Global Workforce Management Forum

London, United Kingdom

June 7-8, 2017

• Develop the

recipe for

crafting a well

designed scale

• Measuring and

balancing

ingredients from

the market and

your organization

• Finishing touches

to achieve the

optimal result

• What data you need, what data you throw out?

– Data aggregation rules

• What to compare to what?

– Determining the

• What problems are you trying to solve?

– Targeting your staffing needs

• Three Judgements and a Prayer

– Practical, not theoretical

Market Data is Raw and has

Inconsistencies

Process for Refinement

Consumable Information

Cleaning Data

• Patterns are examined for

logic and, if necessary,

further validated

• Anomalies are excluded

(outliers that may skew

data)

Selecting the proxy

• Applying exclusion rules

(e.g. minimum matches)

• Which components to

examine (e.g. total

compensation or base

salary only)?

• Use of weights

• Min-Max and/or MRP?

• At what point could there too many

comparators?

IOs and Bilaterals

Health

Humanitarian

Education

Development

Org. X (Max)

Org. X (Min)

Overall Market (Max)

Overall Market (Min)

*Custom Data Set:

NGO Local Pay +

Selected Employers

from BG Multisector

Survey, 2016

October, in Zambian

Kwacha

• 54 available

comparators

across the

NGOLP and MS

surveys

• How many is

too many

employers?

• Ask: Which are

the most

relevant?

Employer Name

Abt Associates

ACDI/VOCA

African Development Bank (AfDB)

AIDS Healthcare Foundation

Airtel

American Institutes for Research (AIR)

American International Health Alliance (AIHA)

Association of Chartered Certified

Accountants (ACCA)

Barloworld Logistics

Canadian High Commission

CARE International

Catholic Relief Services (CRS)

CBM International

ChildFund International

Children International

Concern Worldwide

Creative Associates

Education Development Center (EDC)

Elizabeth Glaser Pediatric AIDS Foundation

Embassy of Sweden

Embassy of the United States

European Union

FHI 360

Habitat for Humanity International

Heifer International

ICAP-Columbia University

Innovations for Poverty Action (IPA)

Employer Name

International Institute of Tropical Agriculture

(IITA)

IntraHealth International

Ipas

Living Water International

Management Sciences for Health (MSH)

Nokia

Norwegian Church Aid

Operation Eyesight Universal

Oxfam GB

PATH

PCI

Plan International

Population Council

Restless Development

RTI International

Save the Children International

Sightsavers

TechnoServe

United Nations

VSO International

VVOB vzw

WaterAid

Winrock International

World Bank

World Vision International

WorldFish

Zamtel

• Zambia Sample Selection: Canadian High Commission,

Embassy of the United Status, European Union, United

Nations, World Vision International, WorldFish

Employer vs. the Samples Selection at the 50th

percentile

Jobs to Grades - The impact of weights

•

Allows better assessment of

market comparison against

internal job populations

•

Should be used with caution –

the issue of DOMINANCE

• A sample selection:

– All CGIAR centres in the country

– Embassies and Bilateral Aid that may be donors

• Embassy of the United States

• Embassy/High Commission of Canada

• British Embassy/High Commission

• DFID

• European Union

– The United Nations

– NGOs with established methodologies including the use of

labour market data for setting compensation

• World Vision

• Helen Keller International

• Six to seven comparators per country

• There are a total of

585 unique employer

profiles across the

client’s 11 survey

locations (average of

53.2 employers per

country)

• Using the criteria

previously set this

focuses the selection

to 69 unique employer

profiles (11.8% of

initial available data;

average of 6.3

employers per country)

Employer Name Sector Burundi CameroonCongo, D.R.Ghana Malawi MozambiqueNigeria Sierra LeoneTanzania Uganda Zambia

AfricaRice CGIAR 0 0 0 0 0 0 0 0 1 0 0

Bioversity CGIAR 0 0 0 0 0 0 0 0 0 1 0

CIFOR CGIAR 0 1 0 0 0 0 0 0 0 0 0

CIAT CGIAR 0 0 1 0 1 0 0 0 1 1 0

ICRISAT CGIAR 0 0 0 0 1 0 1 0 0 0 0

IFPRI CGIAR 0 0 0 0 0 0 0 0 0 1 0

CIP CGIAR 0 0 0 0 1 1 0 0 0 0 0

IRRI CGIAR 1 0 0 0 0 1 0 0 0 0 0

IWMI CGIAR 0 0 0 1 0 0 0 0 0 0 0

ICRAF CGIAR 0 1 1 0 1 0 0 0 1 1 0

WorldFish CGIAR 0 0 0 0 0 0 0 0 0 0 1

Embassy of the United States Embassies/Bilateral Aid 1 1 1 1 1 1 1 1 1 1 1

Canadian Embassy/High Commission Embassies/Bilateral Aid 0 0 1 1 0 1 0 0 0 0 1

British Embassy/High Commission Embassies/Bilateral Aid 1 1 0 0 0 0 0 0 1 0 0

DFID Embassies/Bilateral Aid 0 0 0 1 0 0 1 1 0 0 0

European Union Embassies/Bilateral Aid 1 1 1 1 1 1 1 1 1 1 1

United Nations International Organizations 1 1 1 1 1 1 1 1 1 1 1

Helen Keller International NGO's 0 0 0 0 0 0 1 1 0 0 0

World Vision International NGO's 1 0 0 0 0 0 0 1 0 0 1

Present in country, with data current as of April 2017

NGO LP Multi-Sector Custom Cut

Computing the Market Order of Magnitude

• Grade Average

• Weighted Average Increase (OWAI)

• Understanding the Variance

50th Percentile

Emp. Min Mkt. Min Emp. Max Mkt. Max Ave. Weight Weighted Ave.

