What are It Department metrics? Crafting the perfect It Department metrics can feel overwhelming, particularly when you're juggling daily responsibilities. That's why we've put together a collection of examples to spark your inspiration.
Copy these examples into your preferred app, or you can also use Tability to keep yourself accountable.
Find It Department metrics with AI While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.
Examples of It Department metrics and KPIs 1. Incident Response Time The average time it takes for the IT department to respond to an incident after it is reported.
What good looks like for this metric: 30 minutes to 1 hour
Ideas to improve this metric Implement automated alert systems Conduct regular training sessions Set up a 24/7 support team Streamline incident escalation processes Utilise incident management tools 2. First Contact Resolution Rate The percentage of IT issues resolved during the first contact with the user.
What good looks like for this metric: 70% to 80%
Ideas to improve this metric Enhance self-service tools and resources Improve knowledge base quality Conduct specialised training for support staff Implement a feedback loop for continuous improvement Use advanced diagnostic tools 3. System Uptime The percentage of time that IT systems are operational and available for use.
What good looks like for this metric: 99% to 99.9%
Ideas to improve this metric Regularly update and patch systems Implement high availability solutions Conduct regular system monitoring Perform routine maintenance checks Use redundant systems 4. User Satisfaction Score The average satisfaction rating given by users after IT services are provided.
What good looks like for this metric: 4.0 to 4.5 out of 5
Ideas to improve this metric Offer regular customer service training Obtain user feedback and act on it Enhance communication channels Implement a user-friendly ticketing system Provide regular updates to users 5. Mean Time to Repair (MTTR) The average time taken to fully repair an IT issue after it is reported.
What good looks like for this metric: 2 to 4 hours
Ideas to improve this metric Improve diagnostic procedures Use automated repair tools Maintain an updated inventory of spare parts Enhance collaboration between IT teams Conduct thorough post-incident reviews
← →
1. Data Accuracy Measures the percentage of data entries that are correct and error-free across the system
What good looks like for this metric: Above 95%
Ideas to improve this metric Implement regular data audits Use automated data validation tools Provide staff training on data entry accuracy Establish clear data entry guidelines Enable error-detection algorithms 2. Data Completeness Assesses the percentage of data records that are fully filled and not missing any critical fields
What good looks like for this metric: Above 90%
Ideas to improve this metric Conduct routine completeness checks Utilise automated form filling Standardise data requirements Regularly review data input processes Incentivise complete data entry 3. Data Timeliness Measures the speed at which data is updated or made available for processing
What good looks like for this metric: Within 24 hours
Ideas to improve this metric Automate data update processes Set clear timelines for data entry Monitor data latency regularly Establish a data steward for timely updates Prioritise data updates during peak times 4. Data Consistency Evaluates whether data is consistent across different databases and sources
What good looks like for this metric: Close to 100% consistency
Ideas to improve this metric Implement cross-system data comparisons Use master data management tools Regularly review data transformation processes Ensure consistent data entry formats Provide training for consistent data handling 5. Data Relevance Determines the degree to which data is relevant and useful for current business needs
What good looks like for this metric: Above 85% of data in use
Ideas to improve this metric Regularly review and update data policies Conduct user feedback sessions Align data selection with business objectives Utilise data analytics to assess relevance Remove outdated or redundant data regularly
← →
1. Process Time Reduction Measures the reduction in time taken to complete the billing process after automation compared to before.
What good looks like for this metric: 30% reduction in process time
Ideas to improve this metric Use programmable robotic process automation tools Integrate with existing accounting software Utilise cloud computing for scalability Streamline data entry with OCR technology Implement a database for template management 2. Error Rate in Billing Assesses the percentage of billing errors post-automation compared to manual processes.
What good looks like for this metric: Under 2% error rate
Ideas to improve this metric Implement validation checks Conduct regular training for software use Use automated reconciliation methods Regularly update software for accuracy Use real-time data error alerts 3. Cost Savings Calculates the reduction in costs due to automating the billing process.
