Netflix, Amazon and Hulu upped the value of great content creators. How data will increase the value of great sales professionals.
In 2013, The New York Times published a story about the impact of predictive analytics on the entertainment industry based on the startling success of Netflix’s House of Cards, which is among the first television productions originating from data and machine-generated predictions. John Landgraf, then-president and general manager of the FX Network, dismissed the notion of machine-generated content, telling The Times, “Data can only tell you what people have liked before, not what they don’t know they are going to like in the future.” He argued that machines would squelch innovation by overriding the human “black box that data can never penetrate.”
Even though the success of House of Cards had been replicable, critics balked, arguing that, by deploying machines to aid decision making, Netflix was purging its award-winning shows of originality and creativity while also threatening the livelihoods of the writers, actors and creators who developed the content.
Fast forward to 2017: In four short years, three technology players—Hulu, Netflix and Amazon—have received a total of 32 Emmys for content commissioned and distributed based on data and machine-driven measurements. Apple announced that it would spend $1 billion on original content, according to the Wall Street Journal. Netflix countered with a budget of $6 billion, up from $2.4 billion in 2013, and projected an increase by another billion dollars in 2018. Even HBO allocated a 20 percent budget increase from the prior year. In an age of big data, rather than reduce spending on content creation, budgets have grown.
Orange is the New Black, House of Cards, The Handmaid’s Tale and Transparent are just a few examples of how streaming services have used AI to create better content.
Ironically, in the age of big data, budgets have expanded and innovation has, too. Hits like Transparent (one of the first series to feature transgender actors), Orange Is the New Black (based on Piper Kerman’s account of life in a women’s prison) and The Handmaid’s Tale (an adaptation of Margaret Atwood’s 1985 dystopian novel) all contain subject matter from which traditional networks have historically shied away. The abundance of bold new production companies has created opportunities for actors and writers that hadn’t existed before now.
It turns out that the real value of machine learning is to mitigate the risk of failure due to audience preferences, which can be difficult for individual network executives to gauge. That guidance paved the way for bigger bets on innovative and high-quality content. New companies with distribution muscle could bet on shows overlooked by established players thanks to the data sources and technology that provided extraordinary insights. Free from the risk of massive and unsuspecting failure, creativity blossomed, and distribution companies could argue for higher capital investments in projects.
Despite this outcome, the fear that data and predictive technologies, like artificial intelligence, will replace people persists. According to a 2017 Pew Research Center study, 73 percent of those surveyed are worried about robots and computers taking human jobs. Moreover, technology has not always led to enhancing the value of human input. E-commerce and AI bots have sent retail selling into a tailspin in which online stores without salespeople have destroyed their offline counterparts. Many analysts wonder whether the same trend will make it’s way to the enterprise sale. In fact, a report entitled “Death of a (B2B) Salesman,” published by the market research firm Forrester, predicted that by 2020, one million of 4.5 million B2B sales positions would be replaced by artificial intelligence-enabled E-commerce.
“Artificial intelligence will take over 30 percent to 40 percent of jobs,” echoed Sean Sheppard, a founding partner of the San Francisco–based venture capital firm GrowthX. “We are in the fourth industrial revolution—the innovation economy.”
While the parallel between retail and B2B sales is tempting, a growing number of analysts and industry experts reject Sheppard’s perspective, arguing that talented B2B sales professionals have more in common with creative professionals than retailers and thereby stand to gain massively from artificial intelligence. Proponents of this point of view cite the complexity of B2B sales and the plethora of skills and collaboration required to produce winning outcomes, a very real difference between the highly transactional and binary nature of retail.
Selling into companies, often with various constituents and highly complex products, B2B sales professionals rely on uniquely human skills: persuasive communication, negotiation, relationship building and empathy. “In order to be successful, a truly gifted B2B sales professional must be part politician, diplomat, advocate, business analyst, storyteller and teacher,” says Global Executive Group CEO Bruce Barlag.
Proponents of Barlag’s theory point to the fact that the majority of a sales professional’s time is spent managing risk. The average sales professional juggles a pipeline with up to five times more opportunities than what will likely convert to revenue. This means, by default, they are failing a majority of the time, regardless of skill set. To mitigate the downside, sales professionals are paid quarterly and on commission, with the assumption that a company can cut its losses if they fail to meet quota within any given three-month period. With little more than their gut to rely on, sales professionals guess at which prospects and opportunities to direct their talents. Company executives expect to fire 25 percent of their sales force each year—a tremendous cost to employees and the bottom line.
In 2016, only 59 percent of sales professionals met their quotas, down from 63 percent in 2012, according to the research firm CSO Insights. And it’s why fewer than 45 percent of companies, on average, understand the reason behind their top sales professionals succeeding, therefore rendering the work of hiring wisely and replicating the strategy all but impossible, the study suggests.
Collective[i] CEO Tad Martin predicts a massive talent shortage in senior selling roles. “The goal of AI should be transparency and automation to the extent it frees humans to do higher value tasks,” said Martin, who along with his cofounders developed Intelligence.com, one of the leading sales applications and networks to apply machine learning and predictive analytics to improve outcomes for B2B sales teams. “The opportunity in B2B sales to eliminate the guesswork around what people and prospects matter is enormous when gifted sales professionals can focus on selling and skilled managers on coaching.”
Despite many sales falling apart due to outside factors—a lack of resources or decision-making authority, legal department challenges or macroeconomic variables—the salesperson is held accountable for the result, said Martin. The inability to separate external risks from selling activities has led to a depression of salaries for extraordinary sales professionals, whose compensations are discounted due to the wasted time and resources of risky deals. As a result, the top 20 percent typically generate 80 percent of the revenue for their companies. Without the transparency to separate talent from luck, Martin argues that highly skilled sellers are underpaid due to costs associated with the failures of their teammates.
In Martin’s view, AI’s biggest promise is shedding light on who a sales professional should be targeting and what odds the person has of succeeding. “A great sales professional who knows who to target should succeed 90 percent of the time, which is a huge improvement from the less than 50 percent odds that exist today.”
In the world of B2B sales, professionals who are slightly better than average at figuring out the odds of winning deals are not equal to the exceptional sales leaders who know how to provide value by deploying empathy, negotiation skills and persuasion. Indeed, the latter have skills a machine cannot replace. The machine is only an assistant, recalculating the odds of success through greater intelligence.
“I believe there will be room for sales people, but only the people who can provide concierge service and negotiate big contracts,” said Hannah Kain, CEO of ALOM, a Silicon Valley–based global supply chain management company. “The sales rep will be orchestrating a tight-knit group of experts to elevate personal service.”
Assuming B2B sales technology can level the playing field around knowledge about buyers, as more and more companies embrace technology like artificial intelligence, they should prepare to compete heavily for great talent. Like the art of creating content, selling is so uniquely human and valuable that top talent is extremely important. According to Martin, now is the time to double down on sales—as one of the most meaningful sources of growth—by putting in place the technology to help employees and their teams focus and by then investing heavily in salaries and working environments that attract the best and brightest sales professionals.
An early technology pioneer, Martin draws an analogy to what happened when the tech sector exploded. “In the years before it was obvious that tech was the future, companies used to make fun of Silicon Valley’s high salaries, open office plans, casual dress codes and stocked kitchens,” he recalled. “The Valley invested in the talent that was fueling growth and as a result, trounced companies that viewed people as dispensable. We are on the cusp of a much larger AI-driven growth spurt that will be led by sales. My prediction is that the companies that get ahead of this curve—and view what’s possible with AI through the lens of opportunity rather than fear and hire and retain the best sales talent—will be the big winners in the innovation age.”