Goal 1:  An entrenched culture of evidence-based policy, planning and decision-making at all levels

Evidence-based policy, planning and decision-making is about making public policy, planning and decisions after an open debate which is informed by careful and rigorous analysis using sound and transparent data. This enables a more accountable and sustainable approach to developing public policies and strategic plans as well as making decisions. It also helps build credibility of public policy, planning and decision-making processes.

This goal, therefore, is about evidence generation, synthesis and evidence informed behaviour change which will be achieved through the following strategic objectives (SOs):

SO 1.1   Increase statistical advocacy

Statistical advocacy is about: (i) creating  greater statistical awareness or numeracy as well as demystifying, democratizing and promoting wide use of statistics in society; (ii) making the general case for the importance and role of statistics in the wider context of development and, in particular, in informing the process of governance (e.g. supporting policy development, resource allocation and accountability); (iii) demonstrating the statistics-policy and decision-making chain and in particular, use of statistics  for policy, planning and decision-making at all levels; (iv) making a case for specific statistical activities e.g. the Population and Housing Census; (v) making a business case for statistics and mobilizing national and international resources for statistics; and (vi) promoting statistical planning and coordinated investment in developing statistical capacity.

Thus, statistical advocacy is a strategic issue aiming to bring about necessary changes in decision-making behaviour through quality statistics. It should therefore be recognized and addressed alongside the other strategic issues within the NSDS process and in the strategic management of the NSS, so that the NSDS2 is well-designed, well-implemented and well-financed, leading to better use of statistics, better decision-making and better development outcomes. To foster statistical advocacy, a statistical advocacy programme will be developed and implemented. It will have the following initiatives:

SO 1.2   Improve data analysis and interpretation

In and by themselves, data do not have much value. Their value derives from the fact that they can be processed, analyzed, interpreted and disseminated to those who need them and can be understood and used. Data analysis is about adding value to data by establishing underlying relationships and trends, extracting information from a maze of data and producing value-added products including policy-related information and briefs. Under this initiative, data producers will go beyond basic data analyses to undertake more detailed analyses of data holdings.  This helps to better illuminate development issues, inform policy design and programme development, and form a basis for advocacy. Initiatives that will be undertaken to support this strategic objective include the following:

SO 1.3:    Improve data dissemination and communication, uptake and use

Data dissemination and communication is a critical stage in the data production cycle. It serves to justify the existence of the NSS because if its outputs are widely used and found to have impact, government will get more inclined to continue to fund statistical production and development. But even more crucially, since data are produced at public expense, the public has a right to expect and access data for various purposes. It has been argued that data dissemination acts as a vital barometer of the NSS’s efficiency and effectiveness. So if the data from the NSS are used and to good purpose, this demonstrates their worth. It is also important that the NSS “gives back information to society” from whom primary information were collected in the first instance.

However, as mentioned in the last chapter, there was a tendency in the past to focus too narrowly on the collection and production side of the data value chain under the assumption that whatever was produced would be accessed and used. But it has been shown that a “build it and they will come” mentality is obsolete in today’s data age. Collecting and publishing data alone does not ensure its usage or lead to positive impacts. More attention is needed on their communication, uptake and use, which the data value chain unpacks and illustrates as the report by AidData on “Avoiding Data Graveyards” shows^[1].

SO 1.4   Increase data user satisfaction

Data users are the clientele of data production systems and clearly the most important component of the NSS. Statistics are produced because they are demanded and it is widely acknowledged that demand for data is essential for sustainability of statistical systems. In addition, some of the data users are responsible for dispensing resources – the case with policy makers in ministries of finance/planning. It is, therefore, important that users are satisfied with the data they are getting in terms of relevance, scope, quantity, consistency, quality, disaggregation and timeliness.

Goal 2:  Reformed and more responsive National Statistical System

In recent past, there has been unprecedented increase in demand for data following adoption of development agendas at different levels – national, regional, continental and global levels. The increase is not just in quantity and quality but also in data scope and disaggregation to ensure that no groups are left unaccounted for. The data environment has also been changing with the data ecosystem expanding and diversifying to include new data users, data producers and sources of data; there are new development areas that require development data; new and innovative technological changes are taking place; and indeed, there are new data sources, new ways of gathering data, and new data-based partnerships are being created. There is therefore an urgent need for the NSS to adapt to the increasing complexity of the new data ecosystem and to develop in order to meet the widening, increasing and evolving needs of data users.

To achieve this goal, two strategic objectives will be met.

