Vasil Tsakadze

Head of Social Statistics Department

National Statistics Office of Georgia

National VAW survey in Georgia 2022

Violence Against Women Survey

Survey Characteristics

❖ Violence Against Women Survey in Georgia was conducted for the second time in 2022, during October-

November (the first survey was conducted in 2017)

❖ The survey methodology was designed based on the latest international guidelines and standards

❖ Methodological manual for the EU survey on gender-based violence against women and other forms of

inter-personal violence (EU-GBV), EUROSTAT, 2021

❖ Guidelines for Producing Statistics on Violence against Women - Statistical Surveys, UN, 2014

❖ The Violence Against Women Survey Implementation Toolkit, UN-ESCWA, 2021

❖ Sample size: 3 300 women and 1 104 men

❖ Data Disaggregation:

❖ In case of women survey - Tbilisi; Other urban areas; Rural areas

❖ In case of men survey – Country level

❖ Survey coverage

❖ All regions of Georgia were covered, excluding occupied territories of the country

Violence Against Women Survey

Sampling Design

Primary Sampling Unit (PSU) - Enumeration area

(For the women and men survey different enumeration areas were sampled)

In each sampled enumeration area:

10 households – For women survey

8 households - For men survey

In each sampled household

One respondent aged 15-69 years

For each type of settlement

Three-stage Stratified Cluster Random Sampling

Violence Against Women Survey

Sampling Design

❖ Instrumental of the survey

❖ Women’s questionnaire

❖ Men’s questionnaire

❖ Interviewer manuals – fieldwork procedures and instructions for filling the questionnaires

❖ Questionnaires were prepared in 4 different languages (Georgia, Armenian. Azerbaijani, English)

❖ Data collection methods

❖ Using Computer-Assisted Personal Interview (CAPI)

❖ The World Bank software (Survey Solutions) was used to prepare electronic questionnaires

❖ Fieldwork was conducted by interviewers of Geostat, who were experienced in households surveys

❖ 14 fieldwork supervisors – same for both surveys

❖ 82 interviewers

❖ 59 women for women survey

❖ 23 men for men survey

❖ Data cleaning and processing is carried out by the staff of the head office

❖ Cleaning of database

❖ Process of calculating indicators and data analyses is in progress

Violence Against Women Survey

Questionnaires

Women’s Questionnaire

• Respondent of questions about household — Informed member of household aged 15 years and older

• Respondent of questions about women — randomly selected woman aged 15-69 years

• Data collection method — Computer-Assisted Personal Interview (CAPI)

Men’s Questionnaire

• Respondent of questions about household — Informed member of household aged 15 years and older

• Respondent of questions about men — randomly selected man aged 15-69 years

• Data collection method — Computer-Assisted Personal Interview (CAPI)

Violence Against Women Survey

Questionnaires

BACKGROUND OF THE CURRENT OR MOST RECENT HUSBAND/PARTNER

CHILDHOOD EXPERIENCES

HEALTH

FINANCIAL STATUS AND WORK

MARITAL STATUS

BACKGROUND OF THE RESPONDENT

HOUSEHOLD CHARACTERISTICS

WOMEN’S HOUSEHOLD SELECTION FORM

Women’s Questionnaire

COMPLETING AND CONCLUDING THE INTERVIEW

SOCIAL NORMS AND ATTITUDES

STALKING

SEXUAL HARASSMENT

NON-PARTNER VIOLENCE

IMPACT AND HELP-SEEKING BEHAVIOURS

VIOLENCE-RELATED INJURIES

HUSBAND/PARTNER DOMESTIC VIOLENCE

Violence Against Women Survey

Questionnaires

Men’s Questionnaire

MEN’S HOUSEHOLD SELECTION FORM

HOUSEHOLD CHARACTERISTICS

BACKGROUND OF THE RESPONDENT

CHILDHOOD EXPERIENCES

HEALTH AND WELL- BEING

MARITAL STATUS BACKGROUND OF THE

CURRENT OR MOST RECENT WIFE/PARTNER

ATTITUDES ABOUT RELATIONS BETWEEN

MEN AND WOMEN

SOCIAL NORMS AND ATTITUDES

COMPLETING AND CONCLUDING THE

INTERVIEW

Violence Against Women Survey

Data Quality Assurance

❖ Checking the completed questionnaires

❖ Automatic, logical and arithmetic controls

❖ Supervisors - Approving/rejecting questionnaires

❖ Staff of head office - Approving/rejecting questionnaires

❖ Monitoring system — When visiting the respondent, interviewers recorded the GPS coordinates

❖ GPS coordinates were compared to the GPS coordinates of the Census

Violence Against Women Survey

Pilot Survey

✓ 8 interviewers and 1 local supervisor was involved in the pilot

✓ Training of the field staff was conducted

✓ 30 women and 15 men were interviewed during the pilot (Tbilisi, small city and a village);

✓ Respondents from different age and ethnic groups were selected to test the questionnaires in different settings and languages;

✓ Pilot for the survey took place in enumeration areas that was not part of the final sample;

✓ After the pilot meeting was held where interviewers, Geostat staff, international and national consultants were participating

✓ Based on the pilot results relevant updates were made to finalize the questionnaires and interviewer manuals;

Violence Against Women Survey

Respondent letter and Protocols

Protocol on interviewing children under age 18

Informed consent from adult and child

Protocol when witnessing incidents of serious forms of VAW or revealing child sexual abuse

Reporting to supervisor and reference group rapid response mechanism

Protocol when revealing thoughts/cases of suicide/self-hurting

A special message designed by psychologist/VAW specialist and referral to relevant services

Protocol when revealing any form of violence against women and/or domestic violence

A special message designed by psychologist/VAW specialist and referral to relevant services

Protocol when revealing any form of violence against children

A special message designed by psychologist/VAW specialist and referral to relevant services

✓ Respondent letters were prepared and distributed ✓ Brochures on health and VAW services were prepared and distributed ✓ Protocols on interviewing children and reacting on violence cases were prepared

Social Statistics Department

National Statistics Office of Georgia

[email protected]

www.geostat.ge

Thank you for your attention!

