Product Life Cycle Estimation

A. Abstract

B. An Introduction to Product Life Cycle (PLC)

  1. Seasonal — Products that are seasonal (for e.g. mufflers, that are on shelves mostly in winter) have a steeper incline/decline due to the short growth and decline periods
  2. Non-Seasonal — Products that are non-seasonal (for e.g. jeans, that are promoted in all seasons) have longer maturity and decline periods as sales tend to continue as long as stocks last

Definition of Various stages of PLC

C. Why do businesses need PLC and how does it help them?

  • Provide promotions and markdowns at the right time
  • Plan inventory levels better by incorporating PLC in demand prediction
  • Plan product launch dates/season
  • Determine the optimal discount percentages based on a product’s PLC stage (as discussed later in this paper)

D. How does the solution in this paper help?

  • To identify products similar to a newly released product, we clustered products based on the significant factors affecting sales. This gives us a chance to obtain a data based PLC trend
  • Next, sales is used to plot the Cumulative Sell Through Rate vs Product Age (in weeks)
  • A log-growth model fit across this plot will provide the Life Cycle trend of that product or cluster of products
  • The second differential of this curve can be analyzed to identify shifts in PLC phases, to estimate the durations of each of the PLC phases

E. Detailed Approach to estimate PLC

i. Product Segmentation

Other Methods explored

Method 1:

  • Calculated (Daily Sales / Total Inventory) across Cumulative Sell through rate at a category level
  • A curve between Cumulative Sell through rate (x-axis) and (Daily Sales / Total Inventory) in the y-axis was fitted using non-linear least square regression
  • Using inflexion points of the fitted curve cut-off for different phases of product life cycle is obtained
  • Calculated cumulative sell through rate across age at a category level
  • A curve between age and cumulative sell through rate was fitted using a log linear model
  • Using inflexion points of the fitted curve cut-off for different phases of product life cycle is obtained
  1. Visual inspection of the fitted curve does not reveal any PLC stages
  2. This method could not capture the trend as accurately as the log-growth models

F. Application of PLC stages in Demand prediction

G. Conclusion

References

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