The IT and HR Playbook for Measuring and Improving Operational Efficiency

Your IT team struggles through a backlog of support tickets. Your human resources (HR) department spends hours screening applicants. Across the enterprise, employees reenter data into disconnected systems—time that could be spent on more strategic work. 

What starts as a minor inefficiency in one department can ripple throughout your organization, draining time, resources, and employee satisfaction. And the longer these inefficiencies persist, the harder they become to see, measure, and fix.

Today, agentic AI—AI that can reason, plan, and take autonomous action across systems—can give IT and HR leaders a better way to spot friction and streamline workflows. By connecting systems, surfacing insights, and reducing repetitive work by taking autonomous action, these tools turn everyday operations into a continuous improvement loop. In this guide, you’ll learn what operational efficiency really means, how to measure it, and how to use AI-driven strategies to strengthen performance across every team in your organization.

What is operational efficiency?

Operational efficiency is the ability to deliver maximum output and value with the least possible input of time, resources, and cost, without compromising quality or employee experience. 

Improving your operational productivity requires adaptability and resilience: efficient operations sustain performance during change (new tools, org shifts, demand spikes) through streamlined processes and integrated systems. 

However, workplace efficiency isn’t just an Operations, IT, or HR issue. An outdated system, cumbersome workflow, or manual process in any department could disrupt business operations company-wide, so it’s important to understand efficiency both within and across departments, processes, and systems too. 

For example, poor digital experiences (whether it’s a slow support system or disconnected HR platform) can frustrate employees and even drive turnover, linking efficiency directly to retention and satisfaction.

How is operational efficiency different from productivity?

Productivity measures how much work gets done with the resources available, like tickets closed or employees onboarded. Efficiency measures how well that work gets done while using as few resources as necessary—and whether outcomes align to strategic goals and employee satisfaction (effectiveness vs. efficiency).

Inefficiency can have a widespread impact. According to one study, 64% of organizational projects are delayed by workflow bottlenecks, communication gaps, or other operational issues, showing how quickly small inefficiencies can compound across an entire enterprise, wasting time, money, and employee energy.

As an IT or HR leader, you’re in a unique position to drive change. You oversee the systems every employee relies on—from software provisioning to payroll to onboarding—and face growing pressure to do more with less. Many are now turning to AI to streamline work, eliminate friction, and drive results across the organization.

The link between efficiency and operational excellence

Operational excellence grows out of sustained operational efficiency: when people, business processes, and technology work together to deliver consistent, high-quality results. 

When efficiency becomes part of an organization’s culture, teams spend less time on repetitive tasks and more time driving innovation and value. The benefits extend across every department and include:

• Lower costs through smarter resource allocation
• Faster, data-driven decisions that remove bottlenecks
• Higher employee satisfaction from simpler, more seamless workflows
• Improved productivity and performance across teams

Achieving this level of excellence requires more than new tools. It takes accurate measurement, transparency between departments, and a shared commitment to continuous improvement. It also depends on strong operations management and engagement with stakeholders across departments to ensure everyone who influences employee experience is aligned on common goals and metrics.

When efficiency data is transparent, excellence becomes scalable. 

Learn to improve engagement, productivity, and culture in the Ultimate Guide to Measuring Employee Experience and Productivity.

Key operational efficiency metrics

To improve efficiency, start with visibility. You need consistent, reliable data to give everyone a shared baseline—one source of truth to spot friction, track performance, and prioritize improvements.

Next, focus on technology and integration. Automation and connected systems eliminate manual handoffs and duplicate effort, transforming fragmented workflows into straight-through processes. The result: higher quality and more output with fewer resources.

Finally, make efficiency measurable. Track metrics like cycle time, time to resolution, first-contact resolution rate, automation rate, error rate, and cost per transaction—and connect them directly to employee experience and customer outcomes.

Output-to-input ratios

The output-to-input ratio measures how much value a team or organization generates from the resources it uses. To calculate it, divide the value of your results by the cost of those resources:

Operational Efficiency Ratio = Value of Outputs ÷ Cost of Inputs

This simple equation gives leaders a way to compare how effectively different teams turn effort into impact.

