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Shanmukha Sreenivas P , DoMS 1

HR Analytics: New approaches, higher returns on human capital investment

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Shanmukha Sreenivas P , DoMS 1

To show how business function leaders can

start mining data to measure and improve

HR's contributions to business performance

Shanmukha Sreenivas P , DoMS 2

Identification of 6 analytical tools

Exemplification of these tools through

case studies both in the Indian & western

context

A new holistic model for HR analytical

capability has been devised

Shanmukha Sreenivas P , DoMS 3

Key tools being used by enterprises to

bridge the gap between HR investments

& Business returns

Shanmukha Sreenivas P , DoMS 4

As the case studies reveal, tools

identified here can help HR leaders

actively shape their organization’s future

- managing critical talent

- directing programs towards the long

term needs of the business

New model !!

Shanmukha Sreenivas P , DoMS 5

Personnel Control

People Developer

Talent Multiplier

Boards of directors increasingly asking CEOs to measure people

results.

HR’s primary task:

Growing recognition among HR executives that they must

develop greater business acumen; HR courses that focus on

analytical capabilities are being developed and offered.

Shanmukha Sreenivas P , DoMS 6

Accessible

Reliable

Metrics must be consistent across units and

time

HR ‘s Effectiveness : Revenue/Sales pipeline

Only 14% of the respondents said they used these business-focused

metrics to gauge the impact of HR

- CedarCrestone 2010-11 HR systems survey

Shanmukha Sreenivas P , DoMS 7

Talent Supply Chain

Workforce Planning

Customized EVP

Targeted HR Investments

Critical Talent Management

Employee Database

Shanmukha Sreenivas P , DoMS 8

Accurate, Consistent, Integrated,

Accessible and RelevantComprehensive Database Integrated HR Info

Grade Point

Average

Best

Predictors Of

Performance

IN Q3 of 2007, the company hired 2130 people a 38% increase from the prev Q

Case I

Shanmukha Sreenivas P , DoMS 9

Critical talent data points:

i)Key recruiting targets

ii)High-potential Employees

iii)Top performers

Case II Case III

Shanmukha Sreenivas P , DoMS 10

Playing techniques

Projections based on past performance

Game statistics

Analysis of video feed

Live graphical data streams

Gathers 60,000 data points on each player examining both physical & psychological traits

Maximizing player’s longevity by customized training regimens

Player durability estimatesShanmukha Sreenivas P , DoMS 11

Sophisticated segmentation enables

differentiated action

Case IV

Metrics being used:

Work climate & employee satisfaction

Productivity (employees /100,000 cases of food sold)

Retention

HIGHLY SATISFIED

EMPLOYEES

• Higher revenues/low costs

• Superior customer loyalty

• Higher employee retentionShanmukha Sreenivas P , DoMS 12

To maintain high levels of employee

satisfaction, SYSCO manages 7-D’s of the

work environment Leadership support of employees

Effectiveness of front-line supervisors

Rewards for performance

Quality of life

Employee engagement

Diversity

Customer focus

SYSCO improved the retention rate for delivery associates from 65 percent to 85

percent in six years.

With hiring and training costs of $35,000 per head, SYSCO saved nearly $50 million in

the process . Shanmukha Sreenivas P , DoMS 13

Predict and target employee life cycle actions based on calculations of employee value

Case V

Turned to Conjoint analysis(a marketing technique)-figured out the mix of benefits most likely to improve retention rates.

Key result: employees were more likely to stay with the company if they got half their annual pay rises every six months instead of the entire amount only once per year

Shanmukha Sreenivas P , DoMS 14

Starts with the analysis of the strategic position of the business

Case VI

2007 : in order to reduce operating costs by $700 million, wanted to reduce headcount by 2000 in two years

An analytics group of 20 was formed to perform workforce planning simulations.

-Ideal mix

-Precise talent requirements

-Cost conscious operations

Shanmukha Sreenivas P , DoMS 15

“Real time optimization”

Firstly, future needs of talent are projected (planned capital projects)

These decisions are continuously optimized using real time, system wide performance data for the entire supply chain

Case VII

-> Valero continuously monitors ads placed on job portals & internet , to assess

Speed , Quality & Reliability of the supplier (Dashboard Scorecards)

Supply Chain:Project Managers from the USEngineers from Canada

Programmers from India

Manufacturing workers China

Shanmukha Sreenivas P , DoMS 16

Shanmukha Sreenivas P , DoMS 17

Data-Centric

RIghtQuestions

Analytical tools& metrics

Dedicatedpeople: Analysts

Targeting

Strategicperspective

Level 1

• DATA CENTRIC

• Accesible,reliable and high quality

Level 2

• ASKING THE RIGHT QUESTIONS

• Acting on results

Level 3

• DEVELOPING ANALYTICAL TOOLS AND METRICS

• Consistent across units and over time

level 4

• DEDICATED PEOPLE - ANALYSTS

• Nurturing analytical talent

level 5

• TARGETING

• Sophisticated segmentation enables differentiated action

level 6

• STRATEGIC PERSPECTIVE

• Analytics in tune with the organization's strategies and objectives

Implementing HR analytics :

What Why & How ???

Accurate assessment of the way things really are , one not skewed by emotion or limited to anecdotal evidences.

Diagnose the causes of whatever problems exist and create plans to address the underlying causes.

Develop forecasting and optimizing capabilities to help them see bumps in the road before they encounter them

Shanmukha Sreenivas P , DoMS 18

Queries

Shanmukha Sreenivas P , DoMS 19