Sales Effectiveness 5.0 – Personality Predicts Performance
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Sales Effectiveness5.0 – Personality Predicts Performance
Salesforce Effectiveness Solutions
What results have our clients achieved?
50% additional personal sales revenue when an identified ‘good match’ is hired
Increased commission by 8%
50% reduction in hiring manager time spent on recruitment
What results have our clients achieved? cont.
Using People Analytics to
Identify better and stronger sales professionals
People AnalyticsUsing data to drive business success
• Create smart algorithms• Give insights on your organisation from a people
perspective• Enable a targeted and holistic people strategy • Driving your business needs.
We analyse assessment data and on-the-job performance metrics to create a success profile. This profile can be used to define benchmarks during future selection and development processes.
TOPperformance
Requirements
▪ Performance Data!
Pilot Study:
Gather behavioural data on a large group of employees
Analyze the behavioural profiles of high and low performers
Thereby creating the ideal behavioural profile of a Sales employees
PERFORMANCE METRICS
Key Performance Metrics for their Sales roles could include:
- Sales Revenue
- Profit Generated
- Time to Proficiency
Ideal Profile
Organisational Overview
Model for Selection
Output in client competencies
Assessment Results
Competency Mapping
Performance Data
Understanding Performance:
- Likelihood of Reaching Attainment
- Voluntary Terminations
Sales Employees
Competencies
Behavioural Preferences
Performance DataIdeal
Profile
Organisational Overview
Model for Selection
Model for Development
Data Analytics by cut-e:
Correlation studies between cut-e tools and actual performance data
Advisory by cut-e:
Presentation of results and guidance on how to
implement the findings
Defining the Success Profile
Success ModelValidationProject Definition
SUCCESS PROFILE
Final model ready for roll out for Internal and External
selection as well as development
HYPOTHESIS DEFINITION
Review of relevant performance metrics and formulation of
hypothesis
PILOT PROJECT ASSESSMENT PROCESS
Roll out of cut-e assessments
(shapes/Adept) to 100 people
ANALYSIS BY CUT-E
cut-e review all assessment results and performance data
from employees to create success profiles
STEP 1 STEP 2 STEP 3 STEP 4
Understanding Performance: Approach
▪ Correlation Study of competency results from our shapes questionnaire and scales to sales performance and other business
metrics
▪ We agree the key business metric you wish to improve -> i.e. Sales, Retention etc.
Know what makes for success –and spot this in candidates
When you have the data, it is straightforward to do.
Create a success profile and look for these characteristics, skills and qualities in applicants.
The result is a ‘match score’ which:
▪ shows the fit between job and applicant
▪ helps you sift through all applicants speedily
▪ predicts likely success in the role
Dell: What did the Data tell us?
Turnover Better, Faster
Revenue Profit• It takes time to achieve high levels of productivity• People who stay longer remain on an upwards trajectory – value increases• Some people who show the same initial upwards trajectory will leave • We can use the data to identify those that fit your culture, remain and perform
42%Increase in Average Profit Generation
Reduced likelihood to voluntary term
Time to Proficiency
Reduced amount of time until achieving potential
36%Increase in Average Revenue Generation
Dell – Summary
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