IT metrics: 

• Operating expenses: Measure total operating expenses relative to the total revenue. Consolidate redundant systems, optimize software licenses, or use agentic AI solutions like Moveworks to simplify employee support and reduce overhead. 
• Revenue per employee: Gauge workforce productivity. Improve results through technology that speeds issue resolution and expands self-service options.

HR metrics:

• Operating expenses: Lower costs through smarter hiring, training, and retention programs.
• Revenue per employee: Strengthen engagement and development to boost team productivity.

Tracking these ratios over time helps you compare performance across departments, identify trends, and pinpoint where efficiency improvements will have the greatest impact.

Time-based metrics

Time-based performance metrics track how long it takes to complete key tasks, projects, or processes. Monitoring these helps you spot delays, understand bottlenecks, and identify opportunities for improvement.

IT metrics:

• Mean time to resolution (MTTR): Average time to resolve an incident from the moment it’s reported. Use AI to respond automatically to tickets, prioritize them by urgency, and accelerate diagnosis and routing.
• First contact resolution (FCR): Percentage of support tickets solved during first interaction. AI agents can field common questions, handle password resets, or guide users through self-service steps to resolve issues instantly—no human intervention needed.
• Cycle time: Average time for code to move from development to production. AI can improve code quality, automate testing, and shorten release cycles to speed delivery. 

HR metrics:

• Average handling time: Average time HR spends resolving a single employee request. Automate routine inquiries with AI to free up time for strategic work.
• Time to hire: Number of days between posting a job and a candidate accepting an offer. Use agentic AI to screen applicants, match skills, and schedule interviews effectively.
• Time to fill: Total duration from position approval to a new hire’s start date. Automating parts of the hiring lifecycle helps shorten time-to-hire and improve candidate experience.
• Time to productivity: Average time a new employee takes to reach full productivity. Personalized onboarding and training powered by AI agents help new hires contribute faster. 

If these benchmarks start to rise, it’s a signal that business operations are slowing down. AI-driven tracking and optimization can uncover the cause, streamline processes, and free up teams to focus on higher-value work.

Resource utilization metrics

Resource utilization measures whether your tools, talent, and budget are used to their fullest potential. Tracking these key metrics helps you identify waste, avoid burnout, and reallocate resources to where they’ll have the most value. 

IT metrics:

• Software license utilization: Compares the number of software licenses purchased to the number actually in use. AI can flag underused licenses for cancellation or renegotiation, helping reduce unnecessary spend.
• Application usage/utilization rate: Tracks how often and how long your employees use software applications. Agentic AI tools can surface low-adoption tools and recommend tech consolidation to improve return on investment.

HR metrics:

• Cost per hire: Evaluates the total resources spent recruiting and onboarding new employees. AI agents can help screen the best candidates and streamline onboarding through personalized guidance.
• Training effectiveness: Measures how well training programs improve employee skills and performance. AI insights reveal which programs deliver measurable gains and where additional support may be needed.

Together, these metrics show where resources are underutilized or stretched too thin, and where optimization can drive immediate cost savings and long-term productivity gains.

How AI helps leaders measure efficiency

Using AI in IT, HR, and Operations helps you continuously measure operational efficiency, transforming everyday business data into actionable insight. Instead of waiting for manual reports that are often outdated or error-prone, AI automatically gathers and interprets performance data across systems, giving leaders live visibility into how their organization operates.

Key ways AI supports this include:

• Automated data integration: Connects systems such as HR, IT, and finance to create a unified view of performance.
• Real-time tracking: Monitors response times, cycle times, and resource usage, alerting leaders to drops in efficiency before they affect outcomes.
• Predictive analytics: Identifies early warning signs of inefficiency, like rising ticket volumes or longer time to hire.
• Pattern detection: Uncovers recurring issues or redundancies hidden in tickets, employee feedback, or workflow logs.
• Contextual insights: Links operational data to business outcomes like cost savings, employee engagement, and productivity.
• Continuous improvement loop: Uses dashboards and feedback mechanisms to refine strategies and benchmark progress over time.

In short, AI transforms efficiency measurement into a dynamic process that tracks performance and gets smarter with every insight.

Common barriers to measuring and improving efficiency

Many enterprises struggle to improve operational efficiency due to a few persistent challenges.

