BALANCING EXPLORATION AND EXPLOITATION: A FORMAL
COMPARISON OF PUNCTUATED EQUILIBRIUM AND
AMBIDEXTERITY
Olivier Dupouët
BEM Management School Bordeaux
olivier.dupouet@bem.edu
Tatiana Bouzdine-Chameeva
BEM Management School Bordeaux
tatiana.chameeva@bem.edu
It has long been recognized that firms that succeed in the long run are able both to fulfil
immediate market needs and to forecast and adapt to future trends (Abernathy, 1978). In the
words popularized by March (1991), successful firms are those that balance exploitation and
exploration. To quote March (1991), “The essence of exploitation is the refinement and
extension of existing competencies, technologies, and paradigms. … The essence of
exploration is experimentation with new alternatives” (1991: 85).
If there now seems to be a wide consensus on the above definitions and on the need to balance
adequately these two cognitive activities, there is however little agreement on how this
balance is actually achieved (Gupta et al., 2006). Over time, three main, but significantly
different, mechanisms have been proposed, namely punctuated equilibrium, structural
ambidexterity and contextual ambidexterity.
Following the punctuated equilibrium model (Gersick, 1991; Tushman and Romanelli, 1985)
firms spent most of their life in exploitation phases. However, at some points in their history,
discrepancies between their environments and internal processes, procedures, and knowledge
become so important, that firms trigger major changes and undergo complete reorganization
and strategic reorientation (Ohja et al., 1997). Once changes implemented, firms enter a new
exploitation phase. The key mechanism at the heart of punctuated equilibrium is thus a
sequence unfreeze-modify-refreeze (Weick and Quinn, 1999).
1
Whereas punctuated equilibrium proposes a sequential vision of the relationships between
exploration and exploitation, the notion of ambidexterity proposes that the two kinds of
activities can be conducted in parallel in one single firm (Gupta et al., 2006). However, there
is debate on how firms can actually be ambidextrous, and the ambidexterity approach can be
split into two distinct streams, structural ambidexterity and contextual ambidexterity
(Birkinshaw and Gibson, 2004).
With structural ambidexterity (Benner and Tushman, 2003; O’Reilly and Tushman, 2004), it
is proposed that agile firms have developed specific entities or structures dedicated to either
exploration or exploitation. Depending on the cognitive orientation of a given structure,
specific incentive systems, controls and governance mechanisms should be attached to it. The
coherence and coordination of the overall firm is ensured by the top management that
possesses the necessary skills to arbitrate between exploration and exploitation and to decide
the orientation of future exploration efforts. In this view, ambidexterity thus relates to a
dynamic capability (Teece et al., 1997).
Proponents of the second kind of ambidexterity, contextual ambidexterity, take quite a
different stance. In their view, ambidexterity is not so much realized at the structural level, but
at the one of individuals (Gibson and Birkinshaw, 2004; Birkinshaw and Gibson, 2004;
Hargaddon and Fanelli, 2002). Provided a favourable context, individuals organize their
working time so as to integrate both exploration and exploitation activities in the course of
their daily tasks.
Interestingly, each of these three accounts enjoys empirical support. This raises a range of
questions. Can a firm freely choose one of these approaches? Are the different approaches
substitutable, complementary or orthogonal? Is one solution to be preferred to the others? As
a first step toward answering these questions, this contribution proposes a formal model
providing a framework encompassing the three approaches. Within such a framework, it will
be possible to compare the different mechanisms in an unambiguous way.
The paper is organized as follow. Section 2 presents the theoretical foundations and examples
of each of the three balancing mechanisms. Section 3 and 4 will successively present our
formal models and the derived results. Section 5 discusses and concludes.
2
In this section, we will present in turn the three main mechanisms identified in the literature
through which balance between exploration and exploitation is achieved, namely punctuated
equilibrium, structural and contextual ambidexterity. For each of these processes, we will
present the related decision making processes and organizational designs.
Firms adopting a punctuated equilibrium mechanism mainly live in exploitation phases. We
will call exploitation every activity that reinforces the overall coherence of firm’s activities.
When engaged in exploitation activities, agents will seek to incrementally enhance or
suppress existing competencies (Gatignon et al., 2002). More precisely, let us consider the
firm as a set of activity systems (Blackler et al., 1999; Porter and Siggelkow, 2007). These
systems are articulated in a more or less harmonious manner in order to deliver goods or
services to the markets. Now, firm’s performance will critically depend on the level of
coherence among these activity systems (Milgrom and Roberts, 1990; Siggelkow, 2001;
Porter and Siggelkow, 2007). In order to reach this coherence, firms’ actors will strive to
reduce ambiguities and inconsistencies that hinder their performance at work.
