Retarget outbound to tier A and B accounts
Rebuild outbound lists from ICP tiers and cap tier C at 10%. Pay for meetings held with tier A and B accounts.
+$240kFY27 bookingsFY27 cost $0Counted at 70% odds in the commit
Corvid Analytics, FY27 operating plan
Your team and pipeline get to $6.54M today, 82% of the target. Retarget outbound, build a partner channel, and add 3 mid-market AEs, 1 manager, and 3 SDRs. The commit is the number that holds if hires start a month late and each change lands at its odds.
Comes with the Excel model, a PDF and a summary deck.
Send to your CFOOnly A reaches $8.0M. It books $517k more than R but costs $2.58M more, about $5.00 for each extra dollar booked, and needs 31 hires, 21 of them SDRs. R adds about 40% of today's mid-market AEs in one hiring cycle, a rule of thumb for what one team can recruit and onboard at once, not a measured limit.
Follow our picks or make your own. Every option is measured the same way: the FY27 bookings it adds, the cost it adds, and the cost of each $1 it books.
| Scenario | FY27 bookings | vs submitted plan | FY27 cost | Annual after | Risk |
|---|---|---|---|---|---|
| AHire to the targetAdd 6 mid-market AEs, 4 managers and 21 SDRs from Mar. | $8.19M102% of target | +$1.64M | $4.06M50% of bookings | $4.61M | HighHiring 31 people (6 AEs, 4 managers, 21 SDRs), an SDR team of 25 for 21 AEs. |
| BFix productivityRetarget outbound and build partners. Keep the 4 planned seats, plus 3 SDRs for the pipeline. | $7.13M89% of target | +$589k | $589k8% of bookings | $515k | MediumThe behavior changes land on time. |
| CLower the targetOutbound fix only, plus 3 SDRs to feed it. Commit $6.7M. | $6.78M85% of target | +$240k | $359k5% of bookings | $330k | MediumThe board accepts a lower AE number. |
| RRecommended planB plus 3 mid-market AEs and 1 manager from Mar, a partner manager, and 3 added SDRs in total. | $7.67M96% of target | +$1.13M | $1.47M19% of bookings | $1.41M | MediumHalf the lever value lands; hires start on time. |
3 changes add $1.13M of FY27 bookings. The SDRs make the pipeline possible. Against today's plan, the recommendation adds $1.13M of FY27 bookings for $1.11M more cost, about 2.6x a year after FY27.
Rebuild outbound lists from ICP tiers and cap tier C at 10%. Pay for meetings held with tier A and B accounts.
Recruit 6 to 8 referral partners that already serve your tier A accounts. Pay 10% of first-year value. Route partner deals to an AE within 24 hours.
Weekly deal reviews with the VP Sales, Dana's discovery and mutual action plan as the standard, and a seat decision in Q2 if stage conversion hasn't moved.
Mid-Market hires at median attainment return more per dollar than the other segment. The 90-day hiring clock is the constraint: offers accepted by Jan 30 for a March start. The pipeline feeds $538k of their $822k of capacity; the rest waits on more pipeline.
To feed every AE, outbound needs 22 opportunities a month against 10 today. At 2.4 per SDR that takes 14 SDRs; you have 4. The plan holds the SDR team to one per two AEs, 7, so the pipeline, not the AEs, sets the number: $283k of AE capacity has no pipeline behind it. No more than 3 people start in any month, so SDRs start Feb to Apr, after the managers and AEs, and each creates opportunities 2 months after starting. Later hires produce for fewer months, and the count covers that.
Ready territory and inherited opportunities on day one, a 30-60-90 day ramp plan with weekly milestones, and comp paid on the deal types the plan needs, inside today's commission budget. Usage commits credited at 100% with a clawback below 70% consumption.
The plan needs 40 new opportunities a month against 29 today, with outbound going from 10 to 14: about $41.60M of pipeline to create in FY27, against $28.15M created in the last 12 months. Added FY27 cost is $1.47M, $1.41M a year after; that is $1.11M more than today's plan, because today's plan would also need $359k of SDR hiring. Costs exclude commission and tooling.
