As CIO and acting CISO forDelta Dental of New Jersey and Connecticut, I’ve seen our dental insurance business — which is expanding to include vision insurance and other ancillary lines of coverage — evolve over the past few years to improve access to quality care and a better customer experience.
Insurance buyers have higher expectations now when it comes to digital services, and our 1.9 million customers want a seamless online experience where they can purchase, access, or modify their insurance coverage or personal information with ease.
All these changes have made our IT organization play a more significant and more strategic role in driving long-term business growth, and, as a result, we completely redefined how we manage our DevOps and Security processes. One of our top objectives as an engineering team was to ensure high-quality code. But we didn’t want this process to limit how quickly we released features.
We overcame this and many other challenges by unlocking new opportunities thanks in part to our migration toGoogle Cloud and the use ofDatadog on Google Cloud to monitor and optimize our environment.
Becoming a data-driven business
Our entire business has become very data-driven. We take log data from Datadog and other applications and push it intoBigQuery usingPub/Sub for our analytics initiatives. We also take third-party data (usually in JSON format) and quickly marry all our data with BigQuery.
This lets us capture a robust picture of how our users interact with our online features and quickly produce valuable insights 2X faster than in the past for stakeholders in marketing, underwriting, claims processing, sales, and customer service. When we previously used legacy on-premises infrastructure, data was batched overnight, and our teams looked at a snapshot of data from the previous day. In our new model, we deliver data at the frequency we choose. With Google Cloud, there are no engineering or capacity issues to consume data as quickly as possible.
With Datadog and Google Cloud, we’re quickly bringing data into our data lake and accelerating time to insights. Our data scientists are tapping into critical information and have data available on our platform within a week, thanks to how our data ingestion is streamlined. Before, it might have taken two, three, or even four weeks.
Unlocking greater value from data
Pushing our Datadog information into our analytics platform enhances our visibility into transaction volumes, types, and trends. For example, we have a website feature called Procedure Code Lookup that allows our dental providers to enter a procedure code for a patient and retrieve details on their available benefits.
Using Datadog, we noticed some patterns within the telemetry data in the logs for those transactions. That has led to engineering enhancements and proposed feature enhancements to improve the user experience and value of this service to our providers. Our business loves this because it has reduced the need for providers to call our call center and reduced inbound calls by a significant percentage. Our providers love this because they can get the information they need via self-service 24 hours a day.
Ensuring IT services reliability for better patient experiences
Our engineering and support teams want to know if something’s wrong before our employees or customers do. We used to rely on a mix of ad hoc data collection and system monitoring tools that made it hard to quickly identify the causes of issues because we didn’t have insight across the entire stack. Datadog provided us with enterprise observability where we could bring in all our logging data, aggregate it, and store it in a central place — then leverage that to get alerts and investigate issues that arise.
This was especially helpful since we recently migrated to a more microservices- and API-based architecture, and having logging and APM functionality that’s native to those capabilities has allowed us to have deeper reporting on the types of transactions that are happening across the organization.
We also recently started rolling out Datadog on an infrastructure level to understand local and remote network capacity performance.
Additionally, we developed our call center analytics application on Google Cloud. It usesCloud Functions andSpeech-to-Text for translation and sentiment analysis of voice recordings from our contact center. When one of our agents finishes a customer interaction, team leaders and management can use the software to analyze results and make necessary adjustments.
Now that we’ve moved to more of an agile DevOps model and have Datadog integrated with Google Cloud, we have seen an improvement in identifying and resolving any production-related issues before our customers or the business is aware. Our team uses the solution to identify problems earlier in the process and improve feedback in the development pipeline.
Success worth smiling about
We define success by the speed with which we can update our systems to provide our internal and external customers with the best possible value. With Datadog and Google Cloud, we can get to the market faster with new features to enhance the employee’s capabilities and customer experience. This helps us to remain competitive as we scale and continue to innovate. From ideation to delivery, it’s a 3X to 4X improvement, sometimes more, due to our ability to better use analytics and prioritize activities.
From a leadership perspective, I view IT through the lens of Maslow’s Hierarchy [of Business Needs]. If our deployments aren’t going well and issues are affecting employees or customers, we can’t get increased development resources to explore things like generative AI. Being able to mitigate problems quickly and communicate what’s happening has built trust in our IT organization. That turns into more investment from the business for us to deliver more and richer capabilities.
As for the cost and productivity benefits, our team members have been able to spend less time on traditional types of legacy IT troubleshooting and instead dedicate more time to activities that add value to the business.
We also value the consolidated billing for Datadog software right on our Google Cloud invoice through Google Cloud Marketplace. Google Cloud Marketplace features some of the best third-party software vendors to augment our Google Cloud solutions.
Our management team is familiar with the benefits of the marketplace and is comfortable with it because it’s simpler than one-off contracting with new vendors. For our team, this means we can get quicker access to additional tools to support our goals.
We are excited to continue to evolve our use of Datadog and Google Cloud tools. The environment scales with us as needed, and we don’t have to make large purchases upfront. We can turn on additional capabilities when required as we expand the services we provide to customers in the future. In the end, much of how our customers will judge us relates to driving better customer experiences with less friction, and we believe our work with Google Cloud and tools like DataDog will put us in a leading position to meet those expectations.
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