See blog for slides: http://blog.strimgroup.com/?p=385

Predictive Analytics in HR –Creating a culture of

Geneva, 7th March 2013

analytics-enabled agilityGeneva, 7 March 2013

I t d tiIntroductionThe STRIM group of companies

The STRIM management sphere system with its sevenmanagement principles – grouped into three clusters – is thelogical answer to often occuring implementation problems in practice.

STRIMacademy guides and provides support to employeesSTRIMacademy guides and provides support to employees during the implementation of strategies and measures. Obtaining acceptance and addressing hesitation are both addressed through effective communication.g

STRIMservices aims to have companies focussing on value added activities. Analyses lay the groundwork for monitoring and if required adjusting the strategyand, if required, adjusting the strategy.

STRIMconsult translates strategies in actions and aligns the organization as well as leadership- and incentive systems with the strategy

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the strategy.

I t d tiIntroductionThe Conference Board

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CEO t iti l h ll i 2013

Top 5 Strategies to meet the Top 3 Challenges

CEOs most critical challenges in 2013Human capital and Operational excellence are the top challenges

p g p g

4Source: The Conference Board: CEO Challenge Report 2013

Human Capital being involved

5Source: Predictions for 2013. Corporate Talent, Leadership and HR – Nexus of Global Forces Drives New Models for Talent.Josh Bersin, January 2013

Vi HRView on HRThe core characteristics of the HR function serve to perpetuate many of today s current challenges

Low strategic licenseNot having the roles or the bandwidth to be strategic

Few „home-grown“ strategic capabilities, difficulty attractinghigh-caliber talent, and ineffective tools to assess them

Ultimate ownershiptricky

Lack of ownership orpeer mindset and

Convincing businesscase & burningplatform elusive

Limited use of forward-………………….pacceptance/willingnessto plod along vs. leapfrog

Lack of a budget to

Limited use of forwardlooking metrics that wouldreduce reactive measures

Difficulty in communica-ting convincingly – in

innovateg g y

terms expected of a strategic business partner

6Source: McKinsey & The Conference Board Research, 2012

Vi HRView on HRC-Level and BU leaders view HR as lagging in strategic performance

3,8 / 6,

4 / 6

7Source: McKinsey & The Conference Board Research, 2012Legend: Rating on scale of 1-6, 1 = “needs improvement”, 6 = “best practice”

Vi HRView on HRA minority of CEOs get comprehensive reports on their workforce

P t f CEOPercentage of CEOs

100%Percentage of CEOs whobelieve the relevant information is important orvery important

80%

60%

Information Gap:CEOs believeinformation isimportant butdon´t receive

Don´t receive information

y

40%

don t receivecomprehensive

reports

Not adequate

20%

0%

Adequate but would likeit now

Information received iscomprehensive

0%

Costs ofemployeeturnover

Return oninvestmenton human

capital

Assessmentsof internal

advancement

Labourcosts

Employeesviews and

needs

Staffproductivity

8Source: PwC Saratoga: Key trends in human capital 2012. A global perspective

P di ti A l ti i HR

Stages Ki d f I f tiF

Predictive Analytics in HRStages of development

Stages Kind of InformationFocus

oriented towardsthe past

quantitative & qualitative master data:headcount, FTE, pay and other cost

categories, competencies, recordingHRReporting

actualconnection of deliverables with corporate

goals such as quality, innovation, relating

the past g , p ,engagement, retention, etc.

explicitly & detailed(descriptive

relationships among data without givingmeaning to the patterns (exploratory);comparing &

productivity, risk, etc.

related to thefuture

comparisons between what happenedyesterday to what will probably happen

analytics, benchmarking)

trends from the past (risky!); tie HRmetrics to the business

understanding

HR Analytics

future(prescriptive

analytics)

tomorrow, meaning to the patternsobserved in descriptive analysis;

focus on (a few) leading indicators

predictingBusiness Intelligence

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P di ti A l ti i HRPredictive Analytics in HRMap of causalities (learning and growth perspective)

Managerial Retention of Key

0,506gLeadership

Training HumanC it l

RelationalC it l

Human Capital

of Key People

0,442

0,530 0,326 0,360

R2=68,2%Failure and Availability RiskAlignment

Risk

Training Capital Capital

StructuralC it l

Capital Effectiven.

