Management Today's The Knowledge includes everything you'd expect to see in a regular subscription - full online access and our quarterly print magazine - plus our special in-depth reports. Full subscription information here.
The adherence of developed economies to a model of permanent employment is an ongoing puzzle. In the days of Fordism, when factory work required certainty over staffing, it made perfect sense.But with agile and reactive now key business watchwords, looking to contingent labour seems a no-brainer.
Is coronavirus the push we needed to rethink our obsession with permanence? And if you were starting a business today, would you really do it with permanent, full-time employees?
In Management Today's 12-page special report, exclusively for The Knowledge subscribers, we examine the case for contingent staffing in the context of evolving technology and the rise of the gig economy.
Business has always been a numbers game. There aren’t many senior executives who don’t know their way around a spreadsheet or who would opt to make decisions solely based on gut feeling – important though that can be – without recourse to hard evidence. But the rise of modern data science techniques seems to be turning business from an art and a science into an enigma. There is now an astonishingly successful set of companies, most prominently on the US West Coast, that can do seemingly miraculous things with advanced statistics and computer science – the kind of acrobatics that used to be confined to academic research and sci-fi novels, and that make you wish you paid more attention at school.
Unsurprisingly, and egged on by a cabal of “digital transformation” consultants that have a vested interest in making things seem even more complex, leaders of traditional businesses are falling over themselves to become data-driven – much of the time not really knowing what that means and much of the time failing, yet determined not to be left behind.
This report is designed to demystify data science . We have spoken to leading data scientists in both research and practice to separate the reality from the hype, to explore what happens inside the algorithmic black box and to examine what applied data in its various forms can actually do for businesses. We look at the questions decision-makers should be asking of their data scientists, and how to build data capabilities in your company without betting the farm. And the good news is, you won’t need a degree in statistics to understand it.