Editor’s note: Today’s post highlights five takeaways from our session at the first ever Google Cloud Public Sector Summit. To watch the full session, check out All the Right Moves: Prioritizing Investments in Technology.

Now more than ever, government agencies need to invest in digital services to fulfill their missions and better serve communities. Yet modernization isn’t a one-and-done approach; it’s a sustained effort, with multi-year implications, and requires careful consideration of how to integrate existing investments to optimize costs. Digital transformation requires coordination between different programs and agencies, including all of their many competing considerations. In short, maximizing technology investments requires careful planning, strategic thinking, and industry partners that can provide flexibility and security and meet agencies where they are. 

I sat down with Suzette Kent, former U.S. federal chief information officer, and Dominic Sale, assistant commissioner for Technology Transformation Services at the General Services Administration (GSA) for a conversation to unpack this important topic and discuss industry best practices. 

The panelists had five tips for government employees who are making technology purchasing decisions for their agency.

1.   Put the agency’s mission first.Avoid getting distracted by exciting new trends and focus on long-term goals that can impact which procurement strategies or funds could be used. The discussion started with how government agencies could cut through the noise about technology and prioritize which technology is best for their needs. Sale and Kent agreed that an agency should focus on its core mission outcomes and let its technology needs flow from that. Sale also emphasized the importance of having technology design respond to humans’ needs, which has historically been a challenge for government agencies.

For agencies to stay focused on their mission, final decisions about technology need to be made by the program manager who best understands each program’s mission. The government CIO’s role is to be the enabler for the technology and leverage it at the enterprise level, particularly when it comes to sharing infrastructure.  The takeaway: enable mission programs by empowering your teams and providing access to authorized, compliant, innovative data platforms that programs can move confidently and quickly with.

2.   Invest in interoperability. Agency employees often struggle to balance the need for a positive return on investment (ROI) with requirements for meeting mission objectives. While the panelists agreed that the total cost of ownership was important, they also emphasized taking an expanded view of ROI, including future-proofing and investing in functionality that may not realize its return for many years based on the initiative. Saving money isn’t particularly valuable if the solution doesn’t meet an agency’s needs. When choosing a technology partner, government employees should understand its long-term vision to ensure that the partner fits agency priorities. Partners’ technologies should also integrate seamlessly with existing systems so agencies don’t duplicate investment costs.

For example, Google Anthos extends Google Cloud services and engineering practices into an organization’s existing environment, establishing operational consistency across apps and modernization. With Anthos, agencies can simply and securely build and deploy applications anywhere, integrating cloud services across platforms. This allows them to enjoy a consistent DevOps experience for hybrid and multi-cloud environments and enables new innovation. Most importantly, this enables an enterprise data platform, one of the largest catalysts for mission transformation and applied AI.

3.   Take advantage of artificial intelligence (AI) benefits. Over the course of the pandemic, the rapid application of AI has improved government productivity, efficiency, and the ability to deliver critical new services to the public at scale. This has further cemented AI’s role as an essential government technology for the present and future. In fact, Nextgov reports that “46% of government IT specialists plan to use AI and machine learning (ML) for embedded systems in the near future.”

As we’ve seen over the course of the pandemic, government programs can start small with AI  pilots before moving into broad deployment. This can help agencies understand AI’s potential before moving to full production. People always supervise AI technologies, and the possibilities are endless. Google Cloud’s Contact Center AI (CCAI) has helped government agencies improve the customer experience, by allowing citizens to schedule vaccine appointments via a platform of their choice with up to 28 languages and dialects, and manage vaccine deployment. The U.S. Navy spends billions annually to fight rust and corrosion on its ships. Inspections of ships, aircraft and vehicles are a time-consuming and critical part of keeping the U.S. Navy at top performance so Google Cloud and Simple Technology Solutions (STS) rapidly built an AI-based corrosion-detection and analysis system. The system detected and analyzed corrosion on vessels with 90% accuracy and will eventually be used to automate inspections of vessels, aircraft, and vehicles—saving billions of dollars. Document AI helps a variety of government agencies scale their document processing, reducing the time it typically takes to process enormous amounts of data and related citizen claims.

Successful adoption of AI also depends on the quality of the data. Ultimately, agencies need high-quality enterprise data pipes so that employees and the community trust the system and public sector agencies. Sale described a GSA project that used AI bots to read legal contracts and look for particular phrases that would indicate a specific use case. Previously, an employee would have had to read through the contracts and search for the information. In this way, AI is saving the government both money and time.

