Demand Planning lessons from Covid-19 second wave in India
Demand Planning which is the trigger for the entire Supply side of the Supply Chain to organize itself to meet the market within its SLA's again has been found wanting in its (in)accuracy! And as it stands today in India, the Demand Planning accuracy seems to have been much lower than desired.
A few key insights from the current stage of Covid-19 viewed from the lenses of Demand Planning,
a. Never underestimate the importance of History - "This time its different" is a misnomer. Human history is of similar behaviours exhibited over multiple instances spread over different time periods. Historical data is a goldmine for Demand Planning. e.g. Relating this to Covid-19 - No time in the history of past 400 years of Pandemics (just 400 years as I did only study those 400 years), has the Pandemic ever passed its peak in a single wave or less than two years. So why should one assume it be different this time around?
b. Like modeling is useful - When a New product is to be launched or a variant with no historical data is being introduced, Demand Planners rely on "Like Modeling". While it has its own limitations, I believe that a gross error on the Higher or Lower side without any model is much better than committing the same error but with a base model.e.g. Relating this to Covid-19 - 1918-1920 period of the last pandemic could be used for Like Modeling & deployed for the current pandemic. Like modeling would guide the society to know the number of Waves & their characteristics.
c. Increasing Demand network nodes with increasing Supply side capacity is a show stopper - Most of the organizations like to capture the demand before it is grabbed by the competitor or the demand subsides. While garnering market share is a desire without many objections, the reality is Demand is a "number" which has to be met through a "Supply Chain" structure. Hence adding new channels or channels partners to reach the customer is a good Network Strategy which needs to be equally supported & balanced with Supply side ability to reach the demand nodes.e.g. In India, the vaccination centers have gone up multi fold while the ramp up in the supply of vaccines lags the demand side. As nodes get created, customer expectations also increase. Non availability is perceived as Supply Chain failure than out of step Marketing Strategy.
d. Demand Planning to Demand Driven to Demand Sensing - A lot of Demand Planning professionals (erstwhile me included) deploy forecast based planning. It naturally is Backward planning. Mature organizations have moved toward Demand Driven Planning. Technology enabled systems may move further into Demand sensing. The point to be noted is that Demand, whichever way it is captured & planned requires a certain amount of lead time to be met. Sometimes it can be a change in production process due to a minor change in SKU's priority or it can be as large as creating new infrastructure to meet the demand. Demand Planners need to bear that in mind. e.g. When a new Covid-19 variant was discovered in some other country, it is naive to believe that my home country shall extend the existing variant or only get the same newly discovered other country variant into my home country are the only outcomes. Demand Sensing should have helped to identify potential demand surge due a non existent existing variant which may surface for the first time in my home country.
The lag in Supply side due its infrastructure bottlenecks shall lead to Demand side not getting what it needs when it needs it. The risk also is that by the time Supply side of the Supply Chain is ready to service the demand, the lag is so much so that the Demand may subside. The enterprise (in this case Indian government) Capital expenditure shall be wasted.
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