A sales revolution is coming! That is the message from Jenny Dearborn, an industry thought leader on connecting data analytics and sales enablement. As the chief learning officer at SAP, Dearborn has seen firsthand major changes in the way large and medium-size businesses manage their sales functions.

“Companies that fail to adapt to the new realities and adopt the new practices risk falling behind their competitors who do. If you’re a business leader of an enterprise-level corporation who shoulders some measure of responsibility for sales effectiveness, you need to know about and prepare for this coming revolution,” says Dearborn in her book Data Driven: How Performance Analytics Delivers Extraordinary Sales Results.

To succeed in this new competitive environment, companies will need to harness the power of data—not just as a tool, but as a mindset. “Gone are the days you or your sales leadership can work on intuition, gut feel, or past history,” says Dearborn.

In fact, the May 2016 Forbes article “Ten Ways Big Data Is Revolutionizing Marketing and Sales,” explains that big data is enabling enterprises to gain greater insights and actionable intelligence into each of the key drivers of their business.

“Increasing the quality of sales leads, improving the quality of sales lead data, improving prospecting list accuracy, territory planning, win rates, and decision maker engagement strategies are all areas where big data is making a contribution to sales today,” writes Louis Columbus, director of global cloud product management at Ingram Cloud.

Specifically, data can provide insight into which content is the most effective at each stage of a sales cycle, how investments in customer relationship management systems can be improved, and help sort out strategies for increasing conversion rates, prospect engagement, revenue, and customer lifetime value.

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But to glean those insights, the data must be analyzed. Indeed, winning businesses gain their advantage by taking smarter actions and predicting outcomes. Enter prescriptive analytics.

Prescriptive analytics is related to both descriptive and predictive analytics. While descriptive analytics aims to provide insight into what has happened and predictive analytics helps model and forecast what might happen, prescriptive analytics seeks to determine the best solution or outcome among various choices, given the known parameters. In practice, prescriptive analytics can continually and automatically process new data to improve the accuracy of predictions and provide better decision options.

Unfortunately, many organizations don’t know how to start leveraging their data for prescriptive analytics. ATD's newest virtual event, Data Driven Sales Talent Development, addresses the analytical skills gap that prevents you from taking advantage of the full potential of data analytics to transform sales effectiveness.

Jenny Dearborn is leading the event, and will show you how to design and implement effective learning for your sales teams with measurable business impact using a Prescriptive Action Model. In three breakout sessions, she will guide you through a simulation tool to prescribe a solution to a real-world sales enablement issue by applying the results of data analytics. You’ll leave with the knowledge, resources, and tools to transform your organization from one that manages by “guesstimate” to one whose business decisions are data driven.

Join Dearborn online August 25 for Data Driven Sales Talent Development and learn how to use data analytics to pinpoint sales workforce issues and prescribe effective solutions.