Your SlideShare is downloading. ×
0
Forecasting Product PerformanceLike A MeteorologistProductCamp Boston 2012#pcampBostonA.Chakravarty 6/9/2012
Problems are just as frustrating…        Jim Kosek – Funny Weather Video        Three Key Forecasts related to Product Mgt...
Workshop Overview • Forecasting – why is it important • Forecasting Impacts Decisions • Limitations                       ...
New Product Forecasting• Error Rates are HIGH!• So Why Forecast?                                                     Error...
Forecasting – Why? New Product Development (NPD) On average ~20% of company sales are New Products1 Newer products typic...
Forecasting Impacts DecisionsWeather Forecasts               Product Forecastslet us decide:                  let us decid...
Forecasting NPD LimitationsWeather Forecasts                    Product ForecastsAre limited:                         Are ...
Metrics for Product Managers                                             Qualitative Metrics                       • Empir...
Metrics for Business                         Business Metrics                    Increase           Decrease              ...
Basic Meteorological Forecasting      Key Weather Forecasting Techniques: Persistence    Today = Tommorrow Trends – Now...
Methods & TechniquesThree broad sets capture dozensof methods  Mkt                 Subjective                       Quanti...
Some things to keep in mind to forecast• Timeframe• Assumptions• Units of Measure – atomic• Project Timeline and Milestone...
Workshop Preparation…• TASK 1: Break out into groups of 2-5 people each and introduce  yourselves.
THE FORECAST CASEWORKSHOPWeatherCommerce.com is a clicks-only online business that sellsThermometers, Barometers, Hygromet...
THE FORECAST WORKSHOP• TASK 3: Each team takes 5 minutes to list 3-5 Key Resources and  Key Deliverables that they would r...
THE FORECAST WORKSHOP• TASK 4: Each team takes 5 minutes to list one method they would  rely on to forecast – and a quick ...
THANK YOU!           Ananda S. Chakravarty               @achakravartyhttp://www.linkedin.com/in/anandachakravarty
Upcoming SlideShare
Loading in...5
×

Forecasting Product Performance Like a Meteorologist (June 2012)

694

Published on

Ananda Chakravarty's presentation at ProductCamp Boston, June 2012

Published in: Business, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
694
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
13
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • Most resources on product mgt tell you to go talk to your finance people. They are a great resource, but you need to be able to pull together some basic numbers you can share with leadership and build your own estimations of product performance – a timeline with milestones is a great way to build this out, especially in conjunction with a specific metrics guidelines at specific stages.
  • New products include: (M. Singh)Cost improvements – reduced price/cost productsProduct improvements to existing products/servicesLine Extensions – incremental innovationsMarket Extensions – same product, new segment/marketNew Category Entry – New to company product or market, but already exists in general marketNew to the World – Completely new product concept, may be competing with current marketsWithout knowing what to expect, even if you’re not going to be on target, it helps to drive actual sales & profit, keeps you on top of what you need to mitigate, and helps reduce the market costs of a failed product – it’s just as good to know if a product isn’t worth building…
  • Forecasts enable decision making – including:Product Launch decisions (go/kill)Business Strategic Impact, CannibalizationCapacity PlanningManufacturingLogisticsMarketing BudgetsMarketing PromotionsSales SupportSales TrainingFinance BudgetsFinance ImpactEngineering/Development Feature DevelopmentCustomer service planningPartnership/Distribution of products/servicesStrategic product decisions – Build, buy, partnerStrategic product decisions – extend the line, expand the line, new featuresStrategic market decisions – adjacent market entry, new market creation
  • Short Term – Best meteorology is up to 10 days out with any level of accuracySignificant Data Collection – Satellites, Weather Stations, Direct ReportingMany Data Points –Temperature, humidity, dew point, atmospheric pressure, wind speed, wind direction, geo-location, topography, distance to water bodies, climatologySignificant Change impact - small changes in weather patterns translate to large impactNew patterns emerge – each day brings about significant new patterns in weather and similar conditions are challenging depending on location and historyLong Term Impacts – Impacts to terrain and local environment is a major challenge when considering longer term forecastingProduct Forecasts Limited:High Failure rate – 96% of consumer product fail to break even by year 1No Accuracy – most products have overpromised forecasts and substantial sales hype – cannibalization is not taken into accountData collection – inadequate at best, even with web technology, most new products take into account a few parameters related to it’s nature, e.g. site traffic or conversion rates. These don’t necessarily translate into sales relevant dataIncomplete/Unknown data points – examples are brand presence, market product rejection, native competition, product errors/recall, geographic/cultural preferencesProduct Change Impact – product updates are regularly changing, even for existing (Not-NPDs) product features may not be relevant or include customer sentiment, backward compatibility can become an issue with certain productsEnvironment change impact – review SWOT, but essentially, competitive factors can blot out successes quickly – fast copycats and new entrants can obliterate a product’s successLong Term impacts – Strategic in nature – usually defensive or supportive, impacts product portfolio and product mix hence actual impact to the organization can be indirect. A strong loss leader may be driving substantial value for the company, but examining the product shows poor results. Indirect metrics are challenging
  • Key Metrics:Quant – Empirical, SubjectiveQuality – Subjective, Pattern
  • All metrics roll up to the eventual fiduciary responsibilities of the organization – typically this is profitability best described as increase revenues or decrease expenses.
  • Typical techniques used in Meteorology are quite similar to what we might use in basic product mgt.
  • Dozens of methods, the most common fall into meteorological forecasting stylesQualitative methods, including market research, Delphi, and others are unsubstantiated by quantitative data.Key Quantitative methods, e.g. Bass and other Diffusion models are plagued by parameter and initial value accuracy issues.
  • Review per team up to 3 teams (5-10 min)Key product metrics are critical to define up front– these are the metrics that will have the most impact .Focus on the product should be the physical product, not the ecommerce engine (although this may impact sales)Issues that come to mind include cannibalization, site traffic, similar.No right or wrong answers, looking for the best way to measure product success and tie it back to key business metrics (profitability through incremental revenue or cost savings)
  • Forecasts enable decision making – including:Product Launch decisions (go/kill)Business Strategic Impact, CannibalizationCapacity PlanningManufacturingLogisticsMarketing BudgetsMarketing PromotionsSales SupportSales TrainingFinance BudgetsFinance ImpactEngineering/Development Feature DevelopmentCustomer service planningPartnership/Distribution of products/servicesStrategic product decisions – Build, buy, partnerStrategic product decisions – extend the line, expand the line, new featuresStrategic market decisions – adjacent market entry, new market creation
  • Transcript of "Forecasting Product Performance Like a Meteorologist (June 2012)"