This process of activities tightening leads to greater coherence of the firm but also to a
narrowing of its core business. As a result, firms become increasingly good at what they do,
but unable to develop activities outside their core competencies. It then becomes increasingly
difficult for them to escape their current development path, and core competencies turn into
core rigidities (Leonard-Barton, 1995). The firm can perform well as long as its environment
is stable. However, as the environment drifts, performance decreases, and pressures for
change increase up to a triggering threshold (Ohja et al., 1997). As firms do not have the
adaptive abilities to smoothly cope with changes, firms enter a revolutionary period (Weick
3
and Quinn, 1999). In entering such a period, firms freese their current organization and
processes and start to develop a whole new model that will substitute the current one.
Once the organization frozen, firms enter an intense exploration phase. Whereas exploitation
seeks a convergence between the different activities of the firm, exploration seeks to invent a
new set of activity systems. Exploration mechanisms will lead the development of
competencies that where not previously existing within the firm (Gatignon et al., 2002). Via
the search for and appropriation of knowledge new to the firm (be it the adoption of new
technologies, new management methods, or entry into new markets), exploration mechanisms
will involve the introduction of new activities inside the firm. These new activities will
necessitate the re-design (total or partial) of the existing system (Tushman and Romanelli,
1985). Hence if exploitation can be related to single loop learning, exploration has to do with
double loop learning in the terms of Argyris and Schön (1978).
In the punctuated equilibrium model, changes are dramatic and concern the entire
organization. Exploration here leads to important redesign of the organization and major
strategic re-orientation. Given this wide scope and the amplitude of changes, entering
exploration is decided at the highest hierarchical level of the hierarchy. Decisions and actions
are then passed to lower levels. Such process is thus top-down. Accordingly, changes are
planned and formal. “The change process becomes a sequence of events in which a person (a)
determines or defines what currently exists (what is A), (b) determines or defines its
replacement (Not-A), (c) engages in action to remove what is currently there, and (d) implants
its replacement” (Ford and Ford 1994:773, 775). The organization of change thus implies a
“mirror” organization that is specifically set to carry out exploration. For instance, project
groups and task forces can be created to address some specific aspect of changes.
The intent of the exploration phase in the punctuated equilibrium model is to change the deep
structure of the organization (Gersick, 1991). The output of the process is thus an entirely new
organization endowed with new strategic objectives and processes. Given the importance of
changes and the efforts necessary to conduct these changes, the process is irreversible. For the
better or the worse, once modifications are implemented, the organization cannot return to its
prior state (Gersick, 1991).
4
Given the costs and risks associated with changes through punctuated equilibrium
mechanisms, they are infrequent (Weick and Quinn, 1999; Gersick, 1991). Once the
exploration phase finished, the firm unfreeze the new organization and starts a new
exploitation phase intended to last a long time period.
Whereas punctuated equilibrium sees the balance between exploration and exploitation
achieved in a sequential way, ambidexterity asserts that both can be conducted in parallel. For
structural ambidexterity, this ability stems from a thorough and careful design of the
organization (O’Reilly and Tushman, 2004). Ambidextrous firms are those that manage to
yoke organizational structures dedicated to exploration and others specifically focused on
exploitation.
Because exploration and exploitation are different cognitive activities in nature, they entail
very different management styles, incentives, and control systems (Benner and Tushman,
2003). Since exploration and exploitation are very different activities supported by different
governance mechanisms and structures that are incongruent, clear boundaries must be drawn
around each organizational unit in order to preserve its idiosyncratic subculture and mode of
functioning.
Seen in this way, the firm runs the risk of seeing some of its elements falling apart from the
rest of the organization or of being unable to transfer knowledge across its internal boundaries.
To overcome these potential pitfalls, the firm has to tightly couple its different parts (O’Reilly
and Tushman, 2004). This coupling is made at the top-management level that is
knowledgeable enough to make the relevant resource allocations. According to O’Reilly and
Tushman (2004), managers of ambidextrous organizations are at the same time rigorous cost
cutters and free-thinking entrepreneurs. The very first phase for a firm willing to become
structurally ambidextrous is thus to build a senior management team that would gather such
individuals.
The input of the structurally ambidextrous firm is its organizational design. Such firms appear
as a set of autonomous units engaged either in exploration or in exploitation, tightly coupled
5
by few but strongly maintained and closely controlled communication channels. This setup is
designed and monitored by few artful managers.
Once set in a top-down manner, each of the defined unit will function in an autonomous way.
O’Reilly and Tushman (2004) attach to exploration oriented structures a culture of flexibility
and experimentation, in which entrepreneurship is rewarded and which critical tasks is to
achieve breakthrough innovation. Exploitation-oriented units would be characterized by the
search of efficiency and risks minimizing, where controls would focus on margins and
productivity and which have for mission to increase efficiency in operations.
The different units are connected by few robust and well-controlled pipes. The topmanagement does not limit its role to the implementation of these channels. They also intend
to control the content of communications. In this model, the top management has the ability to
decide where exploration should be carried out, when newly acquired knowledge is mature
enough to be transferred to other parts of the organization, what kind of knowledge should be
transferred, etc. These attributes of the management entail that it is able to screen firm’s
activities and to operate choices on what kind of knowledge should be diffused, how, and at
what pace.
