‘Steps’ to analytics success

Machine learning was a hot topic at the recent INFORMS Business Analytics and Operations Research Conference in Orlando, Fla. Everyone seemed to be talking about sophisticated automated technologies for combing through mountains of data, making predictions, discovering insights and optimizing decisions. In his keynote presentation, Sam Eldersveld described robots that had been introduced by Amazon in its distribution centers, drawing parallels between its control systems and other machine-learning applications. Illustrating these points with video footage, Eldersveld wryly observed that “this is kinda creepy.”

There is surely something creepy about the “Rise of the Machines” scenarios and dystopian futures that science fiction writers and filmmakers are fond of showing us. But for many, the near-term impact of today’s increasingly smart machines is a far more serious concern. A recent article in The Economist observed that “the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution is worth taking seriously [1]”

In their new book “Only Humans Need Apply” [2], Thomas Davenport and Julia Kirby openly acknowledge that “knowledge workers’ jobs are at risk” and observe that “experts engaging in the current debate … fall into two camps – those who say we are heading inexorably into permanent high levels of unemployment and those who are certain new job types will spring up to replace all the ones that go by the wayside.” However, rather than offering yet another opinion on the macroeconomic impact of these ever smarter machines, the authors instead endeavor to describe the relative strengths of smart machines (rigorously following rules, doing repetitive tasks quickly and consistently, rapidly reviewing large volumes of data in search of patterns) and humans (contextual understanding, integration of information, complex communications, empathy and creativity). The core of the book is then focused on particular “steps” that individuals might take to leverage these relative strengths in a world where the pace of technological change continues to increase.

Their steps are based on two fundamental ideas. First, the authors observe that it is specific tasks, rather than particular jobs, that are vulnerable to being automated. Secondly, as more and more routinized tasks are automated, technology itself will produce opportunities for higher-order activities that leverage humans’ unique strengths. “Augment, don’t automate!” is one of the books key mantras, reflecting the authors’ metaphor of smart machines as wheels for the human mind.

Most of you reading this column are engaged in what the authors call “Stepping Forward”: developing the cognitive technologies of the future. The book’s chapter on Stepping Forward reads like an ethnography of today’s tech industry, highlighting not only technical jobs in software engineering, data science and research but also roles in product management, marketing, consulting and entrepreneurship that are essential for these technologies from R&D to the potential customers. This chapter also includes a nice feature on Zahir Balaporia, a longtime INFORMS member and leader within the Analytics Society of INFORMS, profiling his work in facilitating the deployment of smart systems at trucking giant Schneider National. Balaporia is cited as an archetypical internal automation leader, an increasingly important role that interfaces directly with those who are “Stepping In” and “Stepping Up.”

Those that Step In are the frontline employees and managers who develop a deep understanding of how new cognitive technologies work, along with an appreciation of their potential and an awareness of their limitations. These are the power users and change agents who have the skills, the motivation and the inclination to dig under the hood to understand the model logic, identify its weaknesses from a business perspective, and communicate potentially valuable improvements. These are people working hard in the trenches to help their organizations capture the promised ROI associated with new technologies.

In contrast, Step Up people are business leaders who constantly scan the horizon to understand emerging technologies and potential applications, make high-level decisions about which smart solutions to invest in, and manage the myriad challenges of organizational change, all while looking for the next set of big technology-driven opportunities. These are big jobs, few in number but hugely important. As the authors succinctly state, “they decide what smart people do, what smart machines do, and how they work together.”

The conference in Orlando featured a session with Craig Brabec, a prototypical Step Up person (he recently joined McKesson as senior vice president for data and analytics after being chief of analytics at Caterpillar). In his session, he thoughtfully discussed emerging supply chain management technologies, the challenges of earning credibility for new technologies with other business executives, the value of looking to other industries for ideas, and the importance of creative partnerships with early-stage technology vendors. As I listened to Brabec speak, it became clear to me that we should expect more and more C-Level executives to emerge from the ranks of those who have Stepped Up in the way that Brabec has, and I suspect that Davenport and Kirby would agree.

The other two steps described in the book are “Stepping Narrowly” and “Stepping Aside.” The authors describe Stepping Narrowly as finding and cultivating a deep niche for which the opportunity is too small to attract substantial investment for automation. My prototype here is my friend’s small Midwestern law firm, a worldwide leader in cases associated with garage door opener technologies. The book points out that today’s online search capabilities enable such experts to develop, maintain, promote and deliver services based on their specialized expertise.

To Step Aside is to find and/or create a role comprised largely of tasks for which humans have a distinct long-term advantage over smart machines. The authors cite entertainers, artisans, therapists, writers and designers as examples. They also point out that smart machines can enable Step Aside people to leverage their human strengths by freeing them up from repetitive tasks and enabling them to do vastly more of what they do best.

Despite all the disruption that increasingly smart machines are having on the world already, the authors are largely optimistic that organizations will adapt in ways that are positive for people:

“As we move more fully into the age of machines … the key to firms’ competitiveness is not the efficiency that automation provides but the distinctiveness that augmentation [of people] allows … they [organizations] will have to attract highly capable people, engage them, and retain them.”

I am more ambivalent. As our economy recovers from the Great Recession, job growth has continued to be sluggish, and wages for the middle class have been largely stagnant for quite a long time [3]. Late in the book, Davenport describes a recent conversation with an insurance company executive whose desire to deploy automated claims processing technology is driven by the opportunity to please Wall Street by decreasing labor costs. This mindset seems typical of executives in today’s world, and as a result, many of yesterday’s entry-level positions have already been automated (or offshored). Not coincidentally, these issues have also been a big part of this year’s presidential campaign.

As I came to the end of the book, I was struck by the amount of creativity, judgment and entrepreneurial skill that are going to be required of individuals going forward. My broader challenge is to figure out how to pass these lessons on to my students (as well as my 12-year-old daughter) to help them avoid getting Stepped On or Stepped Over. My sense is that they should surely read “Only Humans Need Apply” – and also “The Startup of You” [4]. It’s not just the machines that need to learn.

References

1. http://www.economist.com/news/briefing/21650526-artificial-intelligence-scares-peopleexcessively-so-rise-machines
2. https://www.harpercollins.com/9780062438614/only-humans-need-apply
3. For more on this, see https://www.ted.com/talk/erik_brynjolfsson_the_key_to_growth_race_em_with_em_the_machines?language=en
4. http://www.thestartupofyou.com/