OT Bill Management / Automation

01Business problem

Preparing an overtime bill was a repetitive, multi-step manual calculation: find the employee’s pay, work out an hourly rate, add up the hours day by day, then produce the bill in the required format. Errors were easy to make and hard to spot.

This is overtime billing, not payroll: the system prepares one kind of bill from a small set of inputs.

02Existing workflow

The bill is derived from two inputs: the employee’s profile and the hours worked each day.

1. Operational inputOvertime worked, recorded per day.
2. OT / bill dataEmployee profile plus daily from / to hours.
3. Business rulesHourly rate is basic pay divided by 104, rounded up.
4. CalculationCumulative day-by-day hours multiplied by the rate.
5. RecordA saved bill per employee per month.
6. ReportA4 print, an all-bills view and a dashboard.

1. Manual multi-step processFind the pay, work out the rate, add the hours by hand.
2. Single data-entry workflowEmployee profile once, hours per day.
3. Automated calculationRate, cumulative total and amount in words.
4. A4 billPrint-ready output.

The software is built around the process, not the other way around. Designed to reduce repetitive spreadsheet-based work.

03My approach

I encoded the rate rule once, at the employee-profile level, and made daily hours the only thing entered per bill. Everything else, from the hourly rate to the cumulative total and the amount in words, is derived, so the bill cannot disagree with its inputs.

1. Real operational workflowHow overtime bills were prepared.
2. Business rulesRate derivation and cumulative hours.
3. Structured dataEmployee profiles, dated hour entries, bills.
4. Calculation logicRate, totals and amount in words.
5. Web interfaceThree-step bill flow, Bengali-language UI.
6. ReportsA4 bill, all-bills list, dashboard.

04System design

Employee and bill records live in Firestore behind sign-in, with a local-storage fallback so the tool still works if the connection drops.

1. UserAdmin or employee, signing in with an ID.
2. Web interfaceBengali-language, three-step bill flow.
3. Business rules and calculationHourly rate and cumulative totals, in the browser.
4. Firebase Authentication and Cloud FirestoreAccounts, employee records and bills, with a local-storage fallback.
5. OutputPrint-ready A4 bill.

05Key features

• Employee databaseProfiles with basic pay.
• Automatic hourly rateDerived from basic pay; no manual rate entry.
• Daily overtime entryFrom and to hours per day with running totals.
• Amount in wordsPrinted on the bill.
• Saved description templateReusable work description for the branch.
• Bill historyAll bills in one list.
• DashboardSummary of employees, bills, total hours and amount.
• Admin and employee sign-inRole-based access.
• Offline fallbackLocal storage when the connection is unavailable.
• Print-ready A4 billPrint-ready A4 layout.

06Technology

Frontend

HTML, CSS and JavaScript with no framework; Bengali-language interface.

Backend and data

Firebase Authentication and Cloud Firestore, with a local-storage fallback.

Deployment

Cloudflare Pages.

Development

Git, GitHub, AI-assisted development.

07My role

1. Operations Specialist
2. Business Analyst
3. System Designer
4. AI-Assisted Developer
5. Tester
6. Deployer

• IdentifiedA repetitive, multi-step bill calculation prone to mistakes.
• StudiedHow overtime bills were prepared and checked.
• DefinedHourly rate is basic pay ÷ 104, rounded up; hours accumulate day by day.
• DesignedThe three-step flow and the data model.
• BuiltThe web app, with AI-assisted implementation under my direction.
• TestedCumulative logic against real edge cases; there is no automated test suite.
• DeployedThe working system on Cloudflare Pages, then iterating.
• IteratedRefined through use.

Built with AI-assisted implementation under my direction. I own the requirements, business rules, validation, testing and deployment; I did not hand-write every line, and AI did not decide what the system should do.

08Outcome and business value

• In daily useUsed for overtime bill preparation.
• Faster to prepareHours are entered once instead of repeating the calculation for every bill. No time saving has been measured, so none is claimed.
• Fewer manual stepsReplaced a repetitive manual calculation with a single data-entry step and an instant bill.
• More consistentImproved consistency of overtime calculations and records.
• Designed to reduce errorsDeriving the rate and totals automatically is designed to reduce calculation mistakes.
• ReusableTurned a workflow into a reusable web-based system.