Make improvement a culture, evaluation fair — daily-report-driven management
A business-improvement package built around the daily report. Each day's PDCA becomes an improvement loop, and the accumulated facts become the basis for evaluating by evidence rather than impression. Your coaching policy becomes the axis of the weekly AI review and 1-on-1s, aligning what the company values with how people are evaluated. AI only drafts and hints; the final decision is yours.
Team Demo Sales Team / Name Sato (Sales) / Sat, August 15, 2026
Each day's report is itself a PDCA loop. You make “improvement as the norm” stick through daily structure rather than special training. Approvals and missing-report alerts sit on one screen, so a manager's overhead stays minimal.
The objective facts that pile up in the reports become the basis for evaluation. You can evaluate on evidence rather than memory or impression, and members see clearly what they are judged on.
The coaching policy you set — what the company cares about — becomes the axis of weekly reviews and 1-on-1s. What the company values and what people are evaluated on line up, and development points in one direction.
P — Plan
In the morning, enter today's goal to start the day (drafts are saved).
D — Do / C — Check
In the evening, enter what you did and your reflection.
A — Act / Next-day P
Write it yourself (growth mode). Stuck? AI offers a draft or a hint.
Approve → Record
On approval, everyone's reports are written to the sheet in one call. That accumulation later becomes the evidence for fact-based evaluation. The raw data on our server is erased immediately.
No sign-up needed. These are the actual daily-report, approval and look-back screens. To try them hands-on, use "Try it free (demo)" below.
Team Demo Sales Team / Name Sato (Sales) / Sat, August 15, 2026
AI summarizes how well the company's education policy aligns with actual behavior (report facts) in this period. It is a draft and suggestion; the final evaluation is made by a human.
A feature of Evaluation Pro (paid plan) — this is a demo sample
Over the last 90 days, Sato's actions largely align with the company's guiding policy. No major gap.
Adjusting call times and turning reflections (C) into concrete next-day improvements fits the "learn from action" policy.
Proposal prep tends to take a bit long, a small gap against the "speed first" policy.
A good talking point: review templates and prioritization together to speed up proposal prep.
* This is an AI draft and suggestion. The final evaluation is made by a human.
The facts accumulated in the reports (P/D/C/A) become the basis for evaluation. Because you evaluate on actual actions and reflections rather than memory or impression, it depends far less on subjectivity. Decide the coaching policy first, and the points to praise and to work on fall out along that policy.
In a spreadsheet inside the customer's own Google Drive. Our server keeps the raw data for at most 24 hours and erases it on approval.
The improvement and next-day plan fields are normally blank for the employee to fill in (growth mode). AI only offers drafts or hints; the final call is theirs.
It's priced so a front-line manager can adopt it instantly from a department discretionary budget.