22E25000 Accounting for Management Control
How to design MCS to support innovations
in organizations
Term paper
Group #6:
Otso Manninen
Mikko Junnola
Niko Jäntti
Mika Kortelainen
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1 Introduction
Companies today need to have a crystallized competitive advantage to make it
through competition. This most often requires keen differentiation within the markets.
The obvious way is to have a product, process, strategy or basically any idea that
the competitors lack. In the world where everything is moving faster, closer and more
digitalized and where there are more companies competing than ever before,
innovations have become a very scarce resource.
Still, even with the best of ideas or innovations, companies can fail. This can be due
to just bad luck or it can be due to conditions outside the company. Then again, it
can happen entirely within the company: production can stutter, costs can fly out of
control, customers can be unhappy with the service or perhaps the company is just
not coming up with anything new and slowly disappears with new ideas and products
taking all the fame.
Management control has been in the locus of business management since the
industrial revolution and the introduction of the early scientific management
principles. To this day, it has grown to become an entire field of study for
researchers and is utilized in companies everywhere with a wide range of different
kinds of management control systems. These systems are often used for different
purposes: for the management to understand where the company stands and where
it is going, to place goals or to motivate, to be an indicator for employee or
management incentives. However, the general purpose is still the same as back in
the early industrial world: control.
Innovations tend to arise from some sort of a creative process. This process is often
regarded to be something difficult to control or specify. Therefore, to allow this
process to take place, many seem to believe that all kind of control should be
minimized. So, to have innovations to arise, companies would also need to reduce
control. The reality may not be as simple as it seems, since even the definitions of
innovation are numerous, not to mention the roles of innovations in companies. Also,
as already mentioned, innovations are not the only aspect in the success or survival
of a company. Is reducing the amount of control, in the face of enforcing innovations,
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sensible if it compromises the company? If so, where is the line of successful control
and full potential of innovations?
In this paper we will introduce academic studies that have taken part in this
conversation. We will first state definitions for terminology relating to innovations and
management control systems found in the studies. Second, we will cut into the
discussion about how the management systems may affect the innovations in
companies. Lastly we will conclude with discussion about the managerial
implications on the design of management control system (MCS).
2 Definitions
2.1 Innovations
Although innovations are a common topic in everyday discussions, the media, and in
academic literature nowadays, the term is not self-explanatory and different
speakers may refer to different things. Yet most of the literature studied for this term
paper takes the term for granted and does not give a definition to it. In our term
paper however, we define innovation as the commercialization of a new idea.
There are also different types of innovations. For most people product innovations
come first to mind. Product innovations mean the commercialization of a new
technology in the form of a new product. Many authors have studied management
control systems’ effect on product innovations. These include, for example, Poskela
and Martinsuo (2009) as well as Bisbe and Otley (2004).
However, product innovations are not the only type of innovation. Another common
type of an innovation is a process innovation. In a process innovation, a new process
utilizing technology or methods, not used before, is introduced into the production of
products or services. The new process often utilizes new technology, but does not
need to do that to be called innovative. Alternatively, a rethinking of the process
without any technological advances can be considered a process innovation. In the
management control system literature, process innovations are not that much
concentrated on. However, Haustein et al. (2014) form an exception to the rule
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considering the effect of management control systems in process innovation
companies among other kinds of innovation companies.
Two other, often less discussed, innovation categories are marketing innovations
and organisational innovations. As the name suggest, marketing innovations refer to
new ways of marketing. Similarly, organisational innovations mean new ways of
organising the structure and functioning of an organisation. Just like process
innovations, marketing and organisational innovations get less time in the spotlight in
the management control system literature compared to product innovations.
However, Haustein et al. (2014) also cover them.
2.2 Innovation company
Innovation company is a widely used term that is heard in the media on a daily basis.
Upon hearing the term, for most of us certain companies come to mind. Most
commonly these are IT-companies. However, when asked, not many can give a
clear definition to an innovation company. The term is also commonly used in
academic management and management accounting literature. Despite this, there is
no clear consensus among the authors and the definition may vary a little between
publications. Here, we will briefly go through the definitions used in the articles cited
in this term paper.
