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2 OKR examples for Data Driven Automation

Turn your spreadsheets into OKR dashboards with Tability

Tability is a cheatcode for goal-driven teams. Set perfect OKRs with AI, stay focused on the work that matters.

What are Data Driven Automation OKRs?

The Objective and Key Results (OKR) framework is a simple goal-setting methodology that was introduced at Intel by Andy Grove in the 70s. It became popular after John Doerr introduced it to Google in the 90s, and it's now used by teams of all sizes to set and track ambitious goals at scale.

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 Driven 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 Driven 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.

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.

AI feedback for OKRs in Tability

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 Driven Automation OKRs examples

You'll find below a list of Objectives and Key Results templates for Data Driven Automation. We also included strategic projects for each template to make it easier to understand the difference between key results and projects.

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
  • TaskTrain staff on new tools usage
  • TaskPurchase and install selected tools
  • TaskResearch and choose top two data analytics tools
  • KRImprove response time by 15% using AI automation
  • TaskMonitor and optimize AI performance continually
  • TaskImplement AI automation in customer service operations
  • TaskTrain employees on AI-enhanced tools to speed responses
  • KRReduce customer support complaints by 10% through data-focused strategies
  • TaskAnalyze current customer complaint data
  • TaskImplement changes based on data analysis
  • TaskIdentify frequent complaint areas for improvement

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
  • TaskConduct tests and implement AI automations
  • TaskDevelop AI-based automation plans for those areas
  • TaskIdentify areas in support systems needing AI automation improvements
  • KRReduce customer complaints by 20% through continuous process improvements
  • TaskIdentify common issues from existing customer complaints
  • TaskImplement training programs to boost service quality
  • TaskRegularly review and update customer service processes
  • KRIncrease customer query resolution speed by 30% using data analysis
  • TaskImplement AI tools for faster data interpretation and response
  • TaskTrain staff on utilizing data analysis results effectively
  • TaskAnalyze previous data to identify common query themes

Data Driven 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

Focus can only be achieve by limiting the number of competing priorities. It is crucial that you take the time to identify where you need to move the needle, and avoid adding business-as-usual activities to your 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

Having good goals is only half the effort. You'll get significant more value from your OKRs if you commit to a weekly check-in process.

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 Driven Automation OKR dashboards

AI feedback for OKRs in Tability

Quarterly OKRs should have weekly updates to get all the benefits from the framework. Reviewing progress periodically has several advantages:

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:

That's it! Tability will instantly get access to 10+ dashboards to monitor progress, visualise trends, and identify risks early.

More Data Driven Automation OKR templates

We have more templates to help you draft your team goals and OKRs.

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