2. Why Analytics
• What Do We Report Now?
• What Do We Want to Report?
• What Would Analytics Look Like?
• Example of HR/Learning/Performance Data
3. • Number of trained employees
• Total/Average learning hours
• Test scores
• Training satisfaction
• Knowledge/Skills application
What does that do
with my business?
4. • Performance improvement in
monetary value
• Influencers to performance
changes
• Performance changes by
learning
• Turnover expenses for high
performers vs. low
performers
• …
That’s what I
want!!!
9. Transform organizational conversations/dialogue and outcomes regarding
employee development and human performance by delivering a complete
analytical picture and insights about human capital.
Data
Information Reports
Insight/
Foresight
Actionable and consultative findings
Decisions &
Actions
Follow up
Results
80% Reporting / 20% Analysis 20% Reporting / 80% Analysis
Reporting
Intelligence
Analytics
11. Core
Competency
Functional
Competency
Leadership
Competency
Product Sales Service Claims
Product
Attractiveness
Product
Competitiveness
Close
Ratio
Quote
Age
FCR NPS
QAR
Claim
Age
• Industry report
• Business data warehouse
• Phone systems
• Customer entry survey
• Customer satisfaction
survey
• Employee data
Data Sources
• Performance review
• Succession plan data
• Competency library
• Job family library
• Employee data
Product
Knowledge
Behaviors
Process
Knowledge
behaviors
Technical
Skills
behaviors
Soft skills
behaviors
Leadership
Skills
behaviors
• KSA behavior library
• Learning management
system
• Employee data
Learning
Objective
Learning
Objective
Learning
Objective
Learning
Objective
Learning
Objective
• KSA behavior library
• Employee/manager survey
• Learning management
system
• Employee data
Value Chain
12. Strategic Initiative
Business Performance
Performance Metrics (KPIs)
Competency Behavioral Anchors
KSA Behavioral Anchors
Observable knowledge and skills in products,
policies, processes, systems, soft skills, leadership
skills within each KPI, such as First Time Call
Resolutions
Observable behaviors in each competency in core,
functional, leadership competency categories and
its behavior
KPI descriptions and measure, e.g., “Proactively
keeping customer informed of Claims,” measured by
customer survey and outbound call ratio.
HR/Learning Portfolio Initiative
Organizational HR/Learning Data
Employee HR/Learning Data
HR and Terminal Learning Objectives
Enabling Learning Objectives
Learning objectives matching the KSA behavioral
anchors 1-to-1 and/or many-to-many
Recruiting plans, succession planning, career
development, terminal LOs matching competency
behavioral anchors 1-to-1 and/or many-to-many
Tenure years, salary, performance review, learning
hours, number of completed courses, etc.
Monetary values of performance, such as
revenues, profits, expenses, cash flow, etc.
Monetary values of learning/HR input, such as
internal recruiting, tern-over of high performers,
learning hours, etc.
Strategy driving business performance, such as
growth, innovation, competition, etc.
HR and learning portfolio strategy supporting
strategic initiatives
Hierarchy of Influencers Hierarchy of Performance
13. KPI: Auto Ins. First Call Resolution (target: 95%)
KSABehavioralAnchors
Behavior 1: Accurately identify customer’s needs
by asking quality questions. (weight: 30.0)
Behavior 2: Properly navigate to or search
necessary Auto insurance product information
pages in performance support system.
(weight: 25.5)
Behavior 3: Enter all necessary changes in the
appropriate system(s). (weight: 25.0)
Behavior 4: Review all necessary changes with
the customer. (weight: 15.0)
Behavior 5: Ask if the customer is satisfied with
the changes and further assistance is necessary.
(weight: 4.5)
Learning Objective Pool
LearningObjectives
B1LO1: Given a scenario, tell if the inquiry the
customer has is for adding a car/insurer, change
mailing/garage address, and/or billing changes
(weight: 1.5)
B2LO2-1: Given a scenario, explain what are
necessary steps to solve the inquire (weight: 1.2)
B2LO2-2: Given a scenario, explain underwriting
rules and/or product information that apply to
the customer inquiry or navigate to Auto
performance support system and find the
information (weight: 2.1)
Virtual Job Try-out Level 1 Evaluation Level 2 Evaluation Level 3 Evaluation Level 4 Evaluation Level 5 Evaluation
Aptitude fitness Performance
readiness
Learning satisfaction
Performance
accuracy,
completeness
Performance
competency,
frequency
Business impact ROI
B2LO3: Given a scenario, enter all information to
PAS with 95% completeness or higher.
