Open System Simulation (OSS)

Open System Simulation (OSS) is an instrument for flexible planning and control of business field strategies with the aim of reducing the risk of wrong strategic decisions. Simplifying trend extrapolations of past data over periods of up to ten years often suggest to decision-makers that they are dealing with a completely clear and reliable development line on which complex corporate strategies can be built.
Once such strategies, with their manifold consequences, have been initiated, a strategic “turnaround” becomes almost impossible in the event of serious false prognoses. For example, existence-threatening corporate crises are to be expected if long-term supply contracts have already been concluded for the processing of a certain market segment, special machines with high fixed costs have been purchased and the necessary sales structures have been set up and it is only then that it becomes clear that the forecast demand cannot be realized by any means. The serious mistake of these long-term decisions based on traditional forecasting techniques is the assumption that the forecast development will occur with a probability of 100%.

The OSS avoids this mistake by only generating differentiating scenarios of the future development in the first step and thus deliberately abandoning the tendency to "merge" which is inherent in most other forecasting instruments. In general, the scenario technique aims to make the future development of the object of investigation transparent on the basis of alternative environmental conditions. In doing so, it consciously accepts the uncertainty about the correctness of future-oriented business decisions and does not try to “calculate safely” uncertain data, but rather accepts the uncertainty first in order to subsequently learn to understand its structure. The OSS analysis then tries in a further step to integrate the uncertainty into the strategy considerations. The OSS should run according to the following phase scheme:

• Definition of the examination area,
• Identification of the critical influencing variables of the object of investigation (e.g. demand volumes),
• Design of alternative scenarios depending on different developments of the influencing variables,
• Introduction and impact analysis of significant disruptive events,
• Deriving adequate, scenario-based business field strategies (decision tree analysis, decision trees),
• Selection of a business field strategy based on quantitative criteria (e.g. strategic capital values),
• Generation of flexible back-stop strategies as security equivalent.
The aim of the OSS analysis is therefore to uncover a basic strategy with the support of the scenario technique, which, if necessary, enables a switch to a derivative strategy or an economically justified exit from the chosen strategy (back-stop strategies). An example would be building a hotel. The basic strategy is to offer a certain number of hotel rooms. As a security equivalent against possible overcapacities, the hotel rooms are provided with connections for a kitchenette from the start, so that the hotel rooms can easily be transformed into rentable apartments if there is a shift in demand (derivative strategy).

In the event of further shifts in the demand structure, there is the option of selling the apartments as condominiums (exit strategy). In this way you can Idle coststhat arise due to insufficient capacity utilization in Utility costs transform. The additional costs for the kitchen connections represent flexibility costs and are to be compared with the increase in revenue due to better capacity utilization when calculating the advantages. Similar possibilities for “built-in flexibility strategies” arise, for example, for the technical design of production units, commercial vehicles or aircraft (e.g. as passenger or transport machines). The OSS is particularly suitable for planning and realizing risky investments with high and long-term capital commitment, as they are particularly typical for large-scale plant construction or the real estate industry.

In many cases, there is no constant, but discretionary, scalability of the investments in projects in this regard. With a modular implementation timing that takes derivative strategies into account at an early stage, risks can often be reduced here. It makes perfect sense to align the necessary framework planning and, if necessary, approval procedures to the final stage from the outset.

A strategy planning based on the OSS thus represents a multidimensional alternative planning that does not attempt to eliminate the uncertainty through an undifferentiated correlation of an incalculable number of influencing variables, but instead develops flexible and coherent decision alternatives based on a few significant variables.

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