Richard Pugh – Commercial Director rpugh@mango-solutions.com Using R to Optimise a Sales Team...
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Using R to Optimise a Sales Team Richard Pugh Managing Director,
rpugh@mango-solutions.com Aimee Gott, Richard Weeks, Nick
Burgoyne
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Disclaimer: Cant say much Data and project is of a sensitive nature
Im not able to speak about the customer nor show the data
Simulating the data was fun, though!
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Agenda Project Background The Data What we did Reporting
Forecasting Modelling Extensions Summary
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Project Background
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Project Background Delivered many R-based projects for a company
Invited to present to upper management Strategic use of analytics
to solve meet business challenges Looking across business units
Agile analytics
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Project Background Introduced to the Sales Director who could use
some help with reporting Cant mention the specifics of the customer
so need to simulate a sales team and their behaviours I have
simulated data between January 2011 and December 2014 Lets meet the
sales team
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Sales Person Given sales opportunity by an internal lead generation
team Responsible for taking opportunities to a (hopefully
successful) conclusion John
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Sales Person Quarterly target Communication performed via forecast
stored in a clunky nice CRM tool Actions performed against
opportunity as logged John
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Sales Person John An opportunity is passed to John John thinks:
Opportunity size = 10,000 Likelihood = 60% John communicates:
Opportunity size = 8,000 Likelihood = 30%
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Sales Person John John works on the opportunity Later in the
quarter, John thinks: Opportunity size = 50,000 Likelihood = 90%
Time to close = 2 months John communicates: Opportunity size =
20,000 Likelihood = 50%
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Sales Person Johns behaviours driven by: Habit Situation Time
(within quarter) Target John may have upwards of 50 opportunities
at any time John
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Updates Opportunity JohnPaulGeorgeRingo Central CRM System Johns
Forecast Johns Actions Pauls Forecast Pauls Actions Georges
Forecast Georges Actions Ringos Forecast Ringos Actions
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
JohnPaulGeorgeRingo Central CRM System Johns Forecast Johns Actions
Pauls Forecast Pauls Actions Georges Forecast Georges Actions
Ringos Forecast Ringos Actions Brian also has a quarterly target
Brian communicates via another forecast His forecast is an
amalgamation of the forecasts from his team with some tweaks Brian
Brians Forecast
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
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- Richard Pugh Commercial Director rpugh@mango-solutions.com The
Data
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- Richard Pugh Commercial Director rpugh@mango-solutions.com A
Forecast
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Win/Loss Data
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- Richard Pugh Commercial Director rpugh@mango-solutions.com A
Basic Plot
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Tracking Opportunities over Time
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- Richard Pugh Commercial Director rpugh@mango-solutions.com What
we did?
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- Richard Pugh Commercial Director rpugh@mango-solutions.com What
we did? 1.Reporting 2.Forecasting 3.Modelling
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- Richard Pugh Commercial Director rpugh@mango-solutions.com What
we did: Reporting
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Reporting Reporting from the bad fantastic CRM system was poor
Manual tasks Poor report of forecast change No integration of
forecast with actions performed The Sales Directors view was of
sales as a funnel
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Sales Reports Data extracted from CRM database (SQL Server) using
RODBC Base graphics used to create sales reports The sendmailR
package used to automatically send out the reports each
morning
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Sales Reports Sales Team Individual report each day Sales Managers
Reports for their team Sales Director Amalgamated reports across
teams
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- Richard Pugh Commercial Director rpugh@mango-solutions.com What
we did: Forecasting
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Forecasting Typically, the forecast is reported as a point estimate
within a specific time window
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Forecasting For one of the reports, we simulated expected revenue
over a time period
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Forecast
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Forecast
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Forecasting So far, these simulations include only the reported
forecasts No variation on likelihood, size or close date However,
we can look at variation in these characteristics and
re-simulate
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Forecast
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- Richard Pugh Commercial Director rpugh@mango-solutions.com What
we did: Modelling
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Forecasting We achieved this forecast by varying opportunity
parameters But... What are the right parameters? Do they vary by
sales person?
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Modelling The assumption is that there are, and any point, 3 sets
of opportunity characteristics: The real (unobservable) likelihood
(e.g. 65%) The likelihood guessed by the sales person (e.g. 75%)
The likelihood reported by the sales person (e.g. 40%) The same
holds true for other opportunity characteristics (size, close date)
Some correlations are apparent (size likelihood)
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Modelling Each salesperson will report their forecast differently
based on a number of factors As the forecast is passed up to the
Sales Director, these biases are compounded How can we produce a
more accurate forecast? OR Can we extract the sales behaviours from
the data?
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Modelling So far, simple approaches proving successful ActualSize =
f(fcSize, activity) ActualClose = f(fcClose, fcSize, activity)
ActualProb = f(fcProb, time, fcSize, activity) Key parameters Size
(bias, error, error ~ activity) Close (bias, error, bias ~ size,
error ~ activity) Prob (bias, error, bias ~ time, bias ~ size,
)
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- Richard Pugh Commercial Director rpugh@mango-solutions.com The
Results NameClose DateOpportunity SizeLikelihood
BiasErrorBiasErrorBiasErrorSize Effect
John0.290.30-0.390.10-0.300.100.24 Paul-0.010.49 0.210.000.300.11
George0.010.410.000.200.400.740.30
Ringo-0.250.710.010.370.000.420.79 NameOriginalUpdated
ProbSizeCloseProbSizeClose John15% 2,60020/0455% 3,62001/03 Paul80%
21,50027/0280% 10,90028/02 George40% 1,10013/0120% 1,10012/01
Ringo30% 4,00001/0325% 3,96030/04
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Simulating Forecast
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Simulating Forecast
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Hierarchical Behaviour Change
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Extensions
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Extensions Better allocation of opportunities Target Setting
Within-Quarter Tracking Looking at other data sources Interactive
reports Using Google Charts to track the progress of an
opportunity
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Caveat To model behaviours you need many examples of the behaviour
We are lucky that this is a high(ish) volume business Better
applied to teams with high transaction levels (e.g. telesales with
a standard offering)
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Summary
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Summary Be an Analytic Advocate! Modelling behaviours is great R
perfect tool: Data, modelling, simulation and graphics Watch for
next instalment
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- Richard Pugh Commercial Director rpugh@mango-solutions.com
Questions