ABSTRACT
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The twentieth century brought a massive shift in the developed world, from national economies centered on industrial manufacturing to a global economy dominated by knowledge-based organizations. It’s debatable that the practice of management ever caught up with the implications— yet now, a fresh wave of transformative change is upon us. Artificial intelligence tools are now automating many intellectually challenging tasks, remote work arrangements are distributing them, and new platforms support collaborative innovation.
These new tools produce challenging disruptions at every level, from the strategic shifts required of global companies and the coordination problems faced by leaders of distributed teams, to individuals’ expectations of what work should demand of and provide to them. How shall we find in them the opportunities to achieve benefits for all? We think Peter Drucker was right that “the most important contribution management needs to make in the 21st century is to increase the productivity of knowledge work and knowledge workers.” When more intellect can be applied to solving human problems at lower cost—to the customer, to the producer, to the worker—everyone gains. Now a quarter-century into the century, where do we see organizations achieving breakthrough performance, and how? What lessons are we learning from the pioneers of the next knowledge work?
KEY QUESTIONS
a) What did the term knowledge worker imply in the past? What kind of knowledge did they arrive with and how was it enhanced on the job? How were those people managed? What attracted them to a position? What motivated them to do their best?
b) How has that changed, and why? Who are knowledge workers today? How do organizations think differently about their motivations and how to manage them?
c) What do we know from psychology/anthropology/social psychology research about what fundamentally makes work meaningful and what motivates people to work toward shared objectives?
d) What will knowledge work look like next, and why? How will this challenge organizations and how they are managed?
e) Why is it important to get smarter about the next knowledge work and how to make it more productive? What would a failure to do this cost us? What is at stake?
a) Are there “zombie management” practices affecting knowledge work that are known to be counterproductive and that should be dead by now—but that somehow keep springing back to life? Why are they so hard to get rid of?
b) How do some traditional practices in people management present barriers or undermine the progress of knowledge work? What faulty assumptions are at the heart of them?
c) Beyond traditional “people management” practices, what other realms of management need to be overhauled to achieve better outcomes from knowledge work?
a) Who is doing the most promising and intriguing research relating to the next knowledge work? What do their findings imply for practical changes that could be made?
b) What experiments are taking place in organizational settings to achieve greater outcomes from knowledge work? What was the reason for the intervention, what was the expectation in making it, and is it bearing out? How promising are the results so far?
c) Do different practices or conditions prevail in different places—regionally, nationally, or in specific economic sectors—that enable them to be more creatively productive?
a) What organizations are currently outperforming their peers in terms of knowledge work effectiveness?
b) How do we even know that? How should their success be compared? What metrics are the best ones to focus on in assessing knowledge work performance?
c) What are they doing differently and how much difference has it made to outcomes?
d) Is the approach they are taking portable? To what extent could an organization in a different sector or geography apply it and expect similar success?
e) Will AI have the same impact on knowledge work productivity that industrial machinery had on the craft and manufacturing work of the past? Will its impact be even greater?
f) To what extent will organizations be reshaped by their embrace of AI? How might they come to look different in the next ten years, twenty years?
g) What principles should guide the development and adoption of tools to perform intellectually challenging work?
h) What applications of AI so far should we take lessons from, both encouraging and cautionary?
a) What kind of leadership is required for knowledge work to make faster and more meaningful progress on important objectives?
b) How has that changed? Is there an old model of leadership that must be abandoned?
c) What kind of development path prepares people for the kind of leadership now needed? What do we know already about how that kind of leadership emerges in organizations? Are there any promising new ways to cultivate it?
a) What changes have been shown to boost creative collaboration?
b) What changes would reliably create greater motivation to perform at high levels?
c) What changes would meaningfully raise the expertise of the organization?
d) What kinds of AI or other information technology applications would augment human performance most … do most to build strong customer relationships … have most positive impact on the workforce?
e) How should performance measurement and performance management change?
f) What features of an employment offer would present the most attractive value proposition to today’s talent market?