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  • Sarvesh Kumar, CEO

The need for dynamic forecasting with all market drivers

Growing Retail Market Uncertainty

We are at an important turning point for retail and FMCG businesses.

In an increasingly complex and ever-more quickly changing world, people can no longer be relied upon to predict future fluctuations in supply and demand. We just aren’t fast enough, and we can’t fold in all the necessary variables.

The best example we have of this so far is what happened during the depths of the COVID-19 pandemic. Consumer products from dried beans, and pasta, to toilet rolls, to hand soap was in steeply increasing demand while the supply chains our grocery stores relied on experienced unprecedented stress.

And things haven’t returned to anything like ‘normal’. With war raging in Europe and affecting supplies of gas, wheat, and fertiliser, and a shortage of semiconductors continuing to plague industries as varied as car manufacturing and smartphone production, supply and demand are only becoming more unpredictable.

What does this mean for trends and needs forecasting?

In the past, forecasts have been made with the help of historical data.

But when unexpected and/or sudden internationally significant events occur, this data simply ceases to be representative. Sales of hand soap, for example, were steady year in, year out before Covid. Sales then spiked in 2020. Using that now