BTP Work Time Tracking Application: Dropia eliminates paper timesheets
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5 minMin Read
Construction work time tracking application: how Dropia permanently replaces paper timesheets. Time savings, reliability, legal compliance.
The paper time sheets are still used by 60% of construction companies in 2025. However, they represent a pit of time, money, and errors. The Dropia application replaces them definitively, with immediate and measurable benefits.
The hidden cost of paper time sheets
Cost 1: Lost time (monetizable)
For a company of 10 employees:
Worker time:
Filling out the sheets: 2 min/day × 10 × 20 days = 400 min/month
Searching for lost sheets: 15 min/week = 1h/month
Total: 7h40/month
Supervisory time:
Collecting the sheets: 30 min/week = 2h/month
Verification and correction: 1h/week = 4h/month
Total: 6h/month
Administrative time:
Deciphering: 45 min/week = 3h/month
Data entry: 2h/week = 8h/month
Corrections and adjustments: 1h/week = 4h/month
Total: 15h/month
GENERAL TOTAL: 28h40 per month
Valued at an average hourly cost of €35/h: €1,003 in monthly cost
Cost 2: Errors and their consequences
Entry errors: 5-10% of data
Hours incorrectly assigned to projects → Distorted profitability analysis
Forgotten overtime → Disputes with employees
Meta description: Automated analysis of construction hours with Dropia: project productivity control, gap detection, real-time profitability optimization.
Controlling hours is fundamental in construction. Each incorrectly assigned hour, each unproductive hour directly impacts profitability. Dropia fully automates hour analysis, transforming time sheets into actionable intelligence to optimize your productivity.
Why hour analysis is crucial in construction
Hours account for 40-60% of a project's cost
In most construction projects:
Labor: 40-60% of total cost
Supplies: 30-45%
Other costs: 10-20%
A 10% variation in hours therefore has more impact than a 10% variation in supplies. It’s the primary profitability lever.
Every hour counts
On a project budgeted at 500 hours:
10% excess hours = 50 additional hours
At €45/h charged = €2,250 in extra costs
On a margin of €10,000, that’s -22.5% profitability
Productivity varies greatly
Between workers, between tasks, between projects:
A senior worker can be 30-50% more productive than a junior
A disorganized task can take twice as long as necessary
A project with good access is 20% faster
Identifying these variations allows for optimizing assignments and organization.
The limits of manual hour analysis
Time-consuming
Manually analyzing 500 hours spread across 5 employees and 10 tasks:
Consolidating time sheets: 30 min
Calculating totals by employee and by task: 20 min
Comparison with budget forecasts: 20 min
Identifying discrepancies: 15 min
Producing the report: 15 min
Total: 1h40
For 10 projects per week: 16h of administrative work.
Always behind
Manual analysis is best done weekly, often monthly. Productivity issues are detected 1-4 weeks later.
Inaccurate
Between entry errors, incorrectly assigned times, and oversights, the reliability of manual analysis is rarely optimal.
How Dropia automates hour analysis
Automatic collection and intelligent assignment
Instant mobile time tracking
Each worker clocks in from their smartphone with the Dropia application:
Selecting the project (optional geolocation)
Selecting the task
Start and end of work
Total time: 10 seconds
Automatic assignment
Hours are automatically:
Assigned to the correct project
Linked to the correct task
Attributed to the correct worker
Valued at the specific charged hourly cost
No re-entry, no assignment errors.
Automatic calculations in real time
Dropia instantly calculates:
By project:
Total hours consumed vs budget
Total labor cost vs forecast
Distribution by task
Distribution by worker
Discrepancies in hours and euros
By task:
Actual hours vs budgeted hours
Productivity ratio (budgeted/actual)
Actual cost vs forecast cost
Identification of divergent tasks
By worker:
Hours worked on each project
Relative productivity by type of task
Comparison with team average
Development over time
Automatic comparative analyses
Inter-project
For similar projects:
Which project consumes the most/least hours?
Why these differences?
