Why Artificial Intelligence is Essential to the Modern Sales Organization
U.S. companies invest approximately $900 billion annually into strengthening their sales muscle, redistributing 10 percent of their revenues into hiring talent, training new recruits and implementing technology, according to a 2014 Harvard Business Review study. The investment far outweighs spending on advertising, digital marketing and social media, yet typically only half of the nation’s sales professionals make their quotas each year, according to CSO Insights, the California-based sales-analytics and advisory firm. Meanwhile, Dan Weinfurter, the CEO of GrowthPlay, a Chicago-based sales consulting and training firm, believes the so-called 80/20 rule stubbornly persists among sales organizations, whereby a small group of professionals delivers a majority of the results.
“In nearly all cases, the bottom 20 percent of the sales force is not remotely competent for the role they are in,” Weinfurter, who has advised FedEx, General Motors and Comcast, wrote in Forbes in 2017. “This situation has largely remained unchanged over the past 30 years, due in no small part that despite overwhelming evidence that in the intermediate to long term, the quality of talent a firm is able to hire and deploy is the most important business discipline and the only sustainable competitive advantage for a business.”
Increasingly, cutting-edge sales applications threaded with artificial intelligence—like Collective[i], Gong.io and Tact—are emerging as a remedy to the 80/20 rule and a sophisticated tool to nail quotas, experts believe. Between identifiying lagging sales professionals in need of further training and helping teams identify risks and opportunities, predictive analytics can offer a host of strategic insights to strengthen the selling process while eliminating time-consuming data entry so professionals can spend more time with their customers, experts said. Sales managers, meanwhile, will use the technology to adjust sales projections and commissions while responding to a host of market variables.
Experts believe that by adopting the technology early, sales professionals will significantly increase their competitive edge by eliminating tedious data entry, which can consume as much as 20 percent of an employee’s workweek.
For sales teams large and small, artificial intelligence is a topic of endless debate and, for many businesses, the cause of no small amount of anxiety. Indeed, according to a recent MIT Sloan Management Review survey of 3,000 executives and sales managers, nearly 85 percent of those polled believe artitificial intelligence can help them sustain a competitive advantage—yet only about 20 percent have actually incorporated the new technology. Among the companies that have neglected AI, a lack of resources, competing investment opportunities and a minimal understanding of machine learning were cited as barriers to implementation, according to the report, “Reshaping Business with Artificial Intelligence.”
But experts believe that by adopting the technology early, sales professionals will significantly increase their competitive edge by eliminating tedious data entry, which can consume as much as 20 percent of an employee’s workweek and create unnecessary meetings to review pipelines and market conditions. The streamlining, in turn, offers a more customer-centric approach to selling. For operations managers, meanwhile, greater efficiency and sharper insights will free up time for devising winning sales strategies. In short, the insights provided by an emerging set of modern sales applications have the ability to address a host of challenges and inefficiencies that drastically improve the productivity and output of sales organizations globally.
Demand for sales applications powered by artificial intelligence is growing faster than the technology can be developed. The industry is forecasted to exceed $36 billion in revenue by 2025, according to Tractica, the Colorado-based market intelligence firm. Meanwhile, analysts believe sectors including retail, health care, finance and defense will further integrate AI as businesses develop a deeper understanding of the technology. But like all social animals, C-suite executives frequently cling to a herd mentality when it applies to technology, not least of all state-of-the-art intelligence, the likes of which several outspoken critics—Stephen Hawking and Elon Musk among them—have loudly protested.
Nearly 85 percent of [executives and sales managers] believe artificial intelligence can help them sustain a competitive advantage—yet only about 20 percent have actually incorporated the new technology.
“For those who are slow to embrace AI, what can help change their minds is to see how sales leaders can utilize it to drive growth,” said Catherine Gutowski, a vice president at General Electric, who was tapped in February to revitalize and scale a sales force of more than 25,000 across 200 countries with new technology, including artificial intelligence. “The more concrete examples we have of how we can utilize AI to drive growth, the more the late majority and laggards will eventually come on board.”
Despite such momentum, some businesses are taking a conservative approach. For many—especially smaller companies with fewer resources—an ambitious artificial intelligence expansion can be frightening or. Alysa Taylor, a general manager of business applications at Microsoft who helped spearhead the incubation of its cloud computing service Azure, frequently advises potential customers on how best to implement the new technology. For smaller companies, she said, applications like IBM’s Watson, which relies heavily on intensive customization, rarely offer the biggest bang for the buck.
“Customization, for many organizations, is very time consuming because of the data architecture,” said Taylor, who’s based in Seattle. “To get AI done well, you need a data schema that supports [AI] so that you’re feeding in the right data to be able to do the predictive components that you want your AI solution to deliver. That can be a heavy lift.” By Taylor’s definition, even technologies that tout AI (Watson and Einstein for example) are inherently limited by the data source of individual customers.
In anticipation of the sea change toward business intelligence, Microsoft last year repositioned its Enterprise Resource Planning and CRM platforms under a single umbrella, Azure, and disaggregated those components into myriad purpose-built applications. Buttressed by more than 2,600 third-party applications and the $26 billion acquisition of LinkedIn—a move many saw as devastating for Salesforce—the streamlined platform has drawn attention from analysts, who have praised Microsoft’s pivot to enterprise intelligence. To be sure, in a poll of 235 information technology and application development professionals conducted by the analytics service Sumo Logic, 66 percent named Azure as its vendor of choice—beating Amazon Web Services by a staggering 10 points.
From GE to Microsoft, the world’s largest selling teams are racing to modernize and augment human capital with machine learning delivered via finished applications. Corporate leaders, like Gutowksi and Taylor, who embrace AI share a similar mindset namely that AI is mission critical (with the goal being to augment, not replace sales professionals) and that comprehensive applications that tap into larger data are prefered to customized technologies limited to internal data.
“Those who are slow to embrace AI will be left behind,” said Gutowski, “Many don’t realize it, but AI is already here, and it is not going away. You can fight it, but that doesn’t mean it’s not going to happen. AI represents a big part of the next big thing: the fourth Industrial Revolution. Just like the Industrial Revolution replaced agriculture, the fourth Industrial Revolution is here to help us to further evolve and grow.”