Are you looking for a way to measure and track the progress of your AI team? OKRs, meaning Objectives and Key Results, is an effective goal-setting framework used by organizations worldwide, to set and measure progress toward their specific objectives. In this blog article, we will explore how OKRs can be used for AI teams, provide examples of how to implement OKRs for AI teams & provide tips for writing OKRs for AI teams.
What Are OKRs?
Objectives and Key Results are the goal-setting framework used by organizations to set and measure progress towards large-scale objectives. The framework is based on the idea of setting objectives (what you want to achieve) and key results (how you measure success) to ensure that teams stay focused on the goal and measure their progress along the way.
OKRs can be used for AI teams to track progress and ensure teams stay focused on their goals. By setting clear objectives and key results, teams can clearly define what success looks like and measure their progress along the way. This helps teams stay on track and ensure they are working towards the same goal. Additionally, OKRs can help teams identify improvement areas & make adjustments as needed.
Example of How To Implement OKRs For AI Teams
Although there are many other ways to implement OKRs for AI teams, the following is a straightforward and typical approach:
- A few weeks before the end of the quarter, a firm’s executive team begins to generate ideas & then selects the top 3-5 objectives. Each target is aspirational and often just contains one or two sentences.
- Each goal is supported by three to five key results that are much clearer and easier to measure. Still, it’s only one or two sentences long.
- The goals are communicated from upper management to lower-level employees, who frequently interpret the most necessary outcomes as their goals for the projected month.
- Last quarter’s OKRs are assessed according to their level of completion. Satisfactory performance is indicated with a score of 70 percent. Anything over 70% indicates that the goal was not set high enough.
- They are printed and put outside each individual’s workstation so that everyone can see what their employer or team has pledged and find ways to help achieve it.
- They are subject to weekly review & are subject to change at any time during the quarter if new information becomes available.
A Typical Example of OKR For AI Teams
Here is an example of how OKRs can be used by AI Teams- Let us say you have a group of five advanced analytics researchers who have just started producing models as part of an analytics group. As a team leader, you may suggest the following as an OKR:
Main Objective: The goal is to create an AI software or prediction model that generates more revenue for the company.
Key result 1: To meet with three business representatives from each of the five product divisions to gain an understanding of their challenges and to educate them on the benefits that may be gained by applying AI or predictive modelling.
Key result 2: To give users access to all relevant internal datasets based on their roles and in line with the privacy policies that are already in place.
Key result 3: On-time delivery of 5 models to a business unit. The business unit made the request for the models, and the requirements were discussed and agreed upon with them.
These OKRs won’t include every task your team completes in a given quarter, but they highlight the most crucial ones. If other goals are crucial to the business, they can be added. However, no aim should contain more than five objectives, and no objective should have more than five essential key results.
Several other objectives can be applied to AI teams that will depend on how far you have progressed in the maturity of your team and the particular goals of your organization (is your mission more research or purely business?). The important thing is to start.
OKRs are often presented as a concept to all parties engaged in an organization through a presentation that lasts for two hours and includes a strategy for putting it to use throughout the quarter. You can decide whether to continue, cancel, or amend your OKR process at the end of the quarter.
Tips For Writing OKRs For AI Teams
When writing OKRs for an AI team, it is essential to ensure they are clear, specific, and measurable. Here are some tips to help you write effective OKRs for your AI team:
- Make sure the objectives are clear and measurable. Objectives should be specific and measurable so the progress can be tracked & success can be measured accordingly.
- Set achievable goals. Goals should be realistic and achievable. Setting unrealistic goals can lead to frustration and poor performance.
- Involve team members. Involve team members in the process of setting and tracking OKRs. This ensures everyone is on the same page and working towards the same goals.
- Monitor progress. Monitor progress regularly and make adjustments as needed. This will help ensure that objectives are met & the key results are achieved.
- Celebrate success. Celebrate successes and milestones to keep team members motivated and engaged.
Indeed, OKRs are a great way to set and track objectives and key results for AI teams. By following the tips outlined above, you can ensure your OKRs are effective and help your AI team achieve its goals.
Conclusion
OKRs are a powerful tool that has been shown to work for teams as small as five people and as large as over 60,000 employees. As your AI teams expand, you’ll discover that they’re a fantastic resource for increasing productivity and maintaining a unified front towards the achievement of the company’s goals. By using OKR Software, AI teams can develop a timeline, automate tasks and track progress. Huminos has several easy-to-configure OKR tools that will help your team aspire to impactful outcomes and align themselves, even if they are working remotely. Accomplish more with huminos today.
