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.

MEMO To: Grace Mensah, CPO From: Staff PM Re: What Q3 OKRs tell us, and Q4 OKRs for Learner app, Admin and Growth

Bottom line

Q3 scored 0.81 and missed the company goal. NRR was 102% against a 103% baseline, and churn was 3.4% against 3.1%. Both got worse. Teams delivered what they planned, but the plan didn't move usage, and non-use is why customers leave. The Q4 OKRs below target usage and activation directly.

What Q3 actually tells us

1. The score measures delivery, not results. Ten of 16 KRs are outputs, and all ten scored 1.00. That count includes "Launch 3 HRIS integrations", which Admin labelled an outcome. The six true outcome KRs average 0.48. The 0.81 is mostly shipping.

2. What shipped didn't move the customer metrics. - Offline mode plus streaks and badges shipped, and weekly active learners per seat fell from 0.31 to 0.29. - Three integrations and a new dashboard shipped, and days to first learner moved only from 34 to 31. - Thirteen experiments and upgrade prompts shipped, and seats added fell from 9,200 to 8,100.

3. Customers told us why they left. Of 38 exits, 17 (45%) said their people didn't use it. Seven (18%) moved to their HRIS vendor's bundled LMS, nine cited budget and five cited content fit. Accounts reaching first learner within 14 days churned at a third of the rate of the rest. That could partly be selection, since healthier customers may simply move faster. It is still the strongest lead we have.

4. Two "wins" shouldn't be trusted. - Completion rate (41% to 58%) is not evidence. The definition loosened on 1 August from all modules to 80%, so the baseline and actual are measured differently. It needs restating on one definition before anyone cites it. - Uptime hit target, but no exit cited reliability. That is good hygiene, not a retention lever.

5. Process fix. Outputs should be initiatives, not KRs. Every team should carry at least one KR tied to a churn or NRR driver, and we should report outcome KRs separately from the average.

Q4 OKRs

Assumption (please confirm): the company goal carries forward unchanged: NRR 102% to 108% and quarterly logo churn 3.4% to 2.5%.

Learner app: Learners come back every week

Admin: Admins get learners learning in two weeks

Growth: Expand where seats are used

Growth's experiments should target accounts with healthy usage, since expansion into idle accounts is unlikely. Growth also depends on Learner's usage KR.

How it adds up

Churn: 3.4% to 2.5%. I split the 3.4 points by exit reason, assuming the 38 interviews are representative.

Halving non-use churn takes 0.75 points, shared between Learner (usage) and Admin (activation). The HRIS reduction takes 0.15. That gets to about 2.4, leaving 0.1 of buffer. I've put nothing against budget or content fit, since neither is addressable this quarter.

NRR: 102% to 108%. I'm assuming a 0.9-point quarterly churn improvement is worth about 3.6 NRR points annualised. Expansion has to supply the other 2.4. The 12,000 seats target (about 30% above Q2's 9,200) is a placeholder sized to that gap. I don't have the seat base or ARR to convert it exactly.

Risks and asks

• The churn target is a stretch. On annual contracts, Q4 churn comes from accounts renewing in Q4, so a 31-to-21-day onboarding improvement mostly pays off at later renewals. I want a list of accounts renewing before the end of Q1, with their usage. Learner and Admin should work that list first, so Q4 effort lands on accounts that can still change their decision. If we can't act on it, a realistic fallback is about 2.9% churn and 104-105% NRR. I'd rather agree that with the CEO now than explain it in January.
• Finance: please confirm how churn converts to NRR and what 12,000 seats is worth in NRR points.
• Data: restate completion rate on the 80% rule for Q2 and Q3.
• Exit data: 38 interviews is a small sample, and I assumed it covers all churn. Please confirm.
• Decision for you: confirm the Q4 company goal, and whether you'll back splitting the score into output and outcome in the next all-hands.