The COVID-19 pandemic has altered the buying behaviour of consumers. Not only has it made online shopping a norm, consumers are also buying more regularly at higher volumes and with less brand loyalty. Even though this behaviour was assumed to be specific to the onset of the pandemic, it has not abated at all. Two and a half years on, this buying pattern endures.
However, though online shopping has fuelled demand for products, businesses are struggling to fulfil such demands due to a lack of supplies. This is largely attributed to global lockdowns that have affected various manufacturing sectors and supply chains. Reportedly, as many as 75% of businesses have experienced supply disruption and 16% even encountered a drop in revenue.
But what can retailers do to survive this trying time? Read on to find out how businesses can fine-tune their demand planning considerations to maintain their revenue and growth in this post-pandemic era.
Pandemic and Post-Pandemic Retail Supply Chain Challenges
One of the key challenges that retailers face in their supply chains is getting the right products in the right distribution channels, at the right time. And with a weakened workforce, increase in geopolitical tension, and limited cross-border commercial exchanges, it is becoming increasingly hard for them to cope with such circumstances that threaten to derail their business plans. Additionally, with a shortage of business contracts from manufacturers and suppliers, the supply chain networks are also struggling to survive due to cash flow problems.
Although the pandemic caused a surge in the adoption of e-commerce by consumers, it has also nudged many retail businesses towards the precipice of oblivion, with many of these businesses caught napping, unprepared and unequipped to cope with the consumers’ rising demands. As for businesses who have an existing online presence and the infrastructure to hawk their wares, they too struggled, as instability in the supply chains resulted in the inability to meet demands.
Proper Demand Planning by Retailers
To overcome the aforementioned challenges, many retailers have adopted demand planning systems that leverage historical data, finely tuned parameters, and analytical models to meet new retail priorities. Unlike pre-COVID systems that were not designed to react to short-term demand signals, the demand planning model combines pandemic sales history with cyclical forecasting and promotional analytics to forecast future demands and supplies with worst-case pandemic scenarios as a consideration. In the current retail climate, such a system will be more accurate, as the traditional method of using historical data (usually captured within two to three years’ time frame) is not applicable in this near post-pandemic era.
Although data collated at the onset of the COVID-19 pandemic might not be applicable anymore, it would be erroneous to think that such data can and should be ignored as it is no longer accurate. Such data can still be kept and used in future scenarios that might involve the outbreak of another deadly disease.
The COVID-19 pandemic has modified the behaviour of consumers and we are unlikely to see the situation revert to pre-pandemic levels. What businesses will have to understand is that a paradigm shift has taken place, and consumers will continue to stock up for fear that out-of-stock scenarios may happen again, and retailers will have to find means and ways to forecast product supplies to meet demand.
All things considered; retailers must also take into account that the sales figures generated during the onset of the pandemic might present an exaggerated spike that is unrealistic for current forecasts. To a certain extent, the urgency to stockpile goods did cool down as the world attempted to resume normalcy. As such, retailers ought to exercise discretion and moderate their data before they can be effectively leveraged as a forecast signal.
In a nutshell, analytics and modelling of consumer behaviour are important components for business forecasts, assortment optimisation, and inventory optimisation. Until such time when global shortages no longer pose a threat and consumers can shake off this irrational buying behaviour, retail analytics tools are necessary for data collation, but they must also be subjected to regular fine-tuning to ensure the accuracy of demand planning.