Quality data has often been overlooked by decision makers as something trivial, too tedious and time consuming for their necessary attention. Often, the notion of data and its usefulness is undermined, resulting in an ad hoc inefficient use of resources as well as poorly implemented social development interventions and policies. Albeit, often data that is presented is not simple to understand and is presented in a complex manner contributing to the lack in enthusiasm in interpreting and using it. This has given rise to the increase usage of infographics which depict accurate, simplified data that is easy to remember, yet due to the jadedness of data and its meaning, importance and relevance, insufficient attention has been given to mandate the collection of useful data.
Decision-makers across the world need to base their decisions on information from reliable sources. This is imperative to evidenced based decision making through which relevant, implementable and impactful policies and developmental interventions can arise. They need to learn from the best evidence based knowledge and experience available and they need to know what kinds of research and what type of data could help them make the right choices. Successfully implemented and impactful polices and developmental interventions hinge on appropriate and well-designed monitoring and evaluation frameworks which depend heavily on useful quality data. However, practical work in the development field across sectors has often demonstrated that either too much data is collected with little regard for the quality, or that data is missing, or that useless data is collected because monitoring and evaluation frameworks that clearly articulate what type of data is necessary and relevant is missing.
Why is data missing and the importance of collecting relevant data?
The missing link between research, practice and policy is data that is accurate, valid and reliable. In Africa, there is a large gap between the producers and consumers of knowledge, and research could have a greater impact on development policy than it has had to date. Researchers as “knowledge makers” struggle to understand the resistance to policy change despite clear and convincing evidence whilst policymakers as “knowledge consumers” lament the inability of many researchers to make their findings accessible and digestible in time for policy decisions (Jones, 2011: 7).” Furthermore, the politics surrounding access to information and permission to collect useful data negatively impacts the generation of useful research and subsequently current data. In other instances, slow bureaucratic processes and political bickering can further negatively impact the publication of data contributing to the absence of data to the general public. Additionally, fieldwork experience has highlighted the ignorance of monitoring and evaluation officers in understanding the importance of collecting, collating, analysing, interpreting and presenting user friendly data. Not only are records unkempt, but the nonchalant attitudes towards the value of data is disturbing.
Collecting relevant data is of paramount importance to sourcing the correct information regarding a socio-economic challenge from the beneficiary point of view. Developmental interventions are still heavily carried out with a top down approach with the target beneficiaries often complaining that what is given is not what is required to make the necessary changes the policy seeks to address. Before or during the policy design phase, it would make sense to carry out a situational analysis to understand the key target groups needs and priorities, the demographic factors and the capacity challenges of government, NGOs (non-governmental organisations) and CBOs (community based organisations) staff. There is sufficient evidence from my working experience in the development field that capacity is severely lacking in implementing the required policies hence, the collection of timely, useful and relevant data is frequently compromised. The diagram below illustrates an evidenced based policy pathway.
Source: Adapted from Bowen and Zwi, (2005)
The above pathway to evidence-based policy and practice involves five phases which are:
- sourcing the evidence,
- using the evidence,
- implementing the evidence,
- identifying implementation gaps and
- monitoring and evaluation
The policymaking context is exceedingly political and rapidly changing and depends on a variety of factors, inputs, and relationships. It is of paramount importance to ensure that monitoring and evaluation is part of the agenda setting of the policy to guarantee that useful, relevant and current data is collected. This will enable the assessment of the overall impact of the policy on the beneficiaries. Problem identification of the policy setting phase needs to be informed through research and a situational analysis- the situational analysis can enrich or negate the data of existing research and can necessitate the need of a national survey to update old or missing data. This process can further highlight the correct target group for the policy intervention and areas that are an urgent priority. Often a policy is drafted and only at the evaluation stage does it come to light that there is no useful data that can tell us what impact the policy had. It is only at this late stage that decision makers realise the need for accurate data.
Once the evidence is used to draft a policy discussion paper to make a case for the policy, there needs to be a discussion around what the data says and to ensure that the implementing partners of the policy have the capacity to implement the policy. In developing countries, often it is discovered that great polices are drafted however, there is limited capacity to implement it. Thus, in some countries, more structures are created wasting more financial resources rather than addressing the capacity constraints. From my work in the development field, a significant capacity constraint is work ethic coupled with the ignorance in understanding the job description of monitoring and evaluation officers when it comes to data collection, collation, analysis and presentation. In addition, the absence of understanding the importance of data by key management staff results in data collected in an ad hoc manner with no one being held accountable for the failure of missing data.
Once the policy is in place and is being implemented, monitoring needs to occur to collect data for ongoing activities and outputs and to inform management when the implementation diverges from the objectives of the policy. Monitoring further supports management when implementation of the policy itself has become futile enabling sufficient response time to address these issues bringing implementation back on track. An evaluation has to be conducted to assess what impact the policy had on the target beneficiaries and what areas worked well and what did not and what could be done to improve the policy design.
Important to note is that neither policy nor monitoring and evaluation can occur without useful quality data. It is data that presents a case for a policy or development intervention and it is data that describes how, when and why the policy or intervention worked or did not work and provides insights as to how to improve for the future. The value of data cannot be underestimated and the mandate to ensure accountability for quality and timely collection of data needs to be championed by managers. After all, without data we do not know what the reality is on the ground is and how to address the issues that will result in impactful and meaningful change in the lives of the beneficiaries of the policy or intervention.
 Jones, B. 2011. Linking Research to Policy: The African Development Bank as Knowledge Broker, Series N° 131, African Development Bank, Tunis, Tunisia.
 Bowen, S., & Zwi, A.B. 2005. Pathways to “evidence-informed” policy and practice: A framework for action. PLoS Med, 2(7): e166.