Utilise data capabilities to meet Sustainable Development Goals
Advanced data analysis is key to tracking progress on Sustainable Development Goals. However, government bodies in the GCC often lack these capabilities, while third-party sources pose reliability challenges, according to a new report by management consultancy Oliver Wyman.
The 2030 deadline for SDG implementation is approaching, and data is key to tracking progress to date and in the future. 17 goals for a better and more sustainable future are underpinned with 169 concrete targets – all of which can be traced using 231 quantitative performance indicators.
Collecting this data in real time is a complex task – one for which governments and national statistics organisations in the GCC region are ill-equipped. “In contrast with many European countries that have engaged in sustainability since the 1990s, the trend in the Gulf is relatively new,” noted Seif Sammakieh, a partner at Oliver Wyman in Saudi Arabia.
Globally, much of SDG data modeling is outsourced to third-party data professionals that are better suited to high complexity. In the GCC this is no different, although this approach is not without its drawbacks.
“Region-wide, third-party data sources have come to be viewed as essential in tracking SDG progress on a sufficiently granular level, alongside traditional data sources typically collected by NSOs. This process has proven to be highly problematic due to the lack of alignment to national strategies and the unreliability of the data providers among others,” said Sammakieh.
In the backdrop, administrative, technical and legal barriers persist, while a lack of clear data protection guidelines in the GCC adds to the challenge. In its report, Oliver Wyman presents five steps to meet the potential of a multi-stakeholder data management approach – also termed ‘data disaggregation’.
Steps to data disaggregation
Step one is to ‘prioritise goals and define indicators.’ While all 17 SDGs are universal in their importance, individual countries have to focus on specific goals based on their unique geographic, climatic or socio-economic conditions. In GCC, for instance, gender equality (SDG 5), and water conservation and sanitation (SDG6) hold particular weight in the coming decade.
As a result, countries have to set their own performance indicators – in addition to the 231 laid out by the UN. Setting these data points and priorities is the first step. The more points there are, the higher the need for localised third-party data production and collection.
Once these points are clear, step two is to ‘assess potential data sources’ that can track these indicators. To ensure that data sources align with government needs and priorities, the report suggests several screening metrics. Frequency of data generation; resilience; willingness to cooperate; range of data points; methodology & transparency; and incentive structures should all be taken into account when choosing a third-party data source.
Step three is to ‘assess data quality.’ Data sent in by the selected party must be vetted by the NSOs – checked for quality and accuracy, screened against data laws, and returned with feedback incase it doesn’t meet expectations. On the back-end, this requires considerable investments in tech and legal capabilities.
At the end of this process, NSOs are in a position to ‘integrate data’ from the third-party with administrative data – on health, education, environment, etc – to produce the final picture. “Data integration requires a technical infrastructure that can seamlessly interconnect with multiple inputs, as well as data workflows that ensure quality and standardization while also covering the legal aspects,” said Sammakieh.
Building capacity
Following these steps should ensure a better output on SDG metrics, but such a comprehensive approach is not easy. Indeed, it’ll require targeted investments from governments in the region.
“In order for GCC countries to implement and sustain the mitigation strategies, regional governments must invest in right-skilling the workforce to ensure capabilities meet the rapidly evolving requirements for data management and upgrade and streamline their capacity allowing for smooth data processing and dissemination,” concluded Sammakieh.