Module 05Forecasting

A sales forecast your manager can defend, built from five dashboards and no guesses.

Sales forecasting dashboard setup inside the CRM you already pay for. We configure weighted or category forecasting, build the five dashboards a sales manager actually opens on a Monday, and print the definition of every metric on the dashboard itself. For teams of 3 to 150 seats, run from Mission Street in San Francisco, delivered remotely across the United States.

Price basis
$600 to $1,100 per dashboard
Typical scope
5 dashboards, 1 forecast model
Metric definitions
On the dashboard, not in a wiki
Build time
1 to 2 weeks after data is clean
Fix window
30 days after launch
Sales forecast dashboard with stage conversion and a weighted pipeline chart

Dashboard 01 / Forecast versus quota, weighted by stage

Price, stated before the call

What forecasting dashboards cost

Each dashboard is priced on its own, $600 at the simple end and $1,100 when it needs calculated fields, a snapshot history or data from a second object. Most teams take four or five. Five dashboards at those rates come to $3,000 at the bottom of the band and $5,500 at the top.

Per dashboard$600 to $1,100Charts, filters, definitions panel
Five-dashboard set$3,000 to $5,500The full manager pack below
Forecast modelInside the setWeighted or category, not both

These are bands. We quote in writing after a 45-minute scoping call, once we have seen how clean your stage and close-date data is.

Two models, pick one

Weighted versus category forecasting

A weighted forecast multiplies each open deal by the probability attached to its stage. A $40,000 deal sitting at Proposal with a 50% stage probability contributes $20,000. Add every open deal and you get one number. It is mechanical, it needs no judgment from the rep, and it is only as good as the stage probabilities, which is why we set them from your own last four quarters of closed deals rather than from the CRM defaults.

A category forecast asks the rep to put each deal in a bucket: Pipeline, Best case, Commit, Closed. The manager reads Commit as the number the team is signing up for. It carries the rep's judgment, and so it carries the rep's optimism too.

Teams under 15 seats with short cycles usually do better on weighted. The volume is small enough that a manager knows every deal anyway, and the probabilities do the arithmetic. Teams with enterprise deals over 90 days and a real commit call usually want category, with the weighted number shown next to it as a check. We configure one as the forecast of record. Running two official forecasts is how a Monday meeting turns into an argument about which one is true.

Both depend on the close date. So the close date becomes mandatory at Proposal and nowhere before, and a deal whose close date has already passed drops out of the forecast until someone moves it. That rule alone usually removes 10 to 25% of a pipeline's stated value on day one. Managers hate it for a week.

Worked example / One deal, two modelsProposal
Deal value
$40,000
Stage
05 Proposal
Stage probability
50%, set from closed history
Weighted value
$20,000 counted
Rep category
Best case
Category value
$40,000 in Best case, $0 in Commit
Close date
Required from this stage on
Close dates past due, typical first audit 10–25%

The manager pack

The five dashboards a sales manager actually opens

We have seen CRMs with 60 dashboards and a manager who opens two. These five cover the weekly forecast call, the one-to-ones and the quarter review. Anything past five needs a named person who will act on it.

  1. 01Forecast versus quota

    Where the quarter lands

    Closed won, forecast of record and quota for the period, by rep and by team, with a snapshot line taken every Monday at 06:00 Pacific so you can see how the number moved week over week.

    Opened before the forecast call. Built from the model above and nothing else.

  2. 02Pipeline coverage

    Is there enough to close

    Open pipeline for the next two quarters divided by remaining quota, split by stage. A coverage ratio under 3x for a team closing 25% of qualified deals is a hiring or prospecting problem, not a forecasting one.

    Opened at the start of each month.

  3. 03Stage conversion

    Where deals die

    The share of deals entering each stage that reach the next one, over a rolling 180 days. This is the dashboard that tells you the Demo stage loses 60% of deals and the Proposal stage almost none.

    Opened in the quarter review.

  4. 04Cycle time

    How long each stage takes

    Median days spent in each stage for won deals and for lost ones, side by side. Lost deals that sat in Negotiation for 40 days while won deals took 9 is a signal worth a coaching conversation.

    Opened in one-to-ones.

  5. 05Hygiene

    What is lying to the forecast

    Open deals with a past close date, no activity in 14 days, a missing amount or no next step. One list per rep, sorted by value. When this list is empty the other four dashboards can be trusted.

    Opened every morning by the reps, not the manager.

Forecasting / rule 04

Your forecast is only as honest as the close date. So we make the close date mandatory at Proposal and nowhere before.

Stage sheet, rule 04

Printed on the dashboard

Metric definitions, written down once

Every chart gets a short text panel beside it with the formula and the rule behind it. If the VP of sales and a new rep read the same number two different ways, the dashboard failed. These are the defaults we start from; your stage sheet can change them.