Haustein et al. (2014) define innovation companies based on OECD’s understanding
of innovation-active firms. This definition withholds companies associated with
several different types of innovations. The innovations not only consist of product
innovations, but also contain process innovations, marketing innovations as well as
organisational innovations. In other words, Haustein et al. consider all companies
with innovations on any of these areas innovation companies.
Bisbe and Otley (2004), on the other hand, have a narrower conception of innovation
companies in their article. They only focus on product innovations. Poskela and
Martinsuo (2009) fall somewhere between Bisbe and Otley and Haustein et al. in
their view of innovation companies. While they recognize different aspects of
innovation in their text, they mainly focus on, what they call, the front end of
innovation. With the front end of innovation, they mean the product development
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phase, where no official product development project for a product has yet been
established. Naturally, this focus on their article means that they mainly focus on
product innovations.
The topic of this term paper is to define a management control system that supports
innovations in organizations. This is a somewhat broad definition and requires some
narrowing down. Like most of the articles cited in this term paper, we too focus
mainly in product innovations. However, many of the principles work just as well for
other types of innovations.
2.3 Management control systems
The management control systems (MCS), are mainly based on Simons’ levers of
control (LOC) framework. This framework consists of four layers including belief
systems (e.g. mission statement), boundary systems (e.g. code of conduct),
diagnostic systems (e.g. budgets) and interactive systems (e.g. management
involvement) (Simons, 1995).
The MCS consists of individual management accounting and control systems
(MACS). “MACS comprise multiple formal and informal individual control systems
that operate collectively and interdependently to constitute control packages” (Otley,
1980, 1999; Chiapello, 1996; Merchant and Otley, 2007; Malmi and Brown, 2008).
The generally used individual MACS typically include budget systems, performance
measurement systems and project management systems. Some of the MACS can
be considered as traditional diagnostic tools (e.g. budgets), whereas some are
referred as interactive control systems.
Simons (2000) suggests, that any individual MACS can potentially be used both
diagnostically and interactively. The diagnostic controls are used to monitor
predefined targets and results (Simons, 1995) The interactive use of MACS means,
that the management regularly and personally participates in the decision-making in
the innovation projects and processes (Bonner et al. 2002)
Also Poskela and Martinsuo (2009) follow the idea of Simons’ defining management
control as “management activity that is used to maintain or alter patterns in
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organizational activities to achieve successful results in the front end of innovation “.
Accordingly, management control systems are all the systems that are used by the
management to achieve these targets.
Haustein et al. (2014) have the same kind of logic in their definition of management
control systems. They define management control systems as “all the devices or
systems managers use to ensure that the behaviors and decisions of their
employees are consistent with the organization’s objectives and strategies”. They
further divide management control systems into four categories:
● Results control
● Action control
● Personnel control
● Cultural control
According to Haustein et al. the four categories consist of direct and indirect control
systems. Results control and action control are traditionally direct control methods
whereas personnel control and cultural control are forms of indirect control.
3 MCS effects on innovation
3.1 The Mechanism of Interactive Management Control
Systems
The Simons’ framework (1995), as already mentioned above, has suggested that
traditional measuring, target setting and the towards target guiding management
control systems work poorly on innovation companies, whereas interactive
management control systems have better results and increase successful product
innovation. However, the the relationship between interactive management control
systems and innovation is not specified. Bisbe and Otley (2004) have addressed that
problem in their study.
