Draft OKRs

MEMORANDUM

TO: Grace Mensah, Chief Product Officer FROM: Staff Product Manager DATE: October 3, 2024 SUBJECT: Q3 OKR Post-Mortem & Proposed Q4 Product OKRs

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1. The Disconnect: What Q3 OKRs Actually Tell Us

At our recent all-hands, a product OKR score of 0.81 was celebrated as a “great quarter.” In reality, Q3 was a business failure: * Net Revenue Retention (NRR) dropped from 103% to 102% (Target: 108%). * Quarterly Logo Churn rose from 3.1% to 3.4% (Target: 2.5%).

The 0.81 score is a vanity metric masking acute operational disconnects across four distinct areas:

``` [Output Orientation: 9/16 KRs] ──> Shipped features, missed business outcomes [Metric Manipulation] ──> Completion rate rose via relaxed definition (100% -> 80%) [Activation Breakdown] ──> 31 days to 1st learner (Goal: 14) fuels 45% of churn [Premature Expansion] ──> Pushed upgrade prompts while seat activity fell to 29% ```

#### A. Feature Delivery Was Confused with Value Creation Nine of our 16 Key Results were binary outputs (shipping features or running counts). Teams scored 1.0 on outputs—shipping offline mode, streaks, dashboards, upgrade prompts, and integrations—while customer-facing outcomes collapsed: * Learner App scored 1.0 on features, yet Weekly Active Learners per seat fell from 0.31 to 0.29 (Target: 0.40). * Growth scored 1.0 on experiments and upgrade prompts, yet Seats added in existing accounts fell from 9,200 to 8,100 (Target: 14,000). * Admin delivered 3 HRIS integrations (misclassified as an “outcome”), but the actual outcome—Days from contract to first learner—only improved from 34 to 31 days (Target: 14).

#### B. Vanity Gains and Metric Redefinition Content claimed a 1.0 score by driving Course Completion Rate from 41% to 58% (Target: 55%). However, this was largely engineered by lowering the completion threshold on August 1 from 100% of modules to 80%. Artificially inflating course completions obscured stagnant baseline learner demand.

#### C. Product Neglect Directly Fed Q3 Exit Drivers Our exit interviews across 38 churned accounts reveal direct causation with our product failures: 1. "Our people didn’t use it" (17 accounts / 45%): Directly caused by dropping learner engagement (0.29 weekly active learners per seat). Gamification (streaks/badges) failed to solve core utility. 2. "Moved to HR system’s LMS" (7 accounts / 18%): While we launched 3 HRIS integrations, we treated them as tick-box deliverables rather than driving customer activation. 3. Budget cuts (9 accounts / 24%): When CFOs review seat utilization below 30%, unused seats are cut at renewal. 4. Onboarding Lag: Accounts reaching first learner within 14 days churn at one-third the rate of slower accounts. By taking 31 days to activate, Admin is losing accounts before they even start.

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2. Strategic Narrative for Q4

We cannot expand accounts that are not using the product. To move NRR to 106% and logo churn down to 2.6%, the product strategy must execute in strict sequence across the account lifecycle:

``` [Admin: Days 1–14] [Learner App: Days 15–365] [Growth: Renewal & Expansion] Compress onboarding to <14d ──> Drive habitual weekly usage ──> Monetize 80%+ utilized accounts (Reduces churn by 66%) (Eliminates "nobody used it") (Reverses NRR contraction) ```

1. Admin (Time-to-Value): Compress onboarding to under 14 days using automated HRIS provisioning to unlock the 66% churn reduction.
2. Learner App (Habitual Engagement): Drive weekly active learners per seat from 0.29 to 0.40 to resolve the #1 churn driver and defend against budget cuts.
3. Growth (Expansion Based on Utilization): Stop spamming low-usage accounts with prompts; identify accounts reaching >80% active seat capacity and drive contract tier expansion.