    1. 1. Forecasting Product PerformanceLike A MeteorologistProductCamp Boston 2012#pcampBostonA.Chakravarty 6/9/2012
    2. 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. 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 TechniqueDISCLAIMER: This session will not discuss how you should forecast, but you should walkaway having a better understanding of what to think about and the complexity of goodforecasting for new products.
    4. 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. 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. 6. Forecasting Impacts DecisionsWeather Forecasts Product Forecastslet us decide: let us decide: Cover/Clothing  Product Launch Time/Resources  Sales Support Emergency  See Notes Planning Event Planning
    7. 7. Forecasting NPD LimitationsWeather Forecasts Product ForecastsAre 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 pressuresForecasting is difficult!  Long term Impacts are strategic only
    8. 8. Metrics for Product Managers Qualitative Metrics • Empirical Data • Subjective DataQuantitative 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. 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. 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. 11. Methods & TechniquesThree broad sets capture dozensof methods Mkt Subjective QuantitativeResearch 57% 44% 39% 30% 19% 14% 15% Top methods used are shown by percentage Mkt Executive Sales Force Scenario Looks-Like Trend Line MovingResearch Jury Composite Analysis Analysis Analysis Average1. Managing the Mysterious: How to Forecast New Products. Logistics Summit & Expo, Mexico 2010. Kenneth Kahn2. New Product Forecasting 2006. M. Singh. MIT
    12. 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. 13. Workshop Preparation…• TASK 1: Break out into groups of 2-5 people each and introduce yourselves.
    14. 14. THE FORECAST CASEWORKSHOPWeatherCommerce.com is a clicks-only online business that sellsThermometers, Barometers, Hygrometers, and Weather stations. The sitehas recently launched a new ecommerce sales engine to sell a new line ofproduct – the Baltimore Weather Gauge. We need to forecast productperformance 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 GaugeEXAMPLES:• Monthly Sales (Units Sold) for 12 Months• Monthly Sales ($) for 12 months
    15. 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. 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. 17. THANK YOU! Ananda S. Chakravarty @achakravartyhttp://www.linkedin.com/in/anandachakravarty
    1. A particular slide catching your eye?

      Clipping is a handy way to collect important slides you want to go back to later.

    ×