mercer webcast telling story with data: gaining …€¦ · impact: business performance •...

Astik Ranade, PrincipalJulia Howes, Principal

TELLING STORY WITH DATA: GAINING SENIOR-LEVEL SUPPORT FOR ANALYTICS AND PLANNING24 September 2013

MERCER WEBCAST

MERCER September 27, 2013 1September 27, 2013 1September 27, 2013

Today’s Presenters

Julia HowesPrincipal, Product Line Leader,Workforce Analytics & Planning PracticeMercer+44 207 178 [email protected]

Astik RanadePrincipal, Workforce Analytics andPlanning Leader – Asia, Middle East &AfricaMercer+65 6398 [email protected]

MERCER September 27, 2013

Today’s Discussion

2

Introduction and Setting the Context

Good story development

Story 1: A case in point

Story 2: Data driving business results

Lessons learned and getting started as a power storyteller

Q&A


Storyboard: Patty’s Pitfalls

Patty reads a great article on metricsand decides to assign her two newlyhired HR generalists to staff a newmetrics and analytics function in HR.

She directs the new function toresearch benchmarks and bestpractices in what they shouldmeasure.

BEST PRACTICES IN METRICS & DASHBOARDS

Based on her employees’recommendations, Patty purchasessome software that allows her topush monthly HR reports featuringthe dashboard’s standardized 25+HR metrics to senior leaders’inboxes, and collects data from 10disparate data sources, such asvacancy rates and time to fill. Shesends tables and pie charts.


Storyboard: Patty’s Pitfalls

Patty sends monthly reports on thesame 25+ metrics to senior leadersfor over a year.


Patty’s supervisor informs her thatsenior leadership wants data andthey want her to design an employeesurvey.

Patty feels like she’s not gettingthrough to her senior leaders andthey don’t understand the value ofthe data they are already collectingin the dashboard.

MERCER September 24th, 2013

CEO’s are gaining awareness on the impact of theorganizations’ talent on business performance

1 Innovation

2 Human Capital

3 Global Political /Economic Risk

4 Government Regulation

5 Global Expansion

2012 CEOTop 5 Challenges

1

2

3

4

5 Global Political /Economic Risk

2013 CEOTop 5 Challenges

Source: 2012 and 2013 The Conference Board CEO Challenge

Innovation

Human Capital

Operational Excellence

Customer Relationship

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Level 1Budget-drivenheadcount planning

Stra

tegi

c

Impact: Business Performance

• Spreadsheet driven• Manual processes

• Track and understand workforce flows• Use technology to leverage data

• Identify key segments• Model gaps and “what if” scenarios• Close gaps through buy/build talent strategies

• Optimize strategies to close gaps• Create analytics and planning

centers of expertise

Ope

ratio

nal Level 2

Workforce analysis anddashboards

Level 3Strategic workforceplanning

Level 4Human capitalorganization

Your Journey: Maturity Curve

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Before you can begin interpreting a report, you mustbe able to identify and understand

Time Context

Structural Context

Measure

Attributes (Comparison)

Attributes (Filters)

Required

Optional


Base MeasuresBase Measures

Calculated MeasuresCalculated Measures

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Polling QuestionExercise: Demonstration Data

Q: Based on the visual on the screen, do you think more highperformers have terminated in 2012 than medium performers?

a) True b) False c) Neither



Terminations Voluntary (High Performer)Average Headcount (High Performer)

x 100%

Terminations Voluntary (Medium Performer)Average Headcount (Medium Performer)

x 100%

Terminations Voluntary (Low Performer)Average Headcount (Low Performer) x 100%

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Polling QuestionResults





48%

32%

21%

TRUE

FALSE

Neither






Story 2: Data Driving Business Results


Q&A


Overcome Data Analysis Paralysis

Blend the art of storytelling with the scienceof data analysis andresearch =

Power Story Telling

“A detailed character-based narrative of a character’sstruggles to overcome obstacles and reach an important

goal.”


Good Story Development

• Beginning - introduce the reader to the setting, the characters and thesituation (conflict).

• Plot point - situation that drives the main character from “normal” lifetoward some different conflicting situation that the story is about.

• Middle - series of complications and obstacles, each leading to a minicrisis.

• Climax – the ultimate crisis.

• Resolution of the climax – saving the day, feeling happy, celebrate.

• End - tie up the lose ends; share the morale of the story.

Finish your story and get out!


Typical Data Story Development

Beginning – Introduction to the study.

Plot Point 1 - Discuss the variables studied.

Middle - series of complications and obstacles, each leading to a mini crisis.

Climax – the ultimate crisis.

Resolution - of the Climax, saving the day, feeling happy, celebrate.