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GOGITA TODRADZE Executive Director

National Statistics Office of Georgia (GEOSTAT)

PRODUCTION AND USE OF GENDER STATISTICS IN GEORGIA

Gender Statistics at GEOSTAT

PRODUCTION OF GENDER STATISTICS AT GEOSTAT  STARTED AT THE END OF 1990S

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First activities in Gender Statistics

B O O K L E T “ W O M E N A N D M E N I N G E O R G I A ”

Every booklet, compared to the previous ones, is closer to the

world statistical standards

13 editions of “women and men” were published Since 1999

The booklet represents a simple, but an effective Tool to attract 

attention towards gender data

FURTHER DEVELOPMENT of GENDER STATISTICS

• Increasing the number of available gender-disaggregated indicators

• Improvement of data dissemination

• Strengthening dialogue with users

SINCE 2009 THE NEW LAW ON OFFICIAL STATISTICS OF GEORGIA

Development of gender statistics comprises the following aspects:

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PRODUCTION OF GENDER STATISTICS

• The UNECE’s minimum set of gender indicators showed that despite producing most of the MSGIs, the gaps were mostly related to indicators derived from the surveys on VAW and time use

• Production of gender statistics has been very positively influenced by the active nationalization process of SDG indicators in the country

• GEOSTAT has conducted numerous comprehensive surveys, with the overall support of UN women

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Data sources The picture can't be displayed.

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GENDER STATISTICS

Statistical Sources

Quarterly business surveys

Annual business surveys

Specialized surveys (VAW, TUS, MICS)

Administrative Sources

NAPR

Tax Office

Quarterly business surveys

Annual business surveys

Quarterly business surveys

Annual business surveys

Quarterly business surveys

Annual business surveys

Population Census

regular business surveys

regular household

surveys (HBS, LFS)

Ministry of Health and social protection

Ministry of Education, Culture and Science

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Data Collection methods

Computer Assisted Personal Interview (CAPI)

For Household surveys

Online Questionnaires and

Web based self reporting for Business surveys

Latest achievements in gender statistics

New surveys and indicators

 Survey of Violence Against Women

 Survey on Asset Ownership

 Time Use Survey

 MICS

 Gender pay gap

ASSESMENT of Gender Statistics

STRATEGY of Gender Statistics

IMPROVED data dissemination

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EVIDENCE AND DATA FOR GENDER EQUALITY: MEASURING ASSET OWNERSHIP FROM GENDER PERSPECTIVE

GEOSTAT has been one of the pilot countries within the 

framework of the evidence and data for gender equality (EDGE) 

initiative of the un statistics division

Survey on measuring asset ownership and  Entrepreneurship from a gender perspective

Survey results has been published in 2018

SURVEY ON VIOLANCE AGAINST WOMEN

More than 1 in 4 women (27%) reported having experienced physical and/or sexual violence by an intimate partner, or sexual violence by a non‐partner including during childhood, or sexual harassment in their lifetime.

NATIONAL SURVEY ON VIOLENCE AGAINST  WOMEN IN GEORGIA, 2017, 2022

THE RESULTS OF THE SURVEY SHOWED THAT:

12% of women reported having experienced physical and/or sexual violence by an intimate partner, or sexual violence by a non‐partner in their lifetime.

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Time Use Survey

 The overall proportion of time spent by women on unpaid domestic and caregiving work was 17.8 per cent, which is about 4.8 times that of men’s time (3.7 per cent).

 Women spend approximately four times longer on committed time activities than men s (covering unpaid domestic and caregiving services as well as volunteering).

 Men spent more time on contracted and free time activities than women (such as leisure and socialization)

Key findings

Gender Pay Gap

 In 2021 the adjusted hourly gender pay gap equaled 15.7%. The same indicator calculated at the monthly level equaled 21.4%

 the highest hourly gender pay gap was observed in the Industry sector (30.6%)

 the highest hourly gender pay gap was observed in Craft and related trades workers position (46.4%), Managers position (40.4%) is on the second place

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Data dissemination tools

Means of data dissemination 1

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Detailed releases

Infographics

Video clips

Improved design

New services5

Since 2013 ‐ gender statistics data are also uploaded in the PC AXIS format

GEOSTATs website and applications for Android and IOS

WWW.GEOSTAT.GE

Android  &  IOS

Adapted for persons with disabilities 

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Gender Statistics Portal

DIALOGUE WITH USERS

 Media

 Academia

 Business sector

Mayors, Local government and self-government

 Public institutions

 NGOs

 Respondents

Around 15 meetings annually, with:

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FUTURE PLANS

 Strengthen national statistical capacities and data collection system

 Implementation of international standards and requirements

 Active cooperation with international organizations and experts

 Continuing dialogue with owners of data sources and users

 Asses and looking for new data sources

 Review and discuss data gaps

 Prioritize non-produced indicators

 working with data quality

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Alternative sources and non-traditional methods

Use more and more administrative data sources

Establish modern system for data collection

Looking for new alternative data sources

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GOGITA TODRADZE

Executive Director

National Statistics Office of Georgia

[email protected]

THANK YOU FOR YOUR ATTENTION!

WWW.GEOSTAT.GE

Reliable Data for Right Decisions!

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Gender in Trade in Georgia

Paata Shavishvili Deputy Executive Director

National Statistics Office of Georgia (Geostat)

Main Results of the Assessment

General Approach

❑Sectoral level - gender-in-trade indicators were analyzed for 5 export products

4-digit HS codes for exported commodities linked to the corresponding NACE codes of domestic

production

❑ Micro-linking of available sources to trade data

Almost 60,000 enterprises which conducted exports and/or imports activities in 2016-2020

represented the basis for linking non-trade data

Data Sources

❑Customs data from Revenue Service of the Ministry of Finance

trade in goods

❑Statistical Business Register

enterprise basic characteristics, ownership data

❑Annual Surveys of Enterprises

sex-disaggregated data on employment and wages; data on turnover

❑Structure of Earnings Survey

sex-disaggregated data on employment and wages by occupations at 1-digit ISCO level

Mapping of HS export codes to NACE

8703 Motor cars 45.1 Sale of motor vehicles

2204 Wine of fresh grapes 11.02 Manufacture of wine from grapes

2201 Waters, natural or artificial mineral and aerated waters

11.07.01 Production of mineral waters and other bottled waters

0802 Hazelnuts and other nuts 10.39 Other processing and preserving of fruit and

vegetables

6109 T-shirts and other vests, knitted or crocheted 14.13 Manufacture of outerwear

HS - Export Products NACE (rev.2) - Sector

Sectoral approach

Export product Exporting Sector Export-to-

Turnover, %

Motor cars Sale of motor cars

Grape wines Manufacture of grape wine

Mineral waters Mineral and bottled waters

Hazelnuts and nuts Processing and preserving of fruits and vegetables

T-shirts and other vests Manufacture of wearing apparel

61.2%

71.6%

63.9%

75.6%

62.5%

Percentage share of export values in turnover of exporting sectors, 2015-2019 average

Sectoral approach

Corresponding NACE sectors (4-digit level)

