Crystal Ball enhances your Excel model by letting you create probability distributions that describe the uncertainty surrounding specific input variables. This model includes 13 probability distributions, referred to in Crystal Ball as "assumptions." Read More about Oracle Crystal Ball. Website: http://www.binarysemantics.com/SoftwareProduct/SoftwareProduct_crystalball.htm

1. Oracle Crystal Ball
Product Forecasting Model
Marketing Team
Binary Semantics Ltd.
Plot No: 38, Electronic City
Sector – 18. Gurgaon – 122015
Haryana, India
marketing@binarysemantics.com
www.binarysemantics.com

2. Case Study
• Product Marketing and Forecasting Analysis of an emerging
media product, Interactive TV (ITV).
• Colorado Cable has created a discounted cash flow (DCF)
analysis that examines the success of the product over a six-
year period.
• Monte Carlo simulation and time-series forecasting are used
to provide a greater understanding and quantification of the
risks inherent in a spreadsheet-based business forecast.

3. Quick View

4. Problem Summary
• Colorado Cable, a local cable provider, is evaluating a new technology known
as Interactive TV (ITV). ITV will provide content - movies, sports games, and
news - on demand. Colorado Cable believes that the local audience will
embrace this type of service, but the company is concerned that there might
be some unanticipated risks because of the down economy.
• Management has requested from you a forecast model for ITV from its
introduction in 2004 through to 2009. They want to better understand the
sales and marketing potential of this new technology before making a hefty
investment. Does ITV have enough potential to merit bringing it to market?
What is the Net Present Value (NPV) over six years? What are the key
success factors driving the bottom-line performance of the new product?

5. Problem Summary
• Your model examines four products: cable, satellite dish, broadcast TV, and
ITV. The first three products are already offered by Colorado Cable. The
model estimates the number of households with TV for each future year and
the market share and market size for each of the four products. Based on
twenty years of historical data, you have estimated a constant growth rate
of 50,000 new households with TV per year, although you know that the
actual rate of increase is somewhat less predictable. You will address that
aspect of the model later with time-series forecasting methods.

6. Problem Summary
• You have made the assumption that while the demand for satellite TV will
grow at a slow, steady rate, ITV will draw its growing share of viewers from
households with either cable or broadcast TV. You expect operating costs
for ITV to grow each year, and that while uncertain, the initial investment in
2004 for ITV will average $100 million. You also expect to see an annual
revenue increase of $5 per household. Finally, the model calculates the ITV
revenues, expenses, net profit, and Net Present Value (NPV). Your original,
or base case, NPV estimate for ITV is slightly more than $56 million (with a
10% discount rate).

7. Using Crystal Ball
• Crystal Ball enhances your Excel model by letting you create probability
distributions that describe the uncertainty surrounding specific input variables.
This model includes 13 probability distributions, referred to in Crystal Ball as
"assumptions." Six assumptions describe the uncertainty around the market share
of ITV, and six others describe the uncertainty around the annual operating
expenses for ITV. The final assumption describes the uncertainty for the Initial
Investment in 2004.
• Each assumption cell is colored green and is marked by an Excel note (mouse
over the cell to view the note). To view the details of an assumption,
highlight the cell and either select Define Assumption from the Define menu
or click on the Define Assumption button on the Crystal Ball toolbar. The
ranges and types of assumptions are based on your market research.

8. Using Crystal Ball
• This model also includes one Crystal Ball forecast, shown in light blue.
Forecasts are equations, or outputs, that you want to analyze after a
simulation. During a simulation, Crystal Ball saves the values in the forecast
cells and displays them in a forecast chart, which is a histogram of the
simulated forecast values. In this example, you want to analyze the Net
Present Value. To view a forecast with Crystal Ball, highlight the cell and
either select Define Forecast from the Define menu or click on the Define
Forecast button on the Crystal Ball toolbar.

9. Screenshot

10. Using Crystal Ball
• When you run a simulation, Crystal Ball generates a random number for each
assumption (based on how the assumption has been defined) and places
that new value in the cell. Excel then recalculates the model. You can test
this by selecting Single Step from the Run menu or clicking on the Single
Step button on the Crystal Ball toolbar.
• After you run a simulation, you will see the NPV forecast chart, which you
can use to analyze the potential success of ITV. What is the mean NPV?
What is your certainty of making $51 million (your original prediction)?
What is the certainty that you may lose money on this product? You can
view the statistics and percentiles of the forecast, too. Are the mean and
median values close? If not, can you tell why, and is it important to your
forecast?

11. Screenshot

12. Using Crystal Ball
• To view which of the assumptions had the greatest impact on
the NPV, use a sensitivity chart. Which assumptions most
affect this forecast? What effect does the Initial Investment
have on the NPV? Do the market share assumptions have a
greater or lesser effect than the operating cost assumptions?
Are your market share assumptions reasonable? What will
happen if you reduce the ranges of these distributions and re-
run your simulation?

13. Screenshot

14. Using Crystal Ball Predictor
• To run Predictor, select any cell within the
data series you plan to forecast (to the right of
the model) and open the program from the
Run menu. The first four steps help you to
define, organize, and view the data. An
autocorrelation feature determines if any
seasonality (shown as lags) is present in the
data. In this annual data, there is no
seasonality, just an increase in number of
households.

15. Screenshot

16. Screenshot

17. Thank You!!
Contact us for Oracle Crystal Ball:-
Marketing Team
Binary Semantics Ltd.
Plot No: 38, Electronic City
Sector – 18. Gurgaon – 122015
Haryana, India
marketing@binarysemantics.com | www.binarysemantics.com