Call for change

Running a business today is all about managing dynamic data. Accenture wanted to make better use of platform services that could develop, run and manage applications in the cloud and make data more visible and secure. Data empowers our people and drives innovation for our evolving business.

After just three years of use, the Accenture Global IT organization recognized its analytics platform was fast becoming obsolete. The platform was managed by Accenture but hosted in the cloud. Yet, increasingly, it was difficult to upgrade and grow, creating greater overheads for managing storage and presenting a high learning curve for developers. We were struggling to stay technologically current. Our people were spending valuable time on operations, troubleshooting and maintenance instead of generating insights to drive our business.

Accenture made the strategic decision to move to Google Cloud’s Platform-as-a-Service (PaaS) model to support our IT strategy to be platform powered, cloud first and intelligence driven. The program team needed to determine 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 that enables a digital Accenture.

"We decided to migrate our data platform to Google Cloud for sustainability and performance reasons. But the platform does so much more—it gives us enhancements and capabilities that are delivering new business value."

— LUIS POLANCO, Director – Global IT, Technology Platforms, Accenture

When tech meets human ingenuity

Without doubt, technology—and how the world uses it—has changed dramatically in the last five years. So, too, has the demand for data insights. Accenture began the journey to improve its analytics platform by assessing if cloud-hosted PaaS offerings could address the cost, performance, and scalability challenges of the legacy data lake. Today, Accenture IT infrastructure runs in the hybrid cloud to take advantage of its scale efficiencies.

The Global IT team selected Google Cloud as the platform for its new analytics data lake, taking advantage of its established solutions and technologies and its flexible cloud platform offerings that power applied intelligence. Google Cloud enables options for deploying the right server sizing and configuration to meet the analytics’ job requirements. The Global IT team, partnering with Google, designed a modernized platform with the ability to deploy services faster, realizing improved performance and stability for the applications powered by the data lake.

As part of the transformation journey, the platform architecture and processes had to be created to align with our security needs to make sure that the data coming in and the data going out was secure at the enterprise level. With the move to Google Cloud, Accenture has created a foundation to store and analyze its enterprise data in the data lake—with room to grow.

To take advantage of the architecture, we needed to address who could access the data and who and how we deploy analytics into production. A new data security model, along with project governance, was created, while adhering to our data compliance and audit requirements. In line with industry standards, Accenture adopted a Site Reliability Engineering (SRE) model where teams can build, operate and run their own environments and services. Cloud native services, driven via code, meant that the cloud could optimize efficiency.

Moving to this model means that teams can use repeatable infrastructure deployments, avoid manual configuration and introduce greater consistency. Compliance and security checks before deployment means teams can work with a unified set of practices and tools to deliver applications and their supporting infrastructure rapidly, reliably, at scale and while minimizing vulnerabilities to the systems.

Now, Accenture has advanced our cloud capabilities with self-service analytics, real-time integration across various platforms, such as ServiceNow and Salesforce, and moved into a PaaS model with a cloud native infrastructure.

Data migration

In addition to setting up the new architecture, Accenture needed to execute a migration strategy to move hundreds of terabytes of data from the existing infrastructure to Google Cloud. Sitting on top of the existing analytics platform were more than 50 applications driving insights to users all over the globe. The team needed to manage a seamless transition with minimal impact and no downtime to the 40,000 global consumers of those analytics applications.

Accenture wanted to take advantage of cloud native components quickly and reduce administrative complexity, so the migration team reshaped the current applications to use on-demand infrastructure concepts and on-demand resources optimized for cloud computing. In a phased, targeted approach, applications were evaluated to reimplement the data ingestion and store strategy. Processing code remained the same, but data warehouse interfaces were moved fully to automated services such as Google BigQuery (which gives us the security and control we need when sharing data) and Google Cloud Composer to run workflows.

Since executing a multi-year program to remove silos and make data available, we’ve moved from zero data in the lake to 460 datasets with more than 400 terabytes of business data available to our end users.

As part of the rationalization of existing apps, Accenture has enabled more than 150 source applications and more than 250 business applications.

Applications now available via Google Cloud include:

Accenture Legal Intelligent Contract Exploration (ALICE): Our 2,800-strong Accenture legal teams need to understand our rights and obligations across contracts with clients and precisely how they are documented. The award-winning ALICE tool combines natural language processing (NLP) and artificial intelligence (AI) to help analyze more than 250,000 documents so that legal leaders can quickly evaluate client contracts. ALICE is delivering major time savings, unleashing data that was previously not easily accessible and offering knowledge at the moments that matter.