Measure
Evaluate
16. Infrastructure Work Motivation
Organization
Effectiveness
Individual
Effectiveness
• Culture/Strategy/Vision, etc.
• Product
• Information Flow,
Communication
• Talent Acquisition
1
• Workforce Management
• Processes
• Performance Support
2
• Benefits
• Compensation
• Work/Life Balance
• Recognition
• Succession Planning/Promotion
3
• Career Development
• Learning and Development
4
• Cognitive Knowledge and
Ability
• Psychomotor Skills
• Experience
5
• Attitudes and Willingness to
Perform
• Exposure
6
Lag Performance Indicators: Profitability and Growth
• Time to Market
• Hiring Effectiveness Indicator
• Innovation Indicator
• Etc.
• Time to Proficiency
• KPIs: NPS, Close Ratio, etc.
• Employee Engagement Score
• HR Satisfaction
• Leadership index
• Etc.
Lead
Performance
Indicators
18. Items File type Location/Owner Update
Frequency
Employee information Database HRIS/HR Operations Daily
Hiring information Database HRIS/Talent Acquisition Ac Hoc
Job family description PDF SharePoint/Compensation Ac Hoc
Career development
Guide
PDF SharePoint/Talent Management Yearly
Training course
information
Database SharePoint/AAA University Ac Hoc
Training Expenses Database SharePoint/AAA University Monthly
Infrastructure
101001 Lee, Sean 3/31/2007 AAC04
Business
Consultant
Biz101 $xxx.xx
HRID name Hired
date
Job Family Role Completed
course
Learning
cost
19. Items File type Location/Owner Update
Frequency
Virtual tryout score Database Visier/Talent Mgmt. Ad Hoc
Training test score Database LMS/AAA University Transactional
Learning hours Database LMS/AAA University Transactional
Competency data Database HRIS/Talent Mgmt. Yearly
Performance review Database HRIS/Talent Mgmt. Yearly
Close ratio Database Cognos/Direct Sales Yearly
Net promotor score Database MyGPS/Contact Center Transactional
Work
101001 Lee, Sean 3/31/2007 AAC04
Business
Consultant
Biz101 $xxx.xx 85 91 Analytics 5 Achieved 26%
VJT score L2 score Competency Competency
level
Performance
review
HRID name Hired
date
Job Family Role Completed
course
Learning
cost
Close
ratio
20. Items File type Location/Owner Update
Frequency
Succession Plan Database HRIS/Talent Mgmt. Yearly
Engagement score Database Vendor/Talent Mgmt. Yearly
360 review results Database HRIS/Talent Mgmt. Ac Hoc
Promotion Database HRIS/Business Ac Hoc
Paid Time Off Database HRIS/Compensation Ac Hoc
Salary/Benefit Database HRIS/Compensation Yearly
Motivation
101001 Lee, Sean 3/31/2007 AAC04
Business
Consultant
Biz101 $xxx.xx 85 91 Analytics 5 Achieved 26% $xxx,xxx 97
VJT score L2 score Competency Competency
level
Performance
review
HRID name Hired
date
Job Family Role Completed
course
Learning
cost
Close
ratio
Salary Engage.
score
21. 101001 Lee, Sean 3/31/2007 AAC04
Business
Consultant
Biz101 $xxx.xx 85 91 Analytics 5 Achieved 26% $xxx,xxx 97
Performance
VJT score L2 score Competency Competency
level
Performance
review
HRID name Hired
date
Job Family Role Completed
course
Learning
cost
Close
ratio
Salary Engage.
