How to know what you don’t know, now

There’s an expression “you don’t know what you don’t know” attributed to an American statistician W. Edwards Deming that seems very fitting today with data coming at us from all directions. At Accenture, we’ve long accepted that we need some help with what data we see and process—and that means using analytics wisely across our organization. But keeping pace with the rate of tech progress and our own transformation efforts, we had to admit that even after just three years of use, our analytics capabilities were in need of an overhaul.

There were all kinds of hints that it was time to improve the existing analytics platform. We were struggling to stay technologically current. More often than not we were finding that it was becoming difficult to upgrade and grow, creating greater overheads for managing storage and a high learning curve for developers. And our people were spending valuable time on operations, troubleshooting, and maintenance instead of generating insights to drive our business.

In the global IT team, we knew that if we wanted to support our IT strategy to be platform-powered, cloud-first and intelligence driven, we needed to change. In May 2019 we made the strategic decision to move to Google Cloud’s Platform-as-a-Service (PaaS) model.

We wanted to find out how to create a secure, cost-effective and scalable architecture in the cloud while also driving the migration of data and applications from the legacy system. Using Google Cloud, we could modernize data capabilities to unlock the promise of advanced analytics, increase cost savings via a pay-as-you-go model and drive cutting-edge performance—in short, it was our route to fully enable a digital Accenture.

What we didn’t know at that time, of course, was how cloud was about to become less of an aspiration and more of an urgent mandate. When the pandemic hit and businesses shut down or paused, cloud became the only means to not only facilitate remote working, but also meet the cost, performance and scalability challenges that organizations faced. Suddenly, getting the right data in the right hands became even more important.

A modernized platform

As we shift to a modern data architecture at Accenture, we’re making our best efforts to support cloud native technologies, such as serverless and container services—they mean we can scale in an agile way ourselves and they make all the difference as we implement similar solutions for clients.

The benefits speak for themselves. Google Cloud Platform with its open architecture approach gives our teams greater freedom to be:

• Less complex administratively: We can reduce the infrastructure that we manage and pay for, adjust to meet our changing size and scale. Upgrades and patches take time and effort—our Operations and Architecture teams need to investigate, pull systems down, find fixes and implement upgrades. With the stability of Google Cloud, our people—and our operational overheads—are freed up.
• Even more cost efficient: We now have a platform that is easy to upscale or downscale. A pay-as-you-go model gives our organization cost efficiency and elasticity—we only pay for the compute time used and received discounted process for long-running workloads.
• Able to get the insights we need, fast: We can take advantage of the ecosphere of other innovative solutions and plan our roadmap accordingly. We are moving our people to become skilled on an industry-relevant platform that can meet the evolving needs of our business.

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Read our case study to find out more about how we have completely transformed our analytics platform—reducing overheads, decreasing costs in server storage, and providing our people with cutting-edge, advanced analytics. And we won’t stop here. The reason we say “let there be change” is because we have opened the door to the kind of innovation that can handle it—even when we don’t know what we don’t know.