R2=28,5%0,7510,358

0,307

0,475 -0,337OccupationalSkill RiskCapital

Business Perfor-mance

KnowledgeGeneration

EmployeeEngage-

ment

EmployeeSatisfaction

R2 44 1%

0,4910,734 0,327

0,543 0,439

Skill Risk

EmployeeMotivation

StrategyExecution*

KnowledgeIntegration

R2=44,1%0,456 0,429

0,394

0 430 0 262

-0,372IntegrityRisk

Resignation

Value Alignment

KnowledgeSharing

Human Capital

Depletion

R2 28 5%

0,430

0,285 -0,233

0,262

Motivation Risk

ResignationRisk

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R2=28,5%

Remark: Referring to Nick Bontis and Jac Fitz-Enz: Intellectual Capital ROI, 2010* for further remarks: Mark A. Huselid, Brian E. Becker, Richard W. Beatty: The Workforce Scorecard, 2005

P di ti A l ti i HRPredictive Analytics in HRHC RoI measurement

Levels of measurement RevenueRevenue by business unitRevenue by country/regionRevenue by product line

Levels of measurement

Non-wage costsMaterial costs1 HC RoI = 1,28 2 HC RoI = 1,22

y p

Facilities and overhead costsCosts of outsourced activities…

Revenue Non Wage Costs

5%5%

Average remunerationSalary and wage levelsPerformance-related pay

HC RoI = = 1,13Revenue

Av. Remuneration

Non-Wage Costs

Number of FTEs

-

x

5%

Full-time equivalentsFull-time v part-time

…5%

3 HC RoI = 1,19

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pTemps and casualsContract workers…

Remark: Anonymised project example of an international transport and logistics company

P di ti A l ti i HR T St t iPredictive Analytics in HR – Top StrategiesEffective Leaders

M t M t 2006 2011Eight core practices

Ask, „What needs to bedone?“

MeasurementLevels

MeasurementCategory

2006Status

2011Status

0 Inputs/Indicators1 Reaction2 Learning

100%92%48%

100%89%59% done?

Ask, „What is right for theenterprise?“

Develop action plans

3 Application4 Impact5 RoI

11%8%2%

34%21%11%

Take responsibility fordecisions

Take responsibility forcommunicating

Are focused on opportunities rather thanon problems

Run productive meetings

Think and say „we“ ratherthan „I.“

12Source: Jack Phillips, Patricia Pulliam Phillips, Rebecca L. Ray: Measuring Leadership Development. Quanify YourProgram´s Impact and RoI on Organizational Performance, 2012.

P di ti A l ti i HR T St t iPredictive Analytics in HR – Top StrategiesRaising Engagement (1/2)

Six successful traitsDrivers of Engagement

Trust and integrity

Six successful traits

Nature of the job

Line of sight betweenindividual performance andcompany performance

Career growth opportunity

Pride about the company

Coworkers/team members

E l d lEmployee development

Personal relationships withone s manager

Pay fairness

Personal influence

Well-being

13Source: PwC Saratoga. Managing people in a changing world. Key trends in human capital, a global perspective, 2010.The Conference Board. Linkage of Engagement Drivers to Common Challenges, 2013.