New opportunities each person creates a month: what they create today, and what the plan asks of them. At year end, 7 ramped SDRs at today's rate create about 17 outbound opportunities a month.
| Source | Today, per head | Plan, per head | Who creates it | Check |
|---|---|---|---|---|
| Outbound, per SDR | 2.4 | 2.4 | 4 today, 7 by year end; 6.1 producing on average after a 2-month start | Within history |
| AE-sourced, per AE | 0.64 | 0.64 | 11 AEs today, 18 by year end; 7 a month today, 10 in the plan | Within history |
| Partner, per partner manager | 1.8 with no owner | 2.4 added | 1 partner manager, from month 2 | New, no history |
| Inbound | 8.3 a month | 8.3 a month | Held at today; no marketing hires in this plan | Within history |
Your plan's assumptions add $1.72M of capacity your data doesn't support.
$5.43M in the last 12 months against $5.44M the year before. The $8.0M AE target asks for 47% growth from the same motion.
About 29% of won deal value is usage commit. This plan counts full first-year value, usage commits included. If Finance counts only subscription toward the target, every number here drops by roughly that share.
At today's 29 new opportunities a month and today's win rates, the pipeline books about $5.74M a year. The team has capacity for $6.54M. The difference needs new pipeline, so every scenario below is costed with the SDRs it takes.
Almost nothing closes in months 1 to 3, about 69% in months 4 to 6, and the plan uses about 8 months to full productivity. That rests on 4 hires whose first months are in the data, so it is a judgment, not a measurement. The model credits a straight-line ramp from month 1, which is generous if early months produce little.
Dana Whitlock closed 142% of quota; the other 3 AEs closed 30%, 29% and 6%. The pooled 67% hides that, so each ramped AE is modeled at their own number, and newer AEs and new hires at the median.
Dana Whitlock and Jordan Pike closed $2.33M of the $5.43M booked in the last 12 months. Losing Dana Whitlock after Q1 costs about $1.06M, more than the 4 planned hires add in FY27 ($793k).
46% of closed outbound opportunities were tier C, which outbound wins 4% of the time, against 15% for tier A.
Accounts with a cloud data warehouse win 26% against 12% without one; Healthtech and Fintech win 31% and 28%, Insurance 9%. These signals are sharper than the ICP tiers, so outbound and SDR lists start there.
30% win rate on 47 closed deals, at 2 opportunities a month, with no owner.
Inside enterprise, tier A accounts win 10% (n=21), close to the other tiers. How the AEs run deals matters more than which accounts they work.
| Assumption | Your plan | This plan | Basis |
|---|---|---|---|
| Ramp to full quota | 4 months | About 8 months | 4 recent hires |
| Ramped attainment | 80% | Own number; hires at median ENT 30% · MM 88% | Pooled ENT 67% · MM 93% |
| AE attrition | Not modeled | 10% | 2 leavers in 24 months |
| Win rate | Not modeled | ENT 17% · MM 19% | 645 closed deals |
| Sales cycle | Not modeled | ENT 6 mo · MM 3 mo | Median, won deals |
Good. We received 771 deal rows and 1422 company rows from HubSpot, and kept 755 and 1400 after cleaning.
Already fixed for this plan: Mapped HubSpot column names. Merged stage and source spellings. Matched owner name variants to the AE roster. Removed 16 duplicate deals and merged 22 duplicate companies. Parsed mixed date formats and text amounts. Filled missing amounts and usage splits with segment medians, flagged.
| Issue | Why it matters | Fix | Effort |
|---|---|---|---|
| Hand-typed stage and source values | 243 deals use hand-typed stage names and 229 use one-off source labels. Reports that filter on one spelling miss the rest. | Replace free text with picklists, merge legacy values into one stage list, and map marketing sources to four buckets. | Half a day |
| Companies missing firmographics | 147 companies have no industry, 301 no data-warehouse flag, and 140 no employee count. 418 accounts got an ICP tier on partial data, which weakens territory and tier decisions. | Enrich companies automatically on create with a data provider, and require industry and employee count before an AE can create a deal. | 1 to 2 days |
| Owner and segment inconsistencies | 121 deals list the owner under a different spelling, 54 have no segment on the company, and 100 deals sit in another segment's pipeline. | Assign owners from the user record rather than text, set segment by an employee-count rule, and route deals to the pipeline by segment automatically. | Half a day |
| Deals with no lead source | Source win rates and the sourcing plan run on the other 92% of deals. Partner and outbound results could be off by a few points. | Make Original Source required at deal creation, set it from the contact's first touch with a workflow, and lock it after the first stage so reps can't overwrite it. | 1 day |
| Deals with no usage commit split | Revenue timing depends on the subscription and usage split. We used the segment median for these deals. | Add a required usage commit field on the quote and pass it to the deal at Closed Won. | Half a day |
The biggest single risk is losing Dana Whitlock, worth about $1.06M of FY27 bookings, and it isn't in the commit.
