Converting sales opportunities into customers

Our internal IT develops predictive analytics solutions to help our people make better, faster, more accurate and more consistent decisions.

Challenge

Accenture is an intelligent enterprise that applies artificial intelligence (AI) technologies and embeds analytics into our operations. Our internal IT Enterprise Insight organization collaborates with Accenture business stakeholders to drive new, innovative capabilities and use case-based intelligent products to bring greater insights to Accenture’s businesses.

Included within Enterprise Insight’s analytics capability landscape are predictive models, which are being applied to Accenture’s business processes. Predictive analytics, embedded as AI, drive insights from Accenture’s huge volumes of data to predict the probability of occurrences and relationships to improve decision making. From the many possible use cases within Accenture, Enterprise Insight collaborated with business stakeholders to build an AI model to better predict the winnability of deals in the sales cycle, so that teams focus on opportunities more likely to be sold and walk away from investing business development cost in opportunities more likely to be lost.

The challenge: To create a machine learning model that scores and predicts the probability of winning sales opportunities—converting opportunities into customers and revenue—for Accenture.

Strategy and solution

The starting point for the development of our Win Probability Predictor model was to leverage an existing, third-party artificial intelligence tool we connected to Accenture’s customer relationship management system, Manage mySales. The tool was configured to generate a win probability predictor algorithm. The initial version was configured for Accenture’s business process outsourcing and infrastructure outsourcing businesses. We expanded that to Accenture globally.

Teams from Accenture’s Sales and Pricing Excellence, Manage mySales and Enterprise Insight collaborated to train and improve the Win Probability Predictor model by giving sales teams transparency on how to alter opportunities to win, and by providing real-time scoring capabilities to sales teams as they work. Drawing on five years of sales history, the AI model exposes positive and negative drivers of predicted win probabilities and shows sales teams which deals to continue to pursue and which to stop.

What this means is that an AI model can provide automatic and precise scoring of potential sales opportunities. It also provides the key drivers attributing to a score and explains the scoring. This is presented to sales teams in a way that is easy to read and digest. Sales teams can use this information to decide how best to proceed.

Transformation

AI systems are enabling people and machines to work collaboratively, changing the very nature of work and requiring all of us to manage our operations and employees in dramatically different ways. To exploit AI’s potential, leading companies like Accenture are embracing an evolution of business processes that is more fluid and adaptive, comprised of both human and advanced AI systems. This collaboration is leading to the reinvention of many traditional processes, which is what we are seeing at Accenture.

Today, at any one time, approximately 45,000 sales opportunities are in the Manage mySales CRM system, and every sales opportunity companywide is now scored by the Win Probability Predictor. The model accurately predicts the ability to win an opportunity with 97 percent accuracy—in less than three seconds. We continue to train this AI model on more than 120,000 sales opportunities a year with high speed and accuracy so that sales teams benefit from its best practices.

Connecting this AI to an online CRM system, which is available anytime and anywhere, allows sales representatives to update and test ways to improve opportunities or withdraw from a poorly positioned offer combined with their intuitive knowledge of a sales situation. Win Probability Predictor empowers teams and leadership to make smarter qualification decisions. The AI model is tailored to Accenture’s needs and is applicable and scalable to other service areas. Advanced digital capabilities, especially predictive models, hold the potential to be applied in any use case where scoring would be beneficial. Possibilities include revenue forecasting, risk assessment, sales campaigns, personnel scheduling demand and recruitment candidate matching.

Enterprise Insight continually drives innovation and applies predictive models, AI and machine learning to products to bring greater insights to the business. Within Enterprise Insight is the Studio, the research and development organization of data scientists, user experience experts and software engineers that experiments and builds advanced analytics solutions. It operates with a culture of creative agility, following emerging technology market trends, prototyping new analytics concepts and working with a fail-fast culture. A thriving analytics ecosphere is promoting winning ideas.

Analytics products are advancing Accenture’s transformation journey to becoming an enterprise that is automated, intelligent and insight-driven. Accenture envisions this future digital-insight culture as one that delivers new value in many ways. Accenture’s reporting landscape will become simplified as more clarity on what to use is gained. There will be broader insights into business performance as all business dimensions will be supported with digital insights—anywhere.