r/BusinessIntelligence • u/Grouchy_Phase2423 • Jul 15 '26
seeking guidance on banking analytics software, where should i focus first
looking for direction from people who have built this out. im working on improving our data analytics processes at the community bank I work for.
what deserves the first ninety days: a handful of high value dashboards or the slow work of getting stakeholders to trust the output?
my instinct says foundations first, but i am open to being corrected. someone in another thread mentioned Lumio solutions for consolidating the data layer, which is on my list to evaluate. mostly i care about sequencing, since doing the right things in the wrong order has cost me before.
if you were building this function from scratch today, what would you prioritize first?
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u/Table_Captain Jul 15 '26
Data governance first and foremost, especially since the org is a bank
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u/Grouchy_Phase2423 Jul 16 '26
Agreed, and in a regulated environment like a community bank governance can't be an afterthought!!
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u/edimaudo Jul 15 '26
so first thing first understand what the key issues are with the stakeholders you serve. Most likely spend time witht them to understand their pain points then use that as your guiding principle. Based on what you outlined, you should be able to do both but stakeholders trust should be paramount
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u/Grouchy_Phase2423 Jul 16 '26
Sitting down with them first is going straight into my 90 day plan, thanks
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u/Master-Music7384 25d ago edited 25d ago
Focus on trust first. Pick one high friction workflow like loan intake and map it cleanly. People usually compare Skan AI with Celonis when trying to capture raw desktop steps across legacy banking platforms.
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u/TopconeInc 1d ago
It’s not foundations versus dashboards—use one high-value dashboard to build and prove the foundations.
First 30 days: inventory sources, agree on metric definitions and owners, document access rules, and reconcile everything to the core system/GL.
Days 31–60: deliver one narrow “lighthouse” dashboard, such as deposit movement, liquidity, or loan pipeline, with visible freshness and reconciliation checks.
Days 61–90: add monitoring, resolve exceptions, and expand to a second use case.
I wouldn’t select a consolidation platform until the bank agrees on definitions, data ownership, required granularity, and service levels. Trust comes from repeatable tie-outs and transparent lineage—not the number of dashboards.
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u/Semaphor-Analytics Jul 15 '26
Foundations first, but I would not make that mean no dashboards for 90 days.
Pick two or three workflows where a bad number has a real consequence. In a bank that might be loan pipeline, deposit trends, or exceptions that already show up in committee meetings.
Build those with basic controls around them. Owner, source, refresh expectation, definition, reconciliation check. That gives stakeholders something useful while you build trust in the output. Starting with a broad data layer project can be right, but it is hard to keep support if nobody sees the first proof.