4.   Creating better experiences for the public. Sale observed that, “trust is the government’s currency and profit motive.” And trust comes when the public can be served with the same modern tools and technology they’re used to – in real-time and with transparency in mind. For example, agencies can provide transparency in public-facing dashboards for programs and supply services that deliver information in real-time through solutions like CCAI.

Trust also requires that constituents feel that government agencies will keep their data safe and secure. The need for a globally secure infrastructure with systems that are up-to-date and designed with security at every level, underpinned by zero-trust enterprise-wide remains paramount – particularly after the series of recent cyberattacks targeting government IT infrastructure.

5.   Finding the right technology partner. Government leaders need technology partners who  provide a flexible and interoperable platform to integrate existing investments and maximize technical value. Historically, public sector agencies have largely been forced to adopt private clouds, which has reduced their access to richer features, and hindered their ability to adopt a full range of security and product capabilities. The right partner won’t require government leaders to compromise on functionality or service availability to achieve compliance. The right partner can harness the power of emerging technology to make it Government-ready and the true promise of cloud– the access and integration of open data– to make missions more powerful and impactful for the constituencies they serve.

Since the start of the COVID-19 pandemic, there’s been a rapid acceleration of digital transformation across the entire healthcare industry. Telehealth has become a more mainstream and safe way for patients and caregivers to connect. Machine learning modeling has helped speed up innovation and drug discovery. And new levels of integration and data portability have helped enable greater vaccine availability and equitable access to those who need it.

Data has been at the crux of this digital transformation — helping people stay healthy, accelerating life sciences research and delivering more personalized and equitable care. We recently unveiled partial results from our research with The Harris Poll, which revealed that nearly all physicians (95%) believe increased data interoperability will ultimately help improve patient outcomes. Today, we’re unveiling the second part of that research. 

In February 2020, we commissioned The Harris Poll to survey 300 physicians in the U.S. about their biggest pain points — this was just before the COVID-19 pandemic strained the entire healthcare system and made us all hyper-aware of the risks we take in going to the hospital. In June 2021, we followed-up with those same questions and more. What it unveiled was just how much COVID-19 reshaped technology’s role in the healthcare field and how it’s changing day-to-day operations for physicians. 

Here are some of the highlights: 

Healthcare organizations accelerated technological upgrades over the course of the pandemic. After a year shaped primarily by the COVID-19 pandemic, use of telehealth saw substantial YOY growth, jumping nearly threefold from 32% in February 2020 to 90% this year. Forty-five percent of physicians say the COVID-19 pandemic accelerated the pace of their organization’s adoption of technology. In fact, more than 3 in 5 physicians (62%) say the pandemic has forced their healthcare organization to make technology upgrades that normally would have taken years. For example, 48% of physicians would like to have access to telehealth capabilities in the next five years. Before the COVID-19 pandemic, about half of physicians (53%) say their healthcare organization’s approach to the adoption of technology would best be described as “neutral” (i.e., willing to try new technologies only if they have been in the market for awhile or others have tried and recommended them). 

Despite the technological leaps this year, most physicians still believe the industry lags behind in technology adoption but recognize the opportunity for technological support and advancement. The majority of physicians don’t view the healthcare industry as a leader when it comes to digital adoption. More than half of physicians describe the healthcare industry as lagging behind the gaming (64%), telecommunications (56%), and financial services industries (53%). However, the healthcare industry is not seen to be trailing as much as it was last year behind retail (54% in 2020; 44% in 2021); hospitality and travel (53% in 2020; 43% in 2021); and the public sector (39% in 2020; 26% in 2021). 

Better interoperability alleviates physician burnout, improves health outcomes and speeds up diagnoses. The majority of physicians say increased data interoperability will cut the time to diagnosis for patients significantly (86%) and will ultimately help improve patient outcomes (95%.) In addition to better patient experiences and outcomes, more than half of physicians (54%) believe increased access to data via technology has had a positive impact on their healthcare organization overall. A majority believe that technology can alleviate the likelihood of physician “burn-out” (57%) and that efficient tools help decrease friction and stress (84%). And, as a result, 6 in 10 physicians say access to better technology and clinical data systems would allow them to have better work/life balance (60%) and that better access to/more complete patient data would reduce administrative burdens (61%). It is therefore not surprising that nearly 9 in 10 physicians (89%) say they are increasingly looking for ways to bring together all patient data into a single place for a more complete view of health. 

