From “let’s hope it works” to “we know it will”: how ProBatch anticipates bottlenecks

How anticipate

At 9:42 PM, the dashboard was green. Two hours remained until the SLA deadline, and the Operations team was feeling confident. That is, until the job Conciliación_Interna got stuck waiting for a lock in the accounting database. One minute. Three. Five. The critical path turned red like a traffic light in downtown at rush hour.

If you’ve ever been through a banking closing, you know what comes next: Slack blows up, someone suggests pausing the ETL queue “just for ten minutes,” Treasury asks for the regulatory report, and without anyone saying it, the worst enemy of any closing emerges: reprocessing.

This isn’t a hypothetical story. It happens. It happens when we assume that “because it worked yesterday, it will work today.” It happens when we add a “harmless” job, when card volume spikes 18% due to month-end, when someone locked the database for overnight maintenance “that wouldn’t affect anything.” It happens when we arrive at the closing just to find out.

But at Accusys, when we built ProBatch, we asked a different question:

What if we could see the bottleneck before the batch run even starts?

The shift: rehearsal before execution 🔎

Predictive simulation before execution isn’t a fancy graph or a magic estimate. It’s a full dress rehearsal using your actual batch flow, dependencies, timing history, and resource limits.

Before hitting “Run,” ProBatch sets the stage:

And then it shows you something that changes your night: the projected end time—and more importantly, where it will break if you don’t act.

A real closing: two decisions that prevent disaster🔥

Let’s go back to the 9:42 PM story—but this time, with a simulation. At 7:10 PM, the team ran the rehearsal. Two alerts popped up:

1. ⌛Database contention at 10:15 PM between Conciliación_Interna and Asientos_Generales. The simulation showed that the new process couldn't run concurrently at p95, causing a 7-minute delay and a queue building up like party streamers.
2. ⚡Unusual card file volume (+18% vs. baseline), which pushed the aggregation job for the regulatory report 12 minutes later.

With that information, the team made two simple decisions before the clock started ticking:

• 🔄 Rescheduled Asientos_Generales by 10 minutes and increased threads from 4 to 6 for a 30-minute window.
• 💡 Changed dependencies in the regulatory report sub-tree, reordering two jobs to reduce overload.

Result: the forecast updated. The projected end time turned green again. And most importantly: no reprocessing. There was no heroism. Just proactive management.

Con esa información, el equipo tomó dos decisiones simples antes de que el reloj corriera:

1. 🔄Replanificar Asientos_Generales 10 minutos y aumentar los hilos de 4 a 6 en un tramo de 30 minutos.
2. 💡Cambiar las dependencias del subárbol del regulatorio, reordenando dos jobs para no sobrecargar el procesamiento.

Result 📊

the forecast updated. The projected end time turned green again✅. And most importantly: no reprocessing. There was no heroism. Just proactive management.

 Why this matters (beyond “we hit the SLA”)👌

Closings don’t fail because teams don’t know—they fail because uncertainty creeps in through the cracks: changing volumes, hidden dependencies, shared resources. ProBatch’s predictive simulation flags this uncertainty before it becomes an incident.

• For Operations, it means entering the batch window with a plan (not a wish).
• For Business, it means trusting the regulatory report will be ready on time.
• For Audit, it means traceable reasoning behind why X was prioritized and Y postponed.

And yes—it also means sleeping a little better.

What makes ProBatch different? ♻️

At Accusys, we live the banking world from the inside. We built ProBatch for complex batch flows, where COBIS, ETLs, reconciliations, and regulatory reports must coexist in tight spaces and short nights. Simulation isn’t an isolated module—it integrates into everyday operations:

• ◀️ Before: you run the simulation with the day’s actual batch flow; the system gives actionable recommendations (parallelize here, offset there, reserve resources in this segment).
• 🔛 During: if reality deviates from the forecast, ProBatch updates predictions live and alerts you before anything turns critical.
• ▶️ After: it compares forecast vs. actual, learns, and fine-tunes the model for the next closing.

The goal? 🎯 Making “no reprocessing” the standard for banking closings—not the exception.

The numbers we track (and why)📈

We prefer metrics that change behavior—not just decorate slide decks:

• Deviation vs. plan: lowering the p95 of the critical path in the first month.
• Avoided reprocessing: how many didn't happen thanks to pre-checks and reordering.
• On-time completion: more jobs finished within the window, without deferring.
• Effective SLAs: not just “met,” but met without firefighting.

If we measure right, we improve for real.

“But my batch flow is a Frankenstein…” (all the more reason)

There’s always an objection: “ours is different—we’ve got old integrations, weird peaks, handmade stuff.” Perfect. The more heterogeneous your batch flow is, the more valuable simulation becomes.

ProBatch doesn’t ask for an “ideal flow”—it works with what you have: tagging resources, learning from history, modeling dependencies, and tolerating exceptions. The rehearsal takes place on your stage, not in a lab.

A brief (and human) checklist before your next closing ✅

This isn’t theory. These are three practices we’ve seen make all the difference:

1. Name the critical: define and assign SLA to the chain that really hurts if delayed.
2. Clean your history: remove outlier days from the logs so the model doesn’t learn from what it shouldn’t.
3. Rehearse with volume: run a month-end what-if even if today isn’t. The night of truth isn’t the time for first times.

A quiet closing is also a win🎯

Some nights deserve applause—the best ones don’t make the news. ProBatch’s predictive simulation doesn’t promise miracles; it promises predictability. And in critical closings, predictability is a competitive advantage.

If you’ve read this far, you already know how the 9:42 PM story ends:
No heroics. No panic chats. No Monday morning justifications.
Just a closing. On time 🕒

Shall we continue this conversation? 💬

If you want to rehearse your closing before it happens, we can review your current batch flow and show you where your next bottleneck is—before it exists. Let’s talk.