Dataset opportunity
Goodlogisticsgroup — Mobility Event Dataset Opportunity
Moderate mobility event dataset held by Goodlogisticsgroup, usable for Forecasting and Anomaly Detection.
Score
63.3
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
49%
Action
Partnership (group-level)
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market size (indicative estimate)
Global supply chain analytics market size was valued at USD 11.0 Billion in 2025 and is projected to reach USD 41.2 Billion by 2034, exhibiting a CAGR of 15.85%.
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Profile
Dataset profile
Type
Mobility Event Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify
Buyer persona
Quant funds & demand-forecasting AI teams
Goodlogisticsgroup holds a Mobility Event Dataset structured as a Time Series, compiled from business_records, real-time event_streams, and geo_data. This provides a granular, sequential view of multimodal shipment movements, making it highly suitable for AI-driven Forecasting models to predict transit times, resolve delays, and optimize demand planning.
The global supply chain analytics market was valued at USD 11.0 Billion in 2025 and is projected to reach USD 41.2 Billion by 2034, exhibiting a CAGR of 15.85%. [2] Despite access complexities—including multi-level approvals under the Denholm group, shared data ownership, and regulatory compliance—the rarity and richness of this data, currently locked in legacy systems, offer a significant competitive advantage for a buyer willing to navigate the diligence process. ⚠ Diligence (valuable data, access to negotiate): Subsidiary of a large private group (Denholm) requiring multi-level approval; Data ownership is shared between shippers, carriers, and the logistics provider; Customs and trade data is subject to strict regulatory compliance and confidentiality; Significant volume of data is locked in legacy freight management systems · corporate: subsidiary of Denholm Group.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Goodlogisticsgroup owns a proprietary, multi-modal logistics intelligence asset, combining real-time shipment tracking with deep historical context on customs and route performance. This unique dataset is ideal for quant funds and corporate AI teams building predictive models to forecast supply chain disruptions and commodity flows. In a global supply chain analytics market projected to reach USD 41.2 Billion by 2034, this data offers a significant forecasting edge.
See dimension details ↓- Dataset Specificity78
dominant 'event_streams', sector mobility, 2 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity70
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
fit for Forecasting
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
AI buyer demand is exceptionally high, driven by the fast-growing supply chain analytics market (CAGR 15.85%), where granular time-series data is critical for building valuable predictive forecasting models. [2]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
restricted/unknown
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
high difficulty, subsidiary of Denholm Group
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 evidence types, 3 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
ownership=mixed, licensing=rights_unclear
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence50
subsidiary of Denholm Group
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0 data-appetite signals (0 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high — proprietary data beyond what's already monetised
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit92
✓ good target — This is a real, long-standing logistics and freight forwarding company with physical operations, making it a good potential source of proprietary, dormant operational data. Issues: The company was acquired by the Denholm Group in 2021 and merged with Denholm Global Logistics in 2024 to form 'Denholm Good Logistics'. [5, 8]; It is now part of a larger group, which may complicate decision-making, although it appears to operate as a distinct entity. [5, 9]; The prompt's mention of a 'Mobility Event Dataset' is not found on the company's website; their business is providing logistics services, not selling data. [8,
- Deep Qualification80
✓ pass — The target is a 3PL/4PL logistics service provider, making it a data_holder of a plausible Mobility Event Dataset generated as a by-product of its core operations. However, data ownership is inherently mixed in logistics, and licensing rights for resale are not specified in public documents, requiring direct negotiation.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Event streams
This evidence type is a continuous time-series stream providing real-time visibility into global shipments, essential for models that predict transit times and disruptions.
business_records
This evidence confirms the existence of structured business records, including customs entries and commodity codes, which are critical for forecasting international trade flows and economic activity.
Geospatial data
This evidence points to a rich historical dataset detailing route efficiencies and logistics performance, enabling the training of AI models to optimize multi-modal transit strategies.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
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Deliverable
Premium dataset report
Goodlogisticsgroup Mobility Event — a Moderate mobility event dataset (Time Series modality) in the mobility domain. Primary AI use-case: Forecasting. Market signal: Global supply chain analytics market size was valued at USD 11.0 Billion in 2025 and is projected to reach USD 41.2 Billion by 2034, exhibiting a CAGR of 15.85% (source: IMARC Group). [2]. Investment score 63.3/100 (confidence 0.49). Recommended action: Partnership (group-level).
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