Supply Chain Task Resolution Automation
A global manufacturing leader manages a massive and fast moving supply chain where thousands of daily exceptions affect supplier performance, production plans, and delivery forecasts. Analysts must interpret each issue manually, reading descriptions, checking attachments, reviewing supplier notes, and validating data across CMMS systems. With more than one thousand tasks arriving every day, delays and errors were unavoidable. By deploying Maisa Digital Workers, the company transformed its entire exception handling workflow, achieving dramatic gains in speed, accuracy, and capacity.
Department
Supply Chain
The Challenge
The supply chain monitoring team received more than one thousand operational tasks every day, each containing different levels of information such as images, emails, supplier notes, and contextual data. Analysts had to manually open every task, interpret the issue, cross check information in the CMMS, confirm shipping plans and delivery status, review program changes, and validate buffer stock levels. With five to ten minutes required per task, the team struggled to keep pace.
The speed and volume of the workflow made human mistakes almost certain. Misinterpreting a deviation could disrupt production schedules. Overlooking a delay could trigger penalties or expensive expedited shipments. Closing a task too early could hide a real supply issue. Even small oversights created additional work and financial impact across the supply chain.
Under constant pressure, analysts had no room for strategic work and were forced into a purely reactive posture, focused only on clearing the queue instead of improving processes or preventing future issues.
The Solution
Maisa Digital Workers automate the complete task resolution workflow with clear, consistent, and fully transparent logic. After the process was defined in natural language, the Supply Chain Monitoring Team deployed a Digital Worker that now manages every step of the workflow from beginning to end.
The Digital Worker ingests every incoming task, reads the description, reviews images and attachments, understands supplier notes, and incorporates all available context. It then checks operational data inside the CMMS, including shipping plans, delivery records, supplier schedules, program adjustments, and buffer stock. This allows it to determine whether the issue is real, already resolved, or covered by available capacity.
Using the organization’s supply chain logic, the Digital Worker decides whether to close the task, progress it for monitoring, or escalate it with clear follow up actions. It then writes a complete explanation directly inside the task comments, detailing what was checked, what data sources were used, and why the final decision was reached. Analysts receive clarity instantly without opening any other system.
The Results
By automating the entire task evaluation process, the organization achieved transformative performance improvements. Task resolution time decreased by eighty five percent, enabling the team to move from one thousand tasks per day to more than six thousand with the same number of analysts. The team now saves between sixty seven and one hundred fifty hours every day.
The error rate decreased by more than ninety five percent, preventing production delays, supplier escalations, unnecessary expedited shipments, and penalty costs. Sub minute cycle times now provide real time visibility and a stronger and more predictable supply chain.
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