In just a few decades, the world of data-driven decision making has experienced significant transformation. The use of data for decision support in business has evolved from traditional management information systems (MIS) and decision support systems (DSS) to a vocabulary of business intelligence (BI), data warehousing, data science, big data analytics, data lakes, and now, the emerging discipline of decision science. Underlying this change in vocabulary are some profound changes in the way that businesses approach using data to drive business decisions. Over my career, I've seen three distinct stages of how large businesses have approached problem solving using data, and we're now entering a fourth. Before technology, there were people: Lawyers, accountants, designers and other specialists who could help businesses better understand their organizations, help them create new products and services, restructure through lean times, and find new opportunities for growth.
Salesforce.com Inc. CRM -0.59 % said it would press regulators in the U.S. and Europe to block Microsoft Corp. MSFT -1.09 % 's 26.2 billion acquisition of LinkedIn Corp. LNKD -0.74 %, arguing the deal would hurt competition by giving its business-software rival too much control over the social-networking company's vast pool of data. Salesforce's public broadside against the deal on Thursday came three months after it lost a bidding war for LinkedIn to Microsoft. Both companies' interest in LinkedIn centers on data generated by its members, who typically maintain career résumés on the site. LinkedIn claims 450 million members in more than 200 countries, including 106 million monthly active uses. Burke Norton, Salesforce's chief legal officer, said owning LinkedIn would give Microsoft an unfair competitive advantage because it could block rivals' access to the data on its membership.
At Dreamforce this week, Salesforce finally provided details about Einstein, its artificial intelligence technology that it touts as "AI for everyone." For the last couple of weeks, Mark Benioff has been teasing us about Einstein, and yesterday we saw the fruits of that labor. A series of speakers extolled the benefits of Einstein – from being able to predict the sports gear that a consumer might like, to medical uses such as being able quickly diagnose bleeding in the brain. The real impact of Einstein, however, is that it validates the larger trend of Artificial Intelligence or "AI" being applied across a wide variety of both enterprise and consumer tasks. One of my favorite comments from the keynote was that AI is like electricity, and that when it was first incorporated into appliances they were referred to by names such as "the electric toaster."
Marketing, which is highly quantitative, targeted, and tied to business outcomes, will likely become highly automated by 2025. The few people who will comprise the team of the future will be responsible for ensuring that promotions are creative and for overseeing the automated systems. If I had to place bets on which business function would have the fewest humans and most automated systems by 2025, I'd pick marketing. This is ironic, of course, since marketing has long been known for its creative and artistic orientation. If Mad Men's fictional character, Don Draper, were alive in 2025, he would probably have wished he had never seen such extensive use of analytics and automation in his beloved function.
Some executives may wring their hands over the impact of bot automation, machine learning and AI on job roles. But others see the potential of combining software with people-centric tasks to drive efficiency and enhance human work. At KLM Royal Dutch Airlines, customer service agents deal with a high volume of requests for flight information or help with trip cancellations, particularly during bad weather. In 2015, KLM began experimenting with a hybrid approach -- chatbots combined with human customer service -- to deal with high-volume customer interaction on social media platforms. Bot automation is just one of the many types of artificial intelligence (AI) that major software providers have touted during the past year as the next great thing in technology.