Madrid FC own land in the metropolitan area of Madrid. They would like to build a sports complex which would include state-of the art training facilities for elite athletes. Your consultancy office with the help of architects and sports consultant have drawn up three different projects) (i) 10 hectare site with small capacity for athletes (ii) 20 Ha site and moderate level of capacity; (iii) a high-level complex at 30 Ha.
The success of the project depends upon several factors. Madrid FC want to build make the largest profit. There is uncertainty concerning the demand for the three projects. The decision is to select the optimum project depends on following three decision alternatives:
Decision 1: a small sports complex at 10 Ha Decision 2: a medium complex at 20 Ha Decision 3: a large complex at 30 Ha
Some other information investigated:
Decision 1 would be in the centre of town where property and land are expensive but would have some kudos as it is close to the football ground.
Decision 2 is close to the centre but transport would be needed to get to it. Decision 3 is out of town with lots of opportunity for expansion.
A study was conducted to get some prior knowledge for the probability of each alternative occurring at 2 different demand level. The two directions investigated were high demand and low demand and based on various financial metrics and a probability assigned to these variables (see table 1 below).
Thus, management must first select a decision alternative (complex size), then other states of nature will be investigated e.g. (demand for the sports facility). Given the three decision alternatives and the two states of nature, which sports complex should Madrid FC advance?
To answer this question, Madrid FC will need to know the consequence associated with each decision alternative and each state of nature.
Table 1: Payoff for Madrid FC Sports Complex (payoff in Euros million)
page2image162602768 page2image162599072 page2image6058944 page2image162598624page2image6257664 page2image6254208
Low Demand
page2image162606352
High Demand
page2image162639008
Size
Decision
S1 (p=0.4)
S2 (p=0.6)
page2image6178880 page2image162643264
Small
page2image6191552 page2image162642592page2image5837312
D1
page2image5835008
3000
page2image162657072
3200
page2image162656064
Medium
D2
2500
2800
page2image6187136 page2image162642480
Large
page2image162643376 page2image6173440page2image6166912
D3
page2image6175744
2000
page2image162629824
2100
page2image162642928
Table 2: A survey was completed with 100 people that showed strong interest in signing up to train at the complex. A contingency table of the data is shown below
page2image6206784
Trains more than 3 times a week
page2image5461440
Trains less than 3 times a month
page2image5883392 page2image162802176
TOTAL
Football fan
20
40
60
Non-football fan
20
20
40
TOTAL
page2image5854464
40
60
page2image6183296
100
page2image6009984 page2image162942800
Questions:
1) Based on the information in the case, what are Madrid FCs key drivers and objectives in this decision- making process?
2) Are there any other objectives that you think they should consider?
3) Identify the basic elements governing Madrid FCs decision-making (values, decisions, uncertain events, consequences, etc) ?
4) Develop a decision tree for this decision-making process.
5) What roles do decision trees and influence diagrams play in helping to understand and communicate the structure of your decisions in this project?
6) Which decision would you recommend based on your investigations. Justify your recommendations?
7) Given the information in the contingency table, what is the significance of this data and which marketing solutions might be applicable for Madrid FC?
8) Develop arguments on how decision-making could be improved in a project of this nature?