End - Present the results of the data analysis.

Get out before the audience wakes up!


Story Arc

BeginningSetup, CharactersBackground, Who,

What, Where

MiddleObstaclesConflict

EndResolution

Understanding


Evolving Story From Data

Next, go to a case study to see impact of adding the ‘middle’








Q&A


• Large regional bank with more than 20,000 employees experienced asurge in voluntary turnover, exceeding 40% among some occupationalgroups.

• Upward trend was imposing significant cost on the organization.

Improving Retention Through The Power ofDisciplined Measurement

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What Was The Original Story?

BeginningMoney

Workload

EndRetention

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Turnover had more to do with career opportunity andthe stability of management than with pay

Analysis of actual turnover behavior

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Turnover Had More To Do With Career OpportunityAnd The Stability Of Management Than With Pay

Analysis of actual turnover behavior

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Calculations are based on turnover elasticity at the metropolitan area level.

To achieve a 10% reduction inturnover requires very

different amounts of payincreases in different labor

markets.

The bank could use money to solve turnover, but it would bemisspent in some locations and ineffective in others.

A Dollar Is Not Always A Dollar . . .

City G

City F

City E

City D

City C

City B

City A

$5.20

$3.14

$2.85

$2.37

$1.87

$1.63

$1.09

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What Was The Story?

BeginningMoney

Workload

MiddleCareers

Supervision

EndRetention

Data helped themconfront and slay the

real villain

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Business Results Achieved

• Re-directed focus from “just pay”

• Actions included:– Strengthening of career paths– Enhancing internal mobility– Focusing on career rewards and cash incentives for top-performing

managers

• $50 + million in annual savings– Turnover among non-exempts down by 40% in eight months– Turnover among exempts down by about 25% in the same period








Q&A

MERCER

What Is The Business Case?

What jobsand skills are

critical tobusinesssuccess?Where, andhow many?

What is theright cost

structure?

What are thetalent plansrequired to buy

andbuild the

right capacity?

• Growth concerns or aweak pipeline for thefuture

TalentRisk

• Lost revenue fromhaving to slowoperations or put themon hold

Financial / OperationalRisk

• Investments in thewrong people

• Overspending that canresult fromunpreparedness

HR PracticeRisk

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How Does theWorkforce

Impact

and ProfitabilityStore Revenue

More Sophisticated AnalyticsRetailCo: Advanced Analytics

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How Does theWorkforce

Impact

and ProfitabilityStore Revenue

• Local unemployment rates• Distance to work• Local labor pool (diversity, education, age, income)

• Diversity• Prior year’s sales trends• Supervisor promotion rates,

turnover rates, age, tenure• Non-supervisor promotion rates,

turnover rates, age, tenure

• Size• Supervisor spans of

control• Promotion rates• Turnover rates• Age• Tenure

• Job status• Participation in training• Internal mobility• Employment status• Hire source• Location

• Age• Gender• Ethnicity• Tenure• Performance ratings• Compensation

OrganizationalPractices

ExternalInfluences

IndividualAttributes

RetailCo: Advanced AnalyticsRetailCo: Statistical Analyses Focused on Three BroadCategories of Drivers of Both Turnover and Sales

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RetailCo: What Internal Factors Drove the Sales ofGoods?

The models on which these results arebased control for individual attributes,organizational factors and externalinfluences.

Influ

ence

Performance

The Optimal Model

Full TimeEmployees

Location

HighUnemployment Rate

Part TimeEmployees

OvertimeCompensation

ExperiencedFull Time Manager

HighTenure


Q&A


Data – Dialogue – Action – Results

Data

Dialogue

Action

Results

The “magic” is in thedialogue phase; howyou transform your“big data” to a storythat evokes emotion

and dialogue

Multiplicative effectEvoke emotionDrive action and results


Caveat

Match people to data levels

Data people Dialogue people

Good stories come from all levels of data


• Great story tellers first FIND GOOD STORIES.

• Document stories; keep journals.

• Learn to create your own story by diagnosing the stories you discover:

Find the beginning, middle and end; study how the stories are told.

• GREAT data coaches find good data stories; the place to start.

Starting point


What’s Coming Up NextWorkforce Analytics And Planning Webcast andWorkshop Series

Predictive analytics: How thepower of analytics can helpdrive business successNovember 6, 2:00 PM-3:00 PMwww.mercer.com/webcasts/predictive-analytics

STRATEGIC WORKFORCEPLANNING:Defining and FulfillingBusiness RequirementsOctober 30, 2013

WEBCAST

For more details, visit www.mercer.com/analytics-and-planning-workshops-amea

mercer webcast telling story with data: gaining …€¦ · impact: business performance •...

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