SAS Vice President ASEAN Remco den Heijer says public sector leaders need to create a paradigm that engages citizens in new ways if we are to be prepared for future crises.
By Remco den Heijer
The pandemic has brought about changes to the way we live, work and play – from healthcare workers taking on additional roles, to the new normal of office staff working from home. It is a time when every step or misstep of civil servants is magnified – when they adapt and pivot to serve citizens or lapse to reveal a lack of resources or planning. Through analytical insights, government agencies can go beyond responding to emergencies, and can ensure that policy planning and execution of policies result in positive outcomes for citizens.
As we emerge from the ruins of the pandemic and assess its unfolding impact, analytics can help in the recovery. Analytics can inform strategy and policies through providing a holistic understanding of our environment and circumstances through situational awareness.
Governments will need a strategic framework to navigate the country out of this crisis. A three-phased framework, when applied to government agency decisions, can guide leaders in making critical decisions.
In the initial stages of a crisis, when governments are responding to it, analytics can provide insights for situational awareness to understand the potential threats and trajectory of a given situation. Decisions have to be made quickly based on rapidly evolving data, and analytics can help in refining situational awareness through assessing the situation, visualizing it and charting trends to predict future possibilities. SAS provides an example of visual analytics showing epidemiological, location and trend analyses as well, spread over time of the pandemic.
Analytics in medical resource optimization predicts the need for limited resources such as medical equipment and infrastructure. Public health agencies can use specialized analytics and scenario analysis tools to predict for situations to help governments build capacity before it is needed. Analytics can also be used in manual contact tracing efforts to better understand who should be tested, where the virus is spreading, which communities are at greatest risk and identify missing or unexpected linkages in the community.
In India, SAS worked with the Odisha state government to develop analytic models predicting the pandemic’s peak periods for infections and deaths at district levels, and forecasting covid-19 hotspots and containment areas. It was used to estimate quarantine bed capacity and intensive care unit (ICU) infrastructure, considering the immigrant population.
Insights from analytical modelling for best and worse scenarios have been used to map the regions that would first be reopened for movement, to mitigate the virus spread. With an average of 40,000 hits per day, the dashboard has played a large part in Odisha’s ranking of third among India’s states in Covid data reporting.
As communities begin to recover, analytics can support public sector agency efforts. Countries, states, and local government agencies are currently targeting their support, via direct stimulus payments, at individuals and businesses. These agencies can preserve their limited funding for those in need, by using analytics to identify which entities need aid the most, and to detect fraudulent activities.
One example is New Zealand’s Ministry of Social Development, which developed an analytics data model to estimate risks of welfare dependency among their most vulnerable group consisting of teen parents and young people unable to live with their families, predicting the probability of this population moving on to receive adult benefits.
With the insights, they were offered targeted services intended to reduce their long-term dependency, including mentoring, budgeting skills, education and training. The strategy worked, as findings revealed that those who received the extra investment moved onto an adult benefit at the lowest level since 2008, with employment rising 9.3 percent in 2013.
In the recovery phase, public sector agencies must evaluate their agency situation: they must assess a likely drop in revenues and prioritize activities and projects within limited funding. The decision-making process can be improved by applying analytics to gain evidence-based insights on projects that will have the most impact over specified periods of time.
As we emerge from the pandemic, the use of analytics will help our government agencies reimagine approaches to a changing landscape. The pandemic has accelerated digital transformation, driving online purchases of food as well as services. Government agencies are forced to rethink the way they interact with and service the public as well as the long-term impact on citizen behaviour. Transformation or reimagination is crucial.
Public sector leaders can use analytics to unlock the vast potential of the data within their agency. A sound data governance framework along with effective use of analytics can enable access to data within the organization as well as between agencies for inter-agency collaboration to guide decision making. With this, leaders are empowered to make informed and innovative decisions that will improve outcomes, ensure access to services and programs, and support good stewardship of money and the public trust.
Advanced analytics like artificial intelligence, machine learning and augmented analytics can improve the speed and volume of analytics performance to enhance productivity and efficiency, enabling greater predictive accuracy. As we emerge from the pandemic into a different world, government leaders need to rethink a new paradigm and approach. We should leverage this pandemic to use analytics to transform the current approach of our government as well as to engage citizens in new ways, to equip for future crises.
(Ed. Featured image by Photographer Ian Beckley.)