| Risk | Response |
|---|---|
| Dana Whitlock or Jordan Pike leaves | Retention grants and named successor account lists by Jan. Not in the commit; needs its own decision. |
| March hires slip | About $44k of FY27 bookings lost per AE per month of delay. Checkpoint: if fewer than half the offers are accepted by Jan 9, add a contingency recruiter; all offers accepted by Jan 30. |
| Enterprise coaching doesn't move conversion | Q2 decision: convert one enterprise seat to mid-market. |
| Partner results regress | Already modeled at 24%, not the historical 30%. Monthly partner quality review. |
| Usage customers under-consume | Clawback below 70% consumption and a usage review at day 60. |
| New hires perform like Leo Martins | At 45% attainment the plan drops to $7.02M, below the commit. The commit is not protected against this. Hire against a scorecard and review every new AE at day 90. |
| SDR hiring lags | Each month without the added SDRs leaves about 7 opportunities uncreated. Hold pipeline reviews to the target anyway. |
3 weekly meetings and a short list of leading indicators tell you within two months whether $7.67M is on track.
New opportunities vs target by source and tier
SDR manager, marketing, partners; Mon 30 min; decides: Shift lists or spend
Commit and best case by AE; slips; stage age
VP Sales, AE managers; Thu 45 min; decides: Call the quarter
Every deal past discovery
VP Sales, enterprise AEs; Tue 60 min; decides: Where to step in
Bookings, capacity, hiring, levers vs plan
VP Sales, CFO, RevOps; 60 min; decides: Pull levers, hold or release reqs
Attainment, ramp, win rates, next 2 quarters of pipeline
VP Sales, CFO; Half day; decides: Next quarter's targets and hires
Cost of sales, payouts, behavior rewarded
CFO; 60 min; decides: SPIFs and next-year changes
Change any input and watch the plan move. It starts at the recommended plan and changes nothing above. The math matches the Your scenario column in the Excel model.
Every figure traces to your CRM, your inputs, or a stated model step. The Excel model reproduces the scenarios, capacity and monthly KPIs with live formulas; sheets computed by the engine are labeled as values.
| Number | Value | Source | How it is calculated |
|---|---|---|---|
| AE target | $8.00M | Your input | FY27 target less $1.5M owned by CS expansion |
| Last-year bookings | $5.43M | Your CRM | Won first-year value, Oct 2025 to Sep 2026 |
| Attainment by AE | per AE | Your CRM | Won bookings divided by prorated quota, last 12 months |
| New-hire attainment | ENT 30% · MM 88% | Your CRM | Median of fully ramped AEs in each segment |
| Ramp | 8 months | Your CRM | Bookings by tenure month for 4 hires whose first months are in the data, rounded |
| Attrition | 10% | Your CRM | AE departures per AE-year, last 24 months |
| Win rates and deal sizes | by segment, tier, source | Your CRM | 645 closed opportunities, last 24 months |
| Capacity | $6.54M | Gapline model | Monthly cohort model: quota x attainment x ramp, with attrition and a 3-month backfill |
| Outbound lever | $240k | Gapline model | Outbound volume x change in win rate from moving tier C effort to A and B x average deal, over 8 months |
| Partner lever | $349k | Gapline model | Added partner opportunities x 24% win rate x average deal, with a 4-month cycle |
| Commit | $7.5M | Gapline model | The recommended plan with each lever at its odds and added AEs and SDRs one month late, rounded down |
| Costs | $1.47M | Your input | Your fully loaded costs from each start date, plus recruiting and partner fees |
| Revenue and new ARR | $3.0M · $7.1M | Gapline model | Subscription recognized ratably; usage (29% of bookings) ramps over 6 months |
| Scenario lab | live | Gapline model | Same formulas as the Excel Scenarios and Monthly KPIs sheets |
| Data health score | 84 of 100 | Gapline model | Share of records affected by each issue, weighted by how much it distorts planning |