FINANCE

Weekly SaaS Spend Overlap Report from Snowflake to Coda

Every Monday, queries consolidated vendor spend in Snowflake, groups tools by software category, flags categories where two or more vendors overlap.

CategoryFinance
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly Monday schedule
  • ActionQuery 12-month vendor spend in SnowflakeSnowflakeSnowflake
  • LogicAggregate spend by category and vendor
  • LogicKeep categories with 2+ overlapping vendors
  • LogicRank overlaps and compute consolidation savings
  • OutputPublish ranked overlap table to CodaCodaCoda

What it does

This workflow builds a recurring vendor-spend consolidation report. It reads normalized spend rows from your Snowflake finance warehouse, rolls them up by software category (e.g. project management, observability, email marketing), and surfaces every category where you are paying two or more vendors for overlapping functionality. The result lands in a Coda doc as a ranked table showing redundant tools, combined annual cost, and the estimated savings from consolidating to one.

When to use it

Run this when finance or ops wants a standing view of tool sprawl without manual spreadsheet wrangling. It is ideal for monthly close prep, budget reviews, or a quarterly vendor rationalization push.

How it works

  1. 1A weekly schedule fires Monday morning.
  2. 2Snowflake query pulls 12 months of vendor spend joined to a category mapping table.
  3. 3A grouping step aggregates spend per category and per vendor.
  4. 4A filter keeps only categories with two or more active vendors (true overlap).
  5. 5A ranking step orders overlaps by combined annual spend and computes savings as total minus the cheapest viable single vendor.
  6. 6The report is written to a Coda table, replacing last week's rows.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SnowflakeWarehouses, queries, shares.
  2. 2
    Connect CodaDocs, packs, automations.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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