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.