At Accenture, we have been applying artificial intelligence (AI) as an enabler of business transformation and are seeing it deliver real benefits within key enterprise business processes. By embedding insight into business applications our people can make better business decisions. Making this happen is our Enterprise Insight team within our internal IT organization. We are a global team of business analysts, data scientists, user experience experts, software engineers, and change management practitioners who work with Accenture business stakeholders to shape, deliver, and operate analytics solutions.
One business process we addressed is purchase requisitioning and non-purchase order invoice processing. Given Accenture’s size, we purchase a high volume of goods and services—amounting to nearly 200,000 purchase orders a year. Accenture also processes 1.1 million invoices annually through our accounts payable function.
Our global procurement organization, Procurement Plus, uses SAP Ariba’s Guided Buying capability on SAP Ariba Buying and Invoicing software-as-a-service (SaaS) (which we renamed internally as BuyNow) to optimize spend totaling more than $4.5 billion dollars every year. We realized that buyers of Accenture goods and services were less familiar with the downstream accounting of their purchases, and that this was creating friction and driving inefficiency and cost into the process.
We saw an opportunity to improve the efficiency in purchase requisitioning and non-purchase order invoice processing by using predictive analytics and automating the recommendation of general ledger accounts to buyers at the point of purchase. Predictive analytics, embedded as AI, and automation better prepare buyers who are less familiar with accounting to be more accurate with their purchases. These capabilities held the potential to significantly streamline downstream accounts payable accuracy, time, and cost.
Our Challenge, Our Solution
The challenge for our Enterprise Insight team together with Accenture Procurement Plus was to create an artificial intelligence model using predictive analytics that provides general ledger recommendations for goods or services being purchased, improving subsequent accounts payable accuracy and efficiency, and enhancing the procurement experience for Accenture.
The starting point for the development of what we would ultimately call our General Ledger Recommendation solution was the AI model we connected to our BuyNow procurement solution and our SAP S/4HANA® accounts payable solution. Our joint team developed the solution for both purchase order-based and non-purchase order-based spend. For purchase order-based buys, BuyNow needed to improve the assignment of general ledger accounts at the point of purchase requisition. For non-purchase order-based buys, we needed to improve the assignment of general ledger accounts within the accounts payable process. Both situations were manual, time consuming, and prone to error.
The team designed an artificial intelligence model to recommend the best account from more than 5,000 available general ledger accounts. Drawing from the accounting on historical purchases and invoices, the model recommends the general ledger accounts for new buys at the point of entry. The solution was directly embedded into our Accenture BuyNow platform experience.
From a technology perspective, Enterprise Insight approached the problem as one of classification. First gathering historical purchase and accounts payable activity, the team ingested the data into Accenture’s data lake. The team then used the data to build and train a General Ledger Recommendation model with an AI machine learning algorithm. Using the patterns created on the historical data, the model was also able to make a predictive recommendation of a general ledger for a purchase.
Once the model was trained, the team embedded the solution into both the Accenture SAP S/4HANA accounts payable process for non-purchase order-based buys and the BuyNow procurement process for purchase order-based buys. The managed model continues to increase its accuracy in making classifications for new goods and services buys.
Poised to Deliver Business Value
By integrating seamlessly with Accenture’s BuyNow and SAP S/4HANA solutions to recommend general ledger accounts for purchase order-based and non-purchase order-based buys, the General Ledger Recommendation solution is projected to deliver significant business value including accuracy, efficiency, and an improved procurement experience.
General Ledger Recommendation is an example of how AI can provide an integrated experience to create strong business value and enable people to work smarter. AI is helping Accenture to move to a new generation of business process intelligence. Analytics products like these are advancing Accenture’s transformation journey to becoming an enterprise that is automated, intelligent, and insight-driven.
I’m curious as to what business processes has your organization improved through the application of AI and automation? Leave a comment below.
Patrick
Related Material: Powering procurement with prediction + automation
Patrick Engelking is a Director in Accenture’s Internal IT organization, Digital Business Transformation, Enterprise Analytics.