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One response to these challenges could be to coordinate projects through an
umbrella programme (Evaristo and Van Fenema, 1999). However, in the early
development episodes of some kinds of innovation projects, such as medical inno-
vation or complex engineering programmes, there is much that is unknowable
in advance and interacting projects are often not governed by a programme with
pre-defined super-ordinate goals to coordinate project tasks. Instead, projects
are brought together in a rather more haphazard, opportunistic way as different
‘pieces’ of the scientific and commercial ‘jigsaw’ converge or collide over time.
Product development often follows what Lampel (2001) describes as a ‘switch-
ing’ strategy, with those involved ‘seeking high quality opportunities wherever
they might be found; trying to capture these opportunities, and then turning
their attention to transforming these opportunities into revenues’ (p. 480).
At the same time, however, complex project contexts pose significant bar-
riers to knowledge integration because there are often pragmatic knowledge
boundaries (see previous chapter) that are encountered which can impede proj-
ect interactivity. We look at these special problems next.

>> PROBLEMS ENCOUNTERED IN COMPLEX PROJECT
CONTEXTS
In complex project contexts pragmatic knowledge boundaries are likely to be
acute. For example, taking a medical example, there may be an opportunity to
develop a medical innovation that potentially allows a patient to be treated by
their GP in a local practice rather than by a surgeon in a hospital. However, the
surgeons in the hospital may refuse to work with the GPs in order to bring this
innovation into reality. Two issues thus become relevant in dealing with these
contexts. One is related to power dynamics in the inter-organizational context
and its effect on knowledge integration, and another is related to the knowl-
edge regime (in particular the Intellectual Property or IP framework) of many
high-tech industries.
With respect to the latter, it is not always clear what part of a discovery can be
patented and whether and how this knowledge can be protected. For example, in
relation to medical innovation, it is often not the molecule itself, but knowledge
about how to use it and what its effects are, that is of most value; knowledge
which cannot be easily protected via a patent. Similarly, in software development,
it is difficult to protect the software because it is so easy to work around the code,
as evidenced by Apple’s difficulties in protecting its iPhones from being unlocked
and so used on any network. This makes knowledge sharing problematic as the
financial transactions between the parties involved are based on the value of IP,
and this can be diminished if too much information is shared, even between
formal partners. Given the often fragmented nature of the development pro-
cess, organizations will guard their knowledge (e.g. in the form of IP), meaning
that ‘pieces’ of knowledge and technology tend to be transferred on the back of
economic transactions. Each party will be focused on obtaining maximum value

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