Tability is a cheatcode for goal-driven teams. Set perfect OKRs with AI, stay focused on the work that matters.
What are Data Automation OKRs?
The OKR acronym stands for Objectives and Key Results. It's a goal-setting framework that was introduced at Intel by Andy Grove in the 70s, and it became popular after John Doerr introduced it to Google in the 90s. OKRs helps teams has a shared language to set ambitious goals and track progress towards them.
Formulating strong OKRs can be a complex endeavor, particularly for first-timers. Prioritizing outcomes over projects is crucial when developing your plans.
To aid you in setting your goals, we have compiled a collection of OKR examples customized for Data Automation. Take a look at the templates below for inspiration and guidance.
If you want to learn more about the framework, you can read our OKR guide online.
The best tools for writing perfect Data Automation OKRs
Here are 2 tools that can help you draft your OKRs in no time.
Tability AI: to generate OKRs based on a prompt
Tability AI allows you to describe your goals in a prompt, and generate a fully editable OKR template in seconds.
- 1. Create a Tability account
- 2. Click on the Generate goals using AI
- 3. Describe your goals in a prompt
- 4. Get your fully editable OKR template
- 5. Publish to start tracking progress and get automated OKR dashboards
Watch the video below to see it in action 👇
Tability Feedback: to improve existing OKRs
You can use Tability's AI feedback to improve your OKRs if you already have existing goals.
- 1. Create your Tability account
- 2. Add your existing OKRs (you can import them from a spreadsheet)
- 3. Click on Generate analysis
- 4. Review the suggestions and decide to accept or dismiss them
- 5. Publish to start tracking progress and get automated OKR dashboards

Tability will scan your OKRs and offer different suggestions to improve them. This can range from a small rewrite of a statement to make it clearer to a complete rewrite of the entire OKR.
Data Automation OKRs examples
We've added many examples of Data Automation Objectives and Key Results, but we did not stop there. Understanding the difference between OKRs and projects is important, so we also added examples of strategic initiatives that relate to the OKRs.
Hope you'll find this helpful!
OKRs to optimize data-driven automation in customer support
ObjectiveOptimize data-driven automation in customer support
KRImplement 2 new data analytics tools by end of quarter
Train staff on new tools usage
Purchase and install selected tools
Research and choose top two data analytics tools
KRImprove response time by 15% using AI automation
Monitor and optimize AI performance continually
Implement AI automation in customer service operations
Train employees on AI-enhanced tools to speed responses
KRReduce customer support complaints by 10% through data-focused strategies
Analyze current customer complaint data
Implement changes based on data analysis
Identify frequent complaint areas for improvement
OKRs to enhance data analysis capabilities for improved decision making
ObjectiveEnhance data analysis capabilities for improved decision making
KRImplement three data automation processes to maximize efficiency
Identify three tasks that could benefit from data automation
Implement and test data automation processes
Research and select appropriate data automation tools
KRComplete an advanced data science course boosting technical expertise
Choose a reputable advanced data science course
Actively participate in course assessments
Allocate regular study hours for the course
KRIncrease monthly report accuracy by 25% through diligent data mining
Implement stringent data validation processes
Conduct daily data evaluations for precise information
Regularly train staff on data mining procedures
OKRs to implement automation in data analysis and visualization
ObjectiveImplement automation in data analysis and visualization
KRCreate an automated data visualization tool generating 3 visually impacting reports weekly
Identify key data points for weekly visualization
Design three types of impactful report templates
Program automation for weekly report generation
KRSuccessfully automate 50% of routine data analysis tasks to increase efficiency
Implement and test chosen automation tools
Identify routine data analysis tasks suitable for automation
Research and select relevant automation software
KRDevelop a robust data cleaning and pre-processing automation script by the end of Q1
Design algorithm for automation script
Implement and test the automation script
Identify necessary data cleaning and preprocessing steps
OKRs to streamline data architecture to enhance overall efficiency and decision-making
ObjectiveStreamline data architecture to enhance overall efficiency and decision-making
KRImprove data governance framework to ensure data quality and compliance
Identify and rectify gaps in the current data governance policies
Implement regular compliance checks and audits for data management
Develop comprehensive data quality standards and measurement metrics
KREnhance data infrastructure scalability to support future growth and evolving needs
Implement scalable data management solutions
Monitor and adjust scalability strategies regularly
Evaluate current data infrastructure strengths and limitations
KRIncrease data integration automation to reduce manual efforts by 30%
Implement automation software to streamline data integration
Monitor and assess efficiency improvements post-implementation
Evaluate existing data integration processes and identify manual efforts
OKRs to streamline and enhance data reporting and automation processes
ObjectiveStreamline and enhance data reporting and automation processes
KRAchieve 100% data integrity for all reports through automated validation checks
Regularly review and update the validation parameters
Develop an automated validation check system
Identify all data sources for reporting accuracy
KRSimplify and align 10 major reports for easier understanding and cross-functional use
Develop a unified structure/format for all reports
Condense information and eliminate unnecessary details
Identify key data points and commonalities across all reports
KREnable real-time data connections across 5 key systems to streamline reporting
Test real-time reporting for data accuracy and timeliness
Develop and implement a centralized data synchronization process
Identify the 5 primary systems for data integration and real-time connections
OKRs to maximize data-driven decision making in Customer Support
ObjectiveMaximize data-driven decision making in Customer Support
KRImplement 3 new AI-based automations to streamline support systems
Conduct tests and implement AI automations
