The Mckinsey 7-S Framework

Inter-Regional Workshop on the Production of Gender Statistics NASC Complex New Delhi, India 6-10 August 2007 Data Availability, Accessibility and Quality By Dr. Grace Bediako Government Statistician Ghana Statistical Service February 22, 2020 1 Some key concerns with regards to gender statistics Poor cooperation between users and producers of gender statistics Under-utilization of existing data Inadequate or biased concepts, definitions and measures Data gaps on many critical areas

of concern February 22, 2020 2 Dealing with inadequacies in data Beijing Platform for action requires that Governments: Ensure that producers and users of statistics in each country regularly review the adequacy of the official statistical system and its coverage of gender issues, and prepare a plan for needed improvements, where necessary. (Para. 210(b)) February 22, 2020 3 Focus of the presentation

What are the issues with respect to: Data availability Accessibility of the data Quality How do they influence the production of gender statistics? How can these be improved? February 22, 2020 4

Data availability Questions of data availability at the fore of the production of data Having considered problems and goals with respect to gender in society And identified statistics and indicators required to plan, programme and monitor change There needs to be a review of national sources to determine what data are available and what need to be collected anew. Has direct bearing on the responsibilities of the national statistics office

Relate to whether and how data are used How relevant the data are to a target audience What further plans are to be made for data collection February 22, 2020 5 Major steps in the gender statistics production process Defining data requirements Defining issues Problems and questions on gender issues in society Required improvements in the situation of women and

men Goals for equal opportunity February 22, 2020 Statistics required from various fields Relevant statistics/indicators Assembling data Available statistics Data gaps Determine data sources Review quality Other sources Assess adequacy of concepts, methods, classifications, etc. Collect new data

Dissemination Statistics to be analysed Analysis Presentation Dissemination 6 Promoting the utilization of available data Identify available data Review sources of data Assess quality of data relative to need Generate statistics to be analysed Need for improvements in content, concepts,Identify new data needs

measurement, classifications February 22, 2020 7 Required statistics reflect the several dimensions Subject matter (topics) Unit of analysis (individual, household, institution, enterprise, etc.) Reference period Classified by other characteristics Geographical coverage Periodicity

February 22, 2020 8 Sources of available statistics National censuses of population, housing, industry, agriculture, distributive trade, etc. Sample surveys of households, economic units Registration and administrative records February 22, 2020 9

Considerations in reviewing existing sources of data How closely the original purpose for the data matches the present needs If data were collected without regard for gender, it would be necessary to consider that there is: Sex dissagregation Topics of interest are covered at the broad level, as well as at a level of detailed relating to specific gender issues

Concepts and definitions are relevant Dissaggregations with respect to age, socio-economic characteristics, geographic locations, etc. Time reference February 22, 2020 10 Accessibility: Data may be characterized by the following: Required data were collected: Tabulated and published in at least one form (including yearbooks, booklets, diskettes and compact discs) Tabulated but not published (such data can only be obtained from the responsible office by request) May not have been tabulated (data are available in the form of individual records on computer media, such as magnetic tapes, compact discs, or computer diskettes) and can only be obtained by submitting a specific request to the responsible office Data are collected but not processed (i.e., although the relevant questions were asked in surveys/censuses,

responses are not coded or extracted from the questionnaires) Data are not collected at all or are not collected by sex February 22, 2020 11 Quality considerations further limit use of available data February 22, 2020 12 Components in data quality assessments Validity Reliability Relevance to policy Potential for disaggregation

Currency Punctuality Coherence across different sources Clarity and transparency (regarding limitations) Accessibility and affordability Comparability (conformity to international standards) Consistency over time and space February 22, 2020 Efficiency in the use of resources. 13 The combination of these components use

to determine the quality of any particular set of data may vary from one purpose to another. Data that are acceptable for one purpose might be inadequate for next. Since use of data for gender-specific analysis differs from other purposes, the process of determining `fitness for purpose' requires wide consultation. The trade-offs to balance the different components of quality cannot satisfy all users simultaneously, but the needs of users may be addressed through flexible presentations of the data. Denise Lievesley United Nations Educational, Scientific and Cultural Organisation, Paris February 22, 2020 14 Basic considerations in data quality for gender statistics

Relevance of concepts Comparability of data over time Consistency and comparability among sources Applicability of the classifications and disaggregations February 22, 2020 15 Quality concerns with respect to data available on gender issues

Is the concept/definition used in data collection consistent with the definition required for the gender issue? Do the definitions change from one source to another or between periods? Is the classification for the gender issues appropriate? Have changes occurred in measurements over time or between sources? February 22, 2020 16 General quality issues Introduction of errors at various stages of data collection stemming from practices

Problems with concepts and definitions Problems with measurements February 22, 2020 17 Errors may occur at different stages in the data collection Planning and designing the survey

process Advertising the survey Defining the coverage and target Defining the sampling frame and design Formulating concepts and definitions Designing the questionnaire Defining the reference period Selecting and training the enumerators Selecting the respondents Final checking and coding of the results February 22, 2020 18 Difficulties with concepts and definition

Family/household Household headship Marital status Economic activities Population economically active Status in employment Unemployment February 22, 2020 19 Measurement problems for still many topic/variables

Household composition Infant mortality Maternal mortality Access to safe water Internal and international migration Economic and noneconomic activities February 22, 2020

School enrolment Time-use Agricultural labour Access to resources Access to credit Individual & household income Violence 20 Thank You February 22, 2020 21

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