Automating Workload Management System
For An American Health Services Organization
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Schedule a DemoUncovering the business context
Batch systems play a key role in services companies in managing their critical business functions such as delivering on Service Level Agreements (SLAs), and leveraging operation analytics to manage batch trends. It is important to ensure their on-time completion, especially in case of a heavy volume of service requests and complex service requirements. Today, this is done in a manual and reactive fashion thereby impacting cost, quality and time.
The Challenge
01 The Problem: Lack of end-to-end observability of critical business processes as they are spread across various value streams having a load of 12,000+ batch jobs that run 5.5 million executions per month. This could impact 600+ SLA misses. The IT estate needs to meet numerous business deliverables to run day-to-day business operations efficiently. Batch processes are critical and must be completed within the SLA, ensuring smooth business operations. While the standard reactive operating model can, at best, react to failures and delays, it cannot prevent them from occurring. As a result, batch operations observe unexpected delays and outages.
These batch processes are responsible for key business deliverables such as process daily appointments, new and renewal of policies, claims, outreach programs such as reminders/notifications to members/providers, price optimization, personalized marketing, agent commissions, member incentives and so on. Moreover, missing SLAs of the batch process has an impact on Federal and State compliance.
The Problem 2: The company handles a massive volume of batch jobs, and nearly 15,000+ exceptions batch admin requests are handled manually. Requests are submitted through an online portal and an operations command center, and the batch operations team processes requests manually while responding to users.
The Solution — ignio AIOps
By leveraging ignio AI. Workload Management’s machine learning and analytics capabilities, clients can now monitor batch progress, predict future batch behavior using visual radiators and send early notifications of any possible delays in business deliverables. As a result, instead of reacting to situations, the operations teams can now get a sense of the potential delays and have enough time to take timely corrective actions.
Using ignio AIOps and ignio AI. Workload Management capabilities, nine different batch administration requests have been automated through ESP integration, and the batch exception intake system was eliminated. Manual intervention on batch exception management, which was tedious and time-consuming, was removed.
None. Receiving positive feedback from customers consistently in governance calls.” This is in keeping with the customers’ core values which are accessibility, affordability, and comprehensiveness. ignio has produced a win-win situation for the healthcare provider and its customers.
Measurable Value Across Every Dimension
Reduced revenue loss by addressing missing or incorrect prices and promotional discrepancies before customer impact
Improved online customer experience leading to measurably lower cart abandonment rates across all storefronts
Over 90% reduction in MTTD and MTTR — transforming from reactive to proactive operations
12,000+ manual hours saved annually across L1, L2, AppOps and business teams
~3,600 stuck orders resolved autonomously per year — reducing write-offs and preserving payment collection timelines
1,000+ stores receiving accurate, on-time promotion validation across all three brands
