Sep 26, 2019

Case Study: How Machine Learning Helps Seasonal Delivery


Views expressed here are from author’s industry experience. Author trains on and blogs Machine (Deep) Learning applications; for further details, he will be available at mavuluri.pradeep@gmail.com for more details.

Find more about author at http://in.linkedin.com/in/pradeepmavuluri

Sep 10, 2019

Finite Life Cycle - Fast Moving (Tech) Consumer Goods Demand Behavior


In today’s tech world, few products being introduced into the market that have a finite (or limited) life cycle with new features from time to time in order to show case their innovations or for brand enhancement.
So, how does their sales/demand cycle look alike and what manufacturers need to understand about their demand behavior/forecasts. Towards the same, first one need to understand that new product sales/demand forecasting/behavior becomes an issue due to mainly, a) non-availability of recent data, b) product is not exactly same as old offer, and c) further, it will have distinct phases such as i) introduction with/without promotion phase, ii) growth phase (or growth due to heavy promotions), and iii) decline phase with/with out season ending sales (discounts). In addition to above, till few time points (e.g. first few days/weeks of its launch), it is difficult to understand its recipient nature in the market. Thus, one can generalize their demand with respect to two scenarios as depicted in the below figure.


In the above figure, orange line represents unsuccessful product ending up with more promotions/discount to clear out produced supply, where, as green line represents successful product ending up with less promotions/discounts. Remember, one need to understand that till left of green/orange dotted line is a phase of low promotions/discounts, after that, it moves to higher promotions/discounts phase.

Views expressed here are from author’s industry experience. Author trains on and blogs Machine (Deep) Learning applications; for further details, he will be available at mavuluri.pradeep@gmail.com for more details.


Find more about author at http://in.linkedin.com/in/pradeepmavuluri