An electronic bill of lading could save $6.5 billion in direct costs
Real-time visibility into inventory and movements is increasingly critical in today’s risk-filled environment. Organizations need to reflect the reality of their asset inventories accurately and digitally in their data, for sharing and collaborating internally and across their value chain. Enhanced accuracy improves the information used for supply chain decision making, while AI-based reconciliation delivers a more resilient, efficient organization.
(Source: McKinsey)
Leading organizations are using AI to digitize and automate critical processes, separating themselves from their peers
Improving margins and efficiencies
40%
Lower inventory carrying cost as a percentage of annual inventory value
Digitizing supply chain to support growth
95%
Innovator CSCOs report developing digitized workflows and leveraging AI automation a full 95% more than their peers
Realized cost advantage
2.5x
Cost savings of processes addressed by automation for automation leaders versus laggards
Above are industry benchmarks from leading providers APQC, Bain and IBM Institute of Business Value, highlighting benefits of industry leaders versus peers.
“When we did an analysis between what the truck driver actually loaded versus discharge, we could see clearly from certain tanks and certain fields that there would be constant losses ... we were able to get the data from the strapping tables through ClearDox. We were actually able to do more accurate gauging than the handheld, which was the information we were getting from truck driver, which saved us basically over $2 million with just that one supplier.”
Tim Cannon
Head of Operations, Freepoint Commodities
Using AI to get real-time data for real-time supply chain visibility
Resiliency | Digital data | Capital management
- Inventory status and movements by day, week, and month with full audit capabilities on document, data, reconciliation, commenting, and associated workflows.
- Real-time cross-process and department views to identify and intervene in instances of demand-supply imbalance.
- Accelerate turnover rate while reducing carrying costs with improved timeliness and data accuracy.
- Match external documents from multiple sources with the inventory levels, providing transparency to contract performance and financial requirements.
- Avoid stockouts and excess inventory by reconciling positions through open integrations with CTRM, ETRM, and ERP systems.
- Flexible exception parameters to better align with specific business and user requirements.
- Movement data can be amended by users to ensure accurate volume assessments in the system of record.
- Cloud-based digital access to connect operations with finance to mitigate exceptions/discrepancies and accelerate period close.
- Dynamic data and communication tools including chat and email integration to support business resiliency.
- AI data engineering used to identify and pull disparate data with the embedded intelligence of commodity experts.
- Robust document categorization, storage, grouping and search features, ensuring seamless access and organization.
- Real-time digitized data normalized to improve planning and forecasting.
- Turnkey operations that can scale to match volumes and global reach of operations.
Solution details
SOLUTIONS
Confirmation Manager Solution Sheet
The process of trading confirmations reconciliation is essential to ensure accurate and timely settlement of trades, and to avoid risks and discrepancies that can result in financial losses or legal disputes.
SOLUTIONS
Oil and Gas Solution Brief
Once digitized, broad automated reconciliation efforts including straight through processing, is achievable, freeing resources to focus on higher value activities, and faster response to the next challenge or opportunity.
SOLUTIONS
Before the Next “Black Swan”: Why the Commodities Industry Must Protect Itself With Digitalization
Companies that embrace digitalization will enjoy not only a competitive advantage, but also far greater resilience.
ClearDox FastTrak
Fast Start, Fast Results – 5 weeks, 25 counterparties
1. Gather. Assess. Define.
2 weeks
- Process and data workflows
- Teams impacted
- Counterparties covered (goals prioritized)
- What data matters (sample documents)
- Consume data (normalize dashboards)
- Integration
- Measure impact
2. Design. Adapt/Tune. Validate.
2 weeks
- Design AI-approach for document pipeline
- Adapt and tune models, generate and train new models
- Validate and normalize against commodity semantics knowledge base
3. Activate. Refine. Promote.
1 week
- Activate solutions, integrate workflows
- Continuously monitor quality, refine and optimize
- Promote launch, train team and drive adoption
Next Step: Scale
Scale up – More counterparties / Scale out – New workflows