Familiarity with new Department of Health and Human Services (DHHS) interoperability rules grows, and many physicians are in favor. Most physicians (74%) say they have at least heard of the new DHHS rules (launched in 2019) to improve the interoperability of electronic health information. This is a clear rise from 2020 (64%), but deeper knowledge is fairly low. Only 30% of physicians say they are somewhat or very familiar with the new rules (though, again, this is a rise from 2020, when only 18% said they were very/somewhat familiar). Similar to in 2020, among those who have heard of the new rules, nearly half are in favor (48% in 2021; 45% in 2020) but a similar proportion remain unsure (46% in 2021; 50% in 2020). And like in 2020, by far the top potential benefit of the rules is thought to be forcing EHRs to be more interoperable with other systems (70%).

Google was founded on the idea that bringing more information to more people improves lives on a vast scale. In healthcare, that means creating tools and solutions that make data available in real time to help streamline operations and improve quality of care and patient outcomes. For example, our recently announced Healthcare Data Engine makes it easier for healthcare and life sciences leaders to make smart real-time decisions through clinical, operational, & groundbreaking scientific insights. To find out more about the Healthcare Data Engine, click here.

^{Survey methodology: The 2021 survey was conducted online within the United States by The Harris Poll on behalf of Google Cloud from June 9 – 29, 2021 among 303 physicians who specialize in Family Practice, General Practice, or Internal Medicine, who treat patients, and are duly licensed in the state they practice. The 2020 survey was conducted from February 18 – 25, 2020 among 300 physicians who specialize in Family Practice, General Practice, or Internal Medicine, who treat patients, and are duly licensed in the state they practice. Physicians practicing in Vermont were excluded from the research. This online survey is not based on a probability sample and therefore no estimate of theoretical sampling error can be calculated. For complete survey methodology, including weighting variables and subgroup sample sizes, please contact press@google.com.}

For a business to succeed in the long term, it needs to learn not just to adapt to inevitable change, but to harness it. South Africa-based PPS has been an insurance company since 1941 and today is the biggest mutual insurance provider in the country.

As a mutual company, PPS is owned by more than 200,000 members, making them shareholders. In recent years, PPS and other companies like it have been affected by a number of external factors.

“For one thing, technology platforms have brought in a new gig economy that has all kinds of implications for insurance,” says Avsharn Bachoo, CTO at PPS. “What we’ve been seeing is basically a disruption of the South African insurance industry. We chose to see that as an opportunity.”

“Our servers were at the end of their life cycle and we had to decide whether to refresh them or switch completely. To embrace the world of AI and machine learning effectively, we knew we needed a cloud-based infrastructure. We’ve found the answer in Google Cloud Platform.”

—Avsharn Bachoo, CTO, PPS

In early 2018, faced with an uncertain economic environment that was squeezing growth and profitability, PPS decided to transform itself from a traditional broker-based business into a digital insurance provider. A key pillar of this new strategy was to overhaul the company’s technology infrastructure. To turn the strategy into reality, Avsharn and his team chose Google Cloud Platform (GCP).

“Our servers were at the end of their life cycle and we had to decide whether to refresh them or switch completely,” says Avsharn. “To embrace the world of AI and machine learning (ML) effectively, we knew we needed a cloud-based infrastructure. We’ve found the answer in Google Cloud Platform.”

Power, speed, flexibility with Google Cloud Platform

Previously, PPS maintained an on-premises IT infrastructure, which worked for its traditional business but was unsuited for its new way of working. In early 2018, the company started working on new products for its members but this required large amounts of compute power that proved prohibitively expensive with on-premises servers. Even existing products were starting to require more than the infrastructure could deliver. Aging equipment meant that it’s testing and quality assurance environments bore little resemblance to the actual production environment.

“We had no pre-production environments at all,” says Avsharn, resulting in more work for developers after products had been released. Meanwhile, the capital required to buy and configure more servers for new projects meant fewer resources available for innovation, and left the company less able to react to changes in the market. PPS knew it had to find a cloud-based alternative.

Shortly after devising a new digital strategy, PPS engineers attended a training session on cloud infrastructure given by leading South African Google Cloud Partner Siatik. Impressed with the presentation, PPS engaged Siatik to help run a proof of concept for a cloud-based infrastructure, running on GCP. With on-site engineers and constant communication, Siatik formed a very close working relationship with PPS. “The team at Siatik was exemplary,” recalls Avsharn. “They were well-organized, with cutting-edge technical acumen and very creative solutions to our problems. They were real game-changers.”

“We wanted the platform to retrain its models in response to new data and improve its recommendations with more information. Normally this would be a manual process but Google Cloud ML Engine lets the models do this automatically.”

