Eleven category labels were enough to slow monthly reporting across 14 branches.
From January to June, I coordinated a team effort with branch representatives and an analyst to map those inconsistencies, define a shared schema, and test a validation checklist over two monthly cycles.
Operations records later showed reconciliation moving from about two staff-days a month to four staff-hours. Those times were self-recorded, the workload varied, and this was not a causal experiment—so I treat the change as an operational signal, not proof of one intervention's effect.
My takeaway from this project: data cleanup may start with shared definitions and clear ownership before it needs a more complex formula.
Here is the [approved anonymized schema example]. What checks help your team keep definitions consistent?
#DataQuality #Operations
Versão curta: “Across 14 branches, our team mapped 11 inconsistent labels and tested a shared schema/checklist. Self-recorded reconciliation time later moved from about two staff-days to four staff-hours per month, with changing workload and no causal test. My project takeaway: shared definitions and ownership may matter before more complex formulas. [Approved anonymized schema example]”
Auditoria: “coordinated” preserva a função; a atribuição à equipe está explícita; os números 14 e 11, os dois ciclos, os tempos e os limites vêm dos dados fornecidos. Não há empregador, colega, categoria confidencial, percentual causal, endosso ou reação inventada. Antes de publicar, confirme que o link público leva ao arquivo aprovado e substitua o texto do link entre colchetes pela URL real.
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