A month-long report is not a number. It is a memory.
TDABC only changes decisions if the number arrives in time to use it. At banking scale that takes a data and technology stack, source systems, ETL, BI and increasingly AI, that feeds the time equations automatically and produces profit per customer and per channel in days, not after a month. The speed of the close is not a back-office detail; it is what decides whether cost informs a decision or merely records one.
Cost and Profitability Consulting · 150+ models since 2010 · TDABC
TDABC at banking scale needs a stack that feeds the time equations automatically: ERP and source systems, ETL, a BI layer, and increasingly AI to maintain the equations. As an illustrative pattern, a large retail bank ran TDABC over a terabyte-scale data set processed overnight, collapsing reporting from over a month to a few days; a global brokerage replaced a legacy system that took over a month to produce a single report. A close measured in days, not weeks, is what lets profit per customer and per channel inform pricing and channel decisions while they are still open. A month-long report is a memory; an automated close is a decision tool.
A number that arrives late is a different number.
When a profitability report takes over a month, every decision it could inform has already been made on instinct. Pricing was set, channels were steered, customers were retained or let go, all before the cost was known. The report becomes a post-mortem, useful for explaining the past but powerless to change it. The barrier is rarely the method; it is a manual, survey-bound pipeline that cannot keep up with the institution. Automate the pipeline and the same model becomes a live input instead of a historical record.
THE CLOSE: FROM A MEMORY TO A NUMBER
Illustrative sector pattern. Legacy reporting took over a month; an automated TDABC stack collapses it to days. The difference is whether cost can still change a decision.
Source to decision, without the surveys.
Source systems
ERP and transaction systems already hold the volumes the time equations need. The data exists; it is just not assembled.
ETL pipeline
Automated extraction and transformation feed the equations directly, replacing the monthly survey that killed legacy ABC.
BI & reporting
Profit per customer, channel and transaction surfaces in days, ready to act on while decisions are open.
AI maintenance
AI helps keep the time equations current as volumes and processes change, so the model does not drift.
When cost is current, it changes the call.
A close measured in days turns cost to serve from a report into a control. Repricing happens on current data, channel steering responds to this quarter's behaviour, and customer actions are taken while the relationship is live. As illustrative sector patterns show, the institutions that automated the close, the retail bank processing terabyte-scale data overnight, the brokerage that retired a month-long legacy report, are the ones that converted cost knowledge into market value. Speed is not a luxury on top of the model; it is what makes the model worth building.
Frequently asked questions
- What technology does TDABC need in a bank?
- A data and technology stack that feeds the time equations automatically: ERP and source systems for transaction volumes, ETL to assemble them, a BI layer to report, and increasingly AI to maintain the equations. As an illustrative pattern, a large retail bank ran TDABC over a terabyte-scale data set processed overnight, which is only possible with an automated pipeline rather than manual surveys.
- Why does the speed of the close matter?
- Because a number that arrives weeks late is a memory, not a decision tool. As an illustrative pattern, a legacy system took over a month to produce a single report, while TDABC on an automated stack collapsed reporting to a few days. A close measured in days lets cost inform pricing and channel decisions while they are still open.
- How does automating the close change decisions?
- It moves cost from a backward-looking report to a live input. When profit per customer and per channel is available in days rather than after a month, repricing, channel steering and customer actions happen on current data. The same automated stack that produces the close fast also keeps the time equations current as volumes change.
Turn your close from a memory into a control.
The Profit Check takes five minutes and no data upload. It points to where a faster, automated cost model would change decisions you are making today, and what that speed is worth.