the analytical hr professional: a look at data-driven talent management

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The Analytical HR Professional: A Look at

Data-Driven Talent Management

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Speaker: Lisa Rowan

Program Director, HR and Talent

Management Services

IDC

Moderator: Daniel Margolis

Managing Editor

Talent Management magazine



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Daniel Margolis

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Lisa RowanProgram Director, HR and Talent

Management Services

IDC

Copyright IDC. Reproduction is forbidden unless authorized. All rights reserved.

The Analytical HR Professional A look at the future of data-driven talent management

Lisa Rowan

Program Director, HR, Learning, and

Talent Strategies

May 2011

May-11© IDC Visit us at IDC.com and follow us on Twitter: @IDC

Who is IDC?

• IDC is the premier global market

intelligence, events, and advisory firm

• We analyze and predict technology

trends so that our clients can make

strategic, fact-based strategic decisions

• Now with 1000+ analysts covering 90

countries, we have been delivering IT

intelligence, industry analysis, market

data, and strategic guidance since 1964

• IDC is a division of IDG, the world's

leading technology media, research, and

event company


Agenda

Why analytics now?

Where have we gone wrong?

Brief taxonomy and history

How to think about HR analytics for your organization

Getting started

9


Setting the Stage

10

May-11© IDC Visit us at IDC.com and follow us on Twitter: @IDC 11

Talent Imperative: Situation


U.S. Workforce State of Mind

No plans to leave

44%

Not looking but open

37%

Actively looking

9%

Have plans to leave

3%

Plan to retire

7%

Source: Tower Watson 2010 Global Workforce Study – U.S.

Over 50% are willing or looking to move


Talent Initiatives - Importance

Recruiting - attracting top talent 3.9

Aligning corporate goals with group and individual goals 3.8

Performance management 3.8

Compensation planning and pay-for-performance 3.7

Leadership development 3.5

Employee development 3.2

Workforce planning 3.2

Reducing turnover 3.2

Succession planning

For each of the following talent initiatives, please indicate the level of IMPORTANCE of each to your organization

Source: IDC's CMO Survey, 2010

Very

Important

Less

Important

Least

Important


Workforce of the Future – my Hypothesis

Permanent on-premise Home-based

Contingent Freelance

2009

Permanent on-premise Home-based

Contingent Freelance

2012


Rich Areas for Capitalizing on Data Convergence

Recruiting

• Attributes of

high achievers

Compensation

• Distinguish

rewards for

top performers

LearningMeasure

• Prescribe

Performance(Reward and

Retain)

Career and

Succession• Identify and

develop

Develop

Multiple Strong

Linkages

Source: IDC, 2011


Summing up „why now?‟

Volatility in workforce engagement

More and varied types of workers getting the job done

Unprecedented focus on talent

Richer sources of data to mine for highlighting risk and improving

workforce agility

16



17



It‟s not so much that we‟ve gone wrong as other factors have

come into play:

The „snowflake effect‟ – no two organizations measure the same

things and even if some overlap, they may not measure similarly

Workforce analytics in a vacuum are insufficient to influence

business decisions. Your own data only tells part of the story

Frequently need data outside of HR's direct ownership

HR metrics are just part of the picture

The HR organization frequently doesn‟t have an analytical

orientation

18


Analytics Taxonomy

19


Business Analytics Industry EvolutionN

um

ber

of

peo

ple

Query, Reporting, OLAP, Data Mining, Statistical analysis

ReportingStatistics

Ad-hoc Query, OLAP

DataWarehousing

Knowledge Capture &Learning

Unified Access& Analysis

Collaboration& Workflow

ProcessAwareness

PredictiveAnalytics

UI and ProcessTemplates

Data Quality

Data Models

Appliances

Scorecards

Dashboards &Visualization

Alerting

1975–1989 1990–2004 2005–2020

Technology

Solutions

IT Staff

End-Users

Analysts

Data/Content

Business intelligence Suites and Analytic Applications

Decision Management


Workforce Analytics: Part of A Bigger Picture

21

Spatial Information

Analytics Tools

Content Analysis Tools

Business Intelligence Tools

Query, Reporting, and

Analysis Tools

Dashboards, production reporting,

OLAP, ad-hoc query

Advanced Analytics Tools

Data mining and statistics

Performance Management & Analytic Applications

Financial Performance

& Strategy Management

Budgeting, Planning, Consolidation,

Profitability, Strategy Management

CRM Analytic Applications

Sales -, Customer Service -, Contact

Center -, Marketing -, Web Site

Analytics, Price Optimization

Supply Chain

Analytic Applications

Procurement, logistics, inventory,

manufacturing.

Services Operations

Analytic Applications Financial

services, education, government,

healthcare, communications services,

etc.

Production Planning

Analytic Applications

Demand, supply, and

production planning

Workforce Analytic

Applications

Data Warehouse Management

Data Warehouse Management Platform

Data Warehouse Generation

Data extraction, transformation, loading; data quality


Why is this a good time?

