Business Simulation Interaction Domain
An exploration of a business simulation's interactions (decisions and results) in terms of ambiguity and granularity
This page explores the design of interactions (decisions and results) in terms of positioning terms of granularity (horizontal axis) and ambiguity (vertical axis) on the Simulation Interaction Domain to ensure cognitive processing (learning) and efficiency (best use of time). Next I explore how actual decisions and types of results might be positioned across the interaction domain and finally I discuss design issues.
Ambiguity - the ability to unravel how decisions might impact results - impacts the amount of thinking and discussion about the decision and analysis of the results. Decisions and results range from high ambiguity (requiring considerable thought and discussion - that require considerable time to make or analyse) to low ambiguity (certainty and hence requiring minimal thought and discussion - that take minimal time to make or analyse).
Granularity impacts detail of decisions and results and extends from highly granular purely numeric decisions and results through multiple choice decisions and key measures to highly refined, singular (Yes/No) decisions or comments evaluating the results. As with ambiguity, the more granular a decision or result is, the longer time is required for thought and discussion.
The most time is spent on decisions and results at the bottom left of the domain and the least time on those at the top right.
Simulation Interaction Domain
The Production decision is unambiguous because its outcome (the amount actually produced) will be as decided. As a number can be entered the decision is granular.
The Price decision is more ambiguous as the outcome (the resulting demand) is difficult to forecast. Also, as any number can be entered, the decision is granular.
The Promotion decision is even more granular as this can have an effect both in the short and long-term and on both the company and on the market as a whole.
As the Web Site decision involves having a web site or not as there are only two options (Yes or No) this decision is not granular. But, as it is difficult to forecast the impact on sales of this decision, it is ambiguous.
Decisions need to be positioned based on the cognitive processing needed and duration constraints. So, the production decision will require less cognitive processing than the price or promotion decisions. The low granularity of the Web Site decision means that it takes less time to make than the similarly ambiguous Price decision.
Raw Data is information such as basic costs, revenue, liabilities and assets.. It is presented in the form of basic accounting reports. As such it provides the basis for identifying strengths and weaknesses.
Refined Data takes the raw data a stage further changing it into measures of performance (such as Return on Assets or Profit to Sales). Therefore it is a less ambiguous measure of strengths and weaknesses. And, because the data has been processed further, it is less granular.
Trends refine the data further showing how it is changing over time. Thus it shows whether the company is getting stronger or weaker and is a less ambiguous portrayal of company performance.
Graphs and Charts take trend and other data, refining it further so that it is easier to envisage how the company is progressing.
Finally there are other ways of portraying results - comments, pictures, sounds and animations. All of these tend to have low granularity but different levels of ambiguity.
Like Decisions, Results need to be positioned based on the cognitive processing needed and duration constraints.
When designing a business simulation, the ambiguity of decisions and results depends on balancing learning needs (cognition) with duration (learning efficiency).
In terms of ambiguity the decisions are likely to be spread across the domain with the decisions that are vital for cognitive learning being ambiguous and the decisions that are necessary for the operation of the business but inconsequential (in a learning sense) being relatively unambiguous. This spread is designed to ensure learning in the shortest time. Reducing granularity (from entering numeric decisions, through multiple choice decisions to binary (yes/no) decisions shortens the time required to make the decision but at the expense of the ability to fine-tune the decisions and, perhaps, exploration of the issues.
The ambiguity and granularity of results depend on whether they are for the learners or for the trainer. For learners results are likely to ambiguous. However, for the trainer, as part of the Tutor Support System; the Tutor's Audit should provide unambiguous, refined (low granularity) results; the Reconciliations are likely to be unambiguous but granular and the Team Commentaries a mixture of ambiguity and granularity (with results that are just for the tutor being unambiguous and results that can be provided to the learners being ambiguous).
Changes over time
To reduce/maintain cognitive load it is likely that the range of decisions and results and their ambiguity will change period-by-period as the learners run their simulated business..
A professionally designed simulation will have appropriate decision and result ambiguity and granularity based on learning needs, efficient and effective learning.
This page summarises information from my book "Corporate Cartooning: the art, science and craft of business simulation design" and my keynote Presentation at the 2008 ISAGA Conference.
Most recent update: 13/04/12
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