In their study, Bisbe and Otley (2004) tested three hypotheses regarding the
relationship. The first two hypotheses were that interactive management control
systems have a mediating effect. They boost innovativeness and result directly and
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indirectly in better performance. The third hypothesis was that the interactive use of
management control systems has a moderating effect and boosts the positive
influence of innovations on performance. In the study, Bisbe and Otley focused on
three management control tools: budgeting, balanced scorecard, and project
management system. The sample companies consisted of medium and large
Spanish manufacturing companies with at least some R&D activities. (Bisbe & Otley,
2004)
According to the study, the first two hypotheses do not hold. The third one, on the
other hand, seems to hold. However, also the third one only holds when looking at
the general interactivity in the use of the three control systems or when only looking
at the interactivity of budgeting. For the other two management control systems, the
results are statistically not significant. (Bisbe & Otley, 2004)
Bisbe and Otley suggest that the working mechanism behind the third hypothesis
could be associated with concentration of the company’s innovation efforts or the
increased communication in the organisation. The increased nimbleness of the
organisation that is important in the varying circumstances related to innovations
may also have an effect. (Bisbe & Otley, 2004)
3.2 Strategic innovations
Strategic innovations span a larger effect on the company. It may require a change
in the company culture entirely and such innovations may just as well serve as
drivers for change. Therefore, the level of control could pose an even greater threat
to the company and its innovation processes. A study by Robert Chenhall, JuhaPekka Kallunki and Hanna Silvola (2011) discusses this topic in a holistic manner.
They state that there is a relationship between product differentiation (strategy
innovation), product innovation, social networks, an organic innovative culture and
formal controls as well as that these structures within the company support the
management control systems effect on innovations. Among other direct relationships
between the structures and MCS, they claim that formal controls have an effect on
innovations and also additional benefits can be gained when formal controls are
combined with organic innovative cultures. However, they state that an organic
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innovative culture and formal controls both have a positive effect independently and
that there is not much of a synergic multiplier.
3.3 Measures
Innovations can be also studied from the viewpoint of projects that aim to the result
of releasing a new product. A study done by Tony Davila (2000) introduces findings
that state a relationship between project uncertainty, product strategy and
management control systems. The study found that, when introducing information to
the project team, control measures relating to cost and design had a positive
association with performance, whereas measures relating to time, budget and
profitability had a negative effect. So, the study does not only state that the control
systems indeed have an effect on the innovation processes, but that particular sort of
measures can have opposing results in innovation project performance.
3.4 Effects of tight or loose controls for new products output
The conventional wisdom says: If firms wish to increase their degree of
innovativeness or just rate of new product output, they need to find ways of
becoming less centralized, less formal and less strict in the enforcement of company
rules. This arises a question for companies that what would be the relevance degree
of looseness or tightness of controls that will support product innovations. Bart
(1991) interviewed presidents from large and diversified companies in North America
and despite of this conventional wisdom prediction, his study findings suggest that
company presidents don’t clearly exercise looser control over new products. Instead
presidents seem to use different degree of controls for different category of new
products strategy.
For example, with unrelated new products presidents said to use a quite high degree
of controls. Mainly explanation was an increased business risk and that’s why they
wanted to make sure that everything was done right and increased their controls.
Quite same situation was with exponential new products because “presidents argued
the need to ensure that such products do not get too far “ahead of their time””. Even
research data mainly imply that low output of new products occur when presidential
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controls are “too loose” and high output of new products occur with “tight”
presidential controls. However exponential new products are exception. Bart suggest
that: “A possible lesson for low new products situations, then, might be that higher
quantities of new products will result once presidents give clearer mandates and take
more of a personal interest in them”. (Bart, 1991)
3.5 Product innovations - early product development
Poskela and Martinsuo (2009) have studied the effects of different types of
management control systems on the early stages of product development they call
the front end of innovation. According to Poskela and Martinsuo, the “front end of
innovation” is the most difficult part of the product development to control. However,
the possibilities to affect the outcome are the largest at this stage, so focus should
be put to this. Also much of cost formation is decided at this stage and it is often said
that this stage receives too little attention from the top management in most
companies. (Poskela & Martinsuo, 2009)
As Poskela and Martinsuo (2009) argue, many authors write about the importance of
finding a balance between the freedom to be creative and the control in innovation
processes. However, these claims have not been statistically proven. Using a
questionnaire to Finnish top managers responsible for R&D or product development
activities in their companies, Poskela and Martinsuo tested seven hypotheses
related to the effects of different management control system elements on the early
stages of a product development process.