Sale of motor vehicles

Manufacture of wine from grape

Production of mineral waters and other bottled waters

Processing and preserving of fruit and vegetables

Manufacture of wearing apparel

The share of employed women in total

number of employees, 2015-2019 average

20.4%

40.1%

26.0%

63.5%

87.0%

Sectoral approach

Average wages, GEL

0

500

1000

1500

2000

2500

3000

Males Females Males Females

2015 2019

Sale of motor vehicles

Manufacture of wine from grape

Production of mineral waters and other bottled waters

Processing and preserving of fruit and vegetables

Manufacture of wearing apparel

0.55

0.70

0.70

0.60

0.69

Average ratio of

women’s to men’s

wages, 2015-2019

All economic sectors 0.65

Sectoral approach

Shares of Women and Men in Total Employment by ISCO,

2017

1.6

4.0

1.5

2.5

2.3

1.4

8.8

1.8

17.2

5.6

3.1

2.3

2.4

3.5

3.4

7.5

5.2

25.9

Managers

Professionals

Technicians and associate

professionals

Clerks

Service and sales workers

Skilled agricultural, fishery,

and forestry workers

Craft and related trades

workers

Plant and machine operators

and assemblers

Elementary occupations

Manufacture of wine

from grape

1.6

8.0

0.8

6.4

1.2

8.0

1.6

3.5

6.9

0.3

17.3

0.1

9.8

23.9

12.2

3.5

1.1

1.5

5.5

4.6

0.2

0.2

15.4

0.1

37.1

4.3

1.4

2.1

4.9

1.0

0.1

5.4

2.9

12.2

2.7

24.8

4.8

2.0

2.3

0.2

1.0

15.8

3.3

13.2

2.0

13.4

4.5

4.5

5.4

Manufacture of

wearing apparel Sale of motor vehicle

1.4

1.3

3.1

1.3

0.5

43.7

7.6

29.8

1.6

0.4

1.0

0.3

0.9

3.3

2.1

1.8

Production of mineral

waters and other

bottled waters

Processing and

preserving of fruit

and vegetables

women

men

Sectoral approach

Gender Pay Gap in the Exporting Sectors by ISCO, 2017

49.7

25.8

82.8

5.4

49.2

26.2

41.2 36.2

-21.7

30.2

20.3

1.1

-3.5

54.6

35.8 33.1

15.6

65.6

28.2

-4.3

23.3

-11.0

-20.0

-78.6

44.5

-11.5

-2.3

34.4

-16.3

6.0

-14.0

69.3

17.8

52.5

24.7

-13.1

44.8

23.1 22.6

36.4

44.6

-100.0

-80.0

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

80.0

100.0

Sale of motor vehicles

Manufacture of wine from grape

Production of mineral waters and

other bottled waters

Processing and preserving of fruit

and vegetables

Manufacture of wearing apparel

Managers

Professionals

Technicians and associate professionals

Clerks

Service and sales workers

Skilled agricultural, fishery, and forestry workers Craft and related trades workers

Plant and machine operators and assemblers Elementary occupations

Total, sector

Microlinking approach

▪ Produces more accurate data

▪ Excludes non-trading companies

▪ Provides more detailed picture on gender inequalities

Microlinking approach

Total trade

value (USD

thousands)

Total exports

value (USD

millions)

Total imports

value (USD

thousands)

Share in total

trade value

(%)

Two-way

traders 36,403.5 13,247.1 23,156.4 70.5

Importers 15,541.8 15,541.8 28.5

Exporters 565.2 565.2 1.0

11,735

34,195

2,7362,232

7,040

377

90.4% 82.7%

91.0%

68.1%

0%

50%

100%

150%

200%

0

5000

10000

15000

20000

25000

30000

35000

40000

Two-way traders Importers Exporters

Number of trading companies linked to SBS survey data and their

value shares in total exports and imports in 2016-2020

Number of trading companies in 2016-2020

Number of trading companies linked to SBS survey data

Share of linked companies in total exports value, %

Share of linked companies in total imports value, %

General Characteristics of Trading Companies

Percentage shares of trading companies in 2016-2020 total imports and exports, by NACE rev. 2 sections 0 10 20 30 40 50 60 70

Agriculture, Forestry and Fishing

Mining and Quarrying

Manufacturing

Electricity, Gas, Steam and Air Conditioning Supply

Water Supply; Sewerage, Waste Management and Remediation Activities

Construction

Wholesale and Retail Trade; Repair of Motor Vehicles and Motorcycles

Transportation and Storage

Accommodation and Food Service Activities

Information and Communication

Financial and Insurance Activities

Real Estate Activities

Professional, Scientific and Technical Activities

Administrative and Support Service Activities

Public Administration and Defence; Compulsory Social Security

Education

Human Health and Social Work Activities

Arts, Entertainment and Recreation

Other Service Activities

Activities of Extraterritorial Organisations

Unknown

Share in 2016-2020 imports (%) Share in 2016-2020 exports (%)

Employment

Number of employed persons (thousands) in two-way traders

and importers during 2016-2020, by sex

93.7

49.5

103.4

56.5

109.2

62.8

113.6

72.7

109.4

72.2

96.8

53.5

104.8

59.3

114.6

70.6

123.9

79.3

118.6

75.5

0

20

40

60

80

100

120

140

men women men women men women men women men women

2016 2017 2018 2019 2020

Two-way traders Importers

The women-to-men employment ratio among two-way

traders and importers (%) in 2016-2020

Average Monthly Wages and Wage Ratio

Two-way traders Importers

0.66

0.67

0.68

0.67

0.68

1,461.3 1,542.0

1,611.9

1,742.7 1,735.8

960.0 1,026.4

1,092.5 1,162.7 1,182.7

0.65

0.655

0.66

0.665

0.67

0.675

0.68

0.685

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2016 2017 2018 2019 2020

Wage ratio men women

0.74 0.74

0.70

0.66

0.69

1,196.9 1,302.3

1,432.2 1,539.4 1,569.4

886.2 958.0 996.1 1,011.6

1,075.5

0.62

0.64

0.66

0.68

0.7

0.72

0.74

0.76

0

200

400

600

800

1000

1200

1400

1600

1800

2016 2017 2018 2019 2020

Wage ratio men women

pay ratio - women/men

Employment and Wage Indicators

Women-to-men employment ratio among two-

way traders and importers, by skill levels

Gender pay gap among two-way

traders and importers, by skill levels

Ownership of trade companies

510

2469

103 272

8816

28806

1484 3063

1181

10835

731 863

0

5000

10000

15000

20000

25000

30000

35000

Woman owners Man owners Legal owners Unknown physical owners

Exporters Importers Two-way traders

COVID and key gender-in-trade indicators

39.0% 38.8%

38.9%

38.5% 38.5% 38.5%

40.5% 40.4% 40.5%

37.0%

37.5%

38.0%

38.5%

39.0%

39.5%

40.0%

40.5%

41.0%

importer two-way trader total

Women's share in employment

2019 2020 2021

33.5% 34.0% 33.8%

30.8% 31.2% 31.0%

28.4%

30.2% 29.5%

25.0%

26.0%

27.0%

28.0%

29.0%

30.0%

31.0%

32.0%

33.0%

34.0%

35.0%

importer two-way trader total

Gender pay gap

2019 2020 2021

Future steps

❑ Continue cooperation with the UNECE/UNCTAD which was initiated with the gender-in-trade pilot project

