Tech Savvy: February 26, 2016

When you talk business, starting with Peter Drucker is always a smart move. In Management: Tasks, Responsibilities, Practices, Drucker defined the work of business leaders by its three principal tasks: to deliver financial results, to make work and workers productive, and to manage a company’s social impacts and responsibilities. That’s all, and of course, that’s a lot.

There’s been a lot of change since Druckers’s magnum opus was published in 1974. Technological advances, especially digitization, have transformed — and continue to transform — the world in myriad ways large and small. But new technology hasn’t fundamentally changed Drucker’s tasks. Instead, it is giving rise to new and better ways and means of executing and achieving them. This new MIT SMR column aims to help you identify big ideas and new tactics at the intersection of technology and management.

The mobile method to uncovering abuse in the supply chain: The good news about global supply chains is that they offer competitive and cost advantages that were unthinkable when Ford built the first moving assembly line in 1913. The bad news is that the financial and reputational risks associated with such supply chains have increased exponentially. Ignorance is a flimsy defense when a garment factory collapse in Bangladesh kills and injures thousands of people or it is revealed that slave-workers are harvesting seafood in Thailand.

How can a company gain an unvarnished view of what’s happening in far-flung supply chains? One way is to connect with everyone working in the supply chain by tapping into the extraordinarily high penetration of mobile phones globally. That’s what a nonprofit named Good World Solutions is doing with a program that it calls Labor Link, reports associate editor Bouree Lam in The Atlantic. Labor Link allows companies to conduct surveys over the mobile phones of employees in their own and suppliers’ facilities. They can question employees about their workplaces and working conditions directly, and employees can respond without fear of reprisals.

Reengineering reprised with machines: If you’ve been around for a while, you probably remember reengineering and its catch phrase “Don’t automate, obliterate” with mixed emotions. A lot of inefficient business processes were redesigned and rebuilt; a lot of businesses reaped the rewards; and a lot of people experienced a lot of pain. Well, reengineering is back in a new, and hopefully kinder and gentler, form.

Machine-reengineering, as H. James Wilson, Allan Alter, and Prashant Shukla of the Accenture Institute for High Performance call it in HBR.org, applies machine-learning algorithms to the work of business process improvement. The authors studied more than 30 machine-reengineering pilot projects and found “evidence of significant, even exponential, business gains” in five kinds of processes: customer service, risk and compliance, finance, capability development and management, and most commonly, marketing and sales.

Managing in the Fourth Industrial Revolution: It might seem like the Fourth Industrial Revolution was launched at Davos just last month, but for a glimpse of what it really means for management, read Siemens CEO Joe Kaeser’s interview in strategy+business. In it, Kaeser touches on each of Drucker’s management tasks — talking about how he delivers results, boosts productivity, and manages social impacts in an era of digitization.

Siemens employs 17,500 software engineers — more than many software companies, according to Kaeser. One thing they’re building is virtual digital factories. “We copy a real-time manufacturing process into the virtual world to optimize engineering, processing quality, uptime, and load time — and then we copy it back into the real world of manufacturing,” he tells s+b executive editor Daniel Gross. “Together with Boeing, we simulate the whole development and engineering process for new airplanes.” Sounds like machine-reengineering may be past the pilot stage.

What to do with all the data: “There were countless industry and academic publications describing what Data Science is and why we should care, but very little information was available to explain how to make use of data as a resource. We find that situation to be just as true today as we did two years ago, when we created the first edition of the field guide.” So starts the second edition of Booz Allen Hamilton’s The Field Guide to Data Science.

The great thing about this free e-book is that it sets readers — particularly managers who aren’t well versed in data science — on the path to putting data to work. Big data cognoscenti will likely yawn, but if you, like me, don’t know discrete wavelet transforms from genetic algorithms, The Field Guide will clue you in. Better yet, if you know that your company needs to harness the insights hidden in the tsunami of data rushing by, but don’t know how to begin, one section of the guidebook is devoted to the elements of a data science capability and options involved in developing one. And I did say it’s free, yes?