  1. M01

    Stage conversion

    FormulaDeals that entered stage N and later entered stage N+1, divided by all deals that entered stage N, in the window.

    RuleA deal that skips a stage counts as converted through it. Deals still open in stage N are excluded, not counted as lost.

  2. M02

    Cycle time

    FormulaCalendar days from the date a deal entered Qualified to the date it was marked Closed won or Closed lost. Median, not mean.

    RuleMedian because one 400-day zombie deal drags a mean by weeks. Deals reopened after close restart the clock.

  3. M03

    Win rate

    FormulaClosed won divided by closed won plus closed lost, counted from Qualified onward, by close date.

    RuleLeads that never reached Qualified are not losses. Counting them turns a 30% win rate into 4% and nobody learns anything.

  4. M04

    Pipeline coverage

    FormulaOpen pipeline value with a close date inside the period, divided by quota minus closed won for the same period.

    RuleDeals with a past close date are excluded. Unweighted, so it reads as a raw ratio against your own win rate.

  5. M05

    Weighted pipeline

    FormulaSum of amount multiplied by stage probability for all open deals closing in the period.

    RuleStage probabilities are reviewed every quarter against actual conversion. A probability nobody has checked in a year is decoration.

  6. M06

    Stale deal

    FormulaOpen deal with no logged activity, stage change or amount change in 14 calendar days.

    RuleSame 14 days the stale-deal alert uses, so the dashboard and the reminder never disagree.

Sales manager reviewing the weekly forecast on a laptop
Monday, 08:30Dashboard 01 before the call

Who builds it and where

Built inside your CRM, owned by you

We build with the native report and dashboard tools of the CRM you already license. No separate BI tool, no extra seat to buy, no export job that breaks when someone renames a field. If your CRM genuinely cannot calculate something you need, we say so at scoping and tell you what it would take elsewhere.

Dashboards come after the pipeline. If the stages are still eleven columns nobody can tell apart, a forecast built on them just charts the confusion faster. In that case the work starts with pipeline design and the stage sheet, and duplicate accounts get merged through data cleanup before a single chart is drawn.

  • Every metric carries its definition in a text panel on the dashboard.
  • Stage probabilities set from your closed deals, reviewed quarterly by your admin.
  • Weekly snapshots so forecast movement is visible, not reconstructed from memory.
  • Documented in the admin guide handed over at training.

Process

From audit to the first Monday call

Two weeks for most teams, measured from the day we get read access to the CRM.

  1. Day 0

    Scoping call, 45 minutes

    Which meetings the dashboards serve, which model you forecast on, who reads what. Written quote within two business days.

  2. Days 1–3

    Data audit

    We count past-due close dates, deals without amounts and stages with no conversion history. You get the numbers before we build anything.

  3. Days 4–5

    Definitions sheet signed

    One page listing each metric, its formula and its rule. Your sales lead signs it. Configuration waits for the signature.

  4. Days 6–10

    Build and snapshot setup

    Reports, dashboards, definition panels, the Monday snapshot. Checked against three deals we trace by hand end to end.

  5. Days 11–40

    Live, with the fix window

    For 30 days after launch, anything we configured that does not behave as the definitions sheet says gets fixed at no charge.

Before you book

Questions managers ask about forecast dashboards

Our CRM already ships forecast dashboards. Why pay for new ones?

The shipped ones assume default stages and default probabilities. If your pipeline was customised at all, the defaults are measuring something that no longer exists. We rebuild on your stages and your history.

Can you build a dashboard for every rep and every region?

We build one dashboard with filters for rep and region. Twelve copies of the same dashboard means twelve places to fix a definition when it changes.

Who is this not for?

Teams that want a board-deck revenue model mixing CRM, billing and finance data. That is BI and finance work and we do not take it. Also teams with fewer than about 30 closed deals in the last year: there is not enough history to set honest stage probabilities, so we would recommend a category forecast and a hygiene list and stop there.

What if the numbers look worse after you are done?

They usually do, for about a week. Past-due deals leave the forecast and coverage drops. The pipeline did not shrink. It was never that size.

Who maintains the dashboards after launch?

Your admin, from the admin guide. If you have no admin, the monthly retainer at $1,150 for 10 hours covers definition changes and quarterly probability reviews.

Scoping call

Book a scoping call

Tell us your CRM, your seat count and which meeting the numbers are for. A person replies during business hours, Pacific time.

Studio
415 MISSION STREET, 3RD FLOOR
SAN FRANCISCO, CA 94105

All six services and their scope · Cost estimator

Reply within one business day. No mailing list.