❑ Expand production of international trade statistics by introducing the gender-disaggregated indicators through micro linking

trade data with enterprise-level data from Geostat’s surveys

❑ Asses opportunities of other enterprise-level surveys to gain additional information regarding gender-in-trade statistics;

❑ Develop cooperation with governmental institutions and international partners to identify the policy needs in relation to gender

equality in international trade

Paata Shavishvili

Deputy Executive Director

National Statistics Office of Georgia (Geostat)

[email protected]

www.geostat.ge

Thank you!

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Гендерные аспекты в торговле в Грузии

Паата Шавишвили Заместитель Исполнительного Директора

Национальное статистическое управление Грузии (Грузстат)

Основные результаты оценки

Общий подход

❑Отраслевой уровень – показатели гендерных аспектов в торговле были

проанализированы для 5 экспортных продуктов

4-значные коды ТН ВЭД для экспортируемых товаров, привязанные к соответствующим кодам

КДЕС отечественных производственных отраслей

❑ Микросвязывание доступных источников с данными по торговле

Почти 60 000 предприятий, которые осуществляли экспортную и/или импортную деятельность в

2016-2020 гг., были взяты за основу для увязки данных, не относящихся к торговле.

Источники данных

❑Таможенные данные Службы доходов Министерства финансов

торговля товарами

❑Статистический реестр предприятий

основные характеристики предприятия, данные о собственниках

❑Ежегодные обследования предприятий

данные о занятости и заработной плате в разбивке по полу; данные о

товарообороте

❑Структура обследования доходов

данные с разбивкой по полу о занятости и заработной плате по профессиям согласно МСКЗ с

одноразрядной детализацией

Сопоставление экспортных кодов

ТН ВЭД с кодами КДЕС

8703 Автомобили 45.1 Продажа моторных транспортных средств

2204 Вина виноградные натуральные 11.02 Производство вина из винограда

2201 Воды, включая природные или искусственные минеральные, газированные

11.07.1 Производство упакованных питьевых вод, включая минеральные воды

0802 Орехи лесные и прочие орехи 10.39 Прочие виды переработки и

консервирования фруктов и овощей

6109 Майки и прочие нательные фуфайки трикотажные машинного или ручного вязания

14.13 Производство верхней одежды

ТН ВЭД - Экспортная продукция КДЕС (ред. 2) - Сектор

Секторальный подход

Экспортный продукт Экспортирующий сектор

Доля экспорта в

общем объеме

товарооборота, %

Автомобили Продажа автомобилей

Виноградные вина Производство виноградных вин

Минеральные воды Минеральные и упакованные воды

Лесные орехи и прочие

орехи

Переработка и консервирование фруктов и

овощей

Майки и прочие

нательные фуфайки Производство одежды

61.2%

71.6%

63.9%

75.6%

62.5%

Процентная доля стоимостного объема экспорта в обороте экспортных секторов, в среднем

за 2015-2019 гг.

Секторальный подход

Соответствующие сектора КДЕС (с 4-

разрядной детализацией)

Продажа моторных транспортных средств

Производство вина из винограда

Производство минеральной воды и прочих упакованных питьевых вод

Переработка и консервирование фруктов и овощей

Производство одежды

Доля занятых женщин в общей

численности работающих, в среднем за

2015-2019 гг.

20.4%

40.1%

26.0%

63.5%

87.0%

Секторальный подход

Средняя заработная плата, лари

0

500

1000

1500

2000

2500

3000

Males Females Males Females

2015 2019

Sale of motor vehicles

Manufacture of wine from grape

Production of mineral waters and other bottled waters

Processing and preserving of fruit and vegetables

Manufacture of wearing apparel

0.55

0.70

0.70

0.60

0.69

Среднее соотношение

заработной платы

женщин и мужчин,

2015-2019 гг.

Все сектора экономики 0.65

Продажа моторных транспортных средств

Производство вина из винограда

Производство минеральной воды и прочих упакованных питьевых вод

Переработка и консервирование фруктов и овощей

Производство одежды МужчиныМужчины ЖенщиныЖенщины

Секторальный подход

Доли женщин и мужчин в общей занятости по МСКЗ, 2017 год

1.6

4.0

1.5

2.5

2.3

1.4

8.8

1.8

17.2

5.6

3.1

2.3

2.4

3.5

3.4

7.5

5.2

25.9

Руководители

Специалисты

Технический и

вспомогательный персонал

Служащие общего профиля

Работники сферы

обслуживания и торговли

Квалифицированные работники

сельского и лесного хозяйства,

рыбоводства и рыболовства

Квалифицированные рабочие

промышленности и рабочие

родственных занятий

Операторы и сборщики

промышленных установок и машин

Неквалифицированные

работники

Производство вина из

винограда

1.6

8.0

0.8

6.4

1.2

8.0

1.6

3.5

6.9

0.3

17.3

0.1

9.8

23.9

12.2

3.5

1.1

1.5

5.5

4.6

0.2

0.2

15.4

0.1

37.1

4.3

1.4

2.1

4.9

1.0

0.1

5.4

2.9

12.2

2.7

24.8

4.8

2.0

2.3

0.2

1.0

15.8

3.3

13.2

2.0

13.4

4.5

4.5

5.4

Производство

одежды

Продажа моторных

транспортных

средств

1.4

1.3

3.1

1.3

0.5

43.7

7.6

29.8

1.6

0.4

1.0

0.3

0.9

3.3

2.1

1.8

Производство

минеральной воды и

прочих упакованных

питьевых вод

Переработка и

консервирование

фруктов и овощей

женщины

мужчины

Секторальный подход

Гендерный разрыв в оплате труда в экспортных

секторах в разбивке по категориям МСКЗ, 2017 г.

