building an hr analytics team from scratch!

18
Building an HR Analytics Team from Scratch! June 2015

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Page 1: Building an HR Analytics Team from Scratch!

Building an HR AnalyticsTeam from Scratch!

June 2015

Page 2: Building an HR Analytics Team from Scratch!

CompanyDemographics

2

United Parcel Service, Inc. (“UPS”) was founded in 1907 as a privatemessenger and delivery service in Seattle, Washington.

Today, UPS is the world’s largest package delivery company, a leader in theU.S. less-than-truckload industry and the premier provider of global supplychain management solutions.

We deliver packages each business day for 1.5 million shipping customersto 7.9 million receivers ("consignees") in over 220 countries and territories.

In 2013, we delivered an average of 16.9 million pieces per day worldwide,or a total of 4.3 billion packages.

There are over 424,000 employees worldwide that work at UPS.

Page 3: Building an HR Analytics Team from Scratch!

How many people havewe hired?!

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Page 4: Building an HR Analytics Team from Scratch!

Where to start? Data!

22VariousSystems

HRIS

ER

Benefits

Comp

Training

Retirement

Safety

Page 5: Building an HR Analytics Team from Scratch!

DataAcquisition• Internal• External

DataGovernance• Define• Data quality

Data Stores• SQL Data Repository• TMS Data Mart• EDM/Information

Library• PDM/FDM data views

H.R. Analytics Team• Data Mining• Data Analysis• Business Analysts

Tactical Reporting• Dashboard Data• Standard Reporting

Ad Hoc• Informational• Non-Analytical

• Legal, PR, etc.

• Data Requests

Workforce AnalyticsProgram

Project Project

Project

Identify Define

Store

Leverage

Page 6: Building an HR Analytics Team from Scratch!

Developing our HRAnalytics Capability

StrategicTransactional

Business Value

HR

Info

rma

tio

nM

atu

rity

Predictive/Proscriptive

Analytics

CrossProcess &FunctionalAnalytics

BasicAnalytics

ConsolidatedReporting

Data &Basic

Reporting

What is happening?

Why is it happening?

What might be happening?

Data integrity & quality Basic Employee list & extracts

Process specific analytics Data from a single source

Integrated analytics Data from multiple sources

EE-Level Predictions Cause & effect

We are here

Dashboards& Portal

Page 7: Building an HR Analytics Team from Scratch!

Data Analysis?Ad-Hoc Requests

• How it works

– Online data request form which allows customers to submit aquestion that is emailed to the HR Systems Team

• Number of requests received

– Last year on average = 44/month (26% increase in requests vs 2013)

– This does not include those who call or email to make requests,as well as, the monthly reports that are automatically generated.

• Who are our customers?

– Corporate Campus such as (but not limited to) SCS, GlobalInnovations, Legal, Inside Sales, BIA, I.E., PE, GBS and PublicRelations.

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Page 8: Building an HR Analytics Team from Scratch!

Tactical InformationDelivery

Dashboards developed

– Twenty-eight active Dashboard/Process solutions.

Hits monthly (consumption)

– Sites average a total of 125,000 hits per month.

Customers and how the demand is growing

– Employee Relations

– Safety

– Workforce planning

– Benefits

– Finance/Compliance

– Plant Engineering

– Transportation HUB

– Air

– HR service center 8

Page 9: Building an HR Analytics Team from Scratch!

Journey to “Analytics”

9

Statistician

AdvancedAnalytics

Supervisor

Ph.D. Physics

Data

HR Systems Team

SQL/MS AccessskillsBusiness

Connection

Customer

SME

Utilize allthree

contactsto tell thestory andanswer

thequestion!

ROI

Page 10: Building an HR Analytics Team from Scratch!

Proprietary and Confidential: This presentation may not be used or disclosed to any person other than employees of Customer, unless expressly authorized by UPS.

© 2014 United Parcel Service of America, Inc. UPS, the UPS brandmark, the color brown and photos are trademarks of United Parcel Service of America, Inc. All rights reserved.

Segments ofData Analytics

10

Page 11: Building an HR Analytics Team from Scratch!

Proprietary and Confidential: This presentation may not be used or disclosed to any person other than employees of Customer, unless expressly authorized by UPS.

© 2014 United Parcel Service of America, Inc. UPS, the UPS brandmark, the color brown and photos are trademarks of United Parcel Service of America, Inc. All rights reserved.

• What is the voluntary turnover rate among individuals in critical roles and what is

the associated cost to the business?

• What is the voluntary turnover rate among top performers and what is the

associated cost to the business?

• What percentage of our high performers are at risk for departure?

• Does our sourcing strategy target critical talent segments effectively?

• Do we effectively hire employee with emerging skill sets?

• Are we under staffed in areas, where if we added people, we would increase our

profitability?

• What percentage of our workforce moves internally each year between lines of

business or functional areas?

• What is our average position length of service?

Are these reporting questions or analysis?

11

Start with a Question!

Page 12: Building an HR Analytics Team from Scratch!

Are Managers who score highly and have high leadership competencyproficiency more likely to produce a higher operational result? IS there acorrelation between High performing and High Results?

Data required

ERI Results

Talent Data

– Competency Ratings

– Overall QPR score

– Managers Ratings

– Hogan Results

Operational Data

– Trending over time

– Varies by operation?What is a good center?

External Factors

– Union Environment

Problem Statement

Variables

Operations Management vs.Staff ManagementGeographyAggregate CompetencyScore vs. Individual ratingUPS Career (Assignments)

Enterprise impact

Should we spend resourcesdeveloping target training formanagers?

Page 13: Building an HR Analytics Team from Scratch!

Challenges?

13

• Collection of Data

– Access to information

– Scrubbing/Validation

• Vendor data

– Set up contracts to include access to data

• Reporting versus Analytics

– Using Excel versus SPS

What other issues?

Page 14: Building an HR Analytics Team from Scratch!

Practice makes Perfect!

14

Developingforecastingmethods.

Incorporate“macroeconomic”data.

Socialize!

Page 15: Building an HR Analytics Team from Scratch!

Testing takes time…

15

Various methodologies areimportant to test the algorithms.

TryAgain!

Page 16: Building an HR Analytics Team from Scratch!

Our most popularcreation is…

16

Profiles!

Page 17: Building an HR Analytics Team from Scratch!

Where to go from here.

17

Establish credibility with other functions.

Get buy in from other business units – “talk the talk!”

Answer the “right” questions that provide context outside ofHR and the “duh” (ie: volume increases, hiring increases)

Socialize your ‘analytical’ skills with Senior Management.

Ask for questions that link to open PROJECTS…

What can you do to create visibility for HR Analytics?!

Page 18: Building an HR Analytics Team from Scratch!

Thank you

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