Data Upload & Update

1. 1Upload a CSV or XLSX export from your payroll, time-and-attendance or HRIS system. One row per overtime line.
2. 2Map columns — confirm which of your columns hold Claimant ID, Hours, Value and Date. We pre-guess from your headers.
3. 3Review results — the engine scores every claimant on multiple risk indicators and opens an interactive dashboard for investigation.

• Claimant ID · required
  Unique employee identifier (e.g. payroll number). Names alone aren't reliable — two people can share a name.
• Hours · required
  Numeric hours per row (decimals OK). Strip totals/subtotals from your export.
• Value · required
  Monetary cost per row in a single currency. No symbols or thousands separators where possible.
• Date · required
  Date the overtime was worked or claimed. Any common format (ISO, US, EU, Excel serial, YYYYMMDD) — you'll confirm the format on the mapping step.
• Approver ID · optional
  Manager/approver identifier. Unlocks approver-pattern indicators such as self-approval and approver concentration.
• Descriptive variables · optional, up to 3
  Any categorical column (Department, Location, Role, Shift type) used to slice and filter the dashboard.

• One row per overtime line — not pre-aggregated by employee or week.
• Header row in row 1. Remove blank rows, repeated header rows and total rows.
• Use a consistent Claimant ID across the whole file (don't mix payroll number and email).
• If your file is over 80 MB, save it as .csv from Excel first — it uploads faster and more reliably.
• Extra columns (cost centres, GL codes, comments) are fine — anything you don't map is simply ignored.

Files are uploaded over an encrypted, signed URL into your organisation's private storage. Only members of your organisation can access the dataset and its results. You can delete a dataset at any time from Manage datasets — this removes both the source file and the analysis output.