Structurally ambidextrous organization permits firms to develop on a regular basis new
products, to enter new markets, or to foster new technologies to be combined within existing
activities. While potentially important, these changes are not as dramatic as those delivered by
punctuated equilibrium changes. On the other hand, new knowledge and innovation arise
more frequently in the structural ambidexterity model than in the punctuated equilibrium one.
As Benner and Tushman (2003) underlines, structural ambidexterity is a means to combine
old and new. Structurally ambidextrous organizations are able to maintain significant parts of
their traditional business while exploring new lines of development. The outputs produced by
each experience provide insights that help managers decide whether and where corrections
should be brought to the organizational design.
6
A second line of thought, termed contextual ambidexterity by Gibson and Birkinshaw (2004),
gives a different account for ambidexterity. For contextual ambidexterity, exploration and
exploitation are realized simultaneously by a firm, but this ability does not lie primarily in
structures but at the individual level. In this view, individuals are able at their work stations to
switch in a seamless way between explorative and exploitive activities. Exploration is thus
achieved locally on a daily basis. In this sense, change is continuous rather than episodic
(Orlikowski, 1996).
In the framework provided by the contextual ambidexterity, the role of formal structures is not
totally dismissed but its importance is reduced. The most important role of management here
is to set few, but strong, coordination and alignment mechanisms. Such mechanisms are
called “stretch” and “discipline” by Gibson and Birkinshaw (2004) that borrowed these
concepts from Ghoshal and Bartlett (1994). Stretch captures the idea that incentives
mechanisms exist that pushes individual to give maximal effort. Discipline encompasses a set
of cooperation mechanisms that ensure that every agent will strive toward similar objectives
and will obey common rules. Similar ideas have been developed by Brown and Eisenhardt
(1997) and Okhuisen and Eisenhardt (2002) who propose that simple formal mechanisms
such as information sharing, questioning others, and time management suffice to ensure the
overall alignment of individual endeavours within firms.
Besides these constraining mechanisms, the management must also develop a contextual
dimension that will favour creativity and autonomy (Brown and Eisenhardt, 1997; Gibson and
Birkinshaw, 2004). These attributes are called support and trust by Ghoshal and Bartlett
(1994). They contribute to build a social support that provide security and freedom for people
to experiment new ways and innovate.
Contextually ambidextrous organizations thus appear as mixing mechanistic and
organizational features (Weick and Quinn, 1999). In such a setting, the top management
remains at the backstage and the process of balancing exploration and exploitation is
essentially bottom-up.
Once an enabling structure set, the bulk of cognitive activities is carried out in an informal
way. In the course of their daily activities, individuals can blend exploitative and explorative
7
behaviours. This is rendered easy thanks to the increasing use of information and
communication technologies, and computer-aided simulation tools.
Of course, agents do not work in isolation. However, and contrary to the structural
ambidexterity view, relevant social structures are not the formal but the informal ones.
Through their activities, agents develop informal network (Hansen, 1999) and engage in
communities of knowing (Boland and Tenkasi, 1995). Such structures are the places within
which agents can exchange on new ideas, share best practices, and make sense of their
environment. They thus become privileged social loci for knowledge creation and
maintenance. Besides their role in knowledge creation, informal structures also serve as
channels for knowledge diffusion. They provide the substrate upon which knowledge can
diffuse, and be combined to develop further knowledge.
Newly developed knowledge is made visible to the rest of the organization through different
channels (Knorr-Cetina, 1999). Knowledge can be diffused by editing a public document, by
the action of a spokesperson convincing the organization of the value of a community’s
production, or shifts in practices that are visible in hierarchical functions. Once the newly
produced knowledge is visible, managers can grasp and assess it. As Tsoukas and Chia (2002)
state, managers assess the new knowledge produced and practices sustained by the different
communities and networks. If these knowledge and practices are deemed useful for the
organization, managers will “voice” rules that will permit to foster the new knowledge and/or
practices. The new rules will express the conditions for knowledge expression and enactment
(Tsoukas and Vladimirou, 2001) in the organization. In the contextual ambidexterity view, the
role of management is to recognize emerging behaviors, assess them, and, if judged valuable,
make them more visible and reframe them (Weick and Quinn, 1999).
Compared to the two other models, changes are here very frequent but have low amplitude. In
the contextual ambidexterity model, changes are modest and conducted in localized pockets
of innovation in the firm. Macro-changes arise from the accumulation and aggregation
multiple individual initiatives (Orlikowski, 1996). Seen this way, innovation and introduction
of newness never ends and change is continuous rather than discrete. Corrections in the
structure will seldom occur. The top management will intervene only if it perceives that the
innovation and exploration of new potential paths dry up.
