While Peter Drucker was not the earliest writer on management, he added significantly to post-WW2 understanding. First, he argued it was vital to study business and the legal, social, and ethical consequences of its freedoms to choose its purposes and practices. Second, endorsing America’s distinctive contribution to business thinking – prioritizing the customer – he anticipated our often-breathless talk of rapid market, social, and technology change, and of managing as a global rather than local practice. Third, he pointed to change within organizations. While managers had been managing work for centuries, organizational work was changing. He coined the term ‘knowledge worker’ to capture the huge shift from tangible to intangible assets as the key drivers of business success – evident in asset-light firms like Twitter and Uber. Fourth, he argued managing was never mere application of theory; it was always a craft – practical, hands on, and never entirely computable.
Sometimes the urgency of a business’s responses to changes beyond drowns out what is going on within it. How a business generates economic value remains a puzzle. Customer satisfaction is one thing, profit quite another. Despite Drucker’s many insights into the workings of the socio-economy he did not explain how economic value arises. Management’s presumably central role remained – and remains – unclear. Economists label this puzzle the ‘theory of the firm’. Drucker went beyond pre-WW2 thinking based on military order, control, and efficiency. He refreshed the path-breaking work, for instance, of Chester Barnard and Mary Parker Follett, arguing inspiring leadership lay at the core of managers’ practice and had psychological, ethical, and moral dimensions that demanded full attention. Thus he helped propel today’s psychology-based nostrums, often delivered as lists of managers’ ‘secrets’ or ‘steps to winning’.
‘Big data’ is new on managers’ radar. Its impact is direct, on the business’s processes rather than on the participants’ motivation. Business strategy is based on the facts of the situation and big data provides managers with a stunning magic telescope to reveal facts and relations otherwise hidden in the ‘fog of commerce’. Its power is so considerable many writers assert business survival depends on deploying big data correctly. Wiser commentators push back against any naiveté, pointing to the central place of the ‘human element’. Newer telescopes do indeed provide more detail, but it remains up to us to ‘connect the dots’ and make sense of what is seen, to address the most profound of a business’s questions: “What does it mean for us?”
At first sight Drucker’s contribution was to remind us that managing is not as mechanical as many suggest, rather it is a human practice embedded in the tangled weave of our ambitions, relations, and politics. Many commentators write about making organizational life more sympathetic and here Drucker was clearly in the van. Maybe closer attention to ethics, social responsibility, and ecology will improve us. But his ‘knowledge worker’ moves us in a different direction that may prove even more important. Rather than the interaction between hardness of goal-directed labor and the softness of our social, political, or psychological natures, he reminded us of the complexity of human knowing. This is essential to gauging the impact of big data and its limits. In spite of the flood of exciting news about the mind, computation, and artificial intelligence, Drucker’s notion of ‘knowledge’ was radical because it looked beyond computable facts. What we mean by the human element is tied up with our sense that ‘the facts’ are never all we know about our world or ourselves; facts never fully determine our practice. We have passions, culture, and a history. Drucker’s knowledge worker presumed those other aspects of human knowing that are essential to understanding the human condition – and profit – as non-mechanical and, perhaps most significant of all, deeply shaped by our imagination.
As we know, we do not live by bread (facts) alone, but also by the word. Organizations are contexts of managerially-generated ‘natural language’ or communication with words, signals, and symbols that excite and shape the imaginations of others. Natural language goes way beyond logical ‘formal language’, proofs and formulae, to shape others’ non-factual ways of knowing. A poem is not a rigorous equation; yet it has power to persuade precisely because we are creatures of emotion and imagination. Ultimately leadership is persuading others to do things they would not do otherwise – through passion rather than proof. Hence management’s most powerful tool is persuasive language rather than data. A value-creating business is a poem in motion, an opera perhaps; not a well-structured data repository.
Our insatiable appetite for natural language-interaction drives our newest industries just as Adam Smith noted our tendency to ‘truck and barter’. A Twitter message of 140 characters, surely the opposite of big data, is seldom a packet of dry data. Perhaps it is a haiku or a sonnet. It impacts someone’s living. No question, data is often material but never all we need to determine practice in the lived world. Real time big data may alert a retailer to a product flying off the shelves, but what does it mean? Likewise data from a drone may suggest, perhaps, a rooftop sniper. What is revealed turns on how we respond to the data. Is the item underpriced? Is the figure someone sleeping? Do movements at a North Korean site reveal a nuclear test? Obviously the boundaries around big data’s capabilities and practice are changing fast, with the ‘internet of things’ as much as with deeper mining of ever more voluminous data. But the strategic meaning of what is revealed is never contained in the data gathered. Facts never ‘speak for themselves’; their meaning is always embedded in how we live. Management’s skill lies in layering the knowing they distill from their business’s living over the data they gather. Big or small, the data question is always strategic: “What does it mean to us?”
About the author:
JC Spender trained first as a nuclear engineer then in computing with IBM. He moved into academe as a strategy theorist, opening up a subjectivist/creative approach that complements mainstream rational planning notions of strategizing. This 40-year project was brought to completion in Business Strategy: Managing Uncertainty, Opportunity, and Enterprise (OUP 2014).
One thought on “Drucker’s Knowledge Work and Big Data’s Strategic Impact
by JC Spender”
I completely agree with Professor Spender. Since I first became interested in organizational knowledge several years ago, I have been making the case to place language front and foremost as the stage on which knowledge work – and all other human activities in the context of the organization and beyond – is located, and as such provides a valid target for study from a psychological, discursive perspective.