neon-rutger/b2b-revops-skills/revops-crisis

FORECAST:  ±30%+ variance for 2+ consecutive quarters (practice-based; calibrate per company stage)
WIN RATE:  Declined 5+ points over 3 quarters (e.g. 24% to 19%, below median 19% in 2026; Optifai, Clari)
PIPELINE:  Coverage below 2.8x AND falling month-over-month (below this, quota attainment falls to 52%; Clari, Fullcast, 2026)
RETENTION: NRR below 90% OR GRR below 84% (GRR median 84% in 2026, 75th percentile 91%; Optifai, 2026)
DATA:      Critical deal fields <70% complete (practice-based); CRM does not equal finance by >10%
TRUST:     Sales blames marketing blames CS blames product (3+ parties)
PEOPLE:    2+ top performers leaving in one quarter; open cynicism

DATA BREAKS ──┬── PROCESS FAILS ──┬── PEOPLE FRACTURE
              │                    │
         NOBODY CAN EXECUTE RELIABLY
              │
         TRUST COLLAPSES → CRISIS MODE

EMERGENCY DATA AUDIT (sample 200 random open deals):
 
CRITICAL FIELDS                                   TARGET
□ Deal amounts populated?                         95%+
□ Close dates updated in last 14 days?            95%+
□ Stage assigned and makes sense?                 98%+
□ Contact role(s) assigned?                       80%+
□ Activity logged in last 30 days?                85%+
□ Next step documented?                           80%+
□ Won/lost reason populated (closed deals)?       95%+
□ Customer name matches finance system?           99%+
 
SCORING:
<70% at target = DATA CRISIS. Run 5-day blitz before anything else.
70-84%         = ACCEPTABLE. Proceed with caveats on all forecasts. Target is 85%+ for reliable GTM execution (practice-based).
>85%           = GOOD. Proceed with confidence (data quality directly correlates with forecast accuracy; practice-based).

THE 2-HOUR CASH DIAGNOSIS:
 
1. Pull all open deals closing in 30-60 days + renewals due in 30-90 days
2. Stack rank by $ amount
3. Flag at-risk: no recent activity, no champion, competitive threat,
   economic buyer not engaged
4. Top 10 at-risk = your downside exposure number for leadership
5. Assign executive owner to each (CRO or VP level, not deal owner)
6. Define next tangible action + deadline (this week, not "soon")

DAY 1: PURPOSE    . Clear, agreed definition of success? Target conflict?
DAY 2: DEMAND     . Real market demand? Right ICP? Problem still urgent?
DAY 3: CAPABILITY . Skills, tools, structure match the motion we are running?
DAY 4: FLOW       . Pick 20 random deals. Where do they stall? Bottleneck?
DAY 5: SYSTEM CONDITIONS & THINKING
       Data trusted? Stage exit criteria defined? Leadership mental model
       matches reality?

CRISIS:     [One-line description with numbers]
EVIDENCE:   [Data that proves it is real]
ROOT CAUSE: □ Purpose □ Demand □ Capability □ Flow □ System □ Thinking
IMMEDIATE FIX: [The ONE thing that unblocks everything else]
OWNER:      [Name]
TIMELINE:   [1-3 weeks]

GOVERNANCE:       Decisions being made? Steering mechanism exists?
ENABLEMENT:       Data/process/tool stack working?
REVENUE ENGINE:   Sales/CS engine producing?
CUSTOMER INSIGHT: Understand ICP and why you're winning/losing?
 
Emergency constraint = the ONE scoring 1 when others are at 2.
All four at 1? Start with Governance (you need a steering mechanism first).

Governance = 1:  Install daily standup. Assign decision driver (CRO).
                 Unlock: Everything clearer because leadership knows what matters.
 
Enablement = 1:  Data audit (done Week 1) plus define 3 non-negotiable processes.
                 Unlock: Teams can execute consistently.
 
Revenue = 1:     Win rate analysis. Talk to 5 lost deals fast.
                 Unlock: Know where to focus (discovery? closing? multi-threading?)
 
Insight = 1:     Pull top 5 wins and 5 losses. Pattern-match.
                 Unlock: Stop guessing about ICP.

□ Data quality audit complete; blitz if needed (target: 85%+)
□ Top 10 at-risk deals identified with exec sponsors
□ Daily cash standup running
□ Root cause identified (which Six Stage is broken)
□ First structural fix in place (stage criteria, validation rules, or governance)
□ One quick win executed (visible improvement, however small)
□ All non-essential projects halted

□ Full IFA diagnostic complete (reference revops-diagnostic)
□ Capability maturity assessed (reference revops-four-capability-maturity-assessment)
□ Fix roadmap drafted: 3 initiatives max, prioritized by constraint unlock
□ First major structural change: design complete, stakeholders mapped
□ Change management started (reference revops-change-management)
□ Weekly leadership update: "Here is what broke. Here is how we fix it."
□ Measure Day 1 baseline vs. now (data quality, forecast accuracy, win rate)

□ First structural change at 70%+ adoption
□ Initiatives #2-3 in design (NOT launched yet; don't launch 3 at once)
□ Operating cadence established (reference revenue-operating-cadence skill):
  Weekly ops review (30 min), monthly deep-dive (90 min), quarterly reset
□ Forecast rebuilt with proper methodology (reference revops-forecasting)
□ Metrics dashboard live and trusted (reference revops-metrics)
□ Team sentiment: pulse survey shows improved trust
□ Hand off to revops-diagnostic and revops-four-capability-maturity-assessment for deeper work

ROOT CAUSE PATTERNS:
1. Bad data (amounts missing, close dates stale, wrong stages)
2. Sandbagging (reps entering deals late, hiding pipeline)
3. Pipeline inflation (stalled deals still counted, no stage exit criteria)
4. Wrong methodology (rep confidence instead of data-driven)
 
EMERGENCY FIX (Week 1-2):
• Build shadow forecast from scratch (CRM data multiplied by finance validation)
• Compare to current forecast. Variance greater than 15% equals data problem.
• Run 3 methods: rep probability, historical conversion, high-confidence only
• Take the lowest number. That is your realistic forecast.
• Daily: "How many deals closed that were or were not in forecast?"
 
STRUCTURAL FIX (Week 3-8): reference revops-forecasting skill
• Define stage exit criteria (what moves a deal forward)
• Choose forecast method (start Conservative, move to Blended after 2Q)
• Weekly deal inspection (manager validates every deal in qualified stages)
• Monthly accuracy measurement: target +/- 10% (achievable within 2-3 quarters; AI-driven forecasting teams report variance reduction from 30-40% to under 10%; Forrester, 2026)