49.7

25.8

82.8

5.4

49.2

26.2

41.2 36.2

-21.7

30.2

20.3

1.1

-3.5

54.6

35.8 33.1

15.6

65.6

28.2

-4.3

23.3

-11.0

-20.0

-78.6

44.5

-11.5

-2.3

34.4

-16.3

6.0

-14.0

69.3

17.8

52.5

24.7

-13.1

44.8

23.1 22.6

36.4

44.6

-100.0

-80.0

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

80.0

100.0

Sale of motor vehicles

Manufacture of wine from grape

Production of mineral waters and

other bottled waters

Processing and preserving of fruit

and vegetables

Manufacture of wearing apparel

Managers

Professionals

Technicians and associate professionals

Clerks

Service and sales workers

Skilled agricultural, fishery, and forestry workers Craft and related trades workers

Plant and machine operators and assemblers Elementary occupations

Total, sector

Руководители

Специалисты

Технический и вспомогательный персонал

Служащие общего профиля

Работники сферы обслуживания и торговли

Квалифицированные работники сельского и лесного хозяйства, рыбоводства и рыболовства Квалифицированные рабочие промышленности и родственных занятий Операторы и сборщики промышленных установок и машин Неквалифицированные работники

Всего, сектор

Продажа моторных транспортных средств

Производство вина из винограда

Производство минеральной воды и прочих упакованных питьевых вод

Переработка и консервирование

фруктов и овощей

Производство одежды

Метод микросвязывания

▪ Позволяет получить более точные данные

▪ Позволяет исключить неторговые компании

▪ Позволяет составить более подробную картину гендерного неравенства

Метод микросвязывания

Общий

стоимостной

объем

торговли

(тыс. долл..

США)

Общая

стоимость

экспорта

(млн. долл.

США)

Общая

стоимость

импорта

(тыс. долл..

США)

Доля в

общем

стоимостном

объеме

торговли (%)

Двухсторонн

ие торговые

компании

36,403.5 13,247.1 23,156.4 70.5

Импортеры 15,541.8 15,541.8 28.5

Экспортеры 565.2 565.2 1.0

11,735

34,195

2,7362,232

7,040

377

90.4% 82.7%

91.0%

68.1%

0%

50%

100%

150%

200%

0

5000

10000

15000

20000

25000

30000

35000

40000

Two-way traders Importers Exporters

Количество торговых компаний, связанных с данными

исследования SBS, и их стоимостные доли в общем объеме

экспорта и импорта в 2016-2020 гг.

Number of trading companies in 2016-2020

Number of trading companies linked to SBS survey data

Share of linked companies in total exports value, %

Share of linked companies in total imports value, %

Двухсторонние торговые компании Импортеры Экспортеры

Количество торговых компаний в 2-16-2020 гг. Количество торговых компаний, связанных с данными исследования SBS Доля связанных компаний в общем объеме экспорта, % Доля связанных компаний в общем объеме импорта, %

Общие характеристики торговых компаний

Процентные доли торговых компаний в 2016-2020 гг. в общем объеме импорта и экспорта, по разделам КДЕС ред. 2

0 10 20 30 40 50 60 70

Agriculture, Forestry and Fishing

Mining and Quarrying

Manufacturing

Electricity, Gas, Steam and Air Conditioning Supply

Water Supply; Sewerage, Waste Management and Remediation Activities

Construction

Wholesale and Retail Trade; Repair of Motor Vehicles and Motorcycles

Transportation and Storage

Accommodation and Food Service Activities

Information and Communication

Financial and Insurance Activities

Real Estate Activities

Professional, Scientific and Technical Activities

Administrative and Support Service Activities

Public Administration and Defence; Compulsory Social Security

Education

Human Health and Social Work Activities

Arts, Entertainment and Recreation

Other Service Activities

Activities of Extraterritorial Organisations

Unknown

Share in 2016-2020 imports (%) Share in 2016-2020 exports (%)Доля в объеме импорта в 2016-2020 гг. (%) Доля в объеме экспорта в 2016-2020 гг. (%)

Сельское хозяйство, лесное хозяйство и рыболовство Горнодобывающая промышленность и разработка карьеров Обрабатывающие производства Электроэнергетика, газоснабжение, теплоснабжение и кондиционирование воздуха Водоснабжение; водоотведение, организация сбора и утилизация отходов, деятельность по ликвидации загрязнений Строительство Оптовая и розничная торговля; ремонт моторных транспортных средств и мотоциклов Транспортировка и хранение Гостиничный бизнес и общественное питание Информационно-коммуникационная деятельность Финансовая и страховая деятельность Деятельность в сфере недвижимости Профессиональная, научная и техническая деятельность Административные и вспомогательные услуги Государственное управление и оборона; обязательное социальное страхование Образование Деятельность в области здравоохранения и социальных услуг Искусство, развлечения и отдых Прочие виды услуг Деятельность экстерриториальных организаций

Неизвестно

Занятость

Численность занятых (тыс.) в двухсторонних торговых

компаниях и компаниях-импортерах в 2016-2020 гг., в

разбивке по полу

93.7

49.5

103.4

56.5

109.2

62.8

113.6

72.7

109.4

72.2

96.8

53.5

104.8

59.3

114.6

70.6

123.9

79.3

118.6

75.5

0

20

40

60

80

100

120

140

men women men women men women men women men women

2016 2017 2018 2019 2020

Two-way traders Importers

Соотношение женщин и мужчин, работающих в

двухсторонних торговых компаниях и компаниях-

импортерах (%) в 2016-2020 гг.

