MHD · ACERE People & Culture

Pulse Survey Room

A living read of the employee engagement survey — satisfaction pillars, compensation sentiment, career growth, and P&C trust, with visual diagnostics by division and tenure.

Sample data · 5 responses
Load the full survey export
Drop in the .xlsx HR sends over — parsing happens in the browser. Nothing is uploaded. Charts, heatmaps and comment tags update instantly.
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Analyst briefing

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Engagement pillars

Average score plus the share of favorable (4–5), watch (3) and at-risk (1–2). Tick mark = 4.0 benchmark.

Favorable 4–5 Watch 3 At risk 1–2

Preferred voice channels

Weighted by rank — 1st choice scores highest. Share of first-place votes shown underneath.

Compare two slices

Put two divisions or two tenure bands on the same pillars. Gaps larger than 0.3 are worth a conversation.

Score distribution

Every numeric answer in the current filter, bucketed 1 through 5

Where to act

Lowest and highest rated statements in this slice — act on the floor, protect the ceiling

Every question, ranked

Click any statement to open its distribution, slice breakdown, and linked comments. Tick = 4.0 benchmark.

Division × theme heatmap

Category averages by division. Darker green is stronger; red is a pressure point worth a conversation.

By division

Overall satisfaction index and favorability for each division in the current tenure filter

By tenure

Satisfaction and favorability by years of service — watch the newest and longest-tenured cohorts

Individual responses

Every respondent's ID next to their scores — search by ID or division, sort any column, click a row for that person's full scorecard

Comment intelligence

Auto-tagged sentiment and themes across every written comment

AI analysis

Not configured

This dashboard never holds your OpenRouter API key — it calls a small Cloudflare Worker you deploy yourself, which keeps the key as a server-side secret. The Worker URL and model name above are saved only in this browser.

AI-powered comment analysis

Replaces the keyword-based sentiment/theme tags below with a real language-model read of each comment — much better with sarcasm, mixed Arabic/English text, and nuance. Re-run this any time after uploading new data.

AI action plan

Turns the lowest-scoring questions and negative comment themes in the current filter into a short, prioritized list of concrete next steps — a first draft for P&C, not a final decision.

Ask the data

Ask a plain-language question about the current filtered view. The model only sees a data summary — never the raw employee-level file.

Open comments

Free-text feedback submitted with the survey