P di ti A l ti i HR T St t iPredictive Analytics in HR – Top StrategiesRaising Engagement (2/2)

Effect of motivation and hygiene factors on engagementCulture of Engagement

Set the tone at the top; alignwords and actions

Communicate the importance

Effect of motivation and hygiene factors on engagementand contribution

Communicate the importanceof teamwork and collaboration

Increase company events tomix groups together

La nch peer coaching/Launch peer coaching/ mentoring programs

Financial rewards/peerrecognition

L h f i l kLaunch cross functional taskforces to break down silos

Use technology to enablesharing/access of information

Adapt performancemanagement systems to hold managers and employeesaccountable for success

14Source: Scarlett Surveys International, 2008.The Conference Board. Employee Engagement in a VUCA* World, 2011. (* Volatile, Uncertain, Complex, Ambiguous)

E id B d M tEvidence-Based ManagementConnect scientific coherences with company-specific procedures

Capital E“ and small e“ Capital „E“external evidence

sound scientific evidence

generalizable cause effect

Identification of general causal relations (theories)

Capital „E and small „e

Identification of specific practices (instruments)

generalizable cause-effectrelationships

Small „e“

Science Practice

internal evidence

organization-specificevidence

data that are systematically

Meta-analyses

Casestudy data that are systematically

collected in a particular organization and situation to enable local evidence-based decisions

Controlledlaboratory/fieldexperiments

Systematicreviews

Systematicevaluation

Expertsurvey

Comprehensivecorrelation studies

SystematicFollow-up the interaction creates a

collective intelligence

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P di ti A l ti i HRPredictive Analytics in HRHC RoI analysis

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Cl i R kClosing RemarksOur approach in Predictive Analytics in HR

Scan Focus on leading indicators, corresponding benchmarks

Plan

Transparency on the data collectionprocess, what formulas are being used,whythe data matter to the operationHuman capital facts: quantitative

ScanCommitment on target corridors and timelinesCapability planning and gap-analysis – associated withworkforce categories in terms of valued capabilitiesSuccession planning, scenario planning, forecasts, etc.

Human-capital facts: quantitative and qualitative informationInternal analyses: segmen-tation of HR data, corecompetencies, etc.

Execution of measuresidentified new methods and

Produce

p ,External analyses: targetgroups, PESTEL, etc. HC RoI Analysis: Capital „E“ and small „e“;

identified, new methods andguidelines as well as IT systems and warehousesProcess optimization appliedto hiring, compensation,

impact on bus. performance development or retentionHR service delivery: serviceintegration, outsourcing andoffshoringHR meas rement foc sed on

PredictHR measurement focused on value-adding resultsTalent value model: „Why do employees choose to stay?“

Rethink leading indicators; employee engagement, knowledgemanagement, turnover, executive reward, etc.Reassess the suitability of leadership development programmesand overall effectiveness of learning and development

17Remark: Referring to Fitz-Enz, J.: The New HR Analytics: Predicting the Economic Value of Your Company´s Human Capital Investment, 2010 ( HCM:21) and to Davenport, T.; Harris, J.; Shapiro, J.: Competing on Talent Analytics, HBR October 2010.

Recommendations for policy adjustments

C t t P > F lid i it htt //bl t i /? 385Contact Person ==> For slides, visit: http://blog.strimgroup.com/?p=385

President and CEO at STRIMgroup AG in Zurichin Zurich

Senior Fellow Human Capital atThe Conference Board in New York

Member in several corporate andMember in several corporate and educational networks

Lecturer in the Master degree course Human Capital Management at the Constance University of Appl. Sciences

Author and publicist to strategy and human resources issues

Selected professional positions:

Head of Global HR Analytics, Deutsche Bank AG and

845 Third AvenueNew York NY 10022-6600

Gütschstrasse 22CH-8122 Binz (Zürich)Deutsche Bank AG, and

Senior Manager hrs atPricewaterhouseCoopers AG.

New York, NY 10022-6600

Telefon: +1 410 433 660 558volker.mayer@conferenceboard.org

CH-8122 Binz (Zürich)

Telefon: +41 (0)43 366 05 58volker.mayer@strimgroup.com

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