1. Batista Chilopa-Principal Statistician
Challenges in producing disaggregated data and STRIDES TOWARDS COORDINATED DISAGGREGATION-The Case of Zambia NSO
Presented during the Data Disaggregation Workshop Held at Sogecoa Golden Peacock Hote Lilongwe, Malawi
27th to 29th September, 2017
Prepared By
Batista Chilopa-Principal Statistician

2. Content of Presentation
Common Characteristics used in disaggregation
Challenges faced
Sub-groups at risk of being left behind
Strides Towards Coordinated Disaggregation

3. Common Characteristics used in disaggregation
Geographic: National, Rural, Urban and Provincial (rarely districts)
Demographic: Sex, Age groups, Household Headship (male, female
Economic: Income, Economic Activity, (Paid Employment, Unpaid , Family Worker, Un Employed, Full Time Student, Home Maker, Retired/Too old/Too young), Industry, occupation, Employment Status, Sector of Employment
Social: Education Levels (No Schooling, Primary, Secondary and Higher)
HIV Status
Disability Status
Migration Status
Agriculture: Agricultural Households (Small scale, Medium Scale, Large Scale farming)

4. CHALLENGES FACED
Non Standardised Definitions of Categories - Different data sources not using the same definitions or breakdowns.
orphan-hood (ages 0-17 for ZDHS 0-20 for LCMS)
Sanitation (type of toilet facility, Safe water sources)
Age related categorisation e.g.: (child, youth, adolescents, adults)
Ethnicity: Ethnic group or tribe?)

5. CHALLENGES FACED
Inadequate Sample Sizes-Not easy to see trends when numbers are too small (more so for disaggregation by type of disability)
Hard to reach places sometimes excluded due to budgetary constraints- this leads to missing out a subgroup that could be eligible for certain services
Flooded areas and places that require water transport sometimes end up being excluded

6. CHALLENGES FACED
Inconsistent/Conflicting Methodologies for Classification (Labour-force employment issues especially cut-off criteria especially number of hours, decisions on what informal and formal sector constitute)
Expertise Limitations- not having many staff trained in advanced analysis software to enable certain disaggregation such as wealth or income quintiles
Lack of Coordination-Operating in “self contained manner” both within the Central Statistical Office and as the NSS- no or little interaction for assessing data requirements for effective disaggregation
Stake holder Consultative meetings not taken seriously- Participation left to inexperienced staff

7. Challenges
Limiting of Disaggregation categories (Census Data e.g. Religion Catholic, protestants, other)- Data is most often requested by actual denomination
Administrative records e.g. from the police reports From entry/exit port are not disaggregated by important characteristics such as sex or age

8. WHO is left behind? Migrants Refugees Hard to reach populations
Sub-groups with smaller populations

9. STRIDES TOWARDS COORDINATED DISAGGREGATION
The CSO has taken a stance, to strengthening its coordination role in the National Statistical System (NSS), by creating a coordination Division
The principal responsibility of the Division is to coordinate the Programmes and data production activities of Central Statistical office in particular and the NSS in general;
This will lead to promotion of harmonization and integration of subsystems of data production and embracing the principal of “not leaving anyone behind” as data is produced and disseminated.
The office is currently drafting a statistical coordination policy document

10. STRIDES….
The office in 2016 initiated a training activity (Basic data analysis and utilisation training workshop) for provincial data management staff, mainly planners. This is in order to develop capacities for data management as well as analysis across all sectors in the NSS.

11. STRIDES…..
Reviewed and integrated various indicators prepared by different line ministries and sectors to come up with core indicators that can be used to report both on SDGs and National Development Plan.
Mapping of data sources was done for all indicators at national Level.

12. Benefits of the Coordination Efforts
Standardization of norms, concepts, practices across and within institution;
Provision of internal examination of institutional performance through monitoring and evaluation;
Achievement of synergy and cost effectiveness in the utilization of resources;
Promoting sharing of best practices; and
Strengthening the position of the organization and enhancing the image of official statistics.

13. Thank you very much for your attention
End of presentation.