80% of knowledge is lost in industry: how can we capitalize on it day after day?

1. Tacit knowledge: invisible capital, very real value

As defined by Nonaka & Takeuchi (1995), tacit knowledge is knowledge rooted in personal experience, difficult to verbalize. It includes practical skills, professional intuition, learned-on-the-job gestures, tricks of the trade, reflexes forged by years in the field.

Let’s take the example of a maintenance operator in a food processing plant. He knows, by ear, when a motor starts to drift. He knows the correct tightening level for a specific nut without having to consult the tightening torque. This knowledge is not written down anywhere. Yet it canprevent a breakdown or non-conformity.

Why does it get lost?

• Retirements: according to INSEE, 30% of French industrial technicians will retire by 2030.
• Increased turnover: young technicians stay on the job for shorter periods, and don’t have the time to acquire and pass on skills.
• Under-investment in documentation: breaks and end-of-project times are rarely used to record what has been done, due to a lack of suitable tools.
• Lack of a culture of sharing: in some companies, knowledge is perceived as personal power, not as a common asset.
• Trades in short supply and shortage of personnel: demanding, multi-talented trades that no longer attract many people.
• Numerous informal exchanges: highly sensitive content is exchanged every day, without any traceability (phone calls, Whatsapp exchanges…).

2. The hidden cost of lost knowledge: 4 concrete impacts

Repeated errors and productivity at half-mast

When a breakdown is not immediately documented to extract usable knowledge, it’s a never-ending day: the team systematically starts from scratch. One pump manufacturer measured that 22% of breakdowns corresponded to cases already resolved in the past but never properly documented, atan avoidable cost of €120,000 per year. Beyond the direct cost, these repetitions create queues, delay priority interventions and degrade service indicators. Each incident that is not capitalized on increases the average resolution time, employee stress and the level of dissatisfaction.

Dependence on in-house experts

When technical memory is concentrated in a few people, the organization becomes fragile. At an automotive supplier based in Hauts-de-France, two senior technicians alone were responsible for 90% of non-conformities on the assembly line. When they were absent? Lines slowed down, quality plummeted, costs soared…

Holding back innovation

A company specializing in heating equipment was unable to industrialize a product innovation, because the R&D teams had no access to feedback from the field on actual use. The lack of a knowledge loop between “field” technical support and the design office was blocking continuous improvement.

Human impact

When skills are neither recognized nor shared, they erode or disappear. Experts are in constant demand, which generates stress and ends in disengagement. New recruits make slow progress, depending as they do on ad hoc mentoring rather than a clear frame of reference. Pressure mounts quickly when incidents occur. The social climate suffers, turnover rises and outplacement is extremely costly.

3. Why conventional solutions fail

The false comfort of shared files

Many companies think they secure their knowledge with Excel or Word files, sometimes stored in a Drive or SharePoint. But these documents are rarely consulted, difficult to update, and quickly become obsolete. The result: they exist, but are not used.

Referral overload

The few experts willing to invest in formalizing their knowledge often find themselves doing so on their own time, and without any real recognition. Their motivation erodes. And documentation remains fragmented, dense and unreadable for the uninitiated.

Lack of standardization

The same problem can be described ten different ways by different people. Without a common template or intelligent search engine, finding an existing solution becomes a headache.

A digital divide between the office and the field

Knowledge is born in the field, but capitalization tools are often designed in the office. This creates distance and disinterest. Technicians have neither the time nor the ergonomics to properly document what they do.

Wrong ticketing information

Due to lack of time, disinterest or poor experience of the ticketing tool, technicians archive indecipherable bits of sentences from their colleagues.

4. The operational key: streamlining exchanges and capturing frictional knowledge

Implicit knowledge is formulated during exchanges

A customer provides valuable information for all teams: marketing, sales, quality, engineering, after-sales service, etc. For their part,operational teams deploy their knowledge and collective intelligence to diagnose and resolve incidents. So it’s vital to streamline exchanges and mobilize knowledge at key moments.

Technologies help foster exchanges and document implicit knowledge

People who invest in a profession as demanding as technical support are generally passionate. They create value when they interact to diagnose, understand the root causes of a problem, seek solutions and implement them. It is therefore crucial to enable them to concentrate on these tasks, while capitalizing on the knowledge they acquire as operations progress. The latest technologies based on Artificial Intelligence (AI) can relieve these teams of tedious and often unusable drafting.

5. Three field tests and what they teach

Example 1: video assistance and automatic capitalization (energy)

A local photovoltaic panel supplier has implemented a mobile video-assistance solution coupled with an artificial intelligence engine. For each video call between a customer technician and a support team, the content is recorded, transcribed and analyzed. Effective solutions are automatically extracted and transformed into practical information sheets.

Within 6 months, the database already contained over 1,500 indexed cases, searchable by keyword and incident type. Average resolution time has fallen by 42%.

Example 2: WhatsApp + automated documentation (industrial maintenance)

A small maintenance company has connected its technical support to WhatsApp, which is naturally used by its technicians. Thanks to an intelligent API, each conversation is analyzed and summarized in the form of a mind map. This short format, validated by the supervisor, is directly integrated into a scalable database.

Result: 60% of recurring tickets resolved without human intervention, simply by consulting the knowledge base knowledge base.

Example 3: Tutorials from the agro-equipment sector

An agricultural cooperative has decided to film certain critical interventions (seed drill adjustment, sensor diagnostics). The videos are then edited into short tutorials, with chaptering, commentary and integration into a thematic database.

New technicians can refer to it on the move, via their smartphone. Result: training time saved by 35%, and greater autonomy for juniors.

Joint RETEX :

The value is not in “beautiful documentation”, but in contextual capture, standardized structuring and intelligent search.

6. What a useful, learning knowledge base looks like

• Friction-free documentation: no manual input required, but automatic knowledge extraction in real-life situations (video, chat, call).
• Intelligently structured: contextual search engine, incident typology, index by machine, by part, by symptom.
• Accessible to all: mobile first, multilingual if necessary, intuitive search, quick consultation.
• Evolutive: continuously enriched for each new case, far from fixed bases.
• Validated collectively: with a process of re-reading, updating and continuous improvement.

Conclusion: turning industrial memory into a strategic asset

It is urgent to consider technical knowledge not as an ephemeral flux, but as a strategic asset to be cultivated and valued. In the age of AI, what differentiates customer services is the ability to exchange quickly and efficiently between humans to resolve complex cases. Remote assistance, video, instant messaging and AI tools such as intelligent assistants today offer a unique opportunity: to transform every interventionintoactionableknowledge .

Provided that the right uses are identified, that adoption is simple and rapid, and above all that knowledge capitalization becomes a corporate culture.

In a world where machines are becoming more intelligent, it ‘s the ability to promote efficient exchanges, trace them, documentthem effortlessly, and make the extracted knowledge exploitable that will addvalueto human knowledge and make the real industrial difference.