8
Each of the possible balancing mechanisms described above entails both decision making
processes and specific organizational design. Punctuated equilibrium and structural
ambidexterity supposes a thorough formal structure with clearly identified structures roles. On
the contrary, contextual ambidexterity supposes that informal networks are encouraged within
the organization. However, to our knowledge, there is no systematic exploration of the
various possible combinations of balancing mechanisms and underlying structures. In addition,
there is still significant work needed to investigate the conditions under which one balancing
mechanisms is superior to others. In what follow, we intend to investigate these questions by
resorting to a formal model.
!
The model proposed here is made of two main parts. First, we define a certain number of
design elements that will be used to implement various organizational structures. We define
the organisation as follow.
n – The number of agents in the organisation
T(k)
–
A
task
n-element
array
specifying
the
occupation
of
every
agent
(exploitation/exploration). We shall say that for example Ti(k)=0 means that agent i is
doing exploitation during the period k, then Tj(k)=1 will mean that agent j is doing
exploration during the period k. Quite intuitively, Tj(k)=0.2 will mean agent j is
devoting 20% of his time to exploration and 80% to exploitation. Although there is no
special reason as to why exploration be identified by 1 rather than 0, it is simply a
representation. Note that some of the following formulae will obviously depend on the
choice.
E(k) – An efficiency array Ei(k) would represent the efficiency of agent i in the period k. A
value of 1 would mean that the agent has done all the work he was expected to. For
simulation simplicity (and for social equality and political correctness), we will set this
parameter to 1 for all agents during the simulation.
W(k) – An array representing the amount of work. Wi(k) is the amount of work an agent i is
expected to do during period k. As a result, and as an example, Wi(k)Ei(k) the amount of
9
work an agent has effectively done during the period, if all the other agents have also
done their work correctly.
A – A matrix representing the dependencies between the various agents within the
organisation – aij, would mean the proportion of agent j'
s work that depends on the
work of agent i. As a consequence, the sum of all the elements of a column of matrix A
will be equal to 1.
The organisation structures will be modelled using different configurations for A (e.g. Ishida
and Otha, 2001). Three types of organizations will be considered. The first type corresponds
to a team-based organization. In that case, each agents work will depend on few others, but
will remain independent from most part of the firm. The second type would correspond to a
more hierarchical structure within which all agents work will depend on few managers. The
third type will correspond to a fully decentralized (network) organization in which each agent
has to know a little about the actions of all the others, even though his work mostly depends
on himself.
We suppose that a cost is associated with each communication. We suggest that Cc(A), the
communication cost, is based on the matrix A and can be defined as follows
Cc ( A) =
1, ifai , j > 0 : C c , 0
i , j ,i ≠ j
0, ifai , j = 0 : 0
Which means that there is a cost Cc,0 for the organisation whenever agent j communicates
with agent i about j'
s work.
In addition to structures, we model two different mechanisms of organisational learning
linked with two cognitive regimes, exploration and exploitation tasks undertaken by an
organisation. These two mechanisms differ in that one is sequential whereas the other is
parallel (Knudsen and Stieglitz, 2007):
1) Punctuated Equilibrium case (PE), when an organisation switches periodically and
completely from exploitation to exploration;
2) Ambidexterity case, when exploitation and exploration tasks are carried on
simultaneously. This second case comprises two possibilities: structural (SA) or
contextual ambidexterity (CA).
10
Let us first define exploitation and exploration activities. In our model, we describe
exploitation and exploration by two functions, X and L respectively, that are defined to
depend upon the structure of the organisation. X(k) is defined as
X (k ) = X 0
n
j =1
(1 − T j (k ))
n
i =1
aij (k ) Ei (k ) W j (k )
Where the (1 − T j (k )) part is just intended to exclude exploring agents from the sum, and
n
i =1
aij (k ) Ei (k ) represents the portion of the expected amount of work the agent j has been
able to do, given the work efficiency of his colleagues. We consider that firms earn money
only thanks to their exploiting activities. Exploration is considered as investment and is not
considered as productive. Consequently, X(k) is the benefit earned by the organisation during
the period k. X0 is a general coefficient representing the benefits from exploitation. A high X0
would mean high benefits for a given amount of work (more about this later).
We model exploration as an activity through which an organization is able to enhance its
processes and products. Exploration will move the organization from a level lk to a level lk+1 at
which the firm can expect higher profits. Firms shifts from one level to another following
l k +1 = l k + L(k )
Where L(k) is the level increase obtained through Exploration during period k. We define the
L(k) function, the level increase function, as
L(k ) = L0
n
j =1
T j (k )
n
i =1
a ij (k ) Ei (k ) R j (k ) W j (k ) 1 + ε
In this function, we have added a synergy effect, 1 + ε
Ti (k )Wi (k ) .
i∈[1, n ]
i≠ j
ai , j > 0
Ti (k )Wi (k ) . The agent benefits
i∈[1, n ]
i≠ j
ai , j > 0
from the work of other agents he is in contact with and that are working on exploration. The
effect has its strength defined by ε . ε = 0 would mean no synergy effect. R j (k ) is a random
variable determining the efficiency of the agent'
s exploration during the period k. L0 is a
general coefficient representing the complexity of the exploration.
