The Orbytal Platform

Will we hit the number?
One honest answer, updated continuously.

Orbytal scores six pillars of revenue risk against your live data, watches 23 (and growing) named scenarios inside them, and turns every deviation into a diagnosis with a costed fix. This page shows you how, using the same surfaces you'd see in the product.

The Top of the System

One score. One gap, with every dollar accounted for.

Revenue Health blends the six pillar scores into a single read, with the forecast gap in dollars beside it. Every number decomposes into the risks beneath it, so nothing on this screen is free-floating.

85
Fair
↘ −1 since yesterday
Forecast Gap
−$5.2M
forecast gap to the $50M Q3 plan

Q3 is tracking $5.2M short of the $50M plan. $9.2M is identified and ledgered across the pillars. The biggest driver is coverage erosion from a capacity gap, and the top fix recovers +$1.4M.

PillarDollars at riskHealth
Coverage−$2.4M82 Fair
Capacity−$2.1M80 Fair
Territory−$1.2M86 Fair
ICP−$700K90 Good
Pricing−$1.0M84 Fair
Retention & Expansion−$1.8M88 Fair
The ForwardGap

The forecast a deal rollup can't produce

Orbytal's forecast is partitioned, never a second number beside the plan: what's booked, what today's weighted pipeline should produce, and what has to come from pipeline that doesn't exist yet. At 180 days out, most of what will close hasn't been created, so Orbytal models the conditions that create it. The unfilled remainder is the gap, and it decomposes across the six pillars, each piece carrying a named driver, the dollars at risk, and a fix. When the plan is short, the platform also names the smallest set of in-window deals whose sum covers the gap.

Where the year lands, decomposed
Booked
Weighted pipeline
Not yet created
Gap

Booked is certain. The near band is anchored to today's deals. The far band is modeled from the physics that create pipeline: coverage, capacity, ramp, and conversion. Whatever none of them fill is the gap, priced in dollars and traced to its pillar.

The Unit of Work

A scenario is a diagnosis, not a dashboard tile

When a scenario fires, you don't get a chart to interpret. You get the cause, the cost, the owner, the window to act, and ranked fixes. Here is the full anatomy of one.

Coverage erosion from capacity gap
↘ worsening also Capacity →
−$1.4M
at risk
EMEA Ent coverage · 14 days1.4× vs 2.0× target

DACH AE coverage fell from 2.1× to 1.4× as three opportunities slipped past Q3 while ramping reps under-produced.

If nothing changes — Forecast attainment drops to 82% within 3 weeks; Q4 opens $1.4M under plan.
OwnerMaya Patel
Window to act7 days
1
Lift comp band +12% on 3 West reqsrecommended
Accelerates external candidates 6 to 8 weeks
+$1.4M
2
Move 8 accounts AMER → EMEA Ent
Raises coverage now
+$0.6M
Named, never numbered

Every scenario has a name a CRO can repeat in a board meeting. When the cause lives in another pillar, the card says so and links there.

Priced in dollars

Impact is the revenue at risk to the plan, computed from your data and reconciled into one ledger. The same dollar is never counted twice.

The evidence

The signal that fired the scenario, charted against its target, with the plain-language cause underneath.

The consequence

What happens if nobody acts, and by when. Risk with a deadline gets handled; risk without one gets a meeting.

An owner and a window

A person, not a team, and the time you have to act while the fix is still cheap.

Ranked, costed fixes

Each path shows what it recovers. Apply the top fix, or take it into the sandbox and build your own version around it.

Act With Control

Apply the fix, or argue with it first

Recommendations in most tools are accept-or-dismiss. Orbytal gives every fix two doors, because a revenue leader should be able to weigh options, not just approve them.

✓ Apply fix
The governed path

One click stages the change through a lifecycle: proposed, reviewed, deployed. Nothing silently mutates your live plan, and every change is versioned so you can see what was done, by whom, and roll it back.

Build your own scenario
The modeling path

Take the recommendation as a starting point and adjust the variables around it: different accounts, different reqs, a different quota split. Your version lives in a sandbox with a running tally of its impact, never touching the live plan until you commit.

Then compare. View any scenario against the current plan, or against another scenario, before anything ships. The point is to let you weigh two futures side by side, in dollars.
Every Fix in One Queue

Ranked by recovered revenue, tracked to outcome

Every recommendation across all six pillars lands in one queue, each tied to its root cause. Apply it, assign it, decline it, or build a scenario from it.

Phase quota to ramp capacityCapacity
Root cause  Quota over-assignment cliff −$900K
+$0.6M
✓ Apply fixBuild scenario
Multithread play on 24 single-threaded dealsCoverage
Root cause  Single-threaded deal majority −$900K
+$0.6M
✓ Apply fixBuild scenario
Re-sync routing rules to the current ICPICP
Root cause  Marketing-routing fit collapse −$600K
+$0.5M
✓ Apply fixBuild scenario
Then the scorecard takes over. Every applied fix is tracked from prediction to outcome: what Orbytal said it would recover, and what it actually did. The platform grades its own calls, to the same standard your CFO would hold you to.
Built to Be Believed

Honest math is the product

A revenue platform earns trust with numbers you can inspect and honesty about what it knows so far.

One ledger, three zoom levels

Revenue Health, the pillar scores, and the scenario impacts are one calculation at three resolutions. Any number you see breaks down into the parts beneath it, and the parts always reconcile to the headline.

Confirmed vs learning

Structural findings are confirmed from your plan and current state on day one. Behavioral patterns start labeled “learning your data” and sharpen as your history accrues. Precision is earned, never faked.

Gates, not guesses

When your data can't support a scenario yet, Orbytal says so and tells you exactly what to populate to unlock it. A locked scenario reads “unlock me,” never a number pretending to be real.

Every column names its source

The account, deal, and people registries show where each field comes from: the system that syncs it, or the mark that Orbytal computed it. When a number surprises you, you can see its provenance instead of arguing about it.

What Orbytal is not
Not a forecasting tool. Forecasting tools tell you the size of the gap and stop there. Orbytal decomposes the gap into named, costed risks and stages the fixes.
Not a BI dashboard. Dashboards show every metric and leave the interpretation to you. Orbytal interprets: it names the risk, traces the cause, and prices it in dollars.
Not an FP&A or budgeting tool. FP&A aggregates for the ledger and reports what already happened. Orbytal works at operational resolution, reps, territories, and deals, reads the leading signals, and acts on what it finds.
Built on Your Stack

Every pillar has a real data source

Connect your CRM and a plan target, and the first diagnosis runs the same day. Each additional connection unlocks more scenarios.

Salesforce HubSpot Gong ZoomInfo Gainsight Stripe NetSuite HiBob BambooHR Rippling Pardot CSV upload

See your own diagnosis

Find the gap in your plan

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