Managing Dynamics in Corporate Networks


A crucial issue in collaborating in manufacturing corporate networks between different companies is to identify to what extent different strategic and operational decisions need to be coordinated between the involved companies. In this paper, we elaborate on the issue of synchronization and coordination of information flow based on interconnectivities between companies in order to coordinate a corporate network by the means of DSM, Dependence Structure Matrix. The results show that DSM can be used to identify interconnectivities, dependencies on information flow among actors in a network and to identify which information needs to be shared between companies in the network.

Share and Cite:

Danilovic, M. and Winroth, M. (2014) Managing Dynamics in Corporate Networks. World Journal of Engineering and Technology, 2, 32-40. doi: 10.4236/wjet.2014.21004.

1. Introduction

The competitive situation for many smalland medium-sized companies, often acting as suppliers to larger companies, has become more intense in terms of reduced lead times in product development and manufacturing, cost reductions, and increased demands for higher product quality. The stiffer competition has also forced systems integrators to develop new strategies to meet new demands. Management issues, such as lean production, system strategies, and outsourcing, have been introduced and over time become dominant ideas of a changed direction among many corporations [1,2]. If attributes, such as a high level of customization, short lead times in product development and quick responses to late changes of specifications are important, long distances and perpetual changes of suppliers may cause disturbance.

However, from the literature we can see that relations between systems integrating companies and its suppliers are handled in different ways. Brandes et al. discussed the reduction of the supplier base in terms of the number of suppliers. The selected suppliers are subject to increased demands to participate in the process of product development with the systems integrating corporation and their other suppliers on different supplier levels. The expectation that suppliers participate in the process of innovation and delivery of complete products or subsystems was further discussed [4-6]. These new demands on suppliers from systems integrators to collaborate have more intensively forced smalland medium-sized corporations to find new organizational settings. How can a small company adapt to these new demands with its scarce resources and limited knowledge base? One solution is that several companies work together, acting as one unit outwardly. However there may be a drawback in these close collaborations. Gulati et al. described the so-called lock-in and lock-out effects. These constraints are both consequences of close collaboration with one actor. The lock-in effect is the result of limited resources and implies that a company only has time and resources to form and satisfy the expectations of a limited number of alliances. The lock-out effect is the result of alliances that request total loyalty of its members on the contrary. The consequence of these two constraints could be that companies have to reject collaboration with new partners.

2. Research Approach and Research Methodology

Our approach in this research is to apply an analysis model originally based on research of relations between manufacturing strategy and design of manufacturing system within a single company [8,9]. This model has been extended in the analysis of a dyadic relation between two companies [10,11]. In this research we investigated how this analytical model can be applied to a network setting, in which one systems integrator have close collaboration with three suppliers. This research, presented in this paper, is based on a series of interviews with people at all four companies involved in a collaborative network. We have also studied how this manufacturing network works in order to produce and deliver the complete systems to customers. We have performed four interviews that have been recorded, typed and double checked with the interviewees. Mapping of corporate strategy and their manufacturing design presented in this paper have been performed on the basis of collected information in interviews and is thus our interpretation of the circumstances at hand within each company and between companies.

3. Case study

The systems integrating (SI) company in this case study, Kalmar Industries, is part of a large multinational industrial group, with its head office outside Sweden. The SI has approximately 350 employees. The total turnover at the SI in 2002 was approximately EUR 760 million.

A new great business deals in development, manufacturing, and delivering a number of large-scale lifters was made with a foreign defense authority. This new large business deal was supposed to accommodate 200 people for a period of several years. In addition, this new customer demanded that the supplier of these new heavy lifters, the SI, should take tighter control over the manufacturing facilities and processes of development, manufacturing, and delivery of completed products.

The ability to create a highly flexible organization demands that major suppliers actively take part in the development, manufacture, and delivery of final products to customers. One solution is to increase the number of tasks that the key suppliers could perform. Since one of the most important competitive factors is flexibility in accepting very late changes of product specifications, the delivery lead times from the suppliers would be too long. The solution to this situation was a reallocation of suppliers’ manufacturing units into a mutual Product Supply Centre (PSC).

Supplier A supplies hydraulic hoses, supplier B delivers the tires for the container handlers, and supplier C provides the hydraulic cylinders to the trucks. The reasons for integrating these suppliers vary, but one common driving factor was that geographic closeness would improve communication and reduce lead times.

4. Approaches to Manufacturing Strategies and Production Systems design

The issue of how the manufacturing strategies and the design of the production system influence each other was investigated by e.g. Miltenburg . The original analysis framework was built up by three main parts: a table showing the competitive situation of the company (or business area), a diagram classifying the production system into one of seven production systems and showing the support for different competitive factors, and a list of six decision categories that together show the manufacturing strategy of the company. They were graded according to a four-degree scale, ranging from internally neutral to externally supportive (or “infant” to “worldclass”), i.e. how they support the overall business strategy of the company . Säfsten and Winroth elaborated further on the analysis model and came to the conclusion that the framework worked in general quite well for single organizations. Miltenburg also presented an alternative solution of the framework dealing with the plant-within-a-plant problem. This approach could be relevant also for collaborative settings, since the issue is to prevent information leakage between parts of the plant working towards competing customers.

