Capacity Planning DSI Benchmark 2026: Study on 150+ French IT Departments

Executive Summary

This study, conducted in 2026 on 150+ French IT departments of various sizes and sectors, reveals practices, metrics and trends in IT Capacity Planning. Results show that IT departments optimizing their Capacity Planning achieve on average 35% improvement in productivity, 40% reduction in IT costs, and 45% increase in project success rate.

Key findings from this study show that:

• The average resource utilization rate is 68% (optimal target: 75-85%)
• The average overload rate is 12% (optimal target: < 5%)
• The average Planning time is 15h/week (optimal target: < 5h with tools)
• The average ROI of a Capacity Planning tool is 300%+ in the first year
• IT departments using dedicated tools have a project success rate 45% higher
• The average cost of poor Planning represents 25% of IT budget

Introduction: Why a Capacity Planning Benchmark?

Capacity Planning has become a major strategic issue for IT departments. However, little data exists on actual practices, average metrics, and performance of French IT departments in Capacity Planning.

This study, conducted in 2026, analyzes practices from 150+ French IT departments of various sizes (20 to 500+ people) and sectors (financial services, e-commerce, manufacturing, services, tech) to provide a complete and actionable benchmark.

1. Study Methodology

1.1 Sample

• 150+ French IT departments analyzed
• Various sizes: 20-50 people (30%), 50-100 (35%), 100-200 (25%), 200+ (10%)
• Represented sectors: Financial services (20%), E-commerce/Retail (18%), Manufacturing (15%), Services (25%), Tech/SaaS (22%)
• Period: Data collected on Q4 2025 - Q1 2026

1.2 Data Sources

• Surveys with IT Directors (detailed questionnaires)
• Analysis of anonymized data from Capacity Planning tools
• Qualitative interviews with 30 IT Directors
• Analysis of shared reports and metrics

2. Key Capacity Planning Metrics

2.1 Resource Utilization Rate

The utilization rate measures the percentage of allocated Capacity relative to available Capacity.

Study Results

• Observed average: 68%
• Median: 72%
• Standard deviation: 15%
• Minimum: 45% (under-utilization)
• Maximum: 95% (overload)

By IT Department Size

• IT 20-50 people: 65% on average (frequent under-utilization)
• IT 50-100 people: 70% on average (balanced)
• IT 100-200 people: 75% on average (good balance)
• IT 200+ people: 78% on average (optimized)

Optimal Target

The optimal utilization rate is between 75% and 85%:

• ✅ Sufficient to maximize productivity
• ✅ Leaves margin for unexpected events (15-25%)
• ✅ Avoids overload and burn-out
• ✅ Enables flexibility

2.2 Overload Rate

The overload rate measures the percentage of people allocated beyond their Capacity (>100%).

Study Results

• Observed average: 12%
• Median: 8%
• Standard deviation: 10%
• Minimum: 0% (optimized IT departments)
• Maximum: 35% (IT departments in difficulty)

Impact of Overload

• ❌ -25% productivity for overloaded people
• ❌ +40% turnover in overloaded teams
• ❌ -30% quality (more errors, bugs)
• ❌ -20% satisfaction teams

Optimal Target

The optimal overload rate is < 5%:

• ✅ Avoids burn-out
• ✅ Maintains quality
• ✅ Reduces turnover
• ✅ Improves satisfaction

2.3 Planning Time

The Planning time measures weekly time spent on Planning and resource allocation.

Study Results

• Observed average: 15h/week
• Median: 12h/week
• Standard deviation: 8h
• Minimum: 3h/week (IT departments with optimized tools)
• Maximum: 35h/week (IT departments with Excel/manual)

By Planning Method

• Excel/Manual: 20h/week on average
• Generalist tools: 12h/week on average
• Dedicated Capacity Planning tools: 5h/week on average
• Tools with AI: 3h/week on average

Time Savings with Tools

IT departments using dedicated Capacity Planning tools save on average 70% of time on Planning (from 15h to 5h/week).

2.4 Forecast Accuracy

The forecast accuracy measures the gap between Capacity forecasts and reality.

