{"id":30645,"date":"2026-09-08T16:01:31","date_gmt":"2026-09-08T14:01:31","guid":{"rendered":"https:\/\/res-group.eu\/?p=30645"},"modified":"2026-09-08T16:27:04","modified_gmt":"2026-09-08T14:27:04","slug":"batch-workload-forecasting-in-banking-integration-and-merger-scenarios","status":"publish","type":"post","link":"https:\/\/res-group.eu\/en\/success-stories\/batch-workload-forecasting-in-banking-integration-and-merger-scenarios\/","title":{"rendered":"Batch workload forecasting in banking integration and merger scenarios"},"content":{"rendered":"

CASE STUDY: RES Suite<\/a> supporting batch capacity planning and forecasting<\/span><\/strong><\/h2>\n<\/div>

Batch-Watch<\/a><\/strong>, with its Predict<\/strong> capabilities, supported a major Italian banking group in assessing in advance the impact of increasing batch workloads resulting from the acquisition and integration of another banking institution. The analysis transformed historical data and current monitoring information into predictive scenarios, supporting capacity planning, integration activities and the definition of corrective actions.<\/p>\n<\/div><\/div><\/div>

THE CONTEXT<\/h2>\n

The Italian banking group<\/strong> was undergoing an evolution of its IT environment and the integration of new business entities. As part of this process, it needed to assess in advance the impact of increasing workloads on its batch infrastructure<\/strong>.<\/p>\n

The objective was to determine whether the existing batch infrastructure and workload management model could support the expansion of the operational scope without causing slowdowns, bottlenecks or service disruptions.<\/p>\n

The customer therefore needed to move from a monitoring-based approach to a predictive<\/strong> one: analysing actual batch behaviour<\/strong>, estimating available capacity<\/strong>, identifying the most sensitive areas<\/strong> and preparing any corrective actions<\/strong> in advance.<\/p>\n<\/div><\/div><\/div>

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THE CHALLENGE<\/span><\/h2>\n<\/div><\/div><\/div>

The challenge<\/strong> was to turn historical data and current monitoring information into a reliable basis for predictive simulations<\/strong>.<\/p>\n

Predicting the impact of workload growth does not simply mean assuming a linear increase in volumes. It requires understanding how new workloads interact with existing processes, which time windows may become more critical, where congestion could occur and what capacity margins are actually available.<\/p>\n

In a complex environment, this type of analysis requires an accurate understanding of real-world batch behaviour and tools capable of projecting future scenarios<\/strong> based on objective evidence.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

THE SOLUTION<\/h2>\n<\/div><\/div><\/div>

RES supported the customer through Batch-Watch<\/strong><\/a>, used both to monitor and control workloads and to leverage its Predict<\/strong> capabilities.<\/p>\n

The project allowed the customer to<\/span>:<\/p>\n