Ratingless Performance Management - Amazon S3€¦ · Movement to ratingless performance management...

RatinglessPerformance Management

Lisa Harpe, PhD

Peoplefluent Research Institute (PRI)

Risks and Rewards

Peoplefluent Proprietary and Confidential

Agenda

History of performance ratings

Movement to ratingless performance management

• Components

• Examples

How to reward good performance without ratings

How to include performance in studies if there are no ratings


History of Performance

Ratings

• 1900s: Personnel Administration

Movement

• 1920s: Human Relations Movement

• 1940s: Management style

• 1950s:

• 1950 Performance Rating Act

• 1954 Incentive Awards Act


• 1960s:

• Employer Employee X

• Salary Reform Act

• 1970s: Performance Management

• Most companies had performance

ratings

• 1980s: MBO

• To address central tendency with

ratings movement to forced

distribution systems led by GE

• 1990s: Dissatisfaction with

performance rating systems Peoplefluent Proprietary and Confidential

• 2000s:- Lawsuits

- Technology

- Challenges

• Remote workers• Geographic dispersion• Increased dissatisfaction

• 2008: ‘Get Rid of Performance

Ratings’ by S. Culbert

• 2009: Reuters survey: 4/5 workers

dissatisfied with performance reviews


‘Typical’ Performance Management System

Beginning of Year

• Goal Setting

End of Year

• Manager Provides Ratings

of Employee

• Employee Provides Ratings of Self

• Manager and Employee Meet to Discuss Ratings


Example Performance Rating Form


Types of ‘Typical’ Ratings

Categorical

• Competencies

• Goals or Objectives

Overall

• Category weighting

• Assignment or calculation

Preliminary v. final

Midyear v. annual


Discontent with Ratings

Cumbersome

Poor implementation

Poor training

Bell curve is wrong

Static



Poorly equipped to measure performance

today’s workforce

• No measurable output

• Service / knowledge workforce

• Dynamic nature of industry

• Geographically disperse workforce



Backward looking

Demotivating

• SCARF hypothesis

Not reflective of performance

• Mount et all (2000)

• Joshi et al (2015)


Performance Ratings and the Law

Siegel v. Ford

Donaldson v. Microsoft Corp

Jones v. Goodyear Tire & Rubber Co

Wal-Mart

Novartis


Going Ratingless

Resources

• Harvard Business Review April 2015

• Culbert book 2008


Going Ratingless

Throw out ratings, distributions,

annual review meeting

Focus on regular, on-going

feedback

Keep goal setting

Stay flexible


Key Component: Manager-Employee Discussions

2 options

1. Highly structured conversation

2. Guided conversation

On a regular basis

Emphasize goal setting and adjustments


Examples

Networking Company

• No ratings

• Structured conversations

• J Player v Non J Player

Clothing Retailer

• GPS

• Ongoing support


Examples

Document and Marketing Solutions Company• Regular check-ins

• Focus on 3 elements• Expectations

• Feedback

• Growth & development

Software Company

• Until 2013, used a curve / forced ranking system

• In 2013, abandoned ratings

• Stress continual learning and growth


Examples

Recreational Equipment Retailer• ‘anchor points’• Bi-annual calibration meetings

Financial Advisory Company• Moved away from cascading objectives, annual review,

360-degree feedback

• Performance snapshot based on 4 statements1. Given performance, I would award this person highest possible comp

and bonus.

2. Given performance, I always want this person on my team.

3. This person is at risk for low performance.

4. This person is ready for promotion.


What about rewards for good performance?

A rating by any other name?

• J vs non J player

• Anchor points • Leading performers

• Solid performers

• Developing performers

• Performance snapshot –

agreement with 4 statements


What about rewards for good performance?

World at Work Survey

• 80% use manager discretion

within budget

• 42% use calibration sessions

• 25% use ‘shadow’ ratings

• Many use multiple approaches


Employment Decisions Related to Performance Ratings

Pay

• Merit increases

• Bonuses

Non-monetary rewards

Promotions

Disciplinary actions

Terminations

RIFsPeoplefluent Proprietary and Confidential

Pay

Pay for performance philosophy

When pay disparities exist,

performance often cited

as justification.