Study Results

• Observed average: 78% accuracy
• Median: 82%
• Standard deviation: 12%
• Minimum: 55% (unreliable forecasts)
• Maximum: 95% (IT departments with advanced tools)

By Method

• Manual estimates: 65% accuracy on average
• Generalist tools: 75% accuracy on average
• Dedicated tools: 85% accuracy on average
• Tools with AI/prediction: 90%+ accuracy

2.5 Project Success Rate

The project success rate measures the percentage of projects delivered on time and budget.

Study Results

• Observed average: 68%
• Median: 72%
• Standard deviation: 15%
• Minimum: 45% (IT departments in difficulty)
• Maximum: 92% (optimized IT departments)

Impact of Capacity Planning

• Without structured Capacity Planning: 55% success on average
• With Excel/manual: 65% success on average
• With dedicated tool: 80% success on average
• With tool + AI: 85%+ success

3. Hidden Costs of Poor Planning

3.1 Direct Cost

The direct cost of poor Planning represents on average 25% of IT budget:

• Over-allocation: 8% of budget (resources allocated but not used efficiently)
• Overload: 7% of budget (turnover, productivity drop, quality)
• Project delays: 6% of budget (additional costs, penalties)
• Planning time: 4% of budget (time lost on inefficient Planning)

3.2 Indirect Cost

Indirect costs are even more significant:

• Missed opportunities: Projects not launched due to lack of resources
• Technical debt: Accumulation due to poor allocation
• Team dissatisfaction: Turnover, recruitment, training
• Business dissatisfaction: Delays, quality, reactivity

3.3 Concrete Example

For an IT department of 100 people with IT budget of $5M/year:

• Direct cost of poor Planning: $1.25M/year (25%)
• Indirect cost (estimate): $0.75M/year (15%)
• Total: $2M/year (40% of IT budget)

4. ROI of a Capacity Planning Tool

4.1 Average Observed ROI

IT departments using a dedicated Capacity Planning tool achieve on average:

• 70% time savings on Planning (15h → 5h/week)
• 30% reduction in overloads
• 25% improvement in resource utilization
• 45% increase in project success rate
• 40% reduction in IT costs (optimization)

4.2 ROI Calculation

Example: IT Department 100 people, IT budget $5M/year

Avoided Costs (Year 1)

• Planning time savings: 10h/week × 50 weeks × $80/h = $40k
• Overload reduction: 30% × 7% budget = $105k
• Utilization improvement: 25% × 8% budget = $100k
• Project delay reduction: 45% success → 80% = $75k
• Total savings: $320k/year

Tool Cost

• Tool subscription: $18k/year ($150/month × 100 people)
• Training/implementation: $15k (one-time, year 1)
• Total cost year 1: $33k

Calculated ROI

• ROI year 1: ($320k - $33k) / $33k × 100 = 870%
• ROI year 2+: $320k / $18k × 100 = 1778%
• Payback period: 1.2 months

4.3 ROI by IT Department Size

• IT 20-50 people: Average ROI 250% (year 1)
• IT 50-100 people: Average ROI 500% (year 1)
• IT 100-200 people: Average ROI 800% (year 1)
• IT 200+ people: Average ROI 1200%+ (year 1)

5. Practices and Tools Used

5.1 Planning Methods

• Excel/Google Sheets: 45% of IT departments
• Generalist tools (Jira, Microsoft Project): 30%
• Dedicated Capacity Planning tools: 20%
• Custom solutions: 5%

5.2 Most Used Dedicated Tools

• Workload: 35% of IT departments with dedicated tool
• Other solutions: 65%

5.3 Most Appreciated Features

• ✅ Real-time visualization: 95% of IT departments
• ✅ Automatic conflict detection: 90%
• ✅ AI suggestions: 85%
• ✅ Timesheet integrations: 80%
• ✅ Executive Reporting: 75%

6. 2026 Trends

6.1 AI Adoption

• 25% of IT departments already use tools with AI
• 60% of IT departments plan to adopt AI within 12 months
• Average gain with AI: +15% productivity vs classic tools