11
To define firms’ environment, for simplicity, we examine a case of market saturation. Given
our model, we have to define X0 such that it will reflect the fact that the market has only a
certain capacity to accept products of a given level. When the market is being saturated by a
product the benefits of the company will decrease (Van Looy et al., 2005). We will express
this through the score extracted by the company from its environment S'. S' does not include
the various costs, and it will tend to limit the gains of the company. So to sum up, the more
benefit the company has already extracted from the environment, the less benefit the company
will get, unless it explores for new sources of benefit. The parameters are thus defined as
X 0 (k ) = e
−S '
k
Mlk
S'
k = S'
k −1 +l k X ( k ) : S '
0=0
Where M represents the capacity of the environment to absorb a product of level lk. M can be
understood as an index of environments’ stability. A small M yields to a quick market
saturation and would require a high frequency of exploration to adapt to environmental
changes. Conversely, a large M is indicative of a large market able to absorb large quantities
of a similar product/service and would thus favour exploitation.
Wrapping up things together, we eventually define the benefit of the firm at the end of period
k as:
S k +1 = S k + l k X (k ) − C (l k , l k +1 ) − C D (T (k ), T (k + 1)) − C C ( A); S 0 = 0
Where:
Sk is the benefit at the beginning of the period k, Sk+1 is the benefit at the end of period k
(hence at the beginning of period k+1);
lk is the level achieved at the beginning of period k (and lk+1 the level at the end of the period k
and at the beginning of the period k+1).
In addition, some costs are associated to each decision and action (Nickerson and Zenger,
2002), C (l k , l k +1 ) =50 ln(l k +1 − l k ) is the cost for getting the organisation from level k to level
k+1, which is done during this period. The logarithmic function accounts for an “experience
effect”: the first innovations are costly for firms. However, as they acquire experience, the
cost of moving from one level to another is less and less important.
12
C D (T (k ), T (k + 1)) , the cost of decision making, is the cost of affecting an agent to a task
other than the one he was affected to in the current period. It can be formulated as the
comparison of the arrays T(k) and T(k+1):
C D (T (k ), T (k + 1)) =
n
T j (k ) ≠ T j (k + 1) : w
j =1
else : 0
We now need to include decision making (or managerial effect) into our model. When
exploration is needed, the model would switch all its agents (PE), increase the number of
agents exploring (SA) or increase the time devoted by each agent to exploration (CA). We
suppose that an organisation that sees its profits declining will have a tendency to start
exploring for a new source of benefits, and as opposite, an organisation with rising profits
would tend to spend its resources on getting all it can from its market before the market starts
to crunch. Hence decision-making can be described as affectation of agent-time to exploration
or exploitation according to environment situation. To incorporate this in our model, we
define a simple decision-making algorithm:
if benefits are above an upper threshold
SA: increase proportion of agents exploiting (This decision affects only some agents.)
CA: increase proportion of time devoted to exploitation by each agent (This decision
affects all agents.)
if benefits are below a lower threshold
SA: increase proportion of agents exploring (In the case of structural ambidexterity,
firms will decide to increase the number of agents in the units dedicated to exploration.)
CA: increase proportion of time devoted to exploration by each agent (In the case of
contextual ambidexterity, every member of the organization is encouraged to engage in search
activities.)
Otherwise we stay on the same level (do nothing).
Note that this algorithm does not suit the PE organisation, whose benefits are by definition
negative during exploration. The algorithm for PE would be:
if benefits below a threshold and organisation exploiting
switch to exploring for the next p periods;
if exploring p-period over
switch to exploiting;
13
otherwise we stay on the same level (do nothing)
" # $ $
Our model allows us to build nine organizational types by compounding the three structures
(hierarchical, team-based, and network organizations) and the three balancing mechanisms
(punctuated equilibrium, structural ambidexterity, and contextual ambidexterity). In what
follows, these nine organizational configurations are confronted to two market situations. The
first situation is a stable environment, i.e. the market is very large and can absorb huge
amount of products proposed by firms. As a consequence, there is no strong need for
innovation, and hence for exploration. By contrast, a turbulent environment is conceived as
one quickly saturated by proposed products. As a consequence, in such a situation, firms need
to continuously produce newness and hence to engage in exploration activities. The degree of
turbulence is controlled in our model by the parameter M. Below, we contrast two situations,
stable environment (M = 100) and a fast changing environment (M = 25).
14
The results of numeric simulations for M = 100 are presented in the table 1 below.
Team-based structure
Network structure
Hierarchical structure
Among the nine possible configurations, team-based structure coupled with structural
ambidexterity is performing the best in the long run. This can be explained by two tokens.
