It’s important with any organisation to be strategic and focused with clear goals and targets, and no less so in the Technology Sector.
Your strategy should hold the important objectives and strategic goals and you need to carefully track your progress against strategy. Let’s take a look at some Strategic KPIs / Strategic Metrics or OKR options relevant to the Technology Sector
3D Printing Time For companies involved in 3D printing, this measures the average time it takes to 3D print a product. Shorter times can indicate more efficient technology.
Active Users Per License This is important for software companies selling enterprise licenses. The metric refers to the average number of users actively using each license. If this number is low, the company might not be getting optimal value from its licenses.
API Call Success Rate For technology companies offering APIs to customers or third parties, this measures the percentage of API calls that are successfully executed without errors. A higher rate can indicate a more reliable API and better customer experience.
API Performance For technology companies that offer APIs, the speed and reliability of these APIs are key metrics. This includes metrics such as average response time, error rates, and uptime.
App Crash Rate For mobile app developers, this represents the percentage of app launches that result in the app crashing. Lower crash rates can lead to better user reviews and higher customer retention.
Artificial Intelligence Training Time For AI and machine learning companies, this measures the time taken to train a machine learning model. Faster times can indicate more efficient algorithms or computational resources.
Augmented Reality/Virtual Reality Engagement For companies in the AR/VR space, this measures user engagement with AR/VR content, which can include factors like time spent, interaction levels, and retention rates.
Average Revenue Per User (ARPU) This is used frequently in telecommunications and internet companies. ARPU gives insight into how well a company is monetizing its users and how much revenue it is generating per user.
Average Time to Detect (TTD) For cybersecurity companies, TTD measures the average time it takes to detect a security breach or threat. A lower TTD indicates a more effective security system.
Blockchain Confirmation Time For blockchain technology companies, this measures the time taken for a transaction to be confirmed and added to the blockchain. Shorter times can indicate a more efficient network.
Bug Fixing Time In software companies, this is the average time it takes to fix software bugs. Faster bug-fixing times suggest a more agile and efficient company.
Capital Expenditures (CapEx) as a Percentage of Revenue This is the proportion of the company’s revenues that are reinvested back into the company for long-term growth. For tech companies, this might include expenditures on research and development, hardware, software, and infrastructure.
Churn Rate This is crucial for subscription-based businesses (e.g., SaaS and streaming services). Churn rate indicates the percentage of subscribers who cancel their subscriptions within a given time period. Lower churn rates suggest higher customer satisfaction and product stickiness.
Click-through Rate (CTR) For tech companies that rely heavily on digital marketing or run online platforms, CTR measures the percentage of users who click on a specific link to a total number of users who view a page, email, or advertisement.
Cloud Migration Success Rate For cloud service providers or companies moving their operations to the cloud, this measures the percentage of successful data and application migrations.
Code Deployment Frequency For software development companies or tech companies with a significant software component, how frequently they can deploy new or updated code can show the pace of innovation and efficiency of the development team.
Code Reusability For software development firms, this metric measures the percentage of code that can be reused in other projects. High reusability can indicate efficient coding practices.
Code Review Efficiency In software development, this measures how much time is spent reviewing code versus writing new code. An efficient code review process can lead to higher quality software and faster development times.
Cost per Bug In software development, this refers to the average cost incurred to identify and resolve a bug. This can help companies balance quality and cost in their development processes.
Cost per Line of Code In software development, this KPI measures the average cost to produce a line of code. While it can be tricky to use effectively due to differences in code quality and complexity, it can give some insight into productivity and efficiency.
Daily Active Users (DAUs) to MAUs ratio This ratio gives insight into user engagement. If the ratio is high, it means users are frequently engaging with the product or service, which can be a sign of a compelling product and high customer retention.
Data Breach Incidents Cybersecurity is crucial in the tech industry. A company with frequent data breach incidents may face reputational damage, loss of customer trust, and potential legal liabilities, all of which can impact the bottom line.
Data Compression Ratio For companies involved in data transmission or storage, this ratio measures the size of data after compression relative to its original size. A higher ratio means more effective data compression.
Data Processing Latency For companies that process large volumes of data, this measures the time it takes for data to be processed. Lower latency can indicate a more efficient data processing system.
Data Throughput For companies in sectors like telecommunications or data storage, this measures the amount of data successfully transferred over a given period. Higher throughput rates indicate better system performance.
Failed Deployments This KPI applies to tech companies involved in continuous delivery of software. It shows the number of software deployments that failed. A lower number indicates a more robust and reliable software delivery process.
Feature Usage For software and app developers, this refers to the frequency or extent to which different features of a product are used. This can guide product development efforts by showing what features are most valuable to users.
Hardware Failure Rate For tech hardware companies, this refers to the percentage of sold devices that fail within a certain period. A lower hardware failure rate can indicate high-quality products and result in lower costs related to warranties or returns.
Incident Response Time For cybersecurity companies and IT departments, this is the time it takes to respond to a security incident after it’s detected. Faster response times can limit damage and recovery time.
Infrastructure Scalability For cloud service providers or app developers, this refers to the ability of the infrastructure to handle increased loads. It’s often measured by the time and resources required to increase capacity.
License and Subscription Renewal Rates This applies to software and SaaS companies. It indicates the percentage of customers that renew their software licenses or subscriptions, reflecting customer satisfaction and product value.
Load Time: Faster load times improve user experience and engagement.
Monthly Active Users (MAUs): Measures the number of unique users engaging monthly.
Net Promoter Score (NPS): Gauges customer satisfaction and loyalty.
Network Latency: Measures delay in data transmission, lower is better.
Onboarding Time: Tracks how quickly new users can start using a product.
Page Views Per Visit: Indicates user engagement on websites.
Percentage of Active Users: Shows engagement level of total users.
Platform Uptime: Measures system reliability and service availability.
Quantum Volume: Evaluates the computational ability of a quantum computer.
Return on Research and Development (R&D) Investment: Assesses financial returns on R&D spending.
Revenue Per User (RPU): Tracks average revenue generated per user.
Security Incidents: Measures the frequency of security breaches or threats.
Server Downtime: Tracks downtime of cloud computing and hosting services.
Server Request Handling Time: Measures response time for server-based operations.
Session Duration: Indicates how long users engage with a platform per session.
Software License Utilization: Tracks how effectively software licenses are used.
System Availability Percentage: Measures uptime reliability for cloud and IT services.
Technical Debt: Represents the cost of maintaining quick-fix solutions.
Technical Support Resolution Time: Measures how quickly technical issues are resolved.
Technology Accessibility Score: Assesses how accessible technology is for users with disabilities.
Test Coverage: Evaluates the extent of software testing.
Time Spent in App or Platform: Measures average user engagement time.
Wearable Tech Data Accuracy: Assesses the accuracy of data from wearable devices.
If you’d like to download these in a spreadsheet format you could then use to set value and targets for a two or three year plan then take a look at our Top 50 Technology Sector Strategy KPIs.
So, there are a bunch of important KPIs to track in the Technology sector. As we always say with our lists of KPIs, it’s best practice to not have too many metrics on your KPI Dashboards. KPIs are there to keep everyone focused on the most important aspects of performance that you need to get right. If you have too many, then you will be reducing the focus. So pick your winners, add them to your KPI Dashboards, and start tracking them.
Good luck with hitting your targets 🎯
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