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BOOK REVIEW
Thomas H. Davenport (2005). Thinking for a Living: How to Get Better Performance and
Results from Knowledge Workers (Boston: Harvard Business School Press).
INTRODUCTION
Who are knowledge workers? What does it mean to manage knowledge workers?
And what must line managers and HR personnel do to get the best out of knowledge
workers? These then are the important questions that Thomas Davenport addresses
in this book. This book should be of interest to those in the IT sector, HR, and
management consulting. It will also be of interest to those who are interested in the
interface between knowledge management and HR. The main premise in this book -
which Davenport goes on to corroborate - is that there is an important difference
between managing knowledge workers and other types of workers. The premise is
that knowledge workers cannot be managed; they should be allowed to manage
themselves. In other words, the purpose of this book is to persuade managers that
they should hire smart workers and then leave them alone. The most commonly
made mistake with knowledge workers is to hire them and not only tell them ‘what’
to do, but ‘how’they should go about doing so. The characteristic feature of
knowledge workers is their desire for ‘autonomy’ and the fact that they don’t like to
be told what to do. As Steven Jobs of Apple put it, the whole point of hiring smart
people is to give them a chance to tell the company what needs to be done. If line
managers attempt to tell smart workers what they are supposed to do, it beats the
whole purpose of hiring them in the first place. In that sense, most smart hires are
either underutilized or simply wasted. Tom Davenport’s book is an attempt to
prevent that kind of waste from becoming endemic in not only the IT sector, but
wherever knowledge work happens.

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KNOWLEDGE WORKERS
Tom Davenport teaches at Babson College and has been affiliated with Accenture; an
important theme of his research is to identify the pre-conditions of productivity in
knowledge workers. This problem is interesting because the productivity of
knowledge workers is not reducible to a mechanical process; it partakes of a creative
element; happens in fits and starts; and cannot be planned for in the conventional
sense. But, despite the unpredictable element, knowledge worker productivity will
become - if has not already become – the main stay of an economy that is
increasingly dependent on intellectual capital, human capital, and the optimal
deployment of human resources. While it is not clear if knowledge work can be
optimizedto the extent that manual forms of work can be, it is still worth asking
what ispresently known about the pre-conditions of knowledge worker
productivity. In order to make progress in this area, I think we need to bring
together what HR personnel do with what experts in knowledge management
already know. Another important ingredient is ergonomics which constitutes the
environmental conditions that facilitate productivity. Tom Davenport draws upon
insights from all these areas in this book to make sense of knowledge worker
productivity. His definition of a knowledge worker is not reducible to a computer
programmer, but encompasses anybody (including academics) who work with
databases, knowledge repositories, and symbolically configure data, information,
and knowledge in ways that add value to internal and external customers, clients,
and students. In order to make sense of why knowledge workers are the way they
are, Davenport argues that we must identify some common attributes and segment
them as a category. That is not easy to do since they cut across a number of
professions; nonetheless they can be structured as a matrix of four types of
knowledge workers.
FORMS OF KNOWLEDGE WORK
While the study of knowledge workers in far from being a science, it is important to
at least work from a few elementary descriptions so that those who manage
knowledge workers understand how to make an intervention, increase productivity,
measure the ensuing output, and assess the quality of what is produced. The main
takeaway for Davenport is that managers need to take a soft approach since
knowledge work (except for those of a transactional or repetitive nature) is not
reducible to processes. And, furthermore, managers need to be clear as to whether
what they want from knowledge workers is ‘discipline’ or ‘innovation’ and manage
accordingly. A commonly made mistake is to treat innovative workers as though
they were doing transactional work. It is therefore important to take ‘agile’
approaches rather than conventional‘engineering’ approaches since the latter are
reductive and do not make sense to innovators. In order to manage for productivity,

3. 3
managers need to provide support in terms of organizational technology. The actual
form of such technology will depend on whether the knowledge work should take
the form of ‘integration’(of existing knowledge) or a ‘collaboration’ to put together
new forms of knowledge. It is also important to correctly assess the levels of
‘independence’ or ‘interdependence’ amongst knowledge workers in a firm.
Davenport analyses the different types of technology applications in this context
including decision support systems, artificial intelligence, expert systems,
performance support, role-specific portals, automating decisions, and knowledge
worker software.
MANAGING FOR PRODUCTIVITY
Managing the productivity of workers requires a determination of what the locus of
development should be; possible candidates for this include the levels of the
individual worker, the process flow, or the organization. The knowledge based firm
can invest at a number of levels including the individual expertise of workers,
internal networks, and personal networks. The ergonomic approach to knowledge
worker productivity is best known in the IT sector as a choice between providing
‘closed’ or ‘open’ work spaces. It appears for those trying to integrate pre-existing
knowledge; closed spaces are better but for those who wish to collaborate, open
spaces are better. Studies of knowledge worker productivity should therefore
differentiate between different types of knowledge work and not assume that these
differences do not matter to the final output measures. This approach in ergonomics
is known as ‘workplace segmentation.’Knowledge firms can be distinguished in
terms of whether they use low, medium, or high levels of workplace segmentation.
Furthermore, it is also important to know whether these firms consult with their
employees about what types of workplace environments will be most suitable for
them. These firms canbe distinguished in terms of low, medium and high-choice
from an employee’s point of view. So despite the rise of virtual technology, we find
that the physical structure of workspace plays an important role in not only the
levels of knowledge worker productivity but also in their overall sense of well-being.

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CONCLUSION
And, finally, Davenport points out that those who manage knowledge workers must
alternate between occupying the locus of the player and the locus of the coach.
Furthermore, knowledge work does not always happen inside the firm given the
pervasiveness of outsourcing; it is therefore important to think in terms of managing
communities of knowledge workers. These then are some - though not all - the steps
that will make it possible to manage for knowledge worker productivity.
The importance of this cannot be exaggerated since the long-term competitiveness of
the economy will increasingly become the function of deploying human capital in
the form of knowledge work in the years to come.
SHIVA KUMAR SRINIVASAN