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HomeColumnsZEROCKHow to Achieve 80% Reduction in Information Search Time: A Manufacturing Industry Case Study
ZEROCK

How to Achieve 80% Reduction in Information Search Time: A Manufacturing Industry Case Study

Published2026-01-12Ryuta Hamamoto
Case StudyManufacturingInformation SearchOperational EfficiencyKnowledge ManagementAI AgentAI RobotAI Native

How to Achieve 80% Reduction in Information Search Time: A Manufacturing Industry Case Study. "Can it really make that big a difference?"

How to Achieve 80% Reduction in Information Search Time: A Manufacturing Industry Case Study
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How to Achieve 80% Reduction in Information Search Time: A Manufacturing Industry Case Study

Hamamoto, TIMEWELL. Today I want to share the story of Company A — a manufacturer we supported through a ZEROCK deployment.

"Can it really make that big a difference?"

I've been asked this many times. Search time cut by 80%. Work that took 30 minutes now done in 10 seconds. Hearing those numbers, skepticism is a natural reaction.

But this isn't exaggeration. Through the Company A deployment and others like it, we've confirmed these outcomes repeatedly. This article tells the concrete story: what challenges Company A was dealing with, how they approached the deployment, and what changed — in full detail.

Chapter 1: Fifty Years of History, a Labyrinth of Information

Company Overview and Background

Company A is a precision parts manufacturer with approximately 800 employees. With over 50 years of history, their technical capability is well-regarded in the industry. But that long history brought more than technical expertise.

It also brought an enormous accumulation of documents, a complex folder structure, and the situation where "nobody knows where that information lives."

IT department head Tanaka (name changed) describes the situation: "If you wanted to look into a particular product, the first problem was figuring out which system to check. Engineering drawings were in the PDM system. Manufacturing process records were in the ERP. Quality management data was in a proprietary database. Sales materials were on the file server. And individual employees had enormous quantities of files saved on their local PCs too. Check the PDM, check the ERP, search the file server, and finally email the person responsible to ask. That was the daily routine."

The Problem in Numbers

Before considering ZEROCK, Company A started by quantifying the current situation — a company-wide survey combined with time-and-motion studies in selected departments.

The numbers that emerged were striking.

Metric Value
Daily information search time (technical dept.) Average 1 hour 15 minutes
Annual search time per person 300 hours (approx. 37.5 working days)
Company-wide annual total (800 staff) 240,000 hours (30,000 person-days)
Document management systems in use 7
Daily search time for new employees 2+ hours

Table 1: Company A — Information Search Current-State Survey Results

30,000 person-days per year consumed by the act of "searching." That's the equivalent of roughly 100 full-time employees. Recovering that capacity without adding a single headcount — that possibility was what moved Company A to act.

The Looming Generational Transition

Making the situation more urgent: workforce succession. Company A's founding-era veteran engineers were reaching retirement age in growing numbers, and knowledge inheritance had become an immediate concern.

"Veteran engineer Yamada (name changed) had spent 40 years here and knew everything there was to know about our products. But most of that knowledge lived only in Yamada-san's head. What would happen when Yamada-san retired? We felt real urgency about that."

Documentation efforts had been underway for some time — but when documents were created only to be lost in the system ("I don't know where I saved it," "Can't find it when I search"), those efforts went to waste.

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Chapter 2: The Decision to Deploy and the Approach

Comparing Multiple Tools

Company A evaluated multiple tools to address these challenges — conventional internal search engines, enterprise integrated search platforms, and next-generation AI-powered solutions.

The four evaluation criteria they weighted most heavily:

  1. Search accuracy: Can it answer natural-language questions accurately?
  2. Multi-source capability: Can it search across scattered systems?
  3. Ease of deployment: Can it be built and operated without specialized technical knowledge?
  4. Future-readiness: Can it keep pace with AI technology evolution?

In the end, ZEROCK was selected — evaluated for its high search accuracy through GraphRAG technology and the flexibility of its multi-LLM support.

Choosing to Start Small

Company A's choice for the deployment was not a company-wide simultaneous rollout, but a pilot department and a small start. We at TIMEWELL strongly recommended this approach.

The pilot department selected: Technical Support. Three reasons:

  • Responding to customer technical inquiries requires access to virtually all of the company's technical information — information retrieval challenges were most acute here
  • Inquiry response volume provided a clear KPI, making impact measurement straightforward
  • The department size of approximately 20 people was appropriate for a pilot

Chapter 3: The Deployment in Practice

Phase 1: Data Preparation (Month 1)

The first month of the pilot was spent on data preparation. Our TIMEWELL team worked alongside Company A's IT department to inventory potential data sources and establish priorities.