Base Pay

Identify comparison groups

Identify factors that influence pay

Analyze pay

• Regressions

• Rank sum

• T-tests


Regression by Job

• Suppose you conduct a regression analysis by job to examine disparities in base pay along gender lines

• You identify the following factors as important determinants of base pay:


Regression by Job: Example

The City of Oaks AAP

• 410 employees: 250 females, 160 males

Regression Model (applied, in turn, to each job)

FTE Base Pay = A base amount,

+ An increment for each year in current job,

+ An increment for each other year with company,

+ An increment for each year of prior experience,

+ An increment based on the employee’s average performance rating over the past three years,

+ An increment based on the employee’s pay grade,

+ An increment based on the employee’s job title,

+ An increment if the employee is female


City of Oaks AAP: Regression by Job

Employees 30 R-Square 0.77

Females 15 F-Test 0.00

Parameter Estimate P-Value # Std Devs

Base Amount $35,983.96 <.0001 >3.89

Years in Current Job $2,099.19 <.0001 >3.89

Other Years With Company $536.47 0.0974 1.66

Prior Experience $21.96 0.8424 0.20

Grade B $0.00

Average Rating 1.00 – 1.99 -$3,353.99 0.5414 -0.61

Average Rating 2.00 – 2.99 -$4,709.19 0.2617 -1.12

Average Rating 3.00 – 3.99 $1,450.68 0.7202 0.36

Average Rating 4.00 – 4.99 $0.00

Female -$4,938.39 0.0032 -2.95

Male $0.00

Job IT Support






Base Amount $56,160.92 <.0001 >3.89

Years in Current Job $597.41 0.0112 2.54

Other Years With Company $3.13 0.9680 0.04

Prior Experience $268.17 <.0001 >3.89

Grade A $23,583.20 <.0001 >3.89

Grade B $0.00

Average Rating 1.00 – 1.99 -$4,665.44 0.2145 -1.24

Average Rating 2.00 – 2.99 -$161.61 0.9671 -0.04

Average Rating 3.00 – 3.99 -$3,041.51 0.4186 -0.81

Average Rating 4.00 – 4.99 -$714.56 0.8859 -0.14

Average Rating 5.00 $0.00

Job Title AMM -$1,513.36 0.2870 -1.06

Job Title OCW $32,446.63 <.0001 >3.89

Job Title AEC $63,926.56 <.0001 >3.89

Job Title EAG $0.00

Job Title CRC $6,736.46 <.0001 >3.89

Job Title PMK $0.00

Female -$4,458.68 <.0001 -3.99

Male $0.00

Job

Customer

Support Rep



Job

Project

Manager




Base Amount $31,094.59 <.0001 >3.89

Years in Current Job $716.03 <.0001 >3.89

Other Years With Company $693.97 <.0001 >3.89

Prior Experience $72.92 0.0402 2.05

Grade C $0.00

Average Rating 1.00 – 1.99 -$1,150.18 0.5969 -0.53

Average Rating 2.00 – 2.99 $1,147.69 0.4735 0.72

Average Rating 3.00 – 3.99 -$68.72 0.9656 -0.04

Average Rating 4.00 – 4.99 $0.00

Female -$1,425.69 0.0562 -1.91

Male $0.00


Reconsidering the Pay-for-Performance Relationship

Current Base Pay = f(past starting pay rate, past merit pay increases,past promotion increases)

= f(prior experience,educational attainment,pay grade/band,geographic differentials,years of service,performance, etc.)

Merit Pay = f(performance)


Merit Pay: Regression Example

Supervisors

• 99 employees: 57 females, 42 males

Regression Model

Merit Increase = A base amount,

+ An increment based on the employee’s most recent performance rating,

+ An increment based on the employee’s geographic pay scale,

+ An increment if the employee is female


Regression on Merit Pay

Supervisors Employees 99 R-Square 0.83



Base Amount $31.21 0.9083 0.12

Perf Rating: Exceeds $2,082.79 <.0001 5.59

Perf Rating: Meets All $1,515.78 <.0001 4.08

Perf Rating: Meets Most $841.20 <.0001 5.43

Perf Rating: Does Not Meet $0.00

Geo Pay Scale: A -$579.62 0.0053 -2.79

Geo Pay Scale: B -$381.22 <.0001 -4.69

Geo Pay Scale: C $0.00

Female -$1.55 0.9774 -0.03

Male $0.00


Regression on Base Pay with Avg Perf Rating


Merit as Proxy for Performance?


Bonus as proxy


Issues

Other factors influence merit (or bonus) pay

• Budget

• Department or location

• Supervisor discretion

• Unlikely a linear relationship with performance

Are there disparities in merit (or bonus) pay?

Increases for single year or across multiple years?


Alternatives

Proxy

• % merit increase? One year? Average over multiple years?

• % bonus? One year? Average over multiple years?

• Other? Commissions? Awards?

‘Rating’ for pay purposes only

Analysis with no performance indicator supplemented with qualitative information

• Notes from performance discussions


Possible Issues with Performance Discussions

Number of discussions by race and gender

Content of discussions by race and gender

Recorded notes by race and gender

• Number of positive vs negative comments

• Research findings


Final Comments

Do performance ratings currently explain variance in base pay? Merit pay? Bonuses? other?

If you claim performance is related to pay, • Which kinds of pay?• What kind of relationship?• How will you quantify performance?

What factors influence pay? • Starting Pay?• Merit Increases?• Bonuses?• Other?


Q & A

Questions?

Comments?


Ratingless Performance Management - Amazon S3€¦ · Movement to ratingless performance management...

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