AI-Ready Unified Data & Analytics Platform for A North American Diversified Energy Distribution Company
Our Clients
Engagement Overview
Our client is a leading North American diversified energy distribution company, serving approximately one million residential, commercial, and industrial customers across the U.S. and Canada. With four brands, multiple ERPs, and a complex field footprint, they needed to move from siloed reporting to an AI-native operating model that could support smarter pricing, forecasting, and operations.
TechBlocks partnered with the client to design and implement an AI-ready Unified Data and Analytics Platform, along with the operating model around it. We unified data across ERP, CRM, IoT, and field systems into a governed Unified Data Hub, established an Enterprise Data Office, and delivered a suite of AI and analytics products that improved forecasting, routing, profitability, and customer intelligence across the portfolio.
Key Challenges
The organization was making critical decisions on top of fragmented data, inconsistent definitions, and manual processes. Forecasting, pricing, and route scheduling relied on spreadsheets and siloed reports.
At the same time, the client wanted to unlock AI use cases such as churn prediction and margin optimization, but lacked the data foundation, governance, and platform capabilities to support them at scale across four brands.
Fragmented Data & No Single Source of Truth
Enterprise data was spread across multiple systems, including SAP, CARGAS, Salesforce, IoT platforms, and mobile field tools. There was no unified, trusted view of customers, assets, or operations. This fragmentation made it difficult to answer basic questions about performance, risk, and opportunity across the business.
Inconsistent Definitions & Low Confidence in Reporting
Disparate data ownership and inconsistent definitions across brands and functions undermined confidence in business reporting. Teams spent time reconciling numbers instead of acting on insights. Leadership could not rely on reports as a single version of the truth, which slowed decision-making and created tension between business units.
Manual Forecasting, Pricing, & Route Planning
Forecasting demand, setting prices, and scheduling delivery routes were largely manual. These processes inflated logistics costs, increased truck rolls, and impacted service levels. Opportunities to optimize routes, reduce redundant deliveries, and protect margins were lost because analytics and AI were not embedded in day-to-day decisions.
Organization Not AI-Ready
The company wanted to pursue use cases like predictive churn, demand forecasting, and margin optimization. However, there were no standardized data products, governance structures, or platform capabilities to support these efforts. The organization was not structurally ready for AI and machine learning, and pilots risked stalling without a clear foundation and operating model.
Approach & Solutions
1. Unified Data Hub & Platform Foundation
We built an AI-ready Unified Data and Analytics Platform to centralize and govern data across the client’s technology landscape.
- Unified enterprise data across ERP systems (SAP, CARGAS), CRM (Salesforce), IoT, and mobile field tools into a single Unified Data Hub
- Adopted a Federated and Governed Data Product model so domains could own data while adhering to shared standards
- Synchronized SAP, NiCE, CARGAS, Salesforce, and field systems to keep customer, asset, and operational data aligned
- Designed the platform to support large-scale analytics and AI workloads across multiple brands and business units
2. Enterprise Data Office & Governance Operating Model
We put structure around data ownership, definitions, and policies so stakeholders could trust and use the data at scale.
- Defined and stood up an Enterprise Data Office (EDO) hosted within TechBlocks’ Global Capability Center (GCC)
- Aligned the EDO with the client’s Data and Analytics Center of Excellence to coordinate strategy and execution
- Established clear data ownership and common definitions across domains and brands to reduce conflicts and ambiguity
- Implemented automated lineage and policy enforcement to track where data came from, how it was used, and whether it complied with rules
3. AI & Analytics Product Suite
On top of the Unified Data Hub, we delivered a suite of AI and analytics products that targeted key value levers in the business.
- Built Tank Consumption Forecast and Delivery Optimization models to improve route planning and refill accuracy
- Developed a Serve Engine to consolidate profitability across fleet, labor, and logistics and provide clearer views of contribution margins
- Created a Customer Lifetime Value Estimator that combined historical usage, pricing, and propensity to buy
- Delivered Pricing and Churn Prediction models to support targeted retention and margin-aware pricing strategies
- Implemented an Integrated Margin Optimizer that unified supply chain, pricing, and demand signals to support real-time margin decisions
4. Field Digitization & CSR Intelligence
We extended the platform into the field and contact center, reducing manual work and improving frontline decision-making.
- Replaced paper-based inspections with mobile workflows as part of a Field Intelligence and Compliance Digitization initiative
- Applied AI OCR with 90%+ accuracy to capture tank metadata and inspection information from the field
- Improved field productivity and compliance by making inspection data available in near real time through the Unified Data Hub
- Delivered a CSR 360 view plus a GenAI Agent that reduced CSR call preparation time to under 60 seconds by surfacing contextual insights on demand
Impact & Results
The client moved from siloed reporting and manual planning to an AI-ready, data-driven operating model.
With a Unified Data Hub, an Enterprise Data Office, and targeted AI products in place, the organization reduced waste in the field, improved margins, and equipped teams with trusted data and real-time insights. Field technicians, planners, and CSRs all gained stronger tools to serve customers more efficiently.
Faster field inspections
The Field Intelligence and Compliance Digitization work delivered a 35% reduction in field inspection turnaround time. Mobile workflows and high-accuracy AI OCR improved productivity and strengthened compliance across the tank inspection process.
Uplift from AI optimization
AI-driven optimization and operational efficiencies were projected to deliver a $17M annualized EBITDA uplift. The combination of better routing, demand forecasting, pricing, and margin management created measurable financial impact.
Reduction in redundant deliveries
Route optimization and better forecasting led to a 32% reduction in redundant deliveries, decreasing truck rolls and service waste. Fuel usage dropped by 24%, supporting both cost reduction and sustainability objectives.
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