Двухсторонние торговые компании

Импортеры

Импортеры

Двухсторонние Торговые компании

Двухсторонние торговые компании

Импортеры Женщины МужчиныМужчиныМужчиныМужчины Женщины Женщины Женщины Женщины

Среднемесячная заработная плата и соотношение

заработной платы

Двусторонние торговые компании Импортеры

0.66

0.67

0.68

0.67

0.68

1,461.3 1,542.0

1,611.9

1,742.7 1,735.8

960.0 1,026.4

1,092.5 1,162.7 1,182.7

0.65

0.655

0.66

0.665

0.67

0.675

0.68

0.685

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2016 2017 2018 2019 2020

Wage ratio men womenСоотн. з/п

0.74 0.74

0.70

0.66

0.69

1,196.9 1,302.3

1,432.2 1,539.4 1,569.4

886.2 958.0 996.1 1,011.6

1,075.5

0.62

0.64

0.66

0.68

0.7

0.72

0.74

0.76

0

200

400

600

800

1000

1200

1400

1600

1800

2016 2017 2018 2019 2020

Wage ratio men women

Соотношение заработной платы - женщины/мужчины

Соотн. з/п Мухчины

Мужчины Женщины Женщины

Показатели занятости и заработной платы

Соотношение занятости женщин и мужчин в

двусторонних торговых компаниях и

компаниях-импортерах в разбивке по

уровням квалификации

Гендерный разрыв оплате труда в

двусторонних торговых компаниях и

компаниях-импортерах в разбивке по

уровням квалификации

Двухсторонние торговые компании

Двухсторонние торговые компании

Двухсторонние торговые компании

Двухсторонние торговые компании

Импортеры

Импортеры

Импортеры

Импортеры

Руководители Руководители

Руководители

Высококвалифиц. работники

Высококвалифиц. работники

Низкоквалифиц. работники

Низкоквалифиц. работники

Среднеквалифиц. работники

Среднеквалифиц. работники

Среднеквалифиц. работники

Низкоквалифиц. работники

Среднеквалифиц. работники

Собственники торговых компаний

510

2469

103 272

8816

28806

1484 3063

1181

10835

731 863

0

5000

10000

15000

20000

25000

30000

35000

Woman owners Man owners Legal owners Unknown physical owners

Exporters Importers Two-way traders

Импортеры

Собственнки-мужчины Законные собственники Неизвестные физические лица-собственники Собственнки-женщины

Двухсторонние торговые компании

Экспортеры

COVID и ключевые показатели гендерных

аспектов в торговле

39.0% 38.8%

38.9%

38.5% 38.5% 38.5%

40.5% 40.4% 40.5%

37.0%

37.5%

38.0%

38.5%

39.0%

39.5%

40.0%

40.5%

41.0%

importer two-way trader total

Доля женщин в общей занятости

2019 2020 2021

Импортер Всего

33.5% 34.0% 33.8%

30.8% 31.2% 31.0%

28.4%

30.2% 29.5%

25.0%

26.0%

27.0%

28.0%

29.0%

30.0%

31.0%

32.0%

33.0%

34.0%

35.0%

importer two-way trader total

Гендерный разрыв в оплате труда

2019 2020 2021

Импортер Двухсторонняя торговая компания

Двухсторонняя торговая компания

Всего

Дальнейшие шаги

❑ Продолжение сотрудничества с ЕЭК ООН/ЮНКТАД, которое было начато в рамках пилотного проекта по учету

гендерных аспектов в торговле.

❑ Расширение подготовки статистики международной торговли за счет введения показателей с разбивкой по гендерному

признаку путем микросвязывания данных по торговле с данными на уровне предприятий, полученными из

обследований Грузстата.

❑ Оценка возможностей других обследований, проводимых на уровне предприятий, для получения дополнительной

информации, относящейся к гендерной статистике в области торговли;

❑ Развитие сотрудничества с государственными учреждениями и международными партнерами в целях определения

страгегических потребностей в отношении обеспечения гендерного равенства в международной торговле.

Паата Шавишвили

Заместитель Исполнительного Директора

Национальное статистическое управление Грузии (Грузстат)

[email protected]

www.geostat.ge

Спасибо за внимание!

19

Sector Review of the Implementation of the Generic Statistical Business Process Model

(GSBPM) in Georgia

Final Report March 2023

Introduction There is a strong trend in official statistics to standardise processes and centralise similar statistical functions (e.g. dissemination) within national statistical offices (NSOs). This is done to realise efficiency gains, reduce risk and increase quality, especially where resources are scarce. The Generic Statistical Business Process Model (GSBPM) can help organisations to think about how to achieve this through moving towards a more process-oriented organisation structure. In February 2023, an international team of experts convened by the United Nations Economic Commission for Europe (UNECE) conducted a Sector Review of the implementation of the GSBPM in Georgia, with the aim of producing a roadmap for organisational change. This review was undertaken at the request of, and in partnership with, Geostat, the National Statistics Office of Georgia, in the context of the National Strategy for the Development of Statistics in Georgia1. This report contains the observations and recommendations of the international experts and has been agreed with the management of Geostat. The review team consisted of Mr Zoltan Vereczkei (Central Statistical Office of Hungary), Mr Carlo Vaccari (Independent consultant, Italy), Ms InKyung Choi and Mr Steven Vale (UNECE). The review was conducted in cooperation with the managers and staff of Geostat. Its findings are based on discussions and presentations during a mission of the review team to the Geostat office in Tbilisi, which took place on 20-22 February 2023. The review team was impressed with the work done so far to implement the GSBPM in Geostat, and the willingness of staff to consider new ideas. The current strategy provides a good basis for modernisation, and this theme will be further developed in the next strategy, which will be elaborated in the coming months. The approach Geostat is taking is in line with international good practices, including those promoted by the UNECE High-Level Group for the Modernisation of Official Statistics. The review team worked with Geostat managers and staff to prepare recommendations for next steps in the implementation of the GSBPM and the move towards a more process- oriented organisation structure, as well as a draft roadmap for their implementation. The recommendations are elaborated in Chapters 1 to 3, and the roadmap is presented in Chapter 4. The collaboration between the review team and the staff of Geostat was very positive and constructive throughout all phases of the work. The review team would like to thank the management and staff of Geostat for their full and active collaboration in the conduct of this Sector Review and would like to wish them success with their modernisation journey.

1 https://www.geostat.ge/en/modules/categories/630/strategy-for-the-development-of-statistics

Chapter 1: Awareness raising and communication Modernisation, appropriate organisational structure and capability to manage change are essential for national statistical offices to meet the challenges facing official statistics. They should not be seen as one-off exercises, but rather as the development of a culture of change, a culture that helps statistical offices to become more flexible and adaptable to react to new challenges. For modernisation to succeed, it is vital to have the support and active involvement of staff at all levels. However, the natural reaction for many people when faced with change is often suspicion and fear. This means that raising awareness and communicating the reasons and plans for change is vital. The GSBPM and its extension, the Generic Activity Model for Statistical Organisations (GAMSO), have been proven to support NSOs in their move towards process-oriented statistical production. They support the implementation of standard tools and methods to improve efficiency. Experience in various countries has shown that this allows resources to be freed to support new activities or to strengthen existing ones that add higher value to the outputs of the NSO. Allowing staff to focus on these activities can improve job satisfaction and staff retention. Recommendations 1.1 Conduct basic training and promotion on GSBPM and its role

• Geostat should produce promotional materials to help raise staff awareness about GSBPM.

• Geostat should conduct basic training on GSBPM, one course for the staff in general and a more extensive course for those who will be involved in the change management process as they will require more in-depth knowledge about the model to guide the changes. The training can be conducted by external experts at first, or by just asking staff to follow existing GSBPM training resources which can be found on the UNECE GSBPM wiki (e.g., YouTube video on introduction to GSBPM). However, in the long run, it is important that Geostat grows internal experts on GSBPM who can assist and guide the process for documentation (see Chapter 2) as well as centralisation (see Chapter 3). The initial focus should therefore be to “train the trainers”, to develop these internal Geostat experts.

