This 10 page paper looks at the use of management decision making tools and applies them to a case study provided by the student. The first questions considers which tools would be best to use when forecasting future levels of innovation, after considering several options the paper uses regression analysis. The second part of the paper considers how to get the best value for a set advertising budget with the use of radio and television with given costs and response values. The last paper of the paper looks at a choice of locations which will have different returns according to conditions. The paper shows how to use a probability and weighted probability analysis to decide on which locations may be best. The bibliography cites 10 sources.
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average number of innovations to date. To undertake an analysis if whether the projects should consider for the next our weeks there needs to be a forecast undertaken. The question
is which forecasting mode to use. There are many forecasting models, where projects are very different tools such as Net Present Value (NPV) and internal rate of return (IRR)
may be useful when assessing whether a project should continue. Both tools may use of forecasting and allow for a comparison of very different projects (Watts, 1996). However, in this
case we cannot use any models that have a financial basis as it is made clear that the innovation is not linked to an predicable financial gain. From this
we can look towards the level of innovation that is likely to occur. One tool may be the use of a regression analysis using the past rates and patterns of
innovation to project the way that these are likely to occur in the future. Regression analysis looks at the past trends and uses the data provided to the existing
figures. One method is to draw a graph and then put in a trend line. However, would then make the reading of the trend line difficulty, a tool is needed
where there can be a value given. The method used most often is the least squares regression method. This would mean the trend line would be determined on a line
where there are the least squares between the trend line and the existing findings (Curwin and Slater, 1998) This model is not perfect, there are many variables that
this does not take into account, but the choice of any model has to be based not only on the task to be performed, but as a good fit with
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