score
0.74 0.68 0.84 1 0.12 0.46
Correlation Rate (Correlation Test)
4.5 5.4 7.2 1.5 1.7
Causation Rate (ANOVA, Regression Test)
22. Core
Competency
Functional
Competency
Leadership
Competency
Product Sales Service Claims
Product
Attractiveness
Product
Competitiveness
Close
Ratio
Quote
Age
FCR NPS
QAR
Claim
Age
• Industry report
• Business data warehouse
• Phone systems
• Customer entry survey
• Customer satisfaction
survey
• Employee data
Data Sources
• Performance review
• Succession plan data
• Competency library
• Job family library
• Employee data
Product
Knowledge
Behaviors
Process
Knowledge
behaviors
Technical
Skills
behaviors
Soft skills
behaviors
Leadership
Skills
behaviors
• KSA behavior library
• Learning management
system
• Employee data
Learning
Objective
Learning
Objective
Learning
Objective
Learning
Objective
Learning
Objective
• KSA behavior library
• Employee/manager survey
• Learning management
system
• Employee data
Value Chain
1.6 2.1
3.4 2.7
0.6 0.8
0.3 0.9
1.2
1.8
4.4 1.7 0.5 2.9 3.6 0.1
1.2
2.2
4.7 0.9
4.2 3.7 5.4
0.7
0.9
23. Working With the Business
• Learning/Performance/HR Consulting Flow
• Lessons Learned
24. Business Intelligence
(Sales/Service/Claims)
Partnering Assessing Designing Implementing Measuring
Proactively identify
opportunities
Response to
requests
• Manage &
complete
transactional
requests
• Reframe tactical
requests
Determine if
strategic,
operational
or
tactical
Determine
business and
performance/HR
requirements
Report results to
business units
and agree on
solutions
Plan, design,
and/or select
solutions
Implement
solutions
Measure and
report results to
clients
* Modified from “Performance Consulting Process,” created by Robinson & Robinson, “Performance Consulting,” second edition, p44.
Tactical
HR/Learning & Dev.
Business Management
(Sales/Service/Claims)
Employees
Monitoring
25. Get Executive Support
• Support from Who Actually Handle Data is Also Important.
Find the Original Data Sources
• Business data are usually recorded in IT systems and managed
by Data Governance.
• Be prepared for data disparity, disjoints, missing fields, etc.
Clear Roles and Responsibilities
• We aren’t taking their job away (different purposes of analysis).
• Help them shine (don’t take their credits).
Learn What KPI Means and How They are Used
• Where all the ratios come from.
• Different roles and priorities of KPIs.
• How Managers use KPIs in multiple for performance
management.
27. Analytics
KPI Redesign Support
• Performance mgmt. system
• Performance surveys
• Quality assurance redesign, etc.
Learning Redesign
• Curriculum portfolio
• Learning objectives
• Learning methods, etc.
• Learning surveys
Human Resources Redesign
• Organization
• Competency
• Compensation and benefits
• Engagement surveys, etc.
Employee Performance Improvement
Business Strategy Support
Business Data
Revenues, Sales Close Ratio, Quote,
Customer Satisfaction, QA …
Human Resources Data
Compensation, Learning, Benefits,
Talent Acquisition/Management …
Data Governance
Correlate
Create the
Perfect
Customer
Experience
Strategic Initiatives
Accelerate &
Innovate
Products and
Services
Expand
Distribution &
Grow
Membership
Foster a
Culture of
Insight &
Innovation
Connect to the
Digital World
Complete &
Optimize Our
Member-
Centric Platform
28. Transactional KPI data
• Sales: Close ratio, length
of quote
• Service: NPS, Service
level, handling time, first
call resolution, etc.
• Claims: Outbound call
ratio, Claims quality, etc.
Individual Learning data
• Learning consumption
• Satisfaction
• Application of knowledge
Individual HR data
• Tenure, education, etc.
• Performance review,
succession planning,
career development
• Engagement
Data Gathering Analysis
Performance
Learning
HR
Correlation/causation
between Lead (close
ratio, first call
resolution) and Lag
KPIs (DWP, NPS)
Learning impact
(Learning objective
>> Performance
behavioral anchors)
HR impact
(Recruiting, talent
mgmt., engagement,
turn-over, etc.
KPI Redesign Support
• Performance mgmt.
system
• Performance surveys
• Quality assurance
redesign, etc.
Learning Redesign
• Curriculum portfolio
• Learning objectives
• Learning methods,
etc.
• Learning surveys
HR Redesign
• Organization
• Competency
• Compensation and
benefits
• Engagement surveys,
etc.