1. Innovation at the intersections with

Collaboration

Knowledge capture & learning & sharing

Content analysis

Business process management (incl. complex event processing)

2. Technology & Deployment

In-memory processing, in-database analytics, search-based

applications, non-row databases, non-SQL analytics

Mobile, Cloud, Outsourced, On-Premise

22

Source: IDC, Market Analysis Perspective: Worldwide Business Analytics Solutions 2010 - The Emerging

Mass Market for Business Intelligence, Analytics, and Data Warehousing Mar 2011 Doc # 227397


Anatomy of HR Analytics

23


Dimensionality of Decisions: Decision Management Model

Collaborative Planning, Advanced Analytics

Intelligent Process Automation

HIGH

HIGHLOW

LOW

Level

of

Co

llab

ora

tio

n Nu

mb

er o

f Decis

ion

s

Strategic

Tactical

Operational

(Policy Hub)

Degree of Automation

Scope of Decision

Dimensions:• # of decisions

• Scope/Degree of risk

• Level of collaboration (# of

stakeholders?)

• Degree of automation

Highest level

corporate

objective


Workforce Examples in Motion

HIGH

HIGHLOW

LOW

Level

of

Co

llab

ora

tio

n Nu

mb

er o

f Decis

ion

s

Strategic

Tactical

Operational

(Policy Hub)


Scope of Decision

Level of uncertainty

Reduce time-to-fill

Lower cost of training

Lower cost

of talent

acquisition

Match learning to the

job

Increase quality of

hire

Fill key skills gaps

Speed time to

productivity

Retain top performers

Increase profitability

Maximize workforce

productivity


Workforce Example QuestionsTo Ask Yourselves

General HR

Administration

Do we need to improve processes to reduce manual check production?

Do we have sufficient labor to meet next quarter's demand?

Do we need to reduce payroll costs to be in alignment with the industry?

Recruiting

Do we need to open any job requisitions in light of demand?

Is time-to-fill positions impacting company performance?

Do we need to improve the quality of hire?

Learning Are our people prepared for emerging technology?

Is training reaching those that need it the most?

Are learning programs having the needed impact on performance?

Compensation

Do we need to raise the budget for annual merit increases?

How do we determine who will be eligible for a pay increase?

Do compensation policies for top performers impact retention?

Performance

Do we need to incentivize managers to complete performance appraisals on time?

Is our current performance rating scale appropriate?

Should we appraise workers in high visibility jobs differently?

Succession/career

Planning

Do we need to address turnover in any region, division, department?

Are there key skills gaps in high visibility jobs?

What is our strategy for back filling for the high flight risk employees?

HIGH

HIGHLOW

LOW

Le

ve

l o

f C

oll

ab

ora

tio

n Nu

mb

er o

f De

cis

ion

s

Strategic

Tactical

Operational

(Policy Hub)


Scope of Decision

HIGH

HIGHLOW

LOW

Le

ve

l o

f C

oll

ab

ora

tio

n Nu

mb

er o

f De

cis

ion

s

Strategic

Tactical

Operational

(Policy Hub)


Scope of Decision

HIGH

HIGHLOW

LOW

Le

ve

l o

f C

oll

ab

ora

tio

n Nu

mb

er o

f De

cis

ion

s

Strategic

Tactical

Operational

(Policy Hub)


Scope of Decision

HIGH

HIGHLOW

LOW

Le

ve

l o

f C

oll

ab

ora

tio

n Nu

mb

er o

f De

cis

ion

s

Strategic

Tactical

Operational

(Policy Hub)


Scope of Decision

HIGH

HIGHLOW

LOW

Le

ve

l o

f C

oll

ab

ora

tio

n Nu

mb

er o

f De

cis

ion

s

Strategic

Tactical

Operational

(Policy Hub)


Scope of Decision

HIGH

HIGHLOW

LOW

Le

ve

l o

f C

oll

ab

ora

tio

n Nu

mb

er o

f De

cis

ion

s

Strategic

Tactical

Operational

(Policy Hub)


Scope of Decision


Getting Started

Examine your organization‟s talent culture – learning-focused,

performance-focused, etc and determine organizational

readiness

What keeps your senior executives awake at night? Helping

them get to the people-related data behind those concerns will

help you justify analytics efforts

Choose 2 to 3 things that drive results in your organization and

put each at the top of your matrix to determine how to get there:

– Customer service?

– Faster time-to-market?

– Lower cost of sale?

Don‟t „boil the ocean‟

No out-of-the-box solution meets everyone‟s needs

27


Questions and Answers

• Email me at [email protected]

• Follow me on twitter: lisarowanPerformance

Recruiting

Learning

Compensation

Career

& Succession

Join Our Next TM Webinar

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the analytical hr professional: a look at data-driven talent management

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