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August 27, 2025 · The Bloomfield Team

How to Get Engineers to Actually Document What They Know

Ask any manufacturing engineer whether documentation is important and they will say yes. Ask them how often they update the documentation and the answer changes. A 2024 survey by the Society of Manufacturing Engineers found that 82% of manufacturing engineers consider knowledge documentation a priority, and 67% said they update their documentation less than once per quarter. The gap between knowing it matters and actually doing it is the problem.

The standard management response is to make documentation mandatory. Add it to the job description. Include it in performance reviews. Set up a SharePoint site and a folder structure. Hold a training session on how to use the template. Three months later, the SharePoint has 14 documents in it, 9 of which are copies of the template.

Engineers do not resist documentation because they are lazy or disorganized. They resist it because every documentation system they have been asked to use treats documentation as a separate activity from the work. Open a new application. Switch context. Write in a format designed for an audience they cannot see. File it in a folder nobody checks. The work itself is demanding enough. Adding a disconnected writing task to the end of every project is the kind of overhead that gets deprioritized every time something more urgent appears.

The Real Barrier Is Context Switching

An engineer solves a problem during a product development cycle. They figure out that a specific machining sequence produces better results on a thin-wall Inconel component because the order of operations manages thermal distortion in a way the standard sequence does not. This insight is extremely valuable. It will save the next person who encounters a similar geometry days of trial and error.

Documenting it in the current system means opening a Word document, writing a coherent explanation, adding enough context for someone who was not in the room, saving it to the right folder, and notifying anyone who might need it. That process takes 20 to 30 minutes. The engineer has three other tasks waiting. The documentation does not happen.

The insight lives in their head until they retire, leave, or forget. This is how documentation differs from usable knowledge. The documentation system exists. The knowledge never enters it.

Three Principles That Change the Outcome

Capture at the point of work. The engineer should be able to record the insight within 60 seconds, at the moment they have it, in the tool they are already using. A two-minute voice note attached to the job record. A structured form that takes three fields to complete. A prompt that appears when a job closes, asking "What would you tell the next person who runs this?" The capture mechanism must be faster than the alternative, which is forgetting.

Connect the knowledge to the context. A standalone document about Inconel machining sequences has limited value because the person who needs it has to know it exists and know where to find it. The same knowledge attached to the specific part number, material, machine, and operation surfaces automatically when someone encounters a similar situation. Context connection turns documentation from a filing exercise into a retrieval system. This is how a machinist notebook becomes a knowledge system.

Show them their knowledge being used. The single most effective motivator for engineers to document is seeing their input help someone else. When a process engineer records an insight about a fixture design and two months later a colleague references that exact record to solve a setup problem, the value of documentation becomes tangible. Build a feedback loop where the engineer who contributed the knowledge gets notified when it is accessed. This is not a reward system. It is a proof-of-value signal that reinforces the behavior.

What This Looks Like in Practice

A precision machining shop with 12 engineers implemented a knowledge capture system with a simple interface: at the end of each significant job or problem-solving event, the engineer gets a prompt with four fields. What did you do. Why did you choose that approach. What would you do differently. What should the next person know. The record attaches automatically to the job number, customer, part family, and machine.

In the first month, participation was 38%. By month three, after engineers started seeing their inputs surface during other people's jobs, participation climbed to 74%. By month six, the system contained 340 knowledge records covering machining approaches, material behavior, tooling selections, and customer-specific requirements that had previously existed only in individual heads.

The engineering manager estimated that the knowledge base was preventing two to three quality issues per month and reducing setup time on repeat jobs by an average of 25 minutes per setup. At their volume, that translated to roughly $180,000 in annual value from a system that required an average of 4 minutes per day from each engineer.

For a complete look at how to build this capability, see our guide to manufacturing knowledge management.

The Management Mistake to Avoid

The temptation is to mandate volume. Require every engineer to submit a certain number of knowledge records per week. This produces garbage data quickly. Engineers who are forced to document will document the obvious, the trivial, and the already-known to meet the quota, while skipping the hard-won insights that actually matter because those take more effort to articulate.

Focus on quality, relevance, and timeliness. Make the capture frictionless. Make the retrieval automatic. Let the feedback loop do the motivational work. Engineers who see their peers benefiting from shared knowledge will contribute without being told to, because they are problem solvers by nature and a system that amplifies their problem-solving across the organization aligns with how they already think about the work.

The Compounding Effect

Every knowledge record an engineer creates makes the next similar job faster, more accurate, and less dependent on any single person's availability. A shop that captures 500 records per year builds, over three years, a knowledge base that represents 1,500 individual insights about their specific machines, materials, processes, customers, and common failure modes. No hire, no consultant, and no off-the-shelf system can replicate that asset. It is the accumulated intelligence of the people who do the work, preserved in a format that works for the people who will do the work next.