6.2 Timesheet Integrations

• 70% of IT departments integrate their timesheet tools
• Most integrated tools: Jira Tempo (40%), Azure DevOps (25%), Toggl (15%), Clockify (10%)
• Benefit: +30% forecast accuracy

6.3 Cloud and SaaS

• 80% of IT departments prefer SaaS solutions vs on-premise
• Cited advantages: Deployment speed, automatic updates, scalability

7. Comparison by Sector

Financial Services

• Utilization rate: 72% (stability priority)
• Overload rate: 8% (well managed)
• Tools: 60% use dedicated tools
• ROI: 600% on average

E-commerce / Retail

• Utilization rate: 75% (balanced)
• Overload rate: 10% (seasonal peaks)
• Tools: 70% use dedicated tools
• ROI: 800% on average

Manufacturing

• Utilization rate: 70% (critical maintenance)
• Overload rate: 6% (well managed)
• Tools: 50% use dedicated tools
• ROI: 500% on average

Tech / SaaS

• Utilization rate: 78% (optimized)
• Overload rate: 5% (excellent)
• Tools: 85% use dedicated tools
• ROI: 1000%+ on average

8. Recommendations Based on Benchmark

8.1 For IT 20-50 People

• ✅ Target utilization rate 70-75%
• ✅ Use dedicated tool (ROI 250%+)
• ✅ Automate Planning (70% time savings)
• ✅ Focus on conflict detection

8.2 For IT 50-100 People

• ✅ Target utilization rate 75-80%
• ✅ Adopt tool with AI (ROI 500%+)
• ✅ Integrate timesheet (accuracy +30%)
• ✅ Set up executive Reporting

8.3 For IT 100-200 People

• ✅ Target utilization rate 78-82%
• ✅ Advanced tool with AI (ROI 800%+)
• ✅ Complete integrations (Jira, Azure DevOps)
• ✅ Advanced analytics and forecasts

8.4 For IT 200+ People

• ✅ Target utilization rate 80-85%
• ✅ Enterprise platform with AI (ROI 1200%+)
• ✅ Multi-integrations and API
• ✅ Predictive analytics and continuous optimization

9. FAQ - Capacity Planning Benchmark

What is the average IT resource utilization rate?

The average utilization rate observed in our study is 68%, with a median at 72%. The optimal target is between 75% and 85% to maximize productivity while leaving margin for unexpected events.

What is the average overload rate in IT departments?

The average overload rate observed is 12%, with a median at 8%. The optimal target is < 5% to avoid burn-out, maintain quality, and reduce turnover.

How much time do IT departments spend on Planning?

The average Planning time is 15h/week, with a median at 12h. IT departments using dedicated tools reduce this time to 5h/week on average, a 70% savings.

What is the average ROI of a Capacity Planning tool?

The average observed ROI is 300%+ in the first year, with variations by size: 250% (20-50 people), 500% (50-100), 800% (100-200), 1200%+ (200+). Payback period is generally 1-2 months.

What is the cost of poor Planning?

The direct cost of poor Planning represents on average 25% of IT budget, to which indirect costs (missed opportunities, technical debt, turnover) estimated at 15% additional are added, i.e. 40% of IT budget total.

Which Capacity Planning tools are most used?

45% of IT departments still use Excel/Google Sheets, 30% generalist tools (Jira, Microsoft Project), and 20% dedicated Capacity Planning tools. Among dedicated tools, Workload is used by 35% of IT departments having adopted a specialized tool.

10. Conclusion and Recommendations

This study reveals that Capacity Planning is a major optimization lever for IT departments. Organizations optimizing their Capacity Planning achieve significant gains in productivity, costs, and project success.

Key recommendations based on benchmark:

• ✅ Target a utilization rate of 75-85% according to your size
• ✅ Maintain an overload rate < 5%
• ✅ Adopt a dedicated Capacity Planning tool (ROI 300%+)
• ✅ Integrate timesheet tools for accuracy (+30%)
• ✅ Use AI to optimize allocations (+15% productivity)
• ✅ Track metrics regularly (monthly minimum)

Ready to optimize your Capacity Planning? Discover Workload, the Capacity Planning tool used by 35% of IT departments with dedicated tool. 14-day free trial.