Manage myBusiness: A self-service analytics dashboard that gives our business unit and client account leads real-time, easy and secure access to the information that they need to manage business performance. The application uses AI to provide an interactive experience that enables our business leads to analyze key performance indicators, connect to a wide suite of diagnostics and drill down to transaction systems.

Manage myContracts: A simple way to track and manage contracts through shared data, reporting and dashboards. This collaboration hub uses an intuitive visual representation of a contract health score to enable our teams to quickly understand the overall health of a contract. By better tracking and monitoring the status of a specific contract, curated mitigations can help to avoid risks becoming issues. Shared oversight helps contract managers to help support delivery, work smarter with account teams, inform business planning and manage ever-increasing contract volumes. The application integrates with our contracting tool Manage myDeal and the legal tool ALICE.

Anomaly detection: We process approximately 25 million expense lines annually. Every report is analyzed by a manually designed rules-based system to check for expense compliance. Roughly 10% of expenses are flagged for potential noncompliance and then audited by the Accenture compliance team. Traditional rules-based systems—while effective at detecting known and recurring patterns of noncompliance—can be unreliable or exploited by fraudulent behavior. We developed an anomaly detection solution for our expense reporting system that more accurately identifies noncompliant expenses, reduces false positives and easily identifies hidden patterns using AI.

Skill diversity

When Accenture made the decision to move to Google Cloud, the leadership team recognized this would represent a major change, touching all our processes and the skills of our team. Indeed, data analytics is far from being all about technology—it demands skill diversity and a data culture—and we knew we needed to transform how our people work with the technology.

The team chose to tackle the culture, talent and change barriers to successful cloud adoption. The focus was on preparing the teams to transition to the cloud, assessing the current and desired cloud skills, developing tailored learning paths and creating and enabling a continuous training plan. Transformation leaders were selected across roles, locations and functions to provide 360-degree feedback loops and accelerate the time to development.

The Global IT team recognized that to be a cloud-first organization we needed to shift our talent focus to crafting analytics solutions that bridge Google Cloud capabilities with our internal systems.

Today, skill diversity is helping us to implement the right business cases that are making data analytics shine in our company. We have more than 260 data projects on the Google Cloud platform, more than 60 data science projects and we have created 75 predictive models.

A valuable difference

We embrace innovation while knowing that it is most effective when we adopt a “fail fast and early” approach through purposeful, measured experimentation.

We also understand the important of knowing our customers to provide personalized product offerings that are useful for them.

And we recognize that if we want to be agile in our business, we need to adopt a transparent, as-a-service approach—one that demands the right information at the right time. For example, in the early weeks of the COVID-19 pandemic, our Global IT team delivered value-added analytics quickly to numerous enterprise functions and this enabled our organization to respond with data-driven decision making.

Google Cloud Platform with its open architecture approach is giving our teams greater freedom to:

  • Democratize data: We want to make data accessible to all our people. By providing more autonomy to our users and the ability to quickly explore our data and create analytics insights to answer business questions, our people can reduce their dependencies on our IT teams to deliver analytics products.
  • Manage data as a product: Our business data lake in Google Cloud is helping us to understand ourselves and mature toward managing our data as a product. We aim to give more ownership and visibility to every team that produces data to ensure we have people who know their data best.
  • Reduce administrative complexity: We can reduce the infrastructure that we manage and pay for, adjusting to meet our changing size and scale. Upgrades and patches take time and effort—our Operations and Architecture team 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.
  • Improve cost efficiency: We now have a platform that is faster and more intuitive—and cost effective. It’s 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 we receive discounted prices for long-running workloads.
  • Enable insights at speed: 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.

Throughout the data transformation process, we have discovered that meaningful data matters more than data volume. And we have learned to be patient and consider the technologies we are already using rather than migrating to the next “shiny toy” technology.

Today, through due diligence and careful planning, the Global IT organization has completely transformed its analytics platform—reducing overheads, decreasing costs in server storage and providing our people with cutting-edge, advanced analytics.

Going forward, Accenture intends to continue to transform and strengthen the big data insight capabilities we offer, explore the full value of the cloud ecosystem and open the door to more innovative solutions.


of business data available to Accenture end users


faster in executing high-volume queries


data projects active on the Google Cloud platform


data science projects developed


predictive analytics models created


reduction in operational incidents in production environments

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