# How to test demand factors

27.11.2014

If you want to win in Global Management Challenge, you need to know not only exclusive tips and hints, but also you must correctly forecast sales for each product. This topic describes basic method of testing demand factors.

**Demand factors**

Simulator has 3 markets (Nafta, EU, Internet), and 3 products (1, 2 and 3). The result is 3x3 matrix. Sales in each cell of the matrix depends on particular set of factors. One part of factors affects on the whole matrix, second part of factors affects on the particular market or product, remaining affects strictly on one of the cells. For an accurate demand forecast is necessary to determine the dependence of each of the matrix cells from a common set of factors.

*For example, Corporate advertising effects on particular market, Assembly time effects on particular product, Direct advertising effects on particular cell.*

**How to test factors**

When you find demand factors for each of the cells (3x3 matrix), you can continue to analyze the power of influence. Now we start to test it. Tests can be two types - perfect tests and other. Perfect tests are the most valuable because they give absolutely accurate evaluation of the impact factor on demand. Let see how factor can be tested on Corporate advertising example:

You shoud have two or more teams in one group. The main thing that the teams must be in the same group, otherwise the test will not be perfect (and if the influence of factor is weak, it would be meaningless). It is impossible to compare test results of two teams from different groups correctly, because strong influence on the results will provide competitors in the group.

Prepare an identical decision for both teams, but in one of the teams change a decision on the tested factor. For example, corporate advertising test was made with the values of 30 (basic team) and 80 (test team). In cases when victory in the group is not nessery (for example, if you have about 200+ teams) or you play in demo round, choose for your teams general decision from the 5 report in history. Part of factors has a strong residual effect from past periods and this allows us to neutralize their influence.

1 period - you have input decisions and get reports from your teams from the same group. Team with the base decision (corporate advertising 30) has sales 900-450-225, test team (corporate advertising 80) 900-450-225. Conclusion that corporate advertising has no effect on sales in the current period.

2 period - basic team (30) has sales 1000-500-250, sales of the test team (80) 1070-55-268. Lets take a look on product 1. If we do not have a team with a basic solution in the group, we might think that investments in corporate advertising increased sales from 900 (1 period) to 1070 (2 period), growth is 1070 / 900 = +19%, but this is a mistake. Seasonal fluctuations in demand and other competitors change sales in the group. To neutralize these changes you need basic team. Compared with sales of product 1 between basic team and test team, growth is 1070 / 1000 = +7%, ie much less. This is called a perfect test because allows you to find the true impact of the tested factor.

3, 4 and 5 period - continue test with values of 30 and 80, we estimate the cumulative impact of corporate advertising. 3 period basic team (30) sales 1100-550-270, test team (80) sales 1212-606-298. 1 product growth is 1212 / 1100 = +10.2%, the difference increased, because of cumulative effect. To assess the cumulative effect, continue test with the same parameters to 5 period.

- In the same time perform several tests with values of corporate advertising 30-0, 30-45, 30-60, 30-80, 30-99. Obtain all results for the entire range 0-99 of the corporate advertising and arranges them on the graph. It is important to test the full range to determine the type of connection between demand and factor for further modeling of the market - directly proportional, quadratic, etc.

**Assessing the impact of factors on sales**

As has been previously determined in topic about Corporate advertising, the influence on sales by corporate advertising is directly proportional, for the evaluation single test is enough. In Excel make a table with the results. We use relative change in sales for estimation, otherwise you will not be able to apply this formula to predict demand in the other groups.

Team | Corporate advertising | Product 1 (relative sales) | Product 1 (absolute sale) |
---|---|---|---|

Basic team | 30 | 1 | 1000 |

Test team | 80 | 1,07 | 1070 |

Next, we calculate the coefficient of elasticity of demand from corporate advertising: (107% - 100%) / (80 - 30) = 0.14%. The desired coefficient of 0.14% is the elasticity of the factor, it means that an increase in corporate advertising by 1 gives an increase in demand by 0.14%. It is easy to calculate that with 99 corporate advertising, the demand will increase by: (99 - 30) * 0.14% = 9.66%

To assess the residual effect, it is necessary to compare the results of several periods and select a coefficient that takes into account the preservation of the influence of the investment of the corporate advertising of the previous period based on the general formula:

Δ sales (5 period) = Δ corporate advertising (4 period) * K + Δ corporate advertising (3 period) * K * X + Δ corporate advertising(2 period) * K * X² + Δ corporate advertising (1 time) * K * X³, where K = 0.0014, and we know all Δ from the test. We find that X = 0.6 - 60% of the investments from previous period continue to have an impact on demand in the next period.