BG-11 30,959 45,161 45.9% 55,726 63,912 14.7% 30.3% 1 0.302818

BG-10 25,799 34,803 34.9% 46,438 61,646 32.7% 33.8% 2 0.676486

BG-9 21,499 26,070 21.3% 38,698 43,267 11.8% 16.5% 10 1.653228

BG-8 17,916 22,572 26.0% 32,249 38,715 20.1% 23.0% 3 0.690559

BG-7 14,930 20,558 37.7% 26,874 31,821 18.4% 28.1% 3 0.841593

BG-6 12,442 16,604 33.5% 22,395 28,862 28.9% 31.2% 9 2.805215

BG-5 10,368 12,616 21.7% 18,662 21,476 15.1% 18.4% 11 2.021615

BG-4 8,640 10,236 18.5% 15,552 16,951 9.0% 13.7% 6 0.8239

BG-3 7,200 9,481 31.7% 12,960 15,126 16.7% 24.2% 2 0.483865

BG-2 6,000 7,849 30.8% 10,200 10,884 6.7% 18.8% 3 0.563

BG-1 5,000 6,117 22.3% 8,000 8,058 0.7% 11.5% 5 0.576593

29.5% 15.9% 22.7% 55

OWAI 20.8%

50th Percentile

Emp. Min Mkt. Min Emp. Max Mkt. Max Ave.

BG-11 651,884 1,025,718

BG-10 225,063 499,683 122.0% 331,131 782,202 136.2% 129.1%

BG-9 187,514 354,250 88.9% 301,129 550,578 82.8% 85.9%

BG-8 288,678 437,142

BG-7 168,027 241,109 43.5% 245,576 337,312 37.4% 40.4%

BG-6 142,734 189,492 32.8% 207,862 297,623 43.2% 38.0%

BG-5 122,639 138,618 13.0% 177,495 232,206 30.8% 21.9%

BG-4 87,814 108,020 23.0% 125,707 152,627 21.4% 22.2%

BG-3 53,155 107,625 102.5% 73,764 167,221 126.7% 114.6%

BG-2 39,614 79,295 100.2% 54,838 115,393 110.4% 105.3%

BG-1 30,488 46,446 52.3% 41,332 71,291 72.5% 62.4%

64.2% 73.5% 68.9%

Span InterGrade Diff Scale Min Scale Max

BG-10 47.1% 20.0% 225,063 331,131

BG-9 60.6% 11.6% 187,514 301,129

BG-7 46.2% 17.7% 168,027 245,576

BG-6 45.6% 16.4% 142,734 207,862

BG-5 44.7% 39.7% 122,639 177,495

BG-4 43.2% 65.2% 87,814 125,707

BG-3 38.8% 34.2% 53,155 73,764

BG-2 38.4% 29.9% 39,614 54,838

BG-1 35.6% 30,488 41,332

No overlap

50-70% overlap

Max 50P

Min 50P

Min Comp Value Min InterGrade (Manual)New Min. Min. Max Comp Value Span (Entry) New Max. Max. Recommended vs.

Pivot 2014-08-01 Recommended Difference 2014-01-02 2014-08-01 Recommended Difference Average Diff Overlap

40. 496,635 120.7 % 331,131 50. 744,952 125.0% 122.8 %

40. 354,739 89.2 % 301,129 50. 532,109 76.7% 82.9 % 14.3%

50.8 253,385 50.8 % 245,576 45. 367,408 49.6% 50.2 % 7.1%

25. 202,708 42. % 207,862 45. 293,927 41.4% 41.7 % 35.6%

25. 162,166 32.2 % 177,495 45. 235,141 32.5% 32.4 % 35.6%

30. 124,743 42.1 % 125,707 45. 180,878 43.9% 43. % 25.6%

30. 95,956 80.5 % 73,764 45. 139,137 88.6% 84.6 % 25.6%

35. 71,079 79.4 % 54,838 45. 103,064 87.9% 83.7 % 16.5%

35. 52,651 72.7 % 41,332 45. 76,344 84.7% 78.7 % 16.5%

67.7 % 70. %

Weighted Average Difference 68.9 %

35 to 15% overlap

25% overlap

• Determine the overall target market position

– Acts as the control in the crafting of the scale

• Examine the Intergrade Progression

– Seeking a pattern that aligns both to market and reflecting

a reasonable distinction of job/grade values

• Set the min/max relationship (spans)

– Reflective of both market and creation of the talent

management space needed for the population of jobs at

that level

• Is the recrafted scale a better talent management

tool

– Perceived as equitable, a judicious use of resources,

builds team cohesion and achieves improved competivity