Develop AI-based automation plans for those areas
Identify areas in support systems needing AI automation improvements
KRReduce customer complaints by 20% through continuous process improvements
Identify common issues from existing customer complaints
Implement training programs to boost service quality
Regularly review and update customer service processes
KRIncrease customer query resolution speed by 30% using data analysis
Implement AI tools for faster data interpretation and response
Train staff on utilizing data analysis results effectively
Analyze previous data to identify common query themes
OKRs to implement automation in analytic reporting process
ObjectiveImplement automation in analytic reporting process
KRAchieve 30% reduction in reporting time by final week of the quarter
Implement automated tools for quicker data processing
Streamline workflow for more efficient reporting
Train staff on time management techniques
KRDefine and document all steps of the current analytic reporting process by week 4
Identify all steps involved in analytic reporting process
Complete document outlining process by week 4
Write a detailed document describing each step
KRDetermine and integrate suitable automation tool to existing process by week 8
Research available automation tools that fit the existing process
Choose a suitable automation tool based on research
Implement and integrate the chosen tool by week 8
OKRs to implement automation in the reporting process
ObjectiveImplement automation in the reporting process
KRAchieve 95% accuracy in automated reports and reduce manual effort by 60%
Implement data quality checks in the reporting process
Train team on new automated reporting processes
Automate documentation and validation steps
KRSuccessfully develop and test automation tool for 75% of identified processes
Identify key processes suitable for automation
Validate tool through comprehensive testing
Develop automation tool for chosen processes
KRIdentify and map 100% of the current manual reporting processes by end of first month
Inventory all existing manual reporting procedures
Categorize different manual reporting process types
Create a comprehensive flowchart of all processes
OKRs to implement automation in financial reporting
ObjectiveImplement automation in financial reporting
KRProcure and integrate an automation tool by week 8
Research and select a suitable automation tool by week 4
Install and test automation tool integration by week 8
Purchase chosen automation tool in week 5
KRIdentify and standardize 100% reportable financial data by week 6
Review all current financial data for standardization
Implement standardization protocol by week 6
Establish parameters for 100% reportable data
KRReduce financial report generation time by 50% by week 12
Implement automation software for faster report compilation
Delegate assignments among financial team members
Improve and streamline data collection processes
OKRs to streamline administrative tasks in sales department
ObjectiveStreamline administrative tasks in sales department
KRImplement new software to automate at least 50% of repetitive tasks
Identify repetitive tasks suitable for software automation
Install and test automation software
Research and select appropriate automation software
KRReduce sales report generation time by 30%
Streamline the sales data input process
Train team on faster report generation methods
Implement efficient sales reporting software
KRImprove data entry accuracy to 98%
Utilize automated data validation software
Establish robust data auditing processes
Implement rigorous data entry training programs
Data Automation OKR best practices
Generally speaking, your objectives should be ambitious yet achievable, and your key results should be measurable and time-bound (using the SMART framework can be helpful). It is also recommended to list strategic initiatives under your key results, as it'll help you avoid the common mistake of listing projects in your KRs.
Here are a couple of best practices extracted from our OKR implementation guide 👇
Tip #1: Limit the number of key results
The #1 role of OKRs is to help you and your team focus on what really matters. Business-as-usual activities will still be happening, but you do not need to track your entire roadmap in the OKRs.
We recommend having 3-4 objectives, and 3-4 key results per objective. A platform like Tability can run audits on your data to help you identify the plans that have too many goals.
Tip #2: Commit to weekly OKR check-ins
Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to get the full value of your OKRs and make your strategy agile – otherwise this is nothing more than a reporting exercise.
Being able to see trends for your key results will also keep yourself honest.
Tip #3: No more than 2 yellow statuses in a row
Yes, this is another tip for goal-tracking instead of goal-setting (but you'll get plenty of OKR examples above). But, once you have your goals defined, it will be your ability to keep the right sense of urgency that will make the difference.
As a rule of thumb, it's best to avoid having more than 2 yellow/at risk statuses in a row.
Make a call on the 3rd update. You should be either back on track, or off track. This sounds harsh but it's the best way to signal risks early enough to fix things.
Save hours with automated Data Automation OKR dashboards

OKRs without regular progress updates are just KPIs. You'll need to update progress on your OKRs every week to get the full benefits from the framework. Reviewing progress periodically has several advantages:
- It brings the goals back to the top of the mind
- It will highlight poorly set OKRs
- It will surface execution risks
- It improves transparency and accountability
Spreadsheets are enough to get started. Then, once you need to scale you can use Tability to save time with automated OKR dashboards, data connectors, and actionable insights.
How to get Tability dashboards:
- 1. Create a Tability account
- 2. Use the importers to add your OKRs (works with any spreadsheet or doc)
- 3. Publish your OKR plan
That's it! Tability will instantly get access to 10+ dashboards to monitor progress, visualise trends, and identify risks early.
More Data Automation OKR templates
We have more templates to help you draft your team goals and OKRs.
OKRs to successfully read and complete an entire book
OKRs to establish an active social media volunteer team
OKRs to enhance employee satisfaction and productivity via superior alignment
OKRs to enhance company security standards to safeguard against potential threats
OKRs to enhance and improve the effectiveness of agricultural records
OKRs to achieve full productivity in general accounting role