Companies are, however, open systems and there are always input and output relationships with the environment. In network settings several companies have to collaborate and each of these companies needs to have a set of manufacturing strategies comprising different design production systems.

5. Empirical investigation of a collaborative network

A prerequisite for achieving competitive advantages in network settings is that companies must be supportive to each other regarding supply capability. The individual corporate manufacturing strategy and production systems should be coordinated in order to together support the overall aims of the network. At the same time, the actors of a collaborative network setting are often involved in other networks or supplying a specific customer. This means that they cannot focus the design of the production system and support functions totally on just one situation. They must keep the flexibility thus making trade-offs in order to be able to continue to produce a variety of products or parts. A wider presentation of different issues around network collaboration, necessary organizational actions to take, and factors important to the network if it will succeed was made by Winroth and Danilovic . In our analysis we started with the extended Miltenburg model. In the Miltenburg model manufacturing design is influenced by the manufacturing output and competitive situation within each company of the network. However, in the network settings those aspects have to be synchronized across companies of the network. The network based Miltenburg analysis should therefore precede several steps.

1) First each company performs an analysis of their own manufacturing strategy and production system according to Säfsten and Winroth . The conditions between the SI and each network partner are then synchronized in a number of steps.

2) The SI correlates its competitive priorities with its production system and detects suitable changes.

3) The SI performs an analysis of its strategic decision categories and makes suitable changes, either to the production system design or the decision categories.

4) The SI’s strategic decision categories give input to the decision categories of Suppliers A, B, and C.

5) Each supplier correlates its competitive priorities with its production system and detects suitable changes.

6) Each supplier performs an analysis of its strategic decision categories and makes suitable changes, either to the production system design or the decision categories.

7) The suppliers coordinate their decision categories and take necessary actions.

In our approach to explore the linkages between manufacturing strategies and production system in a collaborative network setting we identified three major processes, loops of information processing, developing a joint manufacturing strategy for the collaborative network and design of production systems within each company enabling manufacturing and delivery of complete products to final customer, as shown in figure 1.

The first loop is a process mainly taking place at the systems integrator level (SI), involving steps 1 and 2. As the leading actor in creating the network setting, the SI has to analyze the market situation and the customer requirements. In this process the present manufacturing systems influence the analysis of decisions areas, which is fed back to the design of the production system. In this case the new customer placed increased demands on the SI to deliver complete products, while the main shareholders placed financial restrictions.

The second loop is a process of synchronization between SI and preferred suppliers. In this synchronization, SI and its suppliers are expected to communicate market situation and customer demands and to negotiate how suppliers should organize their production systems according to what SI was capable of doing on its own and what part of the supplier organization should be relocated to SI area.

The third loop is a process of adaptation on the supplier level within each preferred supplier and also mutual

Figure 1. Coordination loops between systems integrator and suppliers.

adjustments between suppliers. They have to decide how to respond to the demands, what part to relocate, and how to develop new organizational routines to handle the daily life activities not only in their own corporation but also within the entire network.

The methodology that is used to represent and analyze dependencies and relations between items is known as Design Structure Matrix or Dependence Structure Matrix (DSM) and was introduced by Steward . As a matrix structure is used to represent the problem structure , two different kinds of matrices are used. One is square matrix and the other a rectangular matrix. The square matrix is used to represent one domain problem structure while the rectangular matrix is used to represent interactions between items in-between two different sets of items in two different domains. While the first is named as DSM the other one is named as Domain Mapping Matrix (DMM). In complex situations, combinations of DSM and DMM can enrich the analysis and help to analyze the dynamics of complex systems. DSM represents and visualizes interdependencies and relations between items such as tasks and activities, components and subsystems, and among people and teams [16,17].

A DSM-based analysis shows how the design of tasks, sequencing of activities can be organized for the effective problem solving in team-based work and the communication required within and between teams [15,18-22].

DSM—STEP 1: Step 1 in our analysis is to outline all aspects of the Miltenburg model, as shown below, and put all those three aspects of competitive analysis, decision criteria, and production layout for all companies of the network in a matrix. In this matrix all rows and columns contain the same information.

DSM—STEP 2: The matrix containing aspects of the Miltenburg model from all four involved companies is a matrix of 162 rows and columns. Each row meets 162 columns. Each of those meeting points is called point of interaction (POI). Each POI contains information about interconnectivities/interdependencies between elements in the row and column. On the overall level there are 26244 POIs in our network matrix.

During interviews and workshops with people from all four companies of the network all those POIs were investigated if they hold any interconnectivity. In each POI, numbers and colors are used to show identified interconnectivity. No 1, marked with yellow color, shows low level of interconnectivity. No 2, with magenta color, shows medium high interconnectivity, and no 3, with red color, show high level of interconnectivity. Colors are used to enable visualization of patterns of interconnectivities.

