hr_ops · ecommerce · workflow
BARK builds recognition, alignment, and performance at scale with Lattice
As BARK scaled, employee recognition became less frequent and visible, managers lacked consistent frameworks for setting expectations, and employees were unclear on how their work connected to company goals.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Engagement survey surfaces gap
Engagement surveys revealed that employees weren't feeling acknowledged, signaling an opportunity to prioritize recognition.
Tools used
LatticeLattice PraiseLattice UpdatesLattice 1:1sLattice OKRs & GoalsLattice EngagementLattice AI AgentLattice AI toolsGmailWorkday
Outcome
BARK achieved a 93% performance review completion rate while saving the People team 10-15 hours per week, reached 100% goal adoption across nearly 800 active goals, hit a 97% engagement survey response rate, and piloted the Lattice AI Agent resolving up to 78% of HR questions instantly.
What failed first
BARK's previous HR tools were scattered and siloed — reviews, goals, and surveys lived in separate places — leaving the administrative process itself as the focus rather than actual performance conversations.
Results
Time saved10-15 hours per week
Volume93%
Grounding & classification
Source type: vendor customer story
43 fields verified against source quotes.
ai agentcontent generationpredictive analyticssentiment analysisform submissionknowledge basefailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedecommerceautomation rateemployee productivitythroughput increasetime savedvendor customer storyhr opsautonomous resolutiondata sync enrichmenthuman review queue