First, since in the team-based structure design, communications occurs only among team
members, the associated costs are low compared to the other organizational designs. Second,
structural ambidexterity only devotes a portion of agents to exploration activities and keeps a
large proportion of the personnel to exploitation. Since, on a stable market, exploitation is the
most successful strategy, structural ambidexterity is the most suited mechanism.
Another interesting thing to note is that punctuated equilibrium is performing well in any
situation. In other words, punctuated equilibrium may be viewed as a wildcard strategy for
15
firms. This result comforts previous findings according to which punctuated equilibrium may
be a solution preferred by managers since it economizes on their attention (Levinthal and
March, 1993; Burgelman, 2002). Punctuated equilibrium is a rather mechanistic process by
which firms switch from exploration to exploitation every n periods. The cost of decision
making is thus very low in this process. In addition, in punctuated equilibrium, firms have the
power to mobilize all agents either in exploration or exploitation. Hence, in a stable world,
punctuated equilibrium allows firms to reach high scores.
In stable markets, the worst configuration combines network structure and contextual
ambidexterity. Network structure is the one that entail the most important amount of
communications and the costs thereof. This kind of structure is thus ill-suited in stable and
predictable environment. Besides, contextual ambidexterity encapsulates a strong incentive
system toward exploration. As a result, agents are encouraged to explore while this is clearly
not the most valuable cognitive activity in a stable environment.
When the environment becomes unstable, things are quiet different. The results of numeric
simulations for M = 25 are presented in the table 2 below for the 80 first periods and 50 last
periods.
In such a situation, best performances are reached by the configuration combining team-based
structure and contextual ambidexterity. Since the market is now turbulent, engaging in
exploration activities becomes the road to success. Contextual ambidexterity is the process
that engages the most agents in exploration activities. Consequently, firms adopting
contextual ambidexterity react faster than the other in a turbulent market and reach faster the
adequate level of innovation to make benefits. When combined with the team-based structure
that economizes on costs, one ends up with the most successful kind of organization in this
kind of market1.
The worst performance in this market is achieved by the combination of network structure
and punctuated equilibrium. This particular combination cumulates the disadvantages of high
1
We also run simulations with M = 10. Under these conditions, the most successful firm is the one that combines
network structures and contextual ambidexterity. In that case, the exploration power of network offsets the costs
associated with such a structure.
16
structural costs and low adaptation to market changes. In addition, since punctuated
equilibrium can only mechanically switch between exploration and exploitation, this
mechanism does not allow for a smooth adaptation to market signals. As a result, the
organization is never able to properly balance exploration and exploitation in response to
environmental demands.
An interesting case is the behaviour of hierarchical structure for structural ambidexterity and
punctuated equilibrium. In the first period, firms adopting these balancing mechanisms
encounter some difficulties in reaching the level of innovation required by the market. As a
result, their benefits are decreasing in the first periods. However, as time unfold, the portion
of efforts dedicated to exploration is progressively increased in the case of structural
ambidexterity, and the level of innovation is steadily (and quickly enough) raised in the case
of punctuated equilibrium. As a result, after a certain amount of time, these mechanisms allow
firms to catch up with the level of innovation required by the environment2.
Team-based structure
Network structure
2
Hierarchical structure
For M = 10, the requirements in terms of innovation are so high that they offset the advantages that the
hierarchical structure offers in terms of communication costs.
17
!
The results presented so far are roughly congruent with previous work on balancing
exploration and exploitation in organizations (e.g. Nickerson and Zenger, 2002; Eisenhardt
and Santos, 2001). To sum up, the more an environment is stable, the more firms should rely
on exploitation and formal, well-designed structures. Conversely, as the market becomes
more turbulent, firms should encourage individual exploration and favour the development of
informal structures. However, our model allows us to investigate more possibilities.
= 0.01
= 0.5
"
#
!
18
= 0.9
In this section, we have varied the parameter for a given market and organizational structure
(the team-based structure)3. The results are summarized in table 3 above. In our model,
represents a “ synergy effect” . A high value of
work.
means that agents benefit from each other’ s
can thus be seen as a parameter controlling the level of collaboration within
organizational structures. The quality of collaboration can result from a good communication
network or from a high level of trust, for instance.
We introduced in the exploration mechanism, which means that a high level of would lead
to an increase in explorative power. In other words, any kind of organizations will see its
explorative power increase, while the structural costs will remain the same. Under these new
conditions, the network structure and the contextual ambidexterity loose their advantages in
terms of exploration. As a consequence, as each configuration enjoys increasing explorative
power, the discriminating variables become the costs and punctuated equilibrium (that
benefits from the lowest structural and decision making costs) increasingly dominates (table
3).
!
Another lever that can be used by firms is the amount of effort they decide to devote each
time they enter an exploration phase. In our model, each time organizations decide to start
exploration, they also decide the level of effort that would be allocated to exploring activities.
In the case of structural ambidexterity, the firm decides that a certain umber of agents will
spend to exploration activities some of their working time, up to a certain amount. If more
exploration is needed, then more agents will be designated to invest the same time ratio to
exploration. In the case of contextual ambidexterity, all agents spend some of their time to
exploration. To increase exploration, this working time portion is increased for all agents.