Figure 2 shows the entire network matrix, filled with identified interconnectivities. On the network level this large matrix can be seen and handled as a large DSM matrix. In the figure we have also marked a number of sub-areas, in total 16 sub-areas. Each sub-area of the entire network matrix is either a DSM or DMM. Along the diagonal, four DSMs are outlined containing interconnectivities between aspects of the Miltenburg model but within each of the four companies of the network. The other sub-areas are 12 DMMs containing interconnectivities between companies of the network as shown in the matrix. The large network matrix can be seen as a hierarchical system of a number of sub-systems that can be extracted from the large matrix.

Figure 2. Overall picture of the network.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Womack, J.P., Jones, D.T. and Ross, D. (1990) The machine that changed the world. MIT Press, Cambridge.
[2] Ford, D., Cotton, B., Farmer, D., Gross, A.C. and Wilkinsson, I. (1993) Make-or-buy decisions and their implications. Industrial Marketing Management, 22, 207-214.
[3] Brandes, H., Lilliecreutz, J. and Brege, S. (1997) Outsourcing—Success or failure? European Journal of Purchasing and Supply Management, 3, 63-75.
[4] von Hippel, E. (1988) The sources of innovation. Oxford University Press, Oxford.
[5] Clark, K.B. and Fujimoto, T. (1991) Product development performance: Strategy, organization, and management in the world auto industry. HBS Press, Boston.
[6] Quinn, J.B. (2000) Outsourcing innovation: The new wheel engine of growth. Sloan Management Review, 13-28.
[7] Gulati, R., Nitin, N. and Akbar, Z. (2000) Strategic networks. Strategic Management Journal, 21, 203-215.<203::AID-SMJ102>3.0.CO;2-K
[8] Miltenburg, J. (1995) How to formulate and implement a winning plan. Productivity Press, Portland.
[9] Säfsten, K. and Winroth, M. (2002) Analysis of the congruence between manufacturing strategy and production system in SMME. Computers in Industry, 49, 91-106.
[10] Winroth, M. and Danilovic, M. (2002) Manufacturing strategies—Congruence of manufacturing processes within a supply chain. Proceedings of the 13th Annual Conference of the Production and Operations Management Society, San Francisco, 5-8 April 2002.
[11] Danilovic, M. and Winroth, M. (2006) Corporate manufacturing network: From hierarchy to self-organising system. International Journal of Integrated Supply Management, 2, 106-131.
[12] Hayes, R. and Wheelwright, S. (1984) Restoring our competitive edge: Competing through manufacturing. John Wiley & Sons, New York.
[13] Miltenburg, J. (2008) Setting manufacturing strategy for a factory-within-a-factory. International Journal of Production Economics, 113, 307-323.
[14] Steward, D. (1981) The design structure system: A method for managing the design of complex systems. IEEE Transactions on Engineering Management, EM-28, 71-74.
[15] Eppinger, S., Whitney, D., Smith, R. and Gerbala, D. (1994) A model-based method for organizing tasks in product development. Journal of Research in Engineering Design, 6, 1-13.
[16] Danilovic, M. and Sandkull, B. (2005) The use of dependence structure matrix and domain mapping matrix in managing uncertainty in multiple project situations. International Journal of Project Management, 23, 193-203.
[17] Danilovic, M. and Browning, T. (2007) Managing complex product development projects with design structure matrices and domain mapping matrices. International Journal of Project Management, 25, 300-314.
[18] Smith, R., Eppinger, S. and Gopal, A. (1992) Testing an engineering design iteration model in an experimental setting. Design Theory and Methodology, 42, 269-276.
[19] Smith, R. and Eppinger, S. (1997) Identifying controlling features of engineering design iteration. Management Science, 43, 276-293.
[20] Morelli, M., Eppinger, S. and Gulati, R. (1995) Predicting technical communication in product development organizations. IEEE Transactions on Engineering Management, 42, 215-222.
[21] Browning, T. (1997) Exploring integrative mechanisms with a view toward design for integration, advances in concurrent engineering—CE97. Fourth ISPE International Conference on Concurrent Engineering: Research and Applications, Rochester, 20-22 August 1997, 83-90.
[22] Browning, T. (2001) Applying the design structure matrix to system decomposition and integration problems: A review and new directions. IEEE Transactions on Engineering Management, 48, 292-306.
[23] Westley, F.R. (1990) Middle managers and strategy: Micro-dynamics of inclusion. Strategic Management Journal, 11, 337-351.
[24] Garnsey, E. (1992) Critical systems thinking as an integrative perspective in social theory. University of Cambridge, Cambridge.
[25] Garnsey, E. (1993) Cumulative knowledge, determinism, and critical systems thinking. 11th EGOs Colloquium, Working Group on Epistemology of Managerial and Organizational Knowledge, Paris, 6-8 July 1993.
[26] Buckley, W. (1967) Sociology and modern systems theory. Prentice-Hall Inc., Englewood Cliffs.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.