• Messy or siloed data makes it difficult for IT, HR, and other teams to maintain a clear, real-time view of performance. Different data formats, separate systems and spreadsheets often prevent leaders from seeing the full picture. 
• Overreliance on manual tracking compounds the problem. Manual reports are slow, error-prone, and often outdated by the time they’re available, making timely decision-making nearly impossible.
• Cultural resistance can be limiting, as well. Teams accustomed to traditional workflows may hesitate to adopt new tools or share data across departments, reducing visibility and slowing progress toward efficiency goals.

AI-driven strategies to improve operational efficiency

Many teams turn to agentic AI for automation. It is just as powerful for helping you uncover inefficiencies and anticipate future bottlenecks. When used strategically, it turns everyday operational data into clear, actionable insights.

Key agentic AI capabilities that support efficiency include:

• Natural language processing (NLP): Interprets employee queries and delivers the right answers or resources instantly.
• Automated ticket routing and classification: Directs issues to the appropriate specialist or system, reducing response times and improving resolution rates.
• Adaptive insights: Detects recurring pain points or inefficiencies across employee requests, support tickets, and workflows.
• Proactive alerts: Flags performance declines early so leaders can address issues in a timely manner.

Pairing these AI-driven insights with thoughtful process improvements can help you focus on high-impact areas and build long-term efficiency gains that scale across the organization. 

Streamline and automate repetitive workflows

The first step to improving your operations is identifying high-volume, low-complexity tasks that can be automated with agentic AI tools that can reason and act autonomously on your behalf. Time-consuming, repetitive work drains productivity and contributes to employee burnout.

IT departments can use agentic AI to: 

• Route requests to the right team members or specialists.
• Complete routine tasks such as password resets or software access requests.
• Triage system alerts and monitor device provisioning.

HR departments can use agentic AI to: 

• Streamline leave approvals, benefits enrollment, onboarding tasks, and payroll inquiries.
• Manage employee record updates and other recurring admin work.
• Screen, sort, and schedule applicants during the hiring process.

By automating repetitive workflows like these, your team can reclaim valuable time and focus their efforts on high-impact, strategic work that drives organizational performance. 

Moveworks helps reduce bottlenecks with data-driven insights

AI dashboards and analytics tools give you a clear view of workflow friction, helping you identify delays, recurring issues, and patterns that limit performance. With this visibility, it’s easier to reallocate resources, pinpoint overloaded teams, underused tools, or inefficient processes that slow progress. 

Leveraging these insights strengthens operational efficiency—aligning teams, advocating for the right resources, and addressing small issues before they grow into larger disruptions.

Foster cross-department collaboration

True operational efficiency happens as an enterprise-wide effort, not a siloed IT or HR goal. Every team relies on shared workflows that influence productivity and the overall employee experience.

You can start breaking down silos with shared data, transparent reporting, and standardized processes across departments. When everyone works from the same insights, it’s easier to coordinate priorities and make meaningful, lasting improvements.

Agentic AI assistants make this collaboration seamless. They provide instant, consistent access to information across teams, giving employees the answers they need and leaders a unified view of operations. With that visibility, the entire organization can move forward together. 

Drive operational efficiency with agentic AI-powered solutions

Enterprises often struggle with inconsistent measurement, slow manual workflows, and siloed information, all of which limit operational efficiency. 

Agentic AI-powered solutions address these challenges head on by automating repetitive tasks, providing instant access to information, and delivering timely insights that help leaders continuously optimize performance.

Here’s how Moveworks helps:

• AI Assistant: Empowers employees with self-service support, automates tasks across all enterprise systems and applications, and reduces manual effort and resolution time.
• Build and extend with Agent Studio and AI Agent Marketplace—purpose-built to discover and deploy pre-built agents that automate hundreds of workflows.
• Employee Experience Insights (EXI): Continuously measures employee interactions to identify friction points, track trends, and uncover opportunities for improvement across departments.

For enterprise IT and HR leaders focused on improving efficiency across the organization, Moveworks provides a single, scalable platform that delivers measurable gains in speed, accuracy, and employee satisfaction.

Explore how Moveworks can help you transform operational efficiency across your enterprise.