Design/Development
Evaluation
29. Member-Centric Analytical Capabilities
Customer
Segmentation &
Targeting
Product
Performance
Management
Claims Service
Performance
Management
Distribution
Channel
Management
Financial &
Risk
Management
Human
Resource
Management
Functional Capability
Analytical
Tools &
Application
Research &
Development
Human Capital
Infrastructure
Big Data
System
Streaming
Computing
Data
Warehouse
Data Governance
• KPI Redesign
Support
• Learning Redesign
• HR Redesign
30. Four levels of data structure
Our target is to gather and monitor
all four levels of data to provide
business units with analytical
insight to draw their organizational
and individual successes.
Organizational Data
• Revenues / Profit / Underwriting Expenses / PIF
Performance Data
• Sales: Leads/ Contacts/Quote…
• Claims: NPS/Keyed claims/ DRN…
• Service: NPS/ FCR/ AHT/PA…
HR Data
• Acquisition / Promotion / Retention
• Succession Plan / Performance
Review
Learning Data
• Course consumptions
• Reaction to Learning
• Knowledge/Skills
• Application
• Impact
31. Required Data Fields
To provide our business partners with meaningful analytic reports, we need data about
employee, career, learning & performance (L&P) budget, L&P projects, vendor, learning,
learning evaluation, key performance index, competency, performance goals, and other HR
categories.
32. What is learning impact to performance?
• High performers learn more (hours and frequency)?
• Training duration impacts performance?
• Performance readiness/confidence impact actual performance?
What are key HR influencers for performance and learning?
• High performers have higher engagement and desire to learn?
• Higher entry test (VJT) score means higher performance?
• Better employee engagement means higher performance?
• Promotion/compensation/performance review/career development impact
performance and learning desire?
What are monetary values of HR/Learning influencers?
• Cost to hire/train/manage per performer?
• DWP (sales) and member retention (service/claims) per performer?
• DWP and member retention improvement per KPI score improvement?
• Proportion of HR/Learning influencers to DWP/Retention?
33. Statistical Approach
Human Capital (HP)
• DWP per sales rep ($6,000/d)
o High performer ($9,000/d)
o Low performer ($5,000/d)
• Renew per service/Claims rep
($5,000/d)
o High performer ($8,500/d)
o Low performer ($4,000/d)
Descriptive
Method
• Historical data summary
Human KPI
• Average KPI (93%)
o High performer (96%)
o Low performer (89%)
HR Trends (hiring/training/...)
• Cost: $15,000
• VJT/Turnover/promotion/…
Learning Trends
• Learning Hours/Effectiveness)
o High performer (10 hrs/9.2)
o Low performer (3 hrs/8.2)
Method
• Correlation analysis
Correlation
KPI Influence on DPW/Renewal
• Close ratio (CR: 0.91)
• Quote age (QA: 0.72)
• Net Promoter Score
(NPS:0.64)
• Product Attractiveness (PDA:
0.67)
HR Influence on Human KPI
• VJT (0.81)
• Candidate persona (0.45)
• Performance review (0.75)
• Engagement (0.56)
• …
Learning Influence on KPI
• Time to proficiency (0.81)
• Learning hours (0.45)
• Level 2 score (0.62)
• Training satisfaction (0.31)
Method
• ANOVA, Regression test
Causation
KPI Causes on DPW/Renewal
Changes
• Industry growth (IG) influence
size (4.2)
• CR influence size (7.5)
• QA influence size (5.7)
• PDA influence size (4.6)
HR Causes on KPI Changes
• VJT influence size (2.2)
• Candidate personal influence
size (6.5)
• Engagement influence size
(5.7)
• …
Learning Causes on KPI
Changes
• Learning influence size (1.2)
Method
• Statistical model
Predictive
KPI Influence Model
• DWP/Renewal = HP X # of
• Sales HP = ((CR + QO) – IG) X
0.2154
• Service HP = ((NPS + FCR +
PDA) – IG) X 0.3612
HR & Learning Influence Model
• KPI = ((VJT + Engagement +
Level 2 Score + Compensation
+ …) X 0.7413
101001 Lee, Sean 3/31/2007 Achieved 85 12.7 Biz101 4/28/2015 Completed 91 $1,250 $xxx,xxx 15 … … …
HRID name Hired
date
Performance
review
NPS
score
Learning
hours
course Emp.
engagement
Human
capital
Comp. Leave of
absent
Learning
date
Learning
status
… … …