The results were to some extent surprising. Contrary to their (and many other
authors’) expectations they found no support to claims that formalization of the early
stages of product development process would kill creativity and decrease the quality
of innovations. They also did not confirm the popular belief that outcome-based
rewarding would affect the innovation work negatively. (Poskela & Martinsuo, 2009)
Less surprisingly, they did find support to their expectations that management control
in the form of resource allocation and target setting does benefit the innovation
processes of early product development. The result seems intuitively clear and other
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authors in different studies have made similar statements. (Poskela & Martinsuo,
2009)
Poskela and Martinsuo also tested the effect of different circumstances on the
associations of different kinds of management control elements on the innovation
capabilities. Namely, they tested the effect of technological uncertainty and market
uncertainty. The results were again somewhat surprising. (Poskela & Martinsuo,
2009)
Poskela and Martinsuo found no link between increasing market uncertainty and
stronger negative effect of product development process formalization on innovation
capability. Likewise, they found no connection between increasing market
uncertainty and stronger negative effect of outcome-based rewarding on innovation
capability. However, they did find corresponding negative effects with stronger
technological uncertainty. (Poskela & Martinsuo, 2009)
As one would logically suggest, the guarantee of resources and formalization of
goals is helpful for innovations in many cases. However, as can be seen from the
results considering the technological uncertainty, some of the results may only hold
true under specific circumstances and the contingency factors should always be
taken into account as can be learned from the research of Haustein et al. discussed
below.
3.6 The effect on contingency factors
In their literature review, Haustein et al. (2014) combine the results of many studies
and look at the effects of different types of management control systems under
different contingency factors. In their study, Haustein et al. have all together 11
contingency factors that they divide into three categories: external, organizational,
and innovation company. The two first categories contain general contingency
factors for all companies and, as the name suggests, the third category is specific to
innovation companies. As already mentioned in the Innovation Companies section,
their view on innovation companies is wider than the traditional product innovation
company and includes process, marketing, and organizational innovation
companies. (Haustein et al., 2014)
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As mentioned in the Management Control Systems section, Haustein et al. see
management control systems falling into two main categories, direct control types
and indirect control types. The direct control types can be further divided into results
control and action control. Results control consists of control techniques such as
budgeting, performance measurement, and reward structures. Action control on the
other hand contains methods such as operating manuals and supervision of rules.
The indirect control types can be divided into personnel control and cultural control.
Personnel control withholds for example recruitment policies and training
programmes. Cultural control is formed of things such as codes of conduct, manager
serving as a role model, and group-based rewards. (Haustein et al., 2014)
Haustein et al. form 43 hypotheses based on the existing literature. A summary table
of the expected effects as perceived by Haustein et al. can be seen below.
Summary table of the framework of Haustein et al.
As can be seen from the table, Haustein et al. hypothesize that indirect control
methods are positively associated with all contingency factors. The direct control
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methods on the other hand have more mixed results. Both results control and action
control are expected to have negative association with the innovation capacity of the
company. Both control methods are also expected to have negative association with
technological complexity. Based on these results, Haustein et al. suggest careful
consideration when setting performance measures or setting guidelines regarding
innovation activities. (Haustein et al., 2014) The hypotheses of Haustein et al. (2014)
are mainly in line with the results of Poskela and Martinsuo (2009).
Haustein et al. (2014) suggest that innovation companies should put more focus on
indirect control measures than direct control measures as those may be better suited
with the contingencies that innovation companies face. However, the framework
shows that direct controls are beneficial regarding many contingencies. Also,
Haustein et al. (2014) say that the contingencies of each situation should be judged
individually and decisions based on the analysis. In any case, the research suggests
that with right kind of management control systems the innovation capabilities can be
increased and that management control systems do not necessarily kill creativity.
