Factory Digitalization_Ver02. _ “Why Factory Digitalization Progresses Slowly in Japan? - Four Reasons Why Factory Digitalization Stalls.”
- shigenoritanaka3
- 3月8日
- 読了時間: 2分
更新日：3月9日
Mar 08, 2026
Hello everyone,
Today, I'd like to share my insights from on-site support experience about why “factory digitalization” has been slow to advance in Japan's manufacturing sector. The main reasons can be summarized into the following four points:
1. Factories are not connected to the Internet
Many factories avoid internet connectivity due to concerns about cyberattacks or data leakage. This fear is understandable. One solution is to keep all data on local servers without internet access. However, this approach has several limitations:
Server capacity must be expanded continuously
IT maintenance requires additional headcount
Fixed costs increase over time
A more scalable approach is to use a secure third‑party cloud database. Factories can then focus on what to visualize and how to use the data, while encryption and gateway security can be outsourced to specialized IT vendors.
2. Visualization becomes the final goal instead of the starting point
Some factories succeed in visualizing their data but stop there. Visualization is not the goal — it is only the starting point.
Factories should revisit the original purpose of visualization. For example:
Improving traceability
Identifying reasons for defect increases
Understanding why production efficiency fluctuates
Visualization should always lead to better decisions, not just dashboards.
3. Data is not connected to management decisions
Digitalization creates value only when data is used to solve real problems, such as:
Causes of machine breakdown
Reasons for low throughput
Factors behind high scrap rates
When data supports these decisions, digitalization becomes a powerful driver of improvement.
4. Data accuracy is not questioned
Many factories assume that all data is correct. However, not all data comes from PLCs — some rely on manual input, which can be inaccurate.
For example: If an inspection is performed during the midnight shift, say at 2:00 AM on March 1st, for a product manufactured at 4:00 PM on February 28th, but the operator mistakenly enters “Mar 1st” instead of “Feb 28th” for manufacturing timestamp, the entire analysis becomes unreliable.
I will write a separate article focusing on data accuracy, as it is a critical but often overlooked topic.
So What?
Without linking data to decisions, digitalization remains only a tool—not a driver of improvement.
Conclusion
Factory digitalization is not about dashboards. It is about better management decisions.
If you are considering factory data visualization or struggling with persistent defect rates, feel free to reach out.
60-minute free initial consultation: info@metricjapan.com
We look forward to supporting your improvement journey.
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