Ananda Chakravarty's presentation at ProductCamp Boston, June 2012

1. Forecasting Product Performance
Like A Meteorologist
ProductCamp Boston 2012
#pcampBoston
A.Chakravarty 6/9/2012

2. Problems are just as frustrating…
Jim Kosek – Funny Weather Video
Three Key Forecasts related to Product Mgt:
• Domino Effect – Power outages, Traffic backup, Black Ice
• Redundancy Effect - Snow Drifts, Windy
• Anticipated Failure – Heavy Snowfall
http://www.youtube.com/watch?v=Awwg0SO4Nck
PPT Notes provide addt’l information.

3. Workshop Overview
• Forecasting – why is it important
• Forecasting Impacts Decisions
• Limitations Review – 20 min.
• Metrics & Data
• Methods & Techniques
• Leveraging forecasts workshop
– Key Product Metrics
– Internal partnering for product success
Case – 25 min.
– Method and Technique
DISCLAIMER: This session will not discuss how you should forecast, but you should walk
away having a better understanding of what to think about and the complexity of good
forecasting for new products.

4. New Product Forecasting
• Error Rates are HIGH!
• So Why Forecast? Error rate in Guessing a
Coin Toss (50%)
1. New Product Development and Forecasting Problems. R. Simon, Journal of Business Forecasting 2009-
2010.

5. Forecasting – Why?
New Product Development (NPD)
 On average ~20% of company sales are New Products1
 Newer products typically command higher profit margins1
 In the US, 50% of revenues and 40% of profits are from New Products1
 ~26% of revenue from Engineering companies are from products < 3 years
old1
 ~70% of today’s manufactured goods will be obsolete in 6 years1
 In Fashion and High Tech that’s closer to 2 years1
 35%-45% of New Products fail immediately2
 According to Herb Baum, Former CEO of Campbell Soup Company, in
consumer business, “80% of all new products fail, only 4% reach the 20 MM
level and 0.5% break the 100MM mark.”3
Drive Sales & Profit Reduce Market Costs of
Failed Products
1. New Product Forecasting 2006. M. Singh. MIT
2. Doing it Right: Winning with New Products. R. G. Cooper. Product Management Institute 2006.
3. Journal of Business Forecasting C. L. Jain, Editor. Winter 2009-2010.

6. Forecasting Impacts Decisions
Weather Forecasts Product Forecasts
let us decide: let us decide:
 Cover/Clothing  Product Launch
 Time/Resources  Sales Support
 Emergency  See Notes
Planning
 Event Planning

7. Forecasting NPD Limitations
Weather Forecasts Product Forecasts
Are limited: Are limited:
 Short term Accuracy  High failure rate
 Significant data collection  Almost no accuracy
 Many data points  Data collection is sparse, erratic, and
not necessarily sales drivers
 Change Impact
 Incomplete/Unknown data points
 New patterns emerge
 Product Change Impact
 Long term Impacts
 Environment Change Impact, game
theory, competitive pressures
Forecasting is difficult!  Long term Impacts are strategic only

8. Metrics for Product Managers
Qualitative Metrics
• Empirical Data • Subjective Data
Quantitative Metrics
• e.g. Sales • Delphi
• Unique Visitors • Sales Force
• Subjective Data Composite
• Market • Focus Groups
Research • Pattern Data
• Surveys • Pattern Recognition
• Look-Alikes
• Scenario Analysis

9. Metrics for Business
Business Metrics
Increase Decrease
Revenues Expenses
Product
Metrics
Product metrics must impact a business metric
Product metrics need to be translated into a P&L statement
Example: Unique Visitors X Est. Avg Revenue per Visitor = Revenue

10. Basic Meteorological Forecasting
Key Weather Forecasting Techniques:
 Persistence
 Today = Tommorrow
 Trends – Nowcasting
 Extrapolation of current variables
 Climatology
 Historical Extrapolation
 Analog Patterns
 Looks like June 6th, 1874 so…, Scenarios, Looks-Like
 Numerical Weather Predictions
 Computationally heavy, multi-variable predictive algorithms – many variations

11. Methods & Techniques
Three broad sets capture dozens
of methods
Mkt Subjective Quantitative
Research
57%
44%
39%
30%
19%
14% 15% Top methods used are
shown by percentage
Mkt Executive Sales Force Scenario Looks-Like Trend Line Moving
Research Jury Composite Analysis Analysis Analysis Average
1. Managing the Mysterious: How to Forecast New Products. Logistics Summit & Expo, Mexico 2010.
Kenneth Kahn
2. New Product Forecasting 2006. M. Singh. MIT

12. Some things to keep in mind to forecast
• Timeframe
• Assumptions
• Units of Measure – atomic
• Project Timeline and Milestones – including failure to meet impacts
• Ongoing, Cost Structure Estimations (for P&L Pro-Forma development)
• Risks & Mitigation
• Estimation technique for revenue or cost savings
• Revenue Derivation algorithm
• Validation & Assumptions Check

13. Workshop Preparation…
• TASK 1: Break out into groups of 2-5 people each and introduce
yourselves.

14. THE FORECAST CASEWORKSHOP
WeatherCommerce.com is a clicks-only online business that sells
Thermometers, Barometers, Hygrometers, and Weather stations. The site
has recently launched a new ecommerce sales engine to sell a new line of
product – the Baltimore Weather Gauge. We need to forecast product
performance post launch for 12 months.
• TASK 2: Each team take 5 minutes and create a list of 3-5 Key
Product Metrics to measure new launch success for the Baltimore
Weather Gauge
EXAMPLES:
• Monthly Sales (Units Sold) for 12 Months
• Monthly Sales ($) for 12 months

15. THE FORECAST WORKSHOP
• TASK 3: Each team takes 5 minutes to list 3-5 Key Resources and
Key Deliverables that they would reach out to develop their
forecast.
EXAMPLES:
• Marketing - Customer Market Survey, Realistic Price Points,
Existing Customer Interest
• Ecommerce Sales Operations – Site Traffic and Conversion Rates
for similar products.

16. THE FORECAST WORKSHOP
• TASK 4: Each team takes 5 minutes to list one method they would
rely on to forecast – and a quick justification of why they would
choose it.
• Note: There are no right or wrong answers. Many companies use
up to 3 methods at the same time for validation and cross-check.
EXAMPLE:
• Online Market Surveys –With many existing customers through an
ecommerce platform, we can quickly gauge product sentiment.
YOUR ORGANIZATION
• TASK 5: What techniques would you use for your company’s
products?

17. THANK YOU!
Ananda S. Chakravarty
@achakravarty
http://www.linkedin.com/in/anandachakravarty