Talk to an Expert
FP&A

For FP&A and deal desk.

Every deal is a snowflake. Forecasts miss. Margin drifts. Deal desk is full-time firefighting. We rebuild pricing architecture so deal economics become predictable instead of artisanal.

SPP designs pricing architecture to be forecastable. Packaging boundaries that map cleanly to segments. A value metric that scales with customer behavior in a predictable way. Discount authority tiered so 80% of deals never need deal-desk review. Margin variance shrinks because the architecture was rebuilt to produce it, not because you policed it.

LevelSetter becomes the operating layer FP&A actually wants. Pricebook versioned and auditable. Every deal’s margin exposure visible before close. Monthly ARR-mix reports our team produces from LevelSetter, not via spreadsheet heroics. Forecast accuracy goes up because the underlying deal behavior finally stabilizes.

The Expert
Ranked #1 on OpenView’s list of B2B SaaS pricing experts.

Former B2B software CEO — built an angel-backed company ($13M raised) recognized as an Intuit Top 10 Developer. Business of Software keynote speaker. Hired SPP as a client in 2008. Joined the firm in 2013 and built LevelSetter from the problems he’d lived firsthand.

Chris Mele
CEO, Software Pricing Partners
40–60%
Reduction in deal-desk
escalation volume.
3–5×
Tighter margin
forecast variance.
Live
ARR-mix reporting,
not month-end reconciliation.
The signal

The model assumes ARR plus a blended discount rate. The blended rate is never the real rate. Variance by segment is wide. Every deal pays to paper over an architecture gap. Forecastable ARR requires forecastable pricing.

The triggers

When the architecture
blocks the forecast.

01.A

Margin forecasting
breaks every quarter

The model assumes ARR and a blended discount rate. But the blended rate is never the real rate — it’s an aggregate that hides wildly different per-segment behavior. Variance compounds quarter to quarter and Finance is always one explanation behind.

01.B

Deal desk
lives in exceptions

Every deal needs custom review. No two look alike. The “standard” deal is a fiction; approval queues never clear; deal-desk analysts churn because the job is all firefighting.

01.C

Margin leakage is
structural, not behavioral

You have audited reps. You have tightened approvals. Margin still leaks because the pricing architecture has gaps every deal pays to paper over. No discipline program fixes an architecture problem.

01.D

ARR mix is unreadable
across products

Three product lines, three different value metrics, three different packaging norms. Rolling it up takes monthly manual reconciliation. Investors ask questions you cannot answer cleanly.

01.E

Pricing-change impact
can’t be modeled in advance

Change a metric, redraw a packaging boundary, reset a discount tier — and the legacy base reacts in ways nobody modeled in advance. Finance ends up building one-off spreadsheets under deadline pressure, with assumptions that go stale before the change ships.

The problem

You can’t tighten variance
with better spreadsheets.

FP&A keeps tuning the model. Deal desk keeps adding case-by-case rules. Forecast variance stays wide because the architecture that produces deal shape was never designed to be forecastable. The variance is structural, not measurement.

The fix is to rebuild the architecture so it produces predictable deal shape. Packaging boundaries that don’t require custom-shaping at deal desk. Discount authority tiered from data, not policy. Margin variance shrinks at the source. The model gets accurate because the underlying behavior finally stabilizes.

The method

Diagnostic, rebuild,
continuous operation.

Three phases: diagnostic on deal-level variance, architecture rebuild for forecastability, ongoing operation through LevelSetter.

02.A

Diagnostic on deal-level variance by segment

We pull closed deals, tag by customer profile, decompose realized-vs-list into discount, packaging downgrade, and term concessions. The forecast error is never randomly distributed: it clusters in specific segments with specific architectural mismatches. We name them.

02.B

Architecture rebuild engineered for forecastability

Packaging boundaries redesigned so segments don’t require custom-shaping at deal desk. Reps transact against a Scheduled Net Price: what 80% of deals need is built into the schedule, leaving deal desk to route the real exceptions. Margin variance by segment drops because the architecture stops producing it.

02.C

Continuous operation through LevelSetter

Pricebook versioning, deal-level margin exposure, ARR-mix reports built into the operating layer rather than reconstructed monthly from spreadsheets. When licensing, packaging, or pricing changes, we use LevelSetter to compute the legacy-base impact and simulate outcomes for Finance to review, not build. Deal desk routes signal instead of processing every case.

Walker White, President of BDNA — case study video Play

BDNA: $5M to the bottom line when pricing got guardrails.

Hear Walker White, President of BDNA, on the cost of running pricing without guardrails — and what changed when discipline replaced firefighting. The architecture rebuild compounded into a $5M bottom-line gain during the hold.

Read the case study →
The proof

The calendar collapsed.
Exit premium followed.

<3%
Variance to Scheduled Net Price · BDNA

Pre-SPP, BDNA buyers learned to wait. Most business booked in the final weeks of Q4. Reps scrambled to be in the late-night December 31 batch, jamming deals through Finance to clear commissions. The price was whatever year-end pressure produced.

SPP rebuilt the architecture around continuous monetization: reps transact against a Scheduled Net Price.

Variance to Scheduled Net Price fell under 3%, and the calendar effect collapsed. That discipline delivered a 20% premium at exit. Flexera could value the pipeline at full strength because predictable pricing produces a forecastable asset, not a pile of year-end concessions.

Frequently asked questions

LevelSetter sits alongside Salesforce CPQ, NetSuite, Adaptive, Anaplan, Zuora, and Chargebee. It holds the pricebook and governance layer; your existing CPQ handles quote generation and your FP&A tools consume the structured deal data.
Usually the margin model is fine; the variance it reports is the symptom, not the cause. The architecture rebuild shrinks the variance the model has to absorb. The model itself rarely needs structural changes.
Yes, and often it’s the right approach. A single-product-line pilot validates the architecture methodology and the LevelSetter operating layer before you commit to a multi-product rollout. ROI is visible in the pilot window.
Deal-desk shifts from case-by-case processing to signal routing and exception handling. The role becomes more strategic and less reactive. Headcount usually stays flat; the work changes.
Yes. The diagnostic phase produces the architecture recommendation and forecast-variance model before implementation starts. You can stop after diagnostic if the findings do not justify the rebuild. Most clients continue, but the decision point is real.

Stop forecasting against deal-by-deal variance.

If your forecast is fighting the architecture that produces deal shape, that’s the conversation. Renewable. Each renewal is one we earn.