Punctuated equilibrium is not affected by this kind of decision: every p period, either all
agents spend 100% of their time either exploring or exploiting.
T = 0.1
T = 0.2
3
T = 0.5
We have run simulations for different values of M and for each of the organizational structures. Though
quantitatively different, the qualitative analysis remains the same.
19
$
#
%
!
In the table 4 above, we compare performances of the team-based structure for the three
balancing mechanisms when the effort allocated to exploration is varied. Increasing T has no
effect on organizations resorting to punctuated equilibrium and structural ambidexterity.
Concerning punctuated equilibrium, this is not surprising, since this mechanism is
independent of T, agents switching regularly between fully exploring and fully exploiting.
Concerning structural ambidexterity, the effect of increasing T is limited by the fact that
once all agents have been required to spend T of their time to exploration, the organization
has reached its maximum exploration capacity. Hence, investments in exploration are
thwarted by the structure of the balancing mechanism.
Contextual ambidexterity is sensitive to variations in T. Since the exploration potential of
contextual ambidexterity is not structurally bounded (contrary to structural ambidexterity) this
mechanism can benefit from increase in
T. The main effect is to render the curve more
hectic. As T increases, each time step spent in exploration phase leads to higher innovation
level. As a result, organizations resorting to contextual ambidexterity need to spend less time
in exploration phases. However, higher T does not lead significantly higher performances
20
because agents have less time dedicated to exploitation and can thus not reap the benefits of
their innovation efforts.
! %$
$$
&
# $
How organizations can balance their exploration and exploitation activities is an important
topic for practitioners and academic alike. However, a complete answer to this question is still
to be provided. Addressing this question through a formal model allows us to contribute to
this field in several aspects.
Our model broadly validates previous work on the respective application of the different
balancing mechanisms. In a stable market, exploitation and formally designed firms are better
suited. Indeed, under such environmental conditions, firms do not have strong pressure for
innovation and success lies essentially in mastering coordination and decision making costs.
Thus, most efficient structures are those that centralize both communication and decisionmaking. Under turbulent environmental conditions, quick adaptation through exploration
becomes the most important capability for firms. The best way to achieve this is to design an
incentive system that will encourage individual initiatives and to encourage horizontal
communication channels for extensive knowledge sharing. Contextual ambidexterity then
becomes the best balancing mechanisms.
There are however, several conditions to the validity of this line of reasoning. First, if one
hypothesises a high level of collaboration between agents, encouraging organization-wide
network may not be the best alternative. In these cases, one could consider that some of the
burden of exploration is transferred from the organization to individuals, who then
compensate organizational lacks by freely participating to the collective endeavour. Second,
in cases in which structural costs remain an element of the overall performance, it is still
desirable for firms to maintain them at a reasonable level. Developing small informal
networks (or communities) devoted to exploration may still lead to the desired level of
exploration while maintaining exploitation costs at a reasonable level. The paper thus opens
the possibility of identifying configurations that has not been investigated so far in the
literature.
21
There are obviously some limitations to the present paper. First, we only investigated some
organizational ideal types. An obvious second step will be to more systematically investigate
the parameters space and clearly define the domain of efficiency of each organizational
configuration. Second, the paper essentially considers static comparatives. Future work should
seek to make the different balancing mechanisms more endogenous and propose a dynamic
decision making process.
22
'
Abernathy W. J. (1978), The productivity dilemma, Baltimore: Johns Hopkins University
Press.
Argyris C., D.A. Schön (1978), Organizational Learning: A Theory of Action Perspective.
Addison-Wesley, Reading.
Benner, M. J., Tushman, M. L. (2003), Exploitation, exploration, and process management:
The productivity dilemma revisited, Academy of Management Review, Vol. 2, pp. 238–256.
Blackler F., N. Crump, S. McDonald (1999), Managing experts and competing through
innovation: an activity theoretical analysis, Organization, Vol. 6(1), pp.5-31.
Boland, R. J. Jr., and Tenkasi, R. V. (1995). Perspective making and perspective taking in
communities of knowing, Organization Science, Vol.6 (4), 350-372.
Brown S.L., Eisenhardt K.M. (1997), The art of continuous change: linking complexity theory
and time-paced evolution in relentlessly shifting organizations. Administrative Science
Quaterly, Vol. 42, pp.1-34.
Burgelman, R. A. (2002), Strategy as vector and the inertia of coevolutionary lock-in,
Administrative Science Quarterly, Vol. 47, pp. 325–357.
Eisenhardt K.M., F.M. Santos (2001), Knowledge-based view: a new theory of strategy? In A.
Pettigrew, H. Thomas, and R. Whittington (Eds.) Handbook of Strategy and Management, Sage
Publications.
Ford J.D., Ford L.W. (1994) Logics of identity, contradiction, and attraction in change.
