Data-driven product forecasting

Data-Driven Decision Making for Business

Ted Kwartler

Data Dude

Not always simple

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Data-Driven Decision Making for Business

Products on products on products

The number of new products sold dictate the number of customer service phone calls received

Data-Driven Decision Making for Business

Growth model example

BASS model: early adopters curve and late adopter curve combine over time for the total market

curves

Data-Driven Decision Making for Business

Innovation vs. imitation

  • m: Total market capacity
  • p: Rate of innovation
  • q: Rate of imitation

At any given point in time, the forecast is the sum of p and q rates along reaching towards the total market capacity

Data-Driven Decision Making for Business

P: Innovation behavior

  • Steep decline
  • "People enticed and willing to take a chance"
  • Smaller total number

Data-Driven Decision Making for Business

Q: Imitation behavior

  • Larger total number
  • Steep incline as they learn from innovators
  • "People eventually won over"

Data-Driven Decision Making for Business

P & Q side by side

P: Innovation

Q: Imitation

Data-Driven Decision Making for Business

Altogether now

Data-Driven Decision Making for Business

Historical P & Q

Product P-Inno Q - Imit
B/W TV .108 .231
Color TV .059 .146
Room Air Con. .006 .185
Dryers .009 .143
CD Player .055 .378
Cell Phones .008 .421
Steam Iron .031 .128
Microwave .002 .357
Hybrid Corn .000 .797
Home PC .121 .281

Averages:

  • P = 0.03
  • Q = 0.38
1 https://slideplayer.com/slide/1423750/
Data-Driven Decision Making for Business

Let's practice!

Data-Driven Decision Making for Business

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