Every day, professionals in the public sector make complex policy decisions that affect citizens, such as improving service delivery, allocating budget, and responding to crises. Increasingly, they use insights from massive amounts of data—collected initially by governments for reporting purposes—to make strategic decisions.

Governments usually collect a large amount of administrative data, mostly for routine reporting and compliance purposes. Many countries have recently begun finding more advanced and useful ways of leveraging these data sets to allocate resources better, measure success, and improve government-administered programs’ efficiency.

A recent study shows that there were 1000% more data in 2006 than there was in 1999. Another report finds that online data has increased around 1500% since 2017. The actual numbers are mainly beyond human imagination, and it remains unclear who owns all the data. With the digital revolution, we can gather information on an incredible number of natural phenomena and human actions. Yet, we do not fully understand all the complexities of what we are sensing or how machines analyze them.

Data Analyzing challenges. 

Governments have come up against a handful of significant but not insurmountable challenges to use better data for decision-making.

The top four challenges are:

• Expert Staffing. To use data effectively, governments need staff members to understand the technical skills to manage and analyze data, public policy, and the communication skills to present findings to a wide range of audiences. These workers are in short supply, and governments cannot usually offer salaries competitive with the private sector.
• Data Accessibility. Outdated technology can make it difficult for governments to extract their data in a usable format. And when contractors control computer systems, states may not even own their data or lack the technical expertise to use it.
• Data Quality. Data sets are useful when they are accurate and reliable. When data points are inaccurate, missing, or poorly defined, the information is less useful.
• Data Sharing. Data sets are most valuable when shared across programs or agencies and combined with other data sets to get new insights. However, many agencies face uncertainty about how to comply with privacy laws or share data while keeping it secure, limiting the insights gleaned from the data.

Five critical actions for strategically using data to make better decisions

Regardless of a governments’ current data capabilities, they can take five concrete steps to optimize the value of data at their disposal and move toward using data to make better decisions.

1. Plan by setting up guiding goals and structures. By planning, the public sector can significantly offer a better service since the governments’ effort to manage and use their data can help allocate resources. Three strategies that help a government effectively plan are: writing a formal data strategy, developing data governance structures, taking stock of systems, and performing an inventory of current data sets.
2. Build the jurisdiction’s capacity to use data effectively. Adequate staff who have skills in data analysis and appropriate funding can strengthen a government’s success in efficiently harnessing its data’s power.
3. Ensure that quality data are accessible by stakeholders. Before staff can efficiently use data, they must be able to access it. To do that, the public sector should improve data quality and accessibility by establishing data-sharing protocols and agreements among offices within a department, across other offices within an agency, or externally with other government agencies or stakeholders.
4. Analyze data to obtain meaningful insights. If done well, extracting insights from data can change the way governments make decisions.
5. Sustain support for continued data efforts. Once a government invests resources into building data-driven systems, efforts to gain leaders’ commitment and enact policies to ensure the initiative are equally important.

Today’s “extraordinary” will soon become routine in developed countries.

The journey toward data-driven resource allocation needs political leadership, a commitment to sustained technological progress, and a willingness to measure and report success transparently. Done right, it can dramatically boost performance.

We have seen several pioneering government organizations achieve significant results through data-driven initiatives. For now, it is still the exception rather than the rule in governments. However, data analytics’s adoption is likely to increase rapidly. It is reasonable to expect that most organizations will report key performance indicators in near-real-time via transparency portals.

Data-driven decision making is poised to follow the pattern of other innovations in governments. Mission-driven analytics have the potential to help governments to do more with limited resources. The technology has advanced to the point at which data can be gathered, collected, and analyzed effectively. Adding data to an organization’s mission may soon become commonplace. More and more leaders will create a data-driven culture that promotes governments’ missions and public purpose fulfillment.