4 A’s of demand planning for CPG companies in 2020
3 min. read

4 A’s of demand planning for CPG companies in 2020

For CPG companies, 2020 has been a unique year from multiple perspectives. It presents an unprecedented situation that calls for changes on numerous fronts of the value chain. From IoT enabled manufacturing to go “Direct to Customer”, CPG companies have got a lot going on. The dimension of CPG business that we are going to talk about here, is ‘Demand Planning’, in these uncertain times.

We believe demand planning in the CPG world is going to get influenced by the 4 A’s. Agility, Amplitude, Adjustment, and Accuracy. What exactly changed after COVID hit us that makes these 4 A’s extremely crucial and to be handled in conjunction? We think it is – variability. More and more external factors are going to influence short and medium-term demand planning. Even long-term planning must be done considering external variables such as economy, mobility of people, channel shifts, local factors, consumer trends, climate changes, etc.

The new world calls for agility in demand planning tasks. How quickly can a demand planner come up with new Forecasts after making changes to the associated factors. Depending on the category, forecasting exercise might even be needed every month. New variables will be needed to get ingested conveniently during the forecasting exercise. Agility is needed in creating multiple versions of forecasts, in tagging and recording results for future reference. Demand planners will have to predict demand, preferably, at the most granular level. Forecasting demand at county or store for all the SKUs in the category would be critical to identify demand pattern differences between multiple pack sizes, and even counties that are just a few miles apart. The amplitude of forecasting that covers a wide range is the key here.

COVID presented a never seen before situation. For demand planners, it posed a challenge to plan for demand separately by creating different time frames. This would require them to do adjustments to fine-tune the demand predicted by machine learning models. It might take a few years before volatility goes back to pre-COVID levels. Ease of adjusting demand prediction using adjustment factors or other algorithmic techniques is going to be a part and parcel of demand planner’s work now.  All the other A’s need to be balanced keeping in mind the paramount importance of accuracy.

The world might take another 3-5 years before the business environment around us smoothens. Till then, demand planners should be agile, cover amplitude, keep adjusting, and still try to be as accurate as possible.