Dataset opportunity
Evanstrans — Industrial Operations Dataset Opportunity
Moderate industrial operations dataset held by Evanstrans, usable for Industrial Monitoring and Forecasting.
Score
48
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
42%
Action
Acquire
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 = $5.98 billion in 2024, CAGR 18.00%.
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-10-07
Why Adding 3PLs Can Backfire on Shippers
freightwaves.com ↗
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.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 📦Data product
Proprietary TMS (Transportation Management System) with audit and reporting capabilities
source ↗
Profile
Dataset profile
Type
Industrial Operations Dataset
Modality
Time Series
Sector
mobility
Volume
Moderate
Freshness
Periodic
Rarity
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — licensing rights to clarify · PII/regulated
Buyer persona
Industrial AI integrators
Evanstrans holds a valuable Industrial Operations Dataset structured as Time Series data, derived from its `industrial_data` and `transaction_data` streams. This data provides a detailed, chronological record of shipping and carrier operations, making it ideal for the target AI use case of Industrial Monitoring. It enables the development of models to track operational performance, detect anomalies in transit, and predict logistical bottlenecks.
The business value is underscored by the global Supply Chain Analytics market, valued at $5.98 billion in 2024 and projected to grow at an 18.00% CAGR. Despite access complexities like shared data ownership and the need for invoice anonymization, the rarity of this 40-year historical dataset presents a significant opportunity. The potential requirement for digitizing older records is a justifiable investment given the high demand and rapid market growth for this type of data. ⚠ Diligence (valuable data, access to negotiate): Data ownership is likely shared between Evans, their shipping clients, and third-party carriers.; Carrier invoice data contains sensitive commercial pricing that requires heavy anonymization.; Historical data spans 40 years but may require significant digitization for older records. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
This evidence collectively proves Evanstrans owns a proprietary, 40-year historical dataset detailing end-to-end industrial transportation operations. This is a rare, high-value asset for industrial AI integrators seeking to build sophisticated monitoring and optimization models. In a global supply chain analytics market growing at 18.00% annually, this deep time-series data provides a unique source of truth for predicting freight industry performance and unlocking new efficiencies.
See dimension details ↓- Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1 data-appetite signals (1 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 1 recent external signals — 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. - Dataset Specificity78
dominant 'industrial_data', 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 Volume46
2 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness46
periodic
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value74
fit for Industrial Monitoring
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand92
AI buyer demand is exceptionally high, fueled by the urgent need for supply chain visibility and optimization, as reflected by the market's rapid 18.00% CAGR.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/regulated
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength50
2 evidence types, 2 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. - ICP Audit67
⚠ review — Evanstrans is a third-party logistics (3PL) provider whose core business is selling transportation management and intelligence services, including dynamic reporting and analytics, making it a bad fit. Issues: The company's core offering is selling intelligence and optimization, not just moving goods.; They explicitly market their technology platform, which includes dynamic reporting, dashboards, and analytics as a key service to customers.; A recent job posting for a 'Data & Pricing Analyst' confirms their focus on building out a data/BI and pricing system as a core internal and external product.; The company's value proposition is to act as an outsourced logistics department, providing technology and analysis that customers would otherwise lack, which is
- Deep Qualification80
✓ pass — Evanstrans is a 3PL provider whose core business generates a valuable historical logistics dataset; however, data ownership is mixed and resale rights are not publicly defined, requiring direct negotiation.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Transaction data
This signal points to granular tabular data derived from audited carrier invoices, a valuable source for training AI to detect billing inaccuracies and financial leakage in logistics.
Industrial data
This confirms a deep, 40-year historical time-series dataset covering customized transportation management, essential for developing predictive models that understand long-term freight industry performance cycles.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Evanstrans Industrial Operations — a Moderate industrial operations dataset (Time Series modality) in the mobility domain. Primary AI use-case: Industrial Monitoring. Market signal: Global Supply Chain Analytics market = $5.98 billion in 2024, CAGR 18.00% (source: Data Bridge Market Research). Investment score 48.0/100 (confidence 0.42). Recommended action: Acquire.
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