What good looks like for this metric: 20% cost reduction
Ideas to improve this metric Optimise software licenses Reduce paper and printing expenses Automate repetitive tasks to reduce overtime Conduct a cost-benefit analysis regularly Invest in preventive maintenance 4. Employee Productivity Measures the increase in productivity of employees as a result of reducing manual billing tasks.
What good looks like for this metric: 15% increase in productivity
Ideas to improve this metric Reallocate time savings to skill development Schedule regular feedback sessions Use productivity tracking tools Encourage a culture of continuous improvement Provide resources for professional growth 5. Billing Accuracy Rate Monitors the percentage of bills processed accurately after automation.
What good looks like for this metric: 98% accuracy rate
Ideas to improve this metric Ensure comprehensive testing before full deployment Regular data audits Use machine learning for pattern recognition Integrate feedback loops for corrective action Keep detailed records of errors for analysis
← →
1. Latency Time taken for a transaction or processing a fall event from the input to the final output
What good looks like for this metric: 200-500 milliseconds
Ideas to improve this metric Optimize network bandwidth Utilise more efficient consensus algorithms Reduce data complexity in transactions Incorporate edge computing techniques Enhance processing speeds of nodes 2. Throughput Number of transactions processed within a given period
What good looks like for this metric: 10-100 transactions per second
Ideas to improve this metric Increase the number of nodes Upgrade node hardware Implement parallel processing techniques Optimize transaction validation methods Utilise sharding techniques 3. Security Breach Rate Number of successful breaches attempts per month
What good looks like for this metric: 0-1 breach per year
Ideas to improve this metric Regularly update encryption protocols Conduct routine security audits Implement multi-factor authentication Train staff on security awareness Utilise a robust incident response strategy 4. Scalability Ability to maintain performance as network size or data volume increases
What good looks like for this metric: Linear performance degradation with scale
Ideas to improve this metric Adopt more scalable consensus algorithms Reduce data redundancy Utilise cloud resources for storage Implement load balancing techniques Employ distributed ledger technology 5. Data Integrity Accuracy and consistency of data over its lifecycle
What good looks like for this metric: 99.9% integrity rate
Ideas to improve this metric Regularly verify data with hash functions Set permissions and roles for data access Utilise smart contracts for automatic validation Implement data replication strategies Conduct integrity checks at regular intervals
← →
1. Migration Completion Rate The percentage of iOS devices successfully migrated to Microsoft Intune
What good looks like for this metric: 90-95%
Ideas to improve this metric Develop a detailed migration plan Conduct pilot testing before full rollout Ensure adequate training for IT staff Engage in continuous monitoring and feedback Allocate sufficient resources for the project 2. Post-Migration Device Performance Measure the performance of devices post-migration, focusing on speed and application responsiveness
What good looks like for this metric: Performance increase of 10-20%
Ideas to improve this metric Optimize device settings during migration Update applications to the latest versions Conduct regular performance assessments Encourage employee feedback for improvements Monitor and address any reported issues promptly 3. Security Incident Reduction Track the number of security incidents after migration compared to before
What good looks like for this metric: Reduction of incidents by 30%
Ideas to improve this metric Enhance device security configurations Educate users about security best practices Implement regular security audits Continuous monitoring for any anomalies Use threat intelligence platforms 4. User Satisfaction Score Survey scores from users regarding their satisfaction with the new system
What good looks like for this metric: 70% satisfaction rate
Ideas to improve this metric Conduct user training sessions Offer a user-friendly interface Provide efficient troubleshooting support Incorporate user feedback into improvements Continuously update support materials 5. Network Access Success Rate The percentage of successful network access attempts post-migration
What good looks like for this metric: Above 95%
Ideas to improve this metric Ensure seamless network integration Update network policies for Intune compatibility Test network access at regular intervals Implement redundancy measures Provide support for network connectivity issues
← →
Tracking your It Department metrics Having a plan is one thing, sticking to it is another.
Having a good strategy is only half the effort. You'll increase significantly your chances of success if you commit to a weekly check-in process .
A tool like Tability can also help you by combining AI and goal-setting to keep you on track.
More metrics recently published We have more examples to help you below.
Planning resources OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:
Tability's check-ins will save you hours and increase transparency
The best metrics for Recruitment Performance Review