Predictive analytics – creating actionable insights

Predictive HR analytics – creating actionable insights Patrick Coolen

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Why HR analytics @ ABN AMRO

1. Business is demanding more …

• HR Return on investment• Impact (benefits) of HR

2. HR is moving towards fact-based decision making

3. Technology is improving… • HR IT landscape• Analytics on demand

Business goals

Business impactHR ROI

Information TechnologyFact-based HR

HR analytics – maturity model

You can start here!

Some of our research

Retail – customer satisfaction, quality and revenue

Engagement – vision & direction, client focus, fair treatment

IT – Long term and short term sick leave

Leadership program - Effectiveness

Large corporates – Team effectiveness on business

IT operations / call centre – Average Handling Time and satisfaction

Commercial clients – Net promoter score and ‘trusted advisor’

Private Banking – Client Satisfaction, client acquisition and revenue

Vitality program – Effectiveness

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Combine HR and Business data

Engagement•Total score•Vision & Direction•Client Focus•Training & development•Job Challenge

Individual characteristics•Age•Gender•Appraisal score•Potential score•Level•Job title•Competenties

HR themes•Gender ratio•Leadership index•Group mobility•Temp ratio

Client satisfaction(more then 100k

records incl. open questions)

Products sold(offerings approved by

client)

Quality of advice(Independent score by

Internal quality desk)

Net income growth(individual net growth

of client portfolio)

Client satisfaction(Net promoter scores)

New customers(Individual new customers

acquired)

Revenue(Individual revenue on customer)

Revenue (relative)(Individual revenue on customer

corrected for size)

Create your own variables!

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Some examples

Engagement index

Net growth

Products sold

Absenteeism

Vision anddirection

Client focus

Gender diversity

Trust from immediate manager

Discussion on Risk issues

Age diversity

Part ofreorganisation

Clientsatisfaction

Involvement

Expertise Trusted advisor

Clientcentricity Credibility

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Some more examples

Clientsatisfaction

Products sold

Trusted advisorscore

Net growth

TOP PERFORMERS

Age diversityHIGH

CredibilityHIGH Absenteeism

LOW

Trust fromImmediate mgrHIGH

Client focusHIGH

LOW PERFORMERS

EngamgentMEDIUM

InvolvementMEDIUM

Trust fromImmediate mgrLOW

Gender diversityLOW

Vision & DirectionLOW

10 golden rules for HR analytics

1. Strategic workforce planning and HR analytics

2. Combine analytics and intuition

3. Make analytics business relevant and actionable

4. Involve compliance and legal

5. Think of the skills you need

6. Start small and be realistic

9. Preach analytics

10. Teach analytics

7. Try (when ready) self service analytics

8. Understand the models and its outcomes

It is about a balanced blend of skills

HR analytics

5. Think about the skills you need

The next big thing in HR analytics

Easy to use

Quickly exploring data

Methods on demand

Insights on demand

Visualisation on demand

Predictive simulation on demand

7. Try (when ready) self service analytics

8. Understand your models and its outcome

Approach Technique How?

Clustering(understanding hidden group patterns)

• Cluster analysis Clustering based on multiple employee characteristics

Driver Analysis(understandig hidden relationships)

• Correlation• Linear Regression• Random Forest • Decision Trees• Structural Equation

Modeling

• Correlation matrixes showing relationships

• Regression, Random Forest & Decision Trees to isolate effects

Risk Scoring or Analysis(understanding probabilities)

• Logistic Regression• Classification

Creating risk scoring tables and Turnover Risk heat maps and assessing the likelihood of occurring events

Forecasting(understanding future trends)

• Time Series Developing future trend lines, based on historical patterns

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