Capsim Forecasting Guide PDF

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Forecasting in Capsim Forecasting allows companies to help estimate how much they expect to sell from year to year. This is a difficult yet essential process in helping prepare a companies year long operations. The more accurately a company can forecast, the more efficently they can run and manage costs. In order to forecast sales in Capstone, or Foundations, or Global DNA there are three key steps. First, you will choose a formula to use to make your base calculation. Second, you will need to adjust for other changes you have made to your product and/or changes in the market. Third, you will want to give a little bit of a pessimistic offset to your marketing forecast and a more optimistic offset to your production schedule. To easily remember these steps, just consider the following: Formula, Adjust, and Offset. Now, there are variety of different methods to use for your base forecasting formula. The most common are the basic, potential sales, and customer survey score methods which we wil go over below. Formula Method One- Basic Growth The following walk throughs use sample numbers from a round two report (Figure 1.1 below). Feel free to plug in your own starting values and experiment on your own. The first method, called the ‘basic growth method’ takes the actual number of units sold in the last round then multiplied by the growth rate. So, if 648 units were sold for a product, let's call it 'Cab', and a growth rate of 9.8%. So all we would do is 648x1.098=711.5. The basic method is straightforward, but prone to many other factors tossing it off. That is why we recommend adjusting this figure against other factors that will affect sales and desirability. We will discuss these adjustments in the next paragraph. Formula Method Two- Potential Sales The second method is ‘potential sales’. To use this approach, you will want to see the potential units sold by product in segment, found on page 10 of your courier, under "Market share". In this case, we will call our product 'Fox', which sold in both the traditional and low end market for 5.3% and 2.3% of actual sales respectively. However, if we look at the potential market share, we see figures of 5.0% and 1.9%. Since the actual was higher than the potential, that means we got sales we didn't 'deserve' to, likely because somebody else stocked out or the market didn't have enough supply to meet demand. In order to use this method, what you will need to do, is take the total units demanded for each segment your product sold in, which in this case would be 8,809 and 11,180 and then multiply those by their respective segment growth rates, 9.2% and 11.7%, found on their respective segment analysis pages of the courier (pages 5-9). This would then give us total market demand for next year projected at 9619.4 and 12488, and here we would multiply the potential sales shares with the total demand such that our whole equation would look like this: {[0.05 x (8809x 1.092)] + [0.019 x (11180x 1.117)]}= =[(0.05x9619.4) + (0.019 x 12488)] = 480.97+237.272 =718.24 total units sold (across traditional and low end segments)

Formula Method Three- Survey Score The third approach to forecasting is called the 'December Customer Survey Score method'. This method take the customer survey scores for a given segment and then finds what your product's is proportional to its competitors in that segment. That proportion is then multiplied by the total demand expected in the next year. For an applied example, let's use 'Ebb' (See attachment). With a survey score of 33, we would first find the proportion by adding up all the survey scores for the segment: 40+31+27+33+9+12+4+1+1= 158. Next, we would divide our score by the total score: 33/158= 0.2088 or 20.88%. From there we would multiply that by the projected demand for next year: 12488 (11180 x 1.117= 12488). So, 12488 x 0.2088= 2608 units projected for next year. An important caveat to keep in mind here is that these surveys are based upon the favorability of a product at the end of the year (December). So, if you just revised a product, or have revisions coming, pay attention to the revision/release dates and when products will be updated. While the survey score method takes a few more factors into consideration than the basic approach, it is still important to adjust your figures depending upon other factors. Adjusting for Factors You will want to think about the possible impacts of decisions you have made for your products in the R&D and marketing departments. When adjusting your forecasts for various changes in the market, your goal should be to get a barometer on what direction products are going in, and then narrow down by how much, by calculating the differences in desirability and sales that you can expect based upon the changes you have made. This is where the benchmark prediction tool can become handy. While it is not useful for direct forecasting numbers, what it can help with is seeing the effect and magnitude of changes to marketing decisions. For example, let’s say we have a product, "Ant" and that the benchmark prediction says 1000. What we can then do is lower the price from $35 to $30. Then, after hitting 'recalculate', we may see the benchmark prediction figure go up to 1400. Then, what we can do is divide the new figure, 1400, by the old benchmark, 1000 to get 1400/1000= 1.4 or a 140% percent change. From there, we can see that if we do a price drop of $5 for product 'Ant', then we could see a 40% percent increase in demand for that product, holding all other things equal. That being said, since many factors are intertwined, it is hard to actually keep all other things equal, but overall this method can be a helpful tool in estimating the impact of decisions on product demand. Offset In addition, it will be helpful to think about what you expect your competitors to be doing. By attempting to assess what strategies other companies are attempting to pursue and any opportunities that may be presented to you. For example, if you predict someone will be moving toward a niche strategy, by preparing accordingly, you can fill the gap they will leave as they transition out a segment. This is just one example of a change that can significantly change demand in a segment. If TQM is enabled in your simulation, there are several initiatives that may be well worth investing in once the module goes live. Beyond this, you may also want to apply a general offset to your forecasts. We generally advise that you have a pessimistic

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sales forecast, and a more optimisitc production schedule. You can adjust for this by taking the forecast you created using the above methods and then reducing it by a little bit. Some users choose to reduce their forecasts by a certain percentage (like 3%) or do a more general estimation (i.e. rounding down to the nearest 100). Meanwhile, to make your production schedule more optimisitic, you can set supply the market with an extra month or two of sales. To calculate this, simply take your forecast you generated before and multiply it by 1.083 or 1.166 to represent one to two months of sales (1 + 1/12 or 2/12). For practice, consider what other actions a competitor may do that could hurt or help your sales. Review Forecasting is an essential but inexact science. You will never be able to have a perfectly accurate forecast for all your products, but more you can narrow down the range of possiblities, the better you can anticipate how your company will do. This will take some practice, but it will get easier over time. Just remember those three steps we mentioned earlier:

1. Formula 2. Adjust 3. Offset Remember that the whole point of the simulation is to allow you to experiment and learn. So, even if your results are not what you had expected, seize the opportunity to learn from it. Turning mistakes into opportunities is what allows real businesses to adapt and reinvent themselves every day. Also, keep in mind that you are not alone in the simulation. Should you ever have any questions about forecasting or anything else in the simulation, please feel free to reach out and contact our support staff. We are available to help you and your classmates with any contnet or technical questions you may have from 8am CST to 8pm CST, Monday through Friday by phone (1.312.477.7200), email ([email protected]), or support ticket.

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Figure 1.1

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