[SAMPLE] Competitive Intelligence Data for Manufacturing & Industrial Companies

We help our clients to draw connections between companies and facilities, map markets and supply chains and uncover and visualize hidden relations between companies.

Given a specific U.S. or Europe-based company, we draw a connections map, including all detected relationships between that company and other companies and facilities nationwide, statewide, and between countries.

Markets we can address

We can identify and detect connections between facilities and companies across the United States, and across countries and within them in Europe.

What makes us different?

We have developed a brand-new technology that combines the use of alternative data and machine learning methodologies, what allows us to perform competitive analysis in a non-traditional way, by studying a specific facility and detecting and drawing all the connections between the facility and other locations. We use publicly available information such as location data and building footprints to identify and geolocate company facilities.
With a machine learning algorithm, we identify movement patterns between these locations.

Already Validated Use Cases

- Market Intelligence & Due Diligence

Company: A large multinational company that provides specialized materials to different industries.

Challenge: How to find a cost-effective way to analyze the competition and identify potential customers?

Solution: Relationship data with a geolocation approach to unveil the DNA of a facility.

Results: Identify competitors' clients and suppliers.

- Risk Assessment

Company: A leading data analytics provider serving customers in insurance, energy and specialized markets, and financial services.

Challenge: How to anticipate and prevent possible disruptions in all the tiers of the supply chain?

Solution: Inter-company data with a geolocation approach to detect and measure relations between companies and facilities in the US. Using the movements of physical goods between different companies and locations, the supply chains can be inferred and analyzed.

Results: Anticipate potential disruptions by understanding behavior in all the tiers of the supply chain.

- Asset Protection & Loss Prevention

Company: A large multinational corporation in the industrial and logistics sector.

Challenge: How to optimize the asset recovery strategy in a network of more than 1 million locations nationwide?

Solution: A machine learning model that combines client´s own data and a geolocation approach to track assets´ movements between facilities.

Results: Improvement in the identification of facilities where the presence of assets to be recovered is higher.

Other Use Cases

- Monitor company supply chains (paired with import-export data if additive).
- Provide a proxy for manufacturing/production (e.g., monitoring activity from factories to warehouses).

我们协助客户梳理企业与设施间的关联、绘制市场与供应链（supply chain）全景图，并挖掘并可视化企业间的隐性关联关系。

针对指定的美国或欧洲本土注册企业，我们可绘制关联图谱，涵盖该企业与全美、全州范围内及跨国界的其他企业和设施之间的所有已识别关联。

我们可服务的市场范围
我们能够识别全美范围内的设施与企业间的关联，以及欧洲境内跨国及区域内的企业与设施关联。

核心差异化优势
我们研发了一项全新技术，融合另类数据（alternative data）与机器学习（machine learning）方法，可通过研究特定设施，挖掘并搭建该设施与其他场所间的全部关联，从而以非传统方式开展竞争分析。我们依托公开可用的位置数据、建筑轮廓数据（building footprints）识别企业设施，并完成地理定位（geolocation）。我们借助机器学习算法，识别这些场所间的实体流动模式。

已验证的落地应用场景
- 市场情报与尽职调查
合作企业：某家为多行业提供特种材料的大型跨国企业
业务挑战：如何以高性价比的方式开展竞争分析并挖掘潜在客户？
解决方案：采用关联数据结合地理定位方法，解析设施的运营基因。
应用成果：成功识别出竞争对手的客户与供应商。

- 风险评估
合作企业：某家面向保险、能源、专业市场及金融服务领域客户的头部数据分析提供商
业务挑战：如何预判并防范供应链全层级可能出现的中断风险？
解决方案：采用企业间关联数据结合地理定位方法，识别并量化美国境内企业与设施间的关联关系。通过分析不同企业与场所间的实体货物流动情况，可推导并剖析供应链结构。
应用成果：通过洞悉供应链全层级的运作规律，提前预判潜在中断风险。

- 资产保护与损失防控
合作企业：某家深耕工业与物流领域的大型跨国企业
业务挑战：如何在全美超100万个场所组成的网络中优化资产回收策略？
解决方案：搭建融合客户自有数据与地理定位方法的机器学习模型，追踪资产在各设施间的流动轨迹。
应用成果：显著提升了待回收资产富集设施的识别准确率。

其他应用场景
- 监控企业供应链（如需增强分析效果，可搭配进出口数据使用）
- 为制造业生产活动提供替代观测指标（例如，监控从工厂到仓库的物流活动）