—Kimoon Kim, Lead Solution Architect and Data Engineer, Siatik

The proof of concept was successful, with GCP outperforming the existing infrastructure in terms of how it handled compute demands, databases, and storage.

“It’s the speed of GCP that really impresses us,” says Avsharn. PPS saw that GCP wasn’t just an opportunity to migrate its existing infrastructure to the cloud. With Siatik’s help, it redesigned its monolithic core architecture to one based around microservices using Google Kubernetes Engine (GKE). For data processing and storage, Cloud Dataflow and Cloud Datastore proved invaluable, while Stackdriver helped the IT team stay on top of logging and monitoring the system.

“Google Cloud makes migrations very easy,” says Brett St. Clair, CEO at Siatik. “It takes care of all the hard work with configurations and replications, so when we switch the machines on, everything is ready and working.”

The ease with which PPS migrated to GCP means that it can now tackle strategic goals much more quickly than before. The most ambitious of these is an AI-powered product recommendation platform. Information is collected from customers who opt in at a defined point in their journey, this database is queried using BigQuery, and the information is fed into the platform. The AI model then calculates the most appropriate products for each member, according to their personal history.

“Most of the product recommendation engines out there are based on clustering, where you’re offered products based on your peer groups,” explains Avsharn. “For the first time, we can make recommendations to members based on their individual preferences and historical behavior. That’s really powerful for us.”

Siatik helped PPS use TensorFlow and Cloud Machine Learning Engine to build the AI platform. For the engineers, these easy-to-use tools helped speed up the process considerably, allowing them to host the models locally without any fuss. Previously, it took one to three months to manually build the model and match an offer to a customer. With the AI platform, a match takes just a few minutes. Cloud ML Engine, in particular, helped the platform adapt to new information on the fly and easily make adjustments to its hyperparameters, that is, preset variables which define the model-training process.

“We wanted the platform to retrain its models in response to new data and improve its recommendations with more information,” says Kimoon Kim, Lead Solution Architect and Data Engineer at Siatik. “Normally this would be a manual process but Google Cloud ML Engine lets the models do this automatically.”

“Google Cloud helped us cancel out a lot of the noise around machine learning and AI. We don’t have to build new complicated algorithms or hire huge teams of data scientists to benefit. We just bring our data and use the right tools to focus on what’s really important.”

—Avsharn Bachoo, CTO, PPS

Harnessing artificial intelligence for real-world results

PPS deployed its new AI recommendation platform in December, 2018. Just a couple of months later, its impact was clear. “In around eight weeks, we saw a 5 percent growth in sales,” says Avsharn. “It’s been a direct result of building our recommendation platform with Google Cloud. We can offer the right products to the right members.”

For developers and engineers at PPS, working with Google Cloud gives them access to high performance technology and automation options with GKE. As a result, the infrastructure runs 70 percent faster than before with fewer cores and less memory. Developers can also work in mature testing environments, and for the first time, are able to build pre-production environments, leading to better quality products. More strategically, moving to a serverless, cloud-based infrastructure has helped PPS take control of its budget, moving away from intermittent, large capital spends to more manageable, project-to-project flows of operational expenditure. The company expects to see savings of around 50 percent, or $695,000.

“We have a lot more flexibility with our resources thanks to Google Cloud,” says Avsharn. “When we have a new idea, we don’t have to outlay new capital such as servers before we can even start working on it. We just spin up instances when we want and spin them back down when we’re done.”

With the AI platform deployed and working well, PPS is already looking at ways to improve it, including real-time updates and further automation. Soon, the company will integrate the platform with more sales campaigns for more effective targeting to boost sales even further. Meanwhile, it’s also experimenting with machine learning to spot patterns in data at scale for fraud analytics and risk assessment.

For PPS, working with Google Cloud has helped it transform quickly and effectively from disrupted to disruptor. The company is now looking to gain the same transformative effects by implementing G Suite for increased productivity and collaboration.

“Google Cloud helped us cancel out a lot of the noise around machine learning and AI,” says Avsharn. “We don’t have to build new complicated algorithms or hire huge teams of data scientists to benefit. We just bring our data and use the right tools to focus on what’s really important.”

Organizations are currently modernizing their businesses in order to meet the increasing complexity of today’s business landscape. In effect, business leaders must evaluate the best way to mitigate the challenges which plague their cloud operations, all while meeting customers’ growing expectations around digital experience (DX) through agility, automation, and proactive incident avoidance. 