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3. Proposed Q4 OKRs (Learner App, Admin, Growth)

``` ┌──────────────────────────────────────────────────────────────────────────────────┐ │ COMPANY OBJECTIVE (CEO) │ │ Grow by keeping and expanding the customers we have │ │ NRR: 102% -> 106% │ Logo Churn: 3.4% -> 2.6% │ └───────────────────────┬──────────────────────────┬───────────────────────────────┘ │ │ ┌───────────────┴──────────┐ ┌───────────┴──────────────┐ ▼ ▼ ▼ ▼ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ ADMIN │ │ LEARNER APP │ │ GROWTH │ │ Time-to-1st- │ │ Weekly Active│ │ High-Utility │ │ Learner <14d │ │ Learners >38%│ │ Seat Growth │ └──────────────┘ └──────────────┘ └──────────────┘ ```

#### A. Admin Team * Objective: Accelerate customer time-to-value to protect new cohort retention. * Context: Closing the activation gap from 31 to 14 days addresses our highest-leverage retention vector. * Key Results: * KR 1 (Outcome): Reduce median Days from contract to first learner from 31 days to 14 days. * KR 2 (Outcome): Increase % of newly signed accounts with active HRIS employee sync within 7 days from 22% to 65% (Baseline: internal onboarding sample). * KR 3 (Outcome): Increase the percentage of invited admins who configure reporting within 10 days of signature from 28% to 60% (Baseline: Q3 dashboard launch data).

#### B. Learner App Team * Objective: Establish enduring learning habits to eliminate non-usage churn. * Context: Attacking the #1 churn reason ("people didn't use it") by lifting routine learner engagement rather than vanity completions. * Key Results: * KR 1 (Outcome): Increase Weekly active learners per seat from 0.29 to 0.38. * KR 2 (Outcome): Increase 4-week active learner retention (learners active in Week 1 who return in Week 4) from 34% to 48% (Baseline: Q3 cohort average). * KR 3 (Outcome): Reduce the percentage of licensed seats with zero activity in the trailing 30 days from 52% to 35%.

#### C. Growth Team * Objective: Capitalize on active accounts to drive sustainable seat expansion. * Context: Expansion must be an outcome of account saturation, not blind in-app prompts. * Key Results: * KR 1 (Outcome): Increase Seats added in existing accounts from 8,100 to 12,500. * KR 2 (Outcome): Increase account-level seat utilization (accounts with >80% active seats in past 30 days) from 19% to 32% (Baseline: Q3 active accounts). * KR 3 (Outcome): Convert 35% of accounts reaching >90% seat capacity into expanded contracts within 30 days (Baseline: 18%).

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4. OKR Governance Rules for Q4

To ensure we never celebrate a 0.81 score while missing core business commitments again, I propose three immediate operating changes:

1. Zero Pure Output KRs: No KR may simply measure shipping code, closing tickets, or running experiments. Every KR must measure a verifiable shift in customer or business behavior.
2. Target Continuity & Definition Lock: Any changes to metric definitions (such as completion percentages) must maintain restated historical baselines and require Product Operations sign-off.
3. Cross-Functional Dependencies on Onboarding: Admin and Learner App will review weekly leading indicators (TTFL and weekly seat activation) jointly with Customer Success to intercept at-risk renewals early in the contract cycle.

To: Grace Mensah, CPO From: Staff PM Subject: Q3 delivered features, not retained growth; proposed Q4 OKRs

What Q3 actually tells us

We missed the company objective despite a 0.81 product score. NRR fell from 103% to 102%, versus a 108% target. Quarterly logo churn rose from 3.1% to 3.4%, versus a 2.5% target. Calling this “a great quarter” confuses delivery with business impact.

The scorecard explains that disconnect:

• Shipping dominated scoring. Ten of the 16 KRs measured outputs, including “Launch 3 HRIS integrations,” incorrectly labeled an outcome. All ten scored 1.00. The six genuine outcome KRs averaged approximately 0.48, not 0.81.
• Learner value weakened while features shipped. Weekly active learners per paid seat fell from 0.31 to 0.29 despite offline mode, streaks and badges. A better app-store rating does not demonstrate adoption across employer accounts.
• Admin setup barely improved. Contract-to-first-learner time moved from 34 to 31 days, far short of 14. Shipping integrations and reporting did not establish that customers reached value faster.
• Expansion weakened despite experimentation. Seats added in existing accounts fell from 9,200 to 8,100—about 12%—while experiments and upgrade prompts exceeded delivery targets. Seats are also not revenue: discounts, seat removals and account losses can offset additions.
• The content “win” is not comparable. Completion rose from 41% to 58%, but the definition changed from finishing every module to finishing 80%. We cannot separate real improvement from reclassification without recalculating both periods under one definition.
• Reliability genuinely improved. Uptime exceeded target. That is valuable, but insufficient evidence of retention or expansion impact.

The churn evidence suggests where to intervene, without proving causality. Low usage was cited by 17 of 38 interviewed departing accounts, the largest category. Accounts reaching a first learner within 14 days churned at one-third the rate of other accounts. These findings support prioritizing activation and adoption; they do not establish that accelerating activation will itself cut churn by two-thirds. Customer characteristics may explain part of the association.

Q4 company commitment

Retain the CEO’s destination, rebased to Q3 actuals:

Before scoring starts, Finance must confirm consistent NRR periods, cohort rules and revenue treatment. Annual contracts make renewal timing especially important.

Proposed team OKRs

Feature launches become initiatives, not scored KRs. Each team owns customer or commercial results.

The logo-churn KR is one shared result, not three independently credited achievements. Admin coordinates the retention plan with CS; Learner owns adoption improvements. Growth’s revenue KR takes precedence over its seat-volume KR: buying seat growth through discounts is not success.

The revenue baselines are deliberately not invented. The supplied scorecard lacks expansion revenue, contraction revenue, churned revenue and opening recurring revenue. Finance must populate E₃ and L₃ before final approval. If Q3 revenue loss was below three percentage points, the proposed loss reduction is impossible; we must shift that portion of the six-point improvement budget to expansion and reassess feasibility.

How these add up

Using a consistent existing-customer cohort definition:

NRR = 100% + expansion revenue rate − churn/contraction revenue rate.

Q3 therefore implies E₃ − L₃ = 2 percentage points. The proposed Q4 improvement budget is:

• Growth: three additional percentage points of expansion;
• Admin, supported by Learner and CS: three fewer percentage points of revenue loss.

Together: 100% + (E₃ + 3) − (L₃ − 3) = 108%.

This is a six-point commercial bridge, not a claim that engagement or activation mechanically converts into revenue. Logo churn remains a separate constraint: retaining small accounts could improve logo churn without materially improving NRR. Conversely, one large expansion could improve NRR while many customers leave.

Operating discipline

In week one, Finance, Product and CS should establish the revenue baselines, renewal exposure and account-level retention/expansion plan. Validate that the improvement budget is achievable before locking the OKRs.

Review weekly by account cohort, not just company averages. Track activation coverage alongside time-to-first-learner so one early learner cannot conceal a stalled rollout. Inspect engagement across accounts so a few large customers cannot conceal widespread non-use.

Recalculate completion under a constant definition. Keep uptime as a guardrail. Do not average feature delivery and customer outcomes into another celebratory score: Q4 is successful only if customer value improves and the company retention goals are met.