What lessons for the next ones?
Inter-periods
Trends in productivity over time:
Is productivity improving?
Impact of training
Effect of experience
Inter-workers
Anonymized benchmarking:
Who are the most productive by type of task?
Who needs training or support?
Optimizing future assignments
The 5 key analyses automated by Dropia
Analysis 1: Difference between budgeted vs actual hours by task
Automatic table:
Immediate identification: major problem with the framing
Action: In-depth investigation of this task
Which worker? Entire team underperforming or an individual?
Which period? Recent problem or ongoing from the start?
What cause? Technical difficulty, organization, method?
Analysis 2: Productivity by worker on project
Automatic table for the "Villa Durand" project:
*Productivity = ratio between expected and actual output
Insights:
Jean overperforming, candidate for complex projects
Luc underperforming on framing, needs training or reassignment
Marc slightly below on framing, investigate why
Analysis 3: Temporal evolution of hour consumption
Automatic graph
Curve showing week by week:
Hours consumed (blue bars)
Proportional budgeted hours (green line)
Immediate visual detection:
Weeks 1-3: consumption in line
Week 4: consumption spike (+35%) → Investigation
Weeks 5-6: return to normal
Correlation with events
Dropia allows annotating the graph:
Week 4: Delivery of materials delayed → unproductive waits
Explanation for the discrepancy found
Lesson: improve delivery coordination
Analysis 4: Actual hourly cost by project
Automatic comparative table:
Cause analysis for Building C:
Dropia automatically details:
60% of the time: senior workers (high cost)
40% of the time: junior workers (normal cost)
Explanation: Complex project requiring more seniors than expected
Action: Future project estimates will integrate this realistic ratio
Analysis 5: Occupancy rate and unproductive time
Automatic analysis over a monthly period:
Total available hours: 12 workers × 151h = 1,812h
Automatic distribution by Dropia:
Billable project hours: 1,520h (84%) ✅
Travel hours: 145h (8%) ⚠️
Training hours: 40h (2%)
Waiting/unproductive hours: 107h (6%) 🔴
Insight: 6% of unproductive hours = 107h × €45 = €4,815 of cost without value
Automatic investigation of causes:
Waiting for materials: 45h
Unresolved technical issues: 28h
Poor coordination: 34h
Identified corrective actions:
Improve delivery management (savings: ~€2,000/month)
Enhance technical support (savings: ~€1,250/month)
Automatic alerts on hour analysis
Alert for exceeding hours by task
Trigger: hours consumed > budget + 10%
Notification sent to the project manager: "⚠️ Task 'Electricity' project Villa Bertrand: 88h consumed for 75h budgeted (+17%)"
Required action: Immediate investigation
Alert for abnormal productivity
Trigger: worker productivity < 75% for 3 consecutive days
Notification: "⚠️ Worker Luc: productivity 68% on project Extension for 3 days"
Possible actions:
Check if technical or organizational problem
Offer assistance or training
Temporarily reassign
Alert for excessive unproductive time
Trigger: non-billable hours > 10% of total time
Weekly notification: "⚠️ Week 42: 12% of unproductive hours (vs 6% usual)"
Investigation of causes to eliminate sources of waste.
Concrete case: Optimization through hour analysis
Project "Office Renovation" - Budget 850h
Situation after 400h consumed (47% of budget)
The automatic analysis Dropia reveals:
Physical progress: only 38% → Unfavorable gap of 9 points
Detailed task analysis:
✅ Demolition: 95h/100h budgeted (-5%) - OK ⚠️ Plumbing: 78h/70h budgeted (+11%) - Slight excess 🔴 Electricity: 125h/90h budgeted (+39%) - Major problem! ✅ Plastering: 102h/110h budgeted (-7%) - OK
Electricity analysis (the problem):
By worker:
Senior electrician: 70h (productivity 105%) ✅
Electrical helper: 55h (productivity 65%) 🔴
By period:
Weeks 1-2: normal productivity
Weeks 3-5:{