Data selected for inclusion:

  • Technical specifications (past 5 years)
  • Product manuals (all current products)
  • Past inquiry handling history (past 3 years, approx. 15,000 records)
  • Quality control reports (past 3 years)
  • Troubleshooting guides

The critical judgment in this process: what to include. Rather than loading all documents indiscriminately, we prioritized content with a high probability of being referenced in actual work. Excluding overly old information and policies that had since been superseded reduced noise and improved search accuracy.

Phase 2: Initial Build and Training (Month 2)

In parallel with data loading, training was conducted for the 20 Technical Support staff. The focus was on "scenarios for daily work" rather than feature explanations.

Rather than "ZEROCK supports hybrid vector and GraphRAG search," we showed concrete scenarios like this:

"When a customer calls saying 'Error code 001 appeared on Product X,' try asking ZEROCK: 'What causes error code 001 on Product X and how do I fix it?' It will surface a solution from past handling records and technical specifications."

This approach was dramatically more effective.

Phase 3: Adoption Support (Month 3)

For two weeks post-training, our Customer Success team provided near-onsite support — collecting feedback like "I asked but didn't get a good answer" or "this information isn't in the knowledge base" in real time and iterating on improvements.

That intensive early support was a major contributor to long-term adoption. When users have a "tried it, it didn't work" experience early on, their motivation to use the tool drops sharply. Building small wins in the early stage was the key to lasting adoption.

Chapter 4: Post-Deployment Results

80% Search Time Reduction Achieved

Effectiveness measured 3 months post-deployment: information search time in Technical Support dropped from an average of 1 hour 15 minutes to 15 minutes — an 80% reduction.

The most dramatic improvement: searching past cases. "Has this product had a similar error before?" — previously required searching multiple systems sequentially and manually assembling relevant cases. With ZEROCK, entering a natural-language question surfaces relevant past cases alongside a generated answer.

Metric Before After Improvement
Daily search time 75 min 15 min 80% reduction
Per-inquiry handling time 25 min 15 min 40% reduction
Daily inquiry response volume 12 18 50% increase
Customer satisfaction score 72 87 +15 points

Table 2: Quantified Deployment Impact Results

Breaking Knowledge Siloing

The second major result: breaking knowledge siloing. Technical Support had several "knows-everything" veteran employees — difficult inquiries flowed to them. With ZEROCK, new employees could produce answers at a consistent quality level, reducing the load on senior staff.

One veteran employee reflected: "Honestly, I was anxious at first that I'd become less relevant. But what actually happened was that I could focus on the complex technical judgments that only I could make — it actually increased my sense of purpose. I was freed from routine inquiry handling and could spend my time on work that was genuinely valuable."

Veteran Knowledge Inheritance

What mattered most: veteran employees' knowledge was being accumulated in the organization. As veterans answered AI queries during daily work and saved insights from their work into the knowledge base, tacit knowledge was converting into explicit knowledge.

Tanaka reflects: "Part of Yamada-san's knowledge is already inside ZEROCK. Even when Yamada-san retires, that knowledge stays in the organization. That's the most valuable thing."

Chapter 5: Company-Wide Rollout and Beyond

Scaling the Success

Following the pilot's success, Company A committed to company-wide deployment. The Technical Support success story was shared internally, department needs were gathered through interviews, and expansion proceeded in prioritized stages.

Engineering & Design, Manufacturing, and Sales deployed in sequence — one year after initial deployment, ZEROCK was fully operational across the entire organization. A post-rollout survey found an average 78% reduction in search time across the company. Annualized: approximately 180,000 hours (23,000 person-days) in recovered capacity.

Continuous Improvement

After company-wide rollout, improvement work continues. Monthly usage analysis identifies "frequently searched but not found" information, expanding the knowledge base accordingly.

Tanaka concludes: "ZEROCK wasn't a 'deploy it and you're done' tool. The more you use it, the more knowledge accumulates and the more accurate it gets. That's what makes us genuinely glad we deployed it."

Conclusion: Transformation Is Achievable

Company A's case demonstrates that knowledge management transformation is achievable. Fifty years of scattered information, retiring veterans, urgent succession pressure — with the right tool and the right approach, dramatic improvement is within reach.

What matters: not trying to do everything at once, but building success through a small start. Then spreading that success and continuing to improve. Company A's approach is the model.

At TIMEWELL, we've helped many organizations achieve this kind of transformation. The same outcomes are within reach for your organization. Start with a 14-day free trial to experience ZEROCK's impact firsthand.


References

[1] McKinsey Global Institute, "The social economy: Unlocking value and productivity through social technologies," 2012

[2] IDC, "The High Cost of Not Finding Information," 2023

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This article was produced with the help of AI. A human verified the primary sources and edited the text before publication.

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