Academy of Management Review, 19, pp.756.85
Gatignon H., M.L. Tushman, W. Smith, P. Anderson (2002), A structural approach to
assessing innovation: construct development of innovation locus, type, and characteristics,
Management Science, Vol. 48(9), pp. 1103-1122.
Gersick CJG. 1991. Revolutionary change theories: a multilevel exploration of the punctuated
equilibrium paradigm, Academy of Management Review, Vol.16, pp.10.36
Ghoshal S., A. Bartlett (1994), Linking organizational context and managerial action: the
dimensions of quality of management. Strategic Management Journal, Vol. 15, p91-112.
Gibson C.B., J. Birkinshaw (2004), The antecedents, consequences and role of organizational
ambidextererity, Academy of Management Journal, Vol. 47(2), p209-226.
Gupta A.K., K.G. Smith, C.E. Shalley (2006), The interplay between exploration and
exploitation, Academy of Management Journal, Vol. 49(4), pp. 693-706.
Hansen M.T. (1999), The search-transfer problem: the role of weak ties in sharing knowledge
across organization subunits, Administrative Science Quarterly, Vol. 44, pp. 82-111.
Hargadon A. B., A. Fanelli (2002) Action and possibility: reconciling dual perspectives of
knowledge in organizations, Organization Science, Vol. 13(3), pp. 290-302.
Ishida K., T. Ohta (2001), On a mathematical comparison between hierarchy and network
with
a
classification
of
coordination
structures,
Computational
&
Mathematical Organization Theory, Vol. 7, pp. 311–330.
Knorr Cetina K. (1999), Epistemic Cultures, Harvard University Press.
23
Knudsen T., N. Stieglitz (2008), Taming the antagonistic forces of exploration and
exploitation in organizational search. Paper presented at CCSM 2007 (available at
http://www.cbs.dk/forskning_viden/konferencer/ccsm2007/menu/program_and_papers).
Leonard-Barton D. (1995), Wellspring of knowledge, New York: Cambridge University Press.
March J. G. (1991), Exploration and exploitation in organizational learning, Organization
Science, Vol. 2, pp. 71–87.
Milgrom P. R., J. Roberts (1990), The economics of modern manufacturing: technology,
strategy, and organization, American Economic Review, Vol. 80, pp. 511–528.
Nickerson J.A., T.R. Zenger (2002) Being efficiently fickle: a dynamic theory of
organizational choice, Organization Science, Vol. 13, No. 5, pp. 547-566
O’ Reilly C.A., M.L. Tushman (2004), The ambidextrous organization, Harvard Business
Review, Vol. 82, N°4, pp.74-81.
Ohja A., J.L. Brown, N. Phillips (1997) Change and revolutionary change: formalizing and
extending the punctuated equilibrium paradigm, Computational & Mathematical
Organization Theory, Vol. 3, n°2, pp. 91–111.
Okhuisen G.A., K.M. Eisenhardt (2002), Integrating knowledge in groups: how formal
interventions enable flexibility, Organization Science, Vol. 13, No. 4, pp. 370-386.
Orlikowski W.J. (1996), Improvising organizational transformation overtime: a situated
change perspective. Information System Research, Vol. 7(1), pp. 63.92.
Porter M.E., N. Siggelkow (2007), Contextual interactions within activity systems and
sustainability of competitive advantage. Paper available at http://www-management.
wharton.upenn.edu/siggelkow/.
Siggelkow N. (2001), Change in the presence of fit: the rise, the fall, and the renaissance of
Liz Claiborne, Academy of Management Journal, Vol. 44, pp. 838-857.
Teece, D. J., G. Pisano and A. Shuen (1997). Dynamic capabilities and strategic management.
Strategic Management Journal, Vol. 18 (7), pp. 509-533.
Tsoukas H., R. Chia (2002) On organizational becoming: rethinking organizational change,
Organization Science, Vol. 13(5), pp. 567-582.
Tsoukas H., Vladimirou E. (2001), What is organizational knowledge? Journal of Management
Studies, 38(7), pp. 973-993.
Tushman ML, Romanelli E. (1985) Organizational revolution: a metamorphosis model of
convergence and reorientation. Research in Organizational Behavior, 7, pp. 171.222
Van Looy B., T. Martens, K. Debackere (2005) Organizing for continuous innovation: on the
sustainability of ambidextrous organizations. Creativity and Innovation Management, Vol.
14 (3), pp. 208 – 221.
Weick K.E., R.E. Quinn (1999), Organizational change and development. Annual Review of
Psychology, Vol. 50, pp. 361-386.
24
''
()
$ *
'
$*
Parameter
$
Value(s)
n
20
E
1
W
1
R
1
0.5; 0.9
L0
10
M
10; 25; 50
p
30
Increase proportion of exploring agents (SA)
0.1; 0.2; 0.5
Increase proportion of time devoted to 0.1; 0.2; 0.5
exploration (CA)
25
$