(Haustein et al., 2014)
3.7 Perrow’s model
The results of research studies in management accounting have shown that
accounting forms of control are poorly suited to highly uncertain tasks which need
innovativeness. In addition to typical accounting controls there is a possibility to use
e.g. either behavior controls or personnel controls. From these, most supporting
controls for innovativeness are personnel controls which are built on employee’s
natural tendencies to control themselves. Examples of personnel controls can be
placement policies or strict personnel selection. The whole purpose of personnel
control is: “By getting the right people, the organization can rely on the
professionalism of group members and the sharing of common values.” (Abernethy
et al., 1997)
Perrow’s model of technology and structure pointed out two key dimensions of
routines: task analyzability (the degree to which search activity is needed to solve a
problem) and number of exceptions (new or unexpected situations that a person
meets while performing a task). The degree of these two dimensions determine what
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kind of controls are positively related to R&D management performance. Below is
the figure which presents this Perrow’s model.
Perrow’s model arguments about which controls are suitable for different tasks can
be summarized as:
Situation in cell 1 where tasks are highly analyzable and exceptions are few,
reliance on both accounting and behavior controls will be positively related to R&D
management performance.
Situation in cell 2 where tasks are low in analyzability but few exceptions are
encountered, reliance on accounting controls will be positively related to R&D
management performance.
Situation in cell 3 where task analyzability is low and exceptions are many and
frequent, reliance on personnel controls will be positively related to R&D
management performance.
Situation in cell 4 where tasks are highly analyzable, but many exceptions are
encountered, reliance on behavior and personnel controls will be positively related to
R&D management performance. (Abernethy et al., 1997)
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Abernethy et al. (1997) made an empirical study about this subject and their findings
were mostly in same line with Perrow’s views. Main conclusions from their study
suggest that personnel controls are positively related to performance when tasks
uncertainty is highest, whereas accounting controls have positive effect when tasks
uncertainty is lowest and a little surprise was that behavior controls haven’t positive
effect in any situations. But the main contribution of the study is the finding which
shows that where task uncertainty is highest reliance on personnel forms of control
has a positive and significant effect on performance. Moreover, this effect is
significantly more positive than that of either accounting or behavior controls.
So if a company is about to design their management control system to support
innovation and want to rely on Perrow’s model and Abernethy’s et al. study then the
company should use personnel controls to maximize performance. However
practical implementation of personnel controls might be a little problematic. For
example, management might not see personnel controls as proper controls, because
it just basically relies on idea that employees control themselves their work instead of
management would do it in a traditional way and that’s why it may be hard to
understand how personnel controls actually work
4 Conclusions and managerial implications to
MCS design
When it comes to research implications for managers when designing MCS, we must
consider that the effects tend to be very case sensitive and it is therefore difficult to
give general rules for MCS that would help innovations for certain. Contingency
factors need to be taken into account. (Haustein et al. 2014) However, some
guidelines can naturally be given.
The studies clearly state that MCSs do in fact have an effect on innovations. The
effect varies from context to another and whether MCS have a positive or negative
effect depends on various factors, such as the used measures. Nevertheless, it is
safe to say that managers with interest in boosting innovation capabilities in the
organization, should not consider control systems lightly.
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On a more detailed level, the studies do also have indications to MCS designs
depending on various contexts. In an innovation project environment, control
systems should focus on cost and design measures and not on time, budget or
profitability (Davila, 2000). For strategic innovations, both an organic innovation
culture and formal controls support the positive effect an MCS may have on the
innovations (Chenhall et al, 2011). Interactive management control systems seem to
increase performance at the presence of innovations rather than boosting
innovativeness (Simons, 1995). Perrow’s model gives a view about what kind of
controls are suitable for different tasks with positive effect to R&D management
performance. (Abernethy et al., 1997)
5 References
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systems on product innovation. Accounting, Organizations and Society 29: 709-737
(2004)
Bisbe, J. and Malagueno, R. The Choice of Interactive Control Systems under
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405 (2009)
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(1996)
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David, T. Otley. Performance Management: A Framework For Management Control
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