Game mechanics - Product quality estimate
08.12.2014
In new version of GMC simulator appeared important innovation in management reports - sheet "W", which stores data for formation of the remaining sheets (useful in calculation model development). However, if you parse each row in sheet "W", then you will see, that part of rows remains unused data in lines - 102, 103, 104, 105, 106, 107. For example:
- 172
- 164
- 140
- 5.65
- 5.25
- 4.04
Easy to guess that this is customer’s quality estimate of your product. Previously, if you want to find out quality estimate, you must buy information about corporate activity. But now, you only need to open sheet "W". Moreover, in data estimate expressed not in stars (*), but numerically. That allows to find mechanism of quality estimation by comparing different management reports together.
Product quality estimate consists of three components:
Research and Development
Table contains quality estimates for 10 periods (including 5 periods of history).
| Period | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|---|---|---|---|---|---|---|---|---|---|---|
| Product estimate 1 | 96 | 96 | 96 | 96 | 96 | 96 | 134 | 133 | 132 | 131 |
| Product estimate 2 | 96 | 91 | 92 | 93 | 94 | 133 | 151 | 149 | 147 | 164 |
| Product estimate 3 | 153 | 151 | 149 | 166 | 163 | 160 | 176 | 172 | 169 | 166 |
| Quality Product 1 | 1,85 | 1,85 | 1,85 | 1,85 | 1,85 | 1.85 | 3.73 | 3.71 | 3.66 | 3.55 |
| Quality Product 2 | 1,83 | 1,58 | 1,63 | 1,68 | 1,73 | 3.68 | 4.58 | 4.51 | 4.41 | 5.20 |
| Quality Product 3 | 4,68 | 4,58 | 4,48 | 5,33 | 5,18 | 5.03 | 5.80 | 5.66 | 5.51 | 5.30 |
The minimum possible estimate for R&D is 61, which corresponds to 1 star, less estimate is impossible. Next star is 81 points, etc. step is 20:
- > 60 - 1 star
- > 80 - 2 stars
- > 100 - 3 stars
- > 120 - 4 stars
- > 140 - 5 stars
Formula for calculating the number of stars for product quality = (Product estimate - 60) / 20
For example, estimate for the product is 96, count the number of stars = (96 - 60) / 20 = 1.8 - the result is always rounded up and equal 2 stars.
Quality estimate in R&D depends on:
- Getting R&D
- Implementation of R&D
- Obsolescence of product
Getting and implementation MINOR gives +6 points, getting and implementation of MINOR occurs immediately.
Getting MAJOR gives +6 points, getting MAJOR is equal to getting MINOR.
Implementation of MAJOR gives +20 points, implementation MAJOR additionally gives +20 points, ie 1 star. Not implemented R&D before are timeless and always increases quality estimate by 20 points.
This explains the difference between the MINOR and MAJOR, 26 / 6 = 4.33. getting and implementation of MAJOR more profitable to 4.33 times than MINOR.
Obsolescence process reduces quality estimate - depending on the absolute value, estimate is reduced each period. The higher quality estimate of the product, the faster it becomes old.
| Number of stars | Obsolescence |
|---|---|
| > 0 | -4 |
| > 1 | -5 |
| > 2 | -6 |
| > 3 | -7 |
| > 4 | -8 |
| > 5 | -9 |
| > 6 | -10 |
When forecasting product quality estimate in current period, you need to take an estimate of the product in previous period and add the effect of R&D. For example, we have implemented previously received MAJOR development, then estimate of the product in current period will be equal to 96 + 20 = 116. Calculate number of stars after implementation (116 - 60) / 20 = 2.8 stars, which corresponds to obsolescence -6, therefore 116 - 6 = 110 - real estimate of the product. Calculate estimate into stars (110 - 60) / 20 = 2.5 - rounded, equal 3 stars.
Assembly time
Assembly time should be transformed from absolute time in minutes to percentage. If assembly time for Product 3 equals 345 minutes, then percentage will be equal 345/300 = 115% or +15% of normal time. Each additional percentage increases quality estimate of the product, but effect is decreasing and each additional percentage has lighter weight than the previous one. The resulting score should be added to the overall quality estimate of the product. Estimate is rounded according to rule of rounding.
| Assembly time, % | Coefficient |
|---|---|
| 1 - 20 | 0.00315 |
| 21 - 40 | 0.00310 |
| 41 - 60 | 0.00305 |
| 61 - 80 | 0.00300 |
| 81 - 100 | 0.00295 |
For example, assembly time 115% will add to quality of the product 15 * 0.00315 = 0.04725. Proportions are the same for each product.
High quality raw materials
Also, as for the assembly time, each additional percent increase quality estimate of the product, but effect is decreasing and each additional percentage has lighter weight than the previous one. Resulting score should be added to the overall quality estimate of the product. Estimate is rounded according to the rule of rounding.
| High quality raw materials, % | Coefficient |
|---|---|
| 1 - 20 | 0.00165 |
| 21 - 40 | 0,00160 |
| 41 - 60 | 0.00155 |
| 61 - 80 | 0.00150 |
| 81 - 100 | 0.00145 |
For example, high quality raw materials 30% will add to the quality of the product 30 * 0.0016 = 0.048. The proportions are the same for each product.
Overall quality estimate
Estimation value sum from R&D, assembly time and hign quality raw materials. Than it is rounded to the nearest hundredth according to the rule. Actual error of such estimation is +/- 0.01 compared with fact.
Automatic estimation of product quality is built into the Calculation model, which can be purchased in our store.