• The training should not be done for the sake of learning about the GSBPM. It is important to provide the “big picture” and to emphasize the rationale and reasoning behind why training on GSBPM is needed, that it is a tool for the transition to a process-oriented organisation. Internal communication on the model should also highlight this point so that staff learning about GSBPM are also exposed to the broad vision where the organisation is heading toward.

• Geostat should create a centralised repository in the intranet where all resources about GSBPM, including training and awareness raising materials, can be stored. This repository should serve as the Geostat knowledge base on GSBPM.

1.2 Translate GSBPM into Georgian • Geostat should produce an agreed translation of the GSBPM into Georgian, to

ensure the use of standard terminology and to better spread knowledge about the model within Geostat. Given that the transition to a process-oriented organisation concerns all parts of Geostat (statistical production and corporate support such as IT and HR), GSBPM in Georgian will help to ensure a broad and common understanding of the model across Geostat, which is a precondition for many activities that will follow.

• Geostat should store the agreed translation in the centralised repository on the intranet mentioned in the 4th bullet point of Recommendation 1.1.

1.3 Get to know GAMSO and produce a Georgian translation

• Geostat has set the goal to introduce a process-oriented organisation. In order to do this, based on the experience of countries that have already implemented similar organisational structures, GSBPM will not be enough. Therefore, Geostat should also take a look at GAMSO, produce a Georgian translation of the model, and make it available to all staff on the intranet. As demonstrated during the mission, GAMSO can help Geostat to understand the role of corporate support areas in the statistical organisation (e.g. legal, methodology, IT, finance, HR) and what role these areas play in a future process-oriented organisation.

Chapter 2: Documentation Many national statistical offices that have successfully used the GSBPM and GAMSO to help them move towards a more process-oriented approach to statistical production have started by documenting existing process. Process documentation should not be seen as a goal in itself, but as a way of understanding the starting point for modernising statistical production. Documentation should use templates that facilitate the wide re-use of text and avoid the duplication of work. In this way, documentation can be seen as an investment that will reduce efforts in the future. Managing the information in a database format can be useful as it allows different reports to be generated for different users or purposes, based on selections from standard content, e.g. quality reports for international organisations, or lists of processes that use certain software or methods. Recommendations 2.1 Analyse the current state of Geostat

• Geostat should carry out an analysis, focusing on the current state in Geostat using GSBPM and GAMSO as a reference: What processes and activities are present in the current organisation, who is responsible for what etc.

2.2 Conduct skills mapping and develop HR strategy

• Geostat should carry out a skills audit to prepare for a process-oriented organisation and the transition period, by identifying the skills Geostat currently has, and those it will need in the future. This will help to identify gaps between the current and the future situation. This could start in the pilot units (Recommendation 3.3), involving the internal group (Recommendation 3.1) and HR. With the transition to a process- oriented organisation, each person becomes more specialised (as opposed to an individual carrying out a little bit of every function).

• Geostat should develop a HR strategy to develop the missing skills through recruitment, re-training of existing staff, or a mixture of both.

2.3 Develop the intranet further

• Geostat should continue the work started to establish an intranet and make it easily available to all staff. The intranet is typically a good first access point for information internally to the NSO staff.

• As mentioned in Recommendations 1.1, 1.2 and 1.3, Geostat should put all relevant documents on the intranet, including process descriptions, the Georgian translations of the GSBPM and GAMSO, any future documentation (training material, self- assessment material, future descriptions etc.) they produce, as well as materials from all international projects that Geostat is involved in.

• Geostat should consider tagging documents on the intranet according to the GSBPM to make their discovery and use easier, and to signal their importance. Tagging can also go deeper: tagged documents using the GSBPM phases or even sub-processes will enable staff to easily find and link information to the GSBPM.

2.4 Define IT standards

• Geostat should define and declare what IT solutions they intend to use as IT standards for Geostat as a whole. Some examples: database structures or standard tools for Database Management System or for programming languages and for statistical packages (the “R” package is now a standard in many NSOs). These standards must be a “constraint” not only for internal developments but also for donors and international projects, preventing the IT unit from being forced to maintain and support too many software platforms. Identifying these IT standards will be important in the future to have an efficient process-oriented organisation in place and further standardise existing IT solutions and introduce new ones. Geostat should gradually abandon the use of Microsoft Office products such as Excel and Access for the production of official statistics, and introduce more professional tools.

2.5 Start building a metadata system based on the information collected

• Geostat collects and stores a lot of information about processes already, and should continue and complete the intended descriptive exercise. However, it will give the organisation more value if Geostat organises this information into a very first early version of a metadata system. This is a common practice in most process-oriented organisations and will be of great help to ensure smooth operation of process flows in the new organisation.

• As a first step, Geostat should organise the information they manage into databases and not store it only in Excel sheets. This will also help Geostat to prepare to meet future needs related to metadata structures and their management, such as the introduction of the Single Integrated Metadata Structure (SIMS), to be more in line with the requirements of the European Statistical System.

Chapter 3 – Organisation Moving to a process-oriented organisation has been shown in various countries to improve the efficiency of the NSO. Geostat has already started along this path by centralising dissemination and communication activities in the Department of International and Public Relations some years ago. A major staffing challenge in the coming years will be how to redeploy the large number of posts that are currently dedicated to data collection activities in the regional offices of Geostat. This is a natural consequence of the move from collecting data on paper by interviewers, towards more electronic data collection (including by Internet) and the greater use of administrative and other non-statistical data sources. Logically, the posts that are no longer needed for data collection could be re-used to help to improve quality, produce new outputs, or any other activities that add value to Geostat’s work. It is important to note that any organisation structure needs to evolve over time to meet new user needs and take advantage of new opportunities. The current lack of space in the Geostat headquarters building in Tbilisi can be seen as a constraint on redeploying posts to support activities that currently only take place in that building. However, the COVID-19 pandemic has shown the possibilities of remote working, and it may be possible for some staff to work on new tasks whilst still being physically based in regional offices. The sector review team and Geostat staff discussed the most likely next steps and identified possibilities to improve efficiency by consolidating data collection, as well as a further consolidation of methodological support activities. There are several points to take into account when considering whether to consolidate an activity that is currently spread amongst several different organisational units. These can include:

• Evaluating changes in the external environment (e.g. new technologies, new administrative or other data sources)

• Assessing risks and making plans for managing them • Identifying the different capabilities needed, not just the staff and their skills, but all

the other institutional capabilities that should be combined to ensure a successful transition. The diagram below showing the seven dimensions of statistical capabilities is taken from the UNECE Statistical Capacity Development Strategy2, and may help with this

• Identifying the steps needed for capability improvement • Setting quality guidelines and criteria. The GSBPM quality indicators3 may help with

this • Implementing and monitoring the results.

