Data Excellence

The problems we solve

One trusted set of numbers, underneath the processes, the reporting and the planning. Finance data problems rarely announce themselves as data problems. They show up as a meeting that stalls because two reports disagree, as an analyst who spends three days a month exporting and cleaning the same files, or as a new system that turns out to cost far more than quoted because nobody had looked at what was going into it.

  • Two reports show two different revenue figures for the same month, and both are defensible.
  • Every analysis starts with the same export, the same clean-up and the same manual mapping.
  • The chart of accounts has grown by accident and no longer matches how the business is managed.
  • Cost centres, entities, products and customers are maintained differently in each system.
  • A new reporting or planning tool is being considered, and nobody can say what state the source data is in.
  • The numbers are probably right, and nobody is quite willing to sign for them.

Finance data model and master data

What we do

  • Chart of accounts design and rationalisation, aligned to how the business is actually managed and to what has to be reported
  • Dimension design — entity, cost centre, product, customer, project — so that one structure serves accounting, reporting and planning
  • Master data ownership and maintenance, with rules for who creates what and where
  • Mapping between statutory, group and management views that does not have to be rebuilt each period

Outcome

A structure that holds when the group grows, and reports that agree with one another because they are built on the same dimensions.

Data flows and integration

What we do

  • Automated flows between the ERP, the consolidation tool, the planning tool and the reporting layer, replacing manual exports
  • Reconciliation between systems built into the flow, so that a difference is flagged rather than discovered
  • Data preparation moved out of individual spreadsheets and into something repeatable, with Power Query or Python where that fits
  • Data migration and clean-up during a system change, which is the point at which most implementations quietly overrun

Outcome

Numbers that arrive where they are needed without anybody exporting them, and a clear answer whenever two systems disagree.

Definitions, governance and trust

What we do

  • A KPI dictionary in which each measure has one definition, one owner and one source
  • Data quality checks and controls that run as part of the close rather than as a separate exercise
  • Access, ownership and change rules, proportionate to a finance team of your size rather than to a bank
  • Self-service reporting in Power BI, set up so that people can answer their own questions without inventing new numbers

Outcome

A set of figures the management team stops arguing about, and a finance function willing to sign for them.

Why we added this

In twenty years of building consolidation, reporting and planning platforms, the projects that went wrong almost never went wrong because of the software. They went wrong because the chart of accounts did not match how the business was run, because master data was maintained in four places, or because nobody had agreed what a definition meant before it was automated.

We used to treat that as the first phase of another project. It is more honest to treat it as its own discipline, and to offer it on its own — including to companies that are not asking us for anything else.

Supporting the Finance Shift

The right expertise at the right time.

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