Uluru Co., Ltd. to Host 'Public Procurement via Data' Webinar
Uluru Co., Ltd. will host a webinar explaining how to find low-competition bidding projects using historical data from its NJSS procurement information service, in cooperation with Majisemi Co., Ltd.
📋 Article Processing Timeline
- 📰 Published: May 21, 2026 at 18:00
- 🔍 Collected: May 21, 2026 at 09:31
- 🤖 AI Analyzed: May 21, 2026 at 10:20 (48 min after Collected)
Are you exhausted by participating only in highly competitive projects?
The timing of new public tender announcements is unpredictable, and your approach to finding information can change the outcome. Many companies concentrate on projects from well-known institutions, leading to extremely high competition for popular projects. Conversely, for projects with fewer participants, the probability of winning increases significantly. Nevertheless, many companies continue to exhaust themselves, losing out to unseen competitors. Simply increasing the number of attempts is futile if you only participate in projects with high competition, as this fails to build both profits and a track record.
Characteristics of low-competition projects visible through data
In reality, there are a certain number of 'niche projects' in the bidding market with extremely few participants. In fact, cases exist where such projects attract almost no competition, and a company can win by being the sole participant. These niche opportunities share common characteristics that become visible through analysis of historical bidding data.
How to narrow down winning projects using historical data
In this seminar, based on the rich historical bidding data held by the procurement information service 'NJSS', we will demonstrate how to find projects with lower competition levels while showing actual screens. We will explain how to uncover 'low-competition projects' by reading historical bidding data from three perspectives: how to choose ordering institutions, how to decide on estimated amounts, and how to approach project searches.
Organizer: Uluru Co., Ltd.
Cooperation: Majisemi Co., Ltd.
The timing of new public tender announcements is unpredictable, and your approach to finding information can change the outcome. Many companies concentrate on projects from well-known institutions, leading to extremely high competition for popular projects. Conversely, for projects with fewer participants, the probability of winning increases significantly. Nevertheless, many companies continue to exhaust themselves, losing out to unseen competitors. Simply increasing the number of attempts is futile if you only participate in projects with high competition, as this fails to build both profits and a track record.
Characteristics of low-competition projects visible through data
In reality, there are a certain number of 'niche projects' in the bidding market with extremely few participants. In fact, cases exist where such projects attract almost no competition, and a company can win by being the sole participant. These niche opportunities share common characteristics that become visible through analysis of historical bidding data.
How to narrow down winning projects using historical data
In this seminar, based on the rich historical bidding data held by the procurement information service 'NJSS', we will demonstrate how to find projects with lower competition levels while showing actual screens. We will explain how to uncover 'low-competition projects' by reading historical bidding data from three perspectives: how to choose ordering institutions, how to decide on estimated amounts, and how to approach project searches.
Organizer: Uluru Co., Ltd.
Cooperation: Majisemi Co., Ltd.
FAQ
How can I avoid getting exhausted in public bidding?
Use historical data like NJSS to focus on niche projects with lower competition, allowing you to improve your win rate and reduce inefficient bidding.
Why is public bidding highly competitive?
Because many companies flock to well-known government agency projects, leading to skewed information and extremely high competition rates.
What changes with data analysis?
Instead of relying on intuition, you can objectively judge competition trends from historical data and focus on projects with higher chances of success.