2 https://unece.org/sites/default/files/2020-11/Statistical%20capacity%20development%20strategy%20final.pdf 3 https://statswiki.unece.org/display/GSBPM/Quality+Indicators

The seven dimensions of statistical capabilities

In an organisation based on statistical subject-matter domains, most production activities for one domain are carried out within one organisational unit. On the contrary, in a process- oriented organisation with centralised functions, production should be carried out in collaboration and coordination between multiple units (e.g. subject-domain, data collection unit, IT unit). This requires the establishment of formal agreements (sometimes referred to as service-level agreements or SLAs) to define who is responsible for what and to ensure the smooth flows of data and services between units, at the right time, with an agreed level of quality. Recommendations 3.1 Establish change champion(s) and a small internal group

• Geostat should identify one or more change champions amongst mid and senior managers. They should be mandated by the Executive Director to lead the change process across Geostat.

• Geostat should create a small internal group of people who are open to change from different parts of the organisation. They should be people who understand what the process-oriented organisation means. They should drive the discussions about change, bringing in all necessary skills and competencies from across the organisation, and keep the change process going in the right direction.

3.2 Change manager to be mandated

• Geostat should find and mandate an independent change manager to help the top management in the whole transition process of changing the organisation. This change manager should have good knowledge of the Georgian public administration system and Geostat, as well as being an excellent change manager. Ideally, an external change manager can bring in new skills and knowledge on how to manage change that can be as crucial for a successful transition as good knowledge of Geostat.

3.3 Consolidate data collection – step by step • Geostat should centralise the data collection functions across the organisation. Even

in the era of electronic data collection, there is a strong potential in centralising services such as data collection. This will open up new modernisation directions that will result in further efficiency gains and higher quality, such as using multimode design, using more administrative data and other data sources, introduction of new methods in cooperation with the methodology team (such as sampling or survey- methodology), upskilling field interviewers, etc.

• In consolidating data collection, Geostat should consider a step-by-step approach, perhaps starting with a small sub-set of subject-matter domains (for example, agriculture, business, social). This should be seen as a pilot to test the approach and understand the benefits before it is extended to the whole organisation.

3.4 Consider consolidating methodology

• Geostat should consider greater consolidation of methodology functions This can improve efficiency and value added. There is a clear trend towards centralised methodology support in most NSOs having process-oriented organisations.

• As a first step Geostat could try a pilot focusing on data collection-related methodologies, such as sampling or survey-methodology, to see the benefits.

3.5 Introduce and use SLAs

• Geostat should consider introducing SLAs (or similar agreements), to help to clearly define the borders between units working on different processes (for example between data collection and subject-matter domains). SLAs can be used to define quality criteria (including when the output of one team is accepted by the next) and clarify responsibilities.

• SLAs should be supported by a software tool to manage the service request and provision, keeping track of different requests and replies, allowing an analysis of efficiency and bottlenecks.

3.6 Set up an international advisory support group

• Geostat should consider setting up an international group of experts to provide advice and support during the transition period. This group could review the progress periodically and advise on next steps or how to solve any issues encountered, based on their experiences.

Chapter 4: Moving forwards – A roadmap The review team identified a series of actions, some of which are inter-dependent. Based on experiences in other NSOs, these actions could take 3-4 years to complete. They can be grouped as follows:

First 12-18 Months - Foundations • Training on GSBPM / GAMSO / process-based organisation (Recommendation 1.1) • Agreed translations of GSBPM and GAMSO (Recommendations 1.2 and 1.3) • Analysis of the current state of Geostat (Recommendation 2.1) • Skills mapping and HR strategy (Recommendation 2.2) • Define IT standards (Recommendation 2.4) • Initial design for intranet and metadata system (first parts of Recommendations 2.3

and 2.5) • Set up and train group of change champions (Recommendation 3.1) • Appoint change manager (Recommendation 3.2) • Set up international advisory support group (Recommendation 3.6)

Next 24-30 Months - Implementation

• Implement intranet and metadata system (second parts of Recommendations 2.3 and 2.5)

• Consolidate data collection – step by step (Recommendation 3.3) • Consolidate methodology (Recommendation 3.4) • Set up service level agreements (or similar) (Recommendation 3.5)

The review team notes that Geostat is applying for a “twinning” project with a European Union country. Such projects can be very useful, and, in this case, it will be important to include support for at least some of the above steps in that project, so that Geostat can benefit from the experience of the partner NSO. There are likely to also be other opportunities (like IPA projects) for international support in the context of Georgia’s European Union accession process. The review team wishes Geostat success in implementing the above roadmap and in their further steps to modernise official statistics in Georgia. The Georgian experiences will definitely be of interest to other countries that are at a similar point, or further behind on the modernisation journey. UNECE intends to bring together representatives of Geostat and the NSOs of Armenia and Moldova (possibly others) later in 2023, to share ideas and experiences. The review team would also encourage Geostat to present progress and experiences at relevant international events, including the UNECE ModernStats World Workshops. The members of the review team also remain available for follow-up discussions by e-mail and on-line meetings, and are willing to provide further advice and support with the implementation of the recommendations and roadmap.

Annex: Resources

• GSBPM documentation and supporting materials o Maturity Model o Implementation check list

• GAMSO documentation and supporting materials • Sector Review of GAMSO Implementation in Armenia • Mapping of Armstat activities to GAMSO (Note: This is not a public document, but

has been shared with Geostat with the permission of Armstat) • Information flow within GSBPM using GSIM: diagram and full report • Documentation using GSBPM (Excel template) • GSBPM “tasks” (activities at more detailed level than sub-process) that could be

useful for documentation • Quality indicators through GSBPM: in GSBPM clickable (at the bottom of middle

box), full report • Geoinformation in GSBPM • Awesome official statistics software list (github repository for R packages for official

statistics) GSBPM Experiences from other organisations (from GSBPM Resource Repository)

• Slovenia (2022): GSBPM as a Backbone of the Internal Documentation System • Portugal (2019): Describing the Statistical Business Process using the GSBPM as a

reference (for Internal planning and management IT system) • New Zealand (2018): GSBPM: 12+ years of implementation! • IMF (2022): GSBPM Implementation: Experience from the IMF (also see: 2019: IMF

and the GSBPM: Progress So far) • Croatia (2022): Instructions on Quality according to the Generic Statistical Business

Process Model (GSBPM)