A few examples of data you'll need to become effective and reliable at sales forecasting. More detail in the accompanying blog post on http://DataDrivenSalesManagement.com

1. DATA REQUIRED FOR
EFFECTIVE SALES
FORECASTING
Swayne Hill
Twitter: @DataDrivenSales
Blog: DataDrivenSalesManagement.com
Copyright Swayne Hill, 2012

2. Period-to-Date Performance
Copyright Swayne Hill, 2012

3. Days to Closed/Won from Sales Stage
Averge Days to Closed/Won • Calculated using a 6-
From Stage
month historical view on
Stage 2 90
Closed/Won deals
Stage 3 63 captured from
Stage 4 40
Salesforce.com into our
Cloud9 data warehouse
Stage 5 23
• Average number of days
Stage 6 15
it takes to move from
Stage 7 0 any particular stage in
the sales cycle to
Closed/Won
Days to Closed/Won
Copyright Swayne Hill, 2012

4. Propensity to Close/Win from Sales Stage
% of Deals That Go To • Calculated using a 6-
Close/Won
month historical view on
Stage 1 35%
Closed/Won deals
Stage 2 42% captured from
Stage 3 50%
Salesforce.com into our
Cloud9 data warehouse
Stage 4 60%
• Percentage of sales
Stage 5 80%
opportunities that
Stage 6 95% ultimately move to
Stage 7 100%
Closed/Won from each
of our sales stages
% To Close/Won
Copyright Swayne Hill, 2012

5. Sales Forecast Risk Profile
Stalled Deal Risk filter, driven from Opportunity Scoring benchmark
and historical Salesforce.com CRM data
Copyright Swayne Hill, 2012

6. Sales Forecast Risk Profile
Met with VP Sales Risk filter, driven from Opportunity Scoring System
Copyright Swayne Hill, 2012

7. Sales Forecast Risk Profile
Pushed Deal Risk filter, driven from historical Salesforece.com
CRM data
Copyright Swayne Hill, 2012

8. DATA REQUIRED FOR
EFFECTIVE SALES
FORECASTING
Swayne Hill
Twitter: @DataDrivenSales
Blog: DataDrivenSalesManagement.com
Copyright Swayne Hill, 2012