Leading Utility Company Transforms Workload Process With ignio™
Improved SLA compliance and improved workload management.
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For utility service providers and retailers, key business functions like compiling meter readings, invoice generation, payment processing, and customer request processing need to run smoothly. These functions rely on workload automation to execute a series of associated IT tasks (batch processes) in a timely manner and ensure business continuity. Any failure or delay in these batch processes causes operational issues, interfering with the customer experience and revenue streams.
Better revenue assurance from autonomous monitoring and intelligent resolutions
The Challenge
The customer has a complex IT estate, which made it difficult to conduct continuous monitoring of workload processes and remediation or maintenance activities. It not only needed extensive efforts and resources but was also fraught with limitations as processes could not be monitored during non-business hours. Manual monitoring often resulted in lags in identifying anomalies, or in diagnosing and resolving the issues, resulting in serious delays in business operations.
For instance, delays in accurate digital capture of meter readings hampered the process of updating the record against the customer’s account. This also caused slippage in calculating charges and sending out bills, which led to late revenue realization. Additionally, it often resulted in inaccurate charges, or generation of duplicate copies of bills, and incorrect communication with customers, leading to increases in customer complaints as well as potential revenue losses of up to €5 million a day.
The existing Linux-based scheduler couldn’t store historical data in a usable format and was not able to integrate with external systems for real-time data. This was a major obstacle in generating analytics that could have been used to identify, predict, and avoid such IT failures.
The Solution — ignio WLM
Digitate collaborated with the customer to provide a layered solution for monitoring workload processes. Digitate understood that clear visibility into the IT estate is the key to better monitoring. Digitate leveraged ignio AI.Workload Management to create a “blueprint” of the entire batch system that reflects all the jobs, their schedules, interdependencies with each other, and their historical behavior. This was collected from a variety of sources including execution logs, databases, and email reports, to ensure the platform has access to both real-time and historical information.
This blueprint helped the team understand the normal behavior of any job by accurately capturing process flows in depth, identifying focal areas of concern, and pinpointing issues in progress. Now the The customer team has to spend less time and energy on manual monitoring because ignio™ AI.Workload Monitoring provides always-on autonomous monitoring of the entire workload ecosystem and timely notifications of any potential breach. In fact, ignio™ offers a closed-loop solution by diagnosing the probable root cause of anomalies, analyzing the impact on critical business operations, and recommending the right solution to rectify it. This helps The customer ensure business continuity.
Improved SLA compliance by leveraging predictive analytics
The Challenge
The customer had a reactive mode of operation for workload management, where it relied on pre-defined rules to generate alerts in case of a process failure. Also, the utility did not have any defined SLAs (service level agreements) for any batch job or process, which usually help define the optimal timelines for process start time, execution time, and completion time. Lack of foresight and SLAs often prevented timely process completion, leading to escalations and expensive manual efforts, as well as business process violations or poor customer experience.
For example, when receiving payment information from third-party payment gateways, customer payments are routed through middleware to The customer’s SAP ERP system for processing, and then the amount is credited to corresponding accounts. This entire process is done by batch jobs that execute at the close of each business day. In case the process doesn’t complete in a timely manner, it can lead to loss of data or inconsistency in data, leading to faulty dunning (payment reminder) processes. This can cause unnecessary inconvenience for the customers, often resulting in complaints.
To prevent such issues from occurring, The customer needed a solution that could define SLAs, proactively identify potential SLA misses, and curb any impact on business operations.
The Solution — ignio WLM
The customer leveraged ignio™ AI.Workload Management to transform its workload management processes from reactive to proactive. With clear knowledge of the existing workload ecosystem and historical run data, ignio is now able to identify performance trends and patterns and thereby derive the optimum thresholds for every job run.
Leveraging ignio’s AI capabilities, the Digitate team provided dynamic recommendations for SLAs for the execution and completion of business-critical operations; the SLAs can now adjust themselves as per the changes in the environment in order to meet day-to-day requirements. This capability helps prioritize and focus on alerts that are important and meaningful, reducing alert noise.
One of the biggest advantages ignio provided was real-time predictions that could detect potential SLA breaches two to three hours ahead of time, diagnose and localize their probable causes, and recommend fixes, preventing many outages and minimizing the impact of others. This is helping The customer become more proactive in its ITOps process.
For instance, for customer payments, ignio analyzes the data captured from the payment gateways and payment files in real time to predict if the payment will be successfully reflected or not, as per the defined SLAs. In case of any discrepancies from normal behavior, it assesses the impact on the subsequent business operations, and accordingly informs the downstream applications to send or hold dunning letters and reminders to the customer accounts. This both increases customer satisfaction (because it protects users from getting unnecessary or inaccurate reminders) and The customer’s profitability (because payments are being reflected in a timelier way).
Measurable Value Across Every Dimension
Reduced batch-induced delays and risk of batch failure
Reduced effort and time to eliminate batch issues
Improved competitive position due to higher customer satisfaction
Recommended thresholds for business SLAs
Reduced alert noise and risk of missing alerts
Reduced cost of monitoring