In this commissioned study, “Modernize With AIOps To Maximize Your Impact”, Forrester Consulting surveyed organizations worldwide to better understand how they’re approaching artificial intelligence for IT operations (AIOps) in their cloud environments, and what kind of benefits they’re seeing. 

Within this July 2021 study, you’ll see that AIOps systems and principles are here to help. It covers how AIOps increases efficiency and productivity across day-to-day operations, and how businesses are taking note. In fact, 91% of respondents have implemented AIOps to address at least one cloud operations issue, and expansion is set to skyrocket. Those that wait to act, risk losing out on the efficacy of their cloud investment and falling behind their more efficient competitors.

As you can see in the image above, there is a plethora of great information in this complimentary study. So, if you’re looking to enhance your cloud operations and/or adopt AIOps within your organization, be sure to download this free study today.

It’s incredible to see how startups across industries are using cloud technology to help address some of our most pressing, important, and life-altering challenges. Startups and high-growth technology companies are choosing Google Cloud and using technologies like Google Compute Engine (GCE), BigQuery, Looker, Firebase and more to help businesses reduce energy consumption, build more inclusive and sustainable workforces, and in the case of high-growth biotech company Freenome, are creating diagnostic tests that will help detect life-threatening diseases like cancer in the earliest, most-treatable stages.

Freenome is driven by its mission to develop high-quality diagnostic tests to detect and treat diseases like cancer from a simple blood draw. In 2022, Freenome significantly accelerated its growth on Google Cloud to support the business as it began the clinical trials of its diagnostic blood testing technology. Today, the high-growth biotech is further deepening its partnership with Google Cloud in order to support its rapid growth and scale as it concludes clinical validation, takes its tests through FDA approvals, and prepares to bring its product to market.

When detected early, data shows that there is a higher probability for cancer to be beaten, yet not everyone has access to early detection measures. By creating a way to detect the earliest warning signs of cancer with a standard blood test, Freenome is helping bridge the gap between accessibility and early cancer detection. To do this, Freenome built a multiomics platform capable of analyzing and detecting disease-associated patterns in the blood using molecular biology, advanced biology, and machine learning. By applying machine learning models trained to scan for tumor and non-tumor biomarkers to the diagnostic process, Freenome’s tests can identify suspicious molecular patterns in a patient’s blood, which will ultimately help more people detect cancer at its earliest stages in the body.

The amount of molecular data extracted from blood samples can quickly add up to hundreds of terabytes worth of data, so it was clear early on that Freenome would need infrastructure that could support the fast sequencing and processing of large amounts of data. In addition, Freenome’s collaboration technology needed to provide flexibility, security, and proper identity management safeguards, given the nature of its business. To meet these needs and support the company’s plans for growth and innovation, Freenome selected Google Cloud as its primary cloud provider, utilizing services like Google Cloud Storage and Google Kubernetes Engine (GKE), along with Google Workspace as its collaboration platform.

Using Cloud Storage alongside GKE gives Freenome the computing power needed to sequence and process mass amounts of blood sample data with high-performance, speed, and at scale. Cloud Storage also makes it easy for Freenome to leverage other Google Cloud capabilities like BigQuery for analytics with built-in query acceleration. Additionally, the built-in cluster management capabilities of GKE make it easy for Freenome’s engineering and IT teams to manage and deploy new workflows to the high-performance computing clusters used by the machine learning components of its multiomics platform to speed up cancer detection. Freenome also uses Google Cloud technologies like Artifact Registry and Cloud SQL, which help the company ensure a managed and secure software supply chain of containers and other artifacts.

Today, as a part of its expanded partnership with Google Cloud, Freenome is significantly increasing its use of Cloud Storage and GKE as it works to complete the clinical trials related to its diagnostic test. By expanding its use of GKE and Cloud Storage, Freenome will be equipped to perform the compute-intensive analytical work required for running its research workflow and diagnostic classifier algorithms. In addition, Freenome teams will continue leveraging Google Workspace products across the company so they can securely manage and collaborate on business-critical content.

Besides using Cloud Storage, GKE, and Google Workspace to support the company’s rapid growth, Freenome plans to leverage Google Cloud technologies like BigQuery to support the research and development of new products. The company is also testing security technologies like BeyondCorp to keep its growing workforce secure and productive at scale.

As the future of disease detection continues to evolve, Google Cloud is proud to support the growth of innovative companies like Freenome with infrastructure and cloud technologies so they can help empower more people with early disease detection solutions and ultimately, change more lives for the better.