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Self-service analytics at Accenture boosts knowledge workers

Accenture's enterprise analytics and AI models are helping the firm on a number of fronts, including determining sales opportunities, pricing deals and complying with internal and customer expense policies.

Organizations across a range of industries are deploying self-service analytics tools to help knowledge workers sharpen their insights for better decision-making.

That's certainly the case in the IT services sector, where consultancies and systems integrators are looking for a competitive and operational edge in the data they have amassed. In a recent interview, Mike Maresca, managing director and Enterprise Insights program lead within Accenture's CIO organization, shared how the services firm is taking on the analytics challenge to support its employees. He was tasked with building an enterprise analytics service about 18 months ago.

The result is a custom analytics stack that resides on the AWS cloud -- Accenture provisions 95% of all new infrastructure directly in the cloud these days. Several versions of data visualization tools now deliver analytics to users, and the tools take advantage of Accenture's 100 TB data lake.

Using AI models to augment employees

Accenture's approach also involves AI models, Maresca said. The company has been exploring "how we can use AI not only to understand where our business is at and what is trending, but … to augment the employees and drive more efficiency in terms of how Accenture operates," he explained.

Change management is a huge part of what we have done.
Mike MarescaManaging director and Enterprise Insights program lead, Accenture

For example, Accenture has created a sales prediction algorithm that evaluates opportunities with prospective customers. The tool helps the sales team determine if a particular deal would satisfy Accenture's financial targets and meet the needs of the client. The algorithm also provides insight into pricing to make sure the company's bid is competitive in the market, Maresca noted.

In addition, Accenture has rolled out an expense compliance algorithm to help employees stay within the bounds of Accenture's employee expense reimbursement policies. The algorithm also keeps the company in compliance with clients' policies regarding the expenses Accenture can and can't pass through to clients, based on contract terms.

A cloud-native direction

Accenture is currently using a custom analytics stack on AWS, but the future is in a cloud-native approach.

Maresca said the company is moving in that direction, noting a "big push for us to explore cloud-native capabilities and building those into applications going forward."

That shift will likely entail redeploying Accenture's enterprise analytics tools as microservices packaged in a container-based environment.

Enterprise analytics guideposts

Maresca offered a few guideposts for creating a self-service analytics platform.

Make sure there's a digital foundation in place

Maresca said that means reimagining key processes and turning them into "more of an online, real-time conversation." Analytics lets Accenture inject data-driven insights into those processes to support decision-making and boost operational efficiency.

Keep usability in mind

Accenture has invested in design thinking and UI to create tools that are visually appealing and easy to navigate, Maresca said.

Ask for feedback

The company's teams have built-in user advisory forums, which provide a constant stream of feedback. Some parts of Accenture use an online voting process in which users can express preferences for the features and functions they'd like to see. The top vote-getters are prioritized for future updates.

Don't forget change management

Accenture's tech-oriented employees generally pick up new analytics tools fairly quickly. But users may still need one-on-one training. For example, if the company puts a financial process online and provides analytics around it, Accenture would provide training to make sure users grasp the process's operational metrics and how they apply to the part of the business they are managing. The reinforcement of key metrics helps users get the most out of the analytics tools.

"Change management is a huge part of what we have done," Maresca said.

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