Building cloud into your data strategy delivers higher efficiency

Presently, every government agency has to take a hard look at their data capabilities and decide whether their current infrastructure supports their workflow. For many, it doesn't. Most data systems are developed with a strict set of parameters in mind before implementation, which can limit flexibility and long-term use. Particularly during a crisis, flexible “living systems” offer tremendous advantages as they’re able to change capacity rapidly. Building living data systems with the cloud in mind allows organizations to respond to a changing world with confidence.

Last summer, the Government Business Council conducted a survey of government employees to understand the impacts of data efficiency on government operations. The report Built to Last: A Survey on Organizational Data Efficiency in Times of Crisis offers key insights into organizational efficacy and whether organizations can adapt to a crisis at speed. It also highlights differences between traditional data systems and living data systems. 

Data needs to be readily available

When the pandemic first hit, many agencies needed to create or transition their systems to allow employees to work remotely. This change tested the limits of existing data systems. Even after finding a cloud service provider, agencies encountered the challenges of migrating their data to the cloud. 

Government organizations had decades of data stored in paper records. Most have been working to transfer these records to a digital format, but the process has been slow. They are also faced with collecting sizable amounts of data in real time from their ongoing services,  which involves interfacing with the public, external vendors, or third-party institutions. 

Building the cloud into a flexible data system can solve both issues. Old records can be digitized and given an easy-to-access home for those who need them. Incoming data, both internal and external, can be made accessible as well. Migrating data to the cloud also doubles as a way to create backups of raw data, adding an extra layer of security. Most importantly, building in the cloud unlocked the capacity to scale when demand rises. 

Data should be updated in real-time

One of the key takeaways from the Government Business Council report is the fact that agencies are better able to adapt at speed when data efficiencies are higher. 74% of organizations with pandemic related functions reported a moderate to severe impact to their jobs at the onset of the pandemic. Of those organizations, the ones reporting their data efficiency as “very good” have largely already recovered. That adaptability directly affects an agency’s ability to make informed decisions during a time of a crisis.

Having a real-time data solution in place lets agencies make near real-time decisions. A great example of this from early in the pandemic is vaccine distribution. Google Cloud supported multiple states, across the U.S., including Arizona and the Commonwealth of Virginia in distributing vaccines efficiently and at scale. Data systems that gathered real-time patient data made a difference in the number of vaccines distributed. Knowing population data and patient risk factors enabled quick and effective decision-making.

A global pandemic is far from the only crisis that needs effective data analytics. Natural disasters, food deserts, public health issues, and more can all be handled more efficiently by having real-time data at hand. Effective data analytics systems are the digital equal of “having your ear to the ground” in each community. They provide valuable insights into what people  need.

Data needs to be accessible and easy to use

Making data easy to work with and understand sets phenomenal data systems apart from functional ones. Having data in the cloud is a great first step, but agencies need to be able to easily access and quickly use the data to accomplish their goals. This is where traditional data systems fail most often. Traditional IT systems and data strategies are designed for a specific purpose, usually identified before development and implementation begin. That means that when the data living in those systems needs to be used differently, adapting to new requirements can be difficult. 

Data can often feel "locked" in traditional systems; the data is there, but there's no way to get to it or work with it in a way that meets the needs of a crisis. Flexible data systems address this by allowing for greater accessibility. Google Cloud, for example, has customizable tools, such as Contact Center AI and Document AI, which let agencies work with data in ever-changing ways. This also produces greater data transparency since data sets can be worked with and accessed more easily.

Governments need to respond to the changing needs of their constituents in emergencies. While traditional data systems can handle slowly shifting demands on the system, they do not serve agencies well in a crisis. When urgency, accuracy, and accessibility all matter, flexible systems rise to the challenge. The pandemic has pushed agencies to adapt in real time, and many have realized they need a system that adapts with them.

Google Cloud has a suite of tools to create integrated data ecosystems. These ecosystems can scale with increasing demand, meet dynamic development needs, and adapt to a changing landscape. Data-first decision-making is a core tenet of "living data systems." Google Cloud data systems have handled everything from administering vaccines to detecting fraud. In each of these applications, a core tenet of data-first decision making was implemented at scale. 

For more insights on how flexible data systems help the public sector, download the full report “Built to Last: A Survey on Organizational Data Efficiency in Times of Crisis.”