KPIs

Response Time

Number of Bugs

Average Downtime

Pull Request Review Time

Deployment Frequency

OKRs

Engineering

O: Our Engineering team has never been so effective

KR: X% reduction in cycle state by story status

KR: X% improvement in Point Commitment Reliability

KR: X% Defect Removal Efficiency

O: Release an amazing Recommendations Engine

KR: X% positive client feedback

KR: X out of Y accurate recommendations

KR: X% clicks on recommendations

O: Make quality the top priority in our engineering process

KR: Reduce critical bugs by X%

KR: Improve code quality by X%

O: Speed up deployments of important bug fixes

KR: Reduce time to fix from X to Y day

KR: Reduction in client complaints by X%

O: Improve stability of the site

KR: Time to recover reduced from X hour to Y minutes

O: Establish a more efficient team workflow with a simpler architecture

KR: Reduce Pull Request review time from X to Y hours

KR: Increase in new releases/per week from X to Y

O: Give our customers a speedy, uninterrupted experience with our tool
KR: Reduce response time to X

O: Product setup is easy and fast
KR: Reduce time to onboard to X

KR: Improve onboarding NPS to X

IT

O: Build fast while maintaining high quality and low costs

KR: Average test coverage across all projects are X%

KR: Reduce infrastructure costs by X%

KR: Technical debt across all projects is less than X hours

O: Our data security is safer than Alcatraz

KR: “X” data-risk score

KR: “X“ Identity and Access Management Score

KR: “X” Endpoint Protection ScoreKR: “X” Perimeter Defense Score

O: Secure our IT infrastructure

KR: Reduce # vulnerabilities from X to Y

KR: Pass security audit

O: Build proficiency of the tech team

KR: X% receive skill certification

O: Retire legacy technology to drive down operational costs

KR: Reduce operational costs by $Xk

Product

O: Reimagine the product development process to make it more predictable

KR: Increase in on-time deployments by X

O: Give our customers more order flexibility

KR: Increase in online vs. offline initiated returns by X

O: Validate our product hypothesis by testing our prototype

KR: Test group prototype adoption of X%

KR: Test group prototype acceptance of X%

O: One step effortlessly leads to the next in our product user journey

KR: New features have X% utilization

KR: X feature increases usage by Y%

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