price. This is where engineering knowledge becomes business intelligence.
The confidence to commit
Can we deliver what we’re about to promise? The right supplier. Existing tooling. Proven process capability. Available capacity. Delivery commitment. Confidence comes from connecting what the organisation already knows — not from making assumptions under time pressure.
From engineering capability to engineering intelligence
High-mix, low-volume manufacturers compete on their ability to respond quickly and confidently. Yet many RFQs still depend on phone calls, spreadsheets, shared folders and the memories of experienced engineers. Not because companies lack capable people. Not because they lack enterprise systems. But because neither human memory nor enterprise software was designed to connect engineering experience across thousands of similar products.
This is where ShapeSense fits
ShapeSense doesn’t replace engineering judgment. It makes decades of engineering and commercial learning available at decision time. It connects similar geometries across CAD models, drawings and enterprise systems to surface manufacturing knowledge that already exists inside the business.
When an RFQ arrives, the objective isn’t simply to answer technical questions faster. It’s to make better decisions. Those decisions shouldn’t depend on who happens to remember. They should depend on everything the company has already learned.
The manufacturers that win more RFQs won’t necessarily be those with the biggest engineering teams. They’ll be the ones that continuously learn from every drawing, every quote, every supplier, production run, and quality issue — turning each new job into an advantage for the next.
In Part 2, we’ll look beneath the workflow to explore what it actually takes to build a system capable of supporting these three decisions — from geometric identity and deterministic retrieval to connecting engineering knowledge scattered across enterprise systems.