Excel operations reporting

Keep the exports. Reduce the manual analysis around them.

Many operations teams already have usable data in recurring Excel or CSV reports. The friction sits between receiving the file and producing a credible management story. NaraOps is designed for that gap.

Try NaraOps freeExplore synthetic sample

What you need to start

You can start with a single current-state CSV or Excel file for evidence-based measure summaries and segmentation. For snapshot and lifecycle analysis, two or more dated extracts of the same operational population plus a stable work-item reference provide the comparable history needed for movement and persistence conclusions.

A dated event-history file can also provide longitudinal context from its row dates. NaraOps scopes trend, lifecycle, outcome and duration conclusions to the evidence actually present rather than inventing history when a current-state file has none. Related structured files can add activity, quality or outcome evidence where a shared reference joins populations reliably, and approved document or image extractions can contribute structured records after review.

CSV

Useful for current-state data, recurring snapshots, event-history exports and other structured operational data processed in the browser.

Excel .xlsx

Supported directly, including sheet selection where a workbook contains several tabs.

Connected folders

In supported browsers, remember a desktop folder and re-check it while NaraOps is open or regains focus.

Documents & images

PDFs, images, DOCX and text files can be explicitly extracted into proposed records with source review, confidence and approval before analysis.

What NaraOps does that a static spreadsheet normally does not

Depending on the data shape, it can summarise current measures and segments, compare the same IDs across reporting points or analyse repeated event-history rows, distinguish latest movement from longer history, detect concentrations and native measures, connect reliable related evidence, build audience-specific briefs, record actions and evaluate the next cycle against the prior baseline.

The aim is not to remove Excel from an operation that is comfortable with it. It is to stop managers repeating the same manual checking, pivoting and commentary-writing every reporting cycle.

Try the synthetic sample without preparing your own files →

Schema-aware operational intelligence

Use the operational data you already have. NaraOps works out how it is structured.

NaraOps profiles useful fields, infers measures, dimensions, identifiers and dates, and tests how related tables connect. You stay in control: change a mapping, exclude a field or edit a relationship at any time.

Understand unfamiliar columnsUseful fields remain available even when they do not match a predefined label.
Connect related tablesRelationship confidence, coverage and cardinality are checked before joined evidence affects analysis.
Ask questions across your schemaAsk NaraOps selects and calculates relevant local evidence, then sends compact verified context — not the raw workbook.