SO 2.1   Create awareness about the 2018 Statistics Act No. 13 of 2018

Implementation of a Statistics Act No. 13 of 2018 should begin with awareness creation among stakeholders (internal and external) about the Act – its purpose, key provisions, and for internal stakeholders, its relationship with other legal frameworks e.g. SADC Protocol on Statistics, the African Charter on Statistics and the UN Fundamental Principles of Official Statistics. To achieve this strategic objective, the following initiatives will be undertaken:

SO 2.2    Operationalise the Statistics Act No. 13 of 2018

To achieve this strategic objective, the following initiatives will be undertaken:

SO 2.3    Improve statistical coordination

Statistical coordination is such an important strategic issue to the functioning of the NSS that it is explicitly provided for in the Statistics Act No. 13 of 2018,. The title of the Statistic Bill states, “An Act to establish an integrated National Statistical System; provide for mechanisms for coordination, collection, management and dissemination of statistics …..”. Statistical coordination is essential to achieve mutual support and synergy among data producers, avoid duplication of effort and production of conflicting data, rationalize use of available resources for statistics and achieve data quality. It is, therefore, critical that the NSS is well-coordinated. This objective will be realized by undertaking the following initiatives:

SO 2.4:  Undertake change management

Breakthroughs in performance require that major changes be undertaken as drivers of strategic success. Change is always underway with all organizational systems and processes intrinsically subject to constant review caused by the ever-present social, economic and technological trends in society. It is, therefore, very important that changes are introduced and well-managed so that individuals can see change as an opportunity to enrich their organizations, individual careers and personal lives. While change is an opportunity, it is usually viewed as a threat and is always resisted.  Indeed “resistance to change can be considered the single greatest threat to successful strategy implementation” (Kaplan and Norton, 1996). This makes change management an important issue in the discourse on strategic planning.

Goal 3:  Efficient and effective data processes

This goal is about achieving data systems that are efficient and effective, capable of producing quality data and also ensuring cost-effectiveness of data production processes. It is about improvement of existing data processes, investing in new processes and innovating to create value (new value-added products and services) that will meet the emerging data needs.

The goal will be achieved through the following SOs:

3. 3.1 Organisational strengthening

This strategic objective will be about building competent organizations able to address disparate data challenges in sectors. To achieve this, the following initiatives will be undertaken:

SO 3.2   Improve statistical infrastructure

One of the weaknesses of African NSSs is that the infrastructure for statistical production and management is generally weak, inadequate and vulnerable. This is because most resources for statistics are dedicated to data production with fewer resources directed towards infrastructure and capacity development. This objective will be met by undertaking the following initiatives aimed to improve infrastructure for statistics targeting the following for improvement:

• application of international standards and classifications, and
• field organisation.

SO 3.3:  Improve IT infrastructure          

The objective for using information technology (IT) is to maximize benefits that accrue to its application including strengthening work processes (e.g. speeding up data collection and processing), facilitating complex data analyses and standardizing work processes (e.g. publications). IT can therefore not be any viewed as just a set of programmes and tools but rather as an enabler that can effectively and efficiently alter the way work is done thus shrinking the effects of time and space. It is, therefore, important that IT resources are harnessed to improve statistical production and management. IT resources include IT equipment (hardware) and software, networks, Internet, databases, Geographic Information System (GIS) and IT standards and policies. However, this will not be possible until IT infrastructure is put in place. Under this strategic objective, the IT infrastructure will be built and/or enhanced to make statistical production across the NSS more effective and efficient.

SO3.4:   Improve data production processes

This strategic objective is about ensuring that good quality data are produced on time and within the budget. This will be done by strengthening existing data processes, investing in new data processes and bringing on board new data sources. It will be achieved through the following initiatives:

SO 3.5:   Build statistical capacity across the National Statistical System

As mentioned earlier, Zambia has a low statistical capacity as measured by the World Bank Statistical Capacity Indicator. The indicator shows that statistical capacity for the country as a whole is low and has been declining (downward trend) since 2004.  Under the NSDS2, a robust statistical capacity will be built not only to supply needed statistics, on a continuing basis and using best statistical practices but capacity will also be built at different levels and across the data value chain.  The following three initiatives will be undertaken to reverse declining statistical capacity and lay a firmer foundation for sustainable statistical capacity:

Goal 4:  Better funding for statistics

Awareness about the importance of statistics has not been matched by adequate funding commitments to statistics by both government and cooperating partners.  And yet low and unpredictable funding will negatively affect data supply at a time when demand for data has increased astronomically. So this goal aims at achieving better funding for statistics through the following strategic objectives:

SO 4.1:   More and better funding for statistics

Statistical development does not simply need more funding across the NSS (ZamStats and MDAs), it also needs better funding in terms of predictability of funds.  It has been observed that not all budgeted amounts by government are disbursed or disbursed in time to enable time-bound statistical activities to be undertaken. Funding by cooperating partners has largely been piecemeal and uncoordinated.

SO 4.1:   Make better use of funding for statistics

It is important that once funds are secured for statistical production and other operations, they are well utilized. This will be done through the following initiatives: