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Self-Review (述职报告) Template: Structure, Tips and a Full Example

A self-review (述职报告) is your own account for the review committee: what the role is for, what you delivered against goals, how you grew, where you fell short and what you aim at next. It is judged on evidence, so each claim wants a figure or a named deliverable.

Get these right before you write

  1. 1State the role's purpose in one sentence before listing what you did; results only make sense against it.
  2. 2A table of goal, result, evidence is faster to judge than paragraphs.
  3. 3Growth means a capability you did not have a year ago, shown by something you did with it.
  4. 4Shortfalls stated by you cost less than shortfalls found by them.

Structure

The document opens with these headings and blanks.

Self-review — [name], [role], [year]
##Role and responsibilities
[...]
##Key results against goals
[goal] | [result] | [figure] |
##Growth this year
[...]
##Where I fell short
[...]
##Goals for next year
[...]

A complete example

Written by the AI from this brief, exactly as the workbench would write yours:

The 2026 annual self-review of Wang Fang, customer-support team lead: the role runs an 8-person team across email, chat and phone; goals were CSAT 4.5, median first response under 8 minutes, staff turnover under 20%; delivered CSAT 4.6, 6 minutes, turnover 12%; grew in data analysis (built the weekly dashboard) and in cross-team work with payments; fell short on the knowledge-base launch (two months late); 2027 goals: automate first replies for the top five issues, train two deputies.

2026 Annual Self-Review: Wang Fang, Customer Support Team Lead

My Role and Responsibilities

I lead an eight-person customer-support team covering three channels: email, chat and phone. My responsibilities over the year included:

  • Setting and tracking the team's service targets (customer satisfaction, response time, retention).
  • Staffing, scheduling and coaching across all three channels.
  • Reporting on team performance to management.
  • Representing support in cross-team work, in particular with the payments team.
  • Owning support projects, including the knowledge-base launch.

Key Results Against 2026 Goals

All three headline goals for the year were met or exceeded.

Goal Target Delivered Status
Customer satisfaction (CSAT) 4.5 4.6 Exceeded
Median first response time Under 8 minutes 6 minutes Exceeded
Staff turnover Under 20% 12% Exceeded

CSAT: 4.6 against a target of 4.5

The team closed the year above the satisfaction target across email, chat and phone. [source needed: channel-level CSAT breakdown]

Median first response: 6 minutes against a target of under 8

We brought the median first response to 6 minutes, two minutes inside the target. The weekly dashboard (see below) made it possible to see response-time drift early and rebalance staffing across channels before it affected customers.

Turnover: 12% against a target of under 20%

Team turnover came in at 12%, well under the 20% ceiling. Keeping the team stable through the year supported both the CSAT and response-time results, since experienced agents resolve issues faster and more consistently.

How I Grew This Year

Data analysis

I built the team's weekly performance dashboard. It now gives us a regular view of CSAT, first response times and workload by channel, and it has become the basis for our staffing decisions and for my reporting to management. Building it required me to develop skills in working with our support data that I did not have at the start of the year.

Cross-team collaboration

I worked much more closely with the payments team this year. [figure needed: outcome of payments collaboration, e.g. issue volume reduced or process agreed] Working across team boundaries has improved how quickly payment-related customer issues are resolved and has given me a better understanding of how other parts of the business operate.

Where I Fell Short

Knowledge-base launch: two months late

The knowledge-base launch was my main project shortfall this year. It was delivered two months behind schedule. [source needed: planned vs. actual launch dates and the main causes of the delay]

What I take from this:

  • I should have raised the schedule risk earlier rather than trying to absorb it within the team.
  • Project milestones needed to be tracked with the same discipline I applied to the operational metrics on the dashboard.
  • Launching later meant the team spent longer answering repeat questions manually, which is directly relevant to next year's automation goal.

Goals for 2027

1. Automate first replies for the top five issues

Build automated first responses for the five most common customer issues across email and chat. This builds on the now-launched knowledge base and on the dashboard data that identifies which issues recur most.

  • Success measure: [figure needed: target share of first replies automated, or target reduction in agent-handled volume]
  • Expected benefit: faster first responses and more agent time for complex cases.

2. Train two deputies

Develop two team members into deputies who can run the team's day-to-day operations in my absence.

  • Success measure: [figure needed: date by which each deputy covers a full rota independently]
  • Expected benefit: a more resilient team, clearer growth paths for staff, and more of my own time freed for cross-team and project work, which should also reduce the risk of project delays like this year's knowledge-base launch.

Closing

2026 was a year in which the team exceeded every operational target and in which I grew as a manager in both data and cross-team work. The late knowledge-base launch is the clear lesson, and the two 2027 goals are chosen to build on what went well while addressing that gap.

Names, figures and dates in the example are made up for illustration.

How it works

  1. 1Open the template: a document with the skeleton and the brief appears.
  2. 2Add one line about your case to the brief, or attach your notes as sources, and press First draft.
  3. 3Edit directly, or ask the AI to tighten, expand or translate any passage; every AI change is reviewed before it lands.

Questions

Can I use the example as it is?
The example shows the shape and tone; its names and figures are made up. Open the template and give the AI your own facts, and it writes yours in the same shape.
Does it work in English and Chinese?
Yes. The document is written in the language of your brief, and any passage can be translated afterwards.
Is it free?
Writing is billed by the tokens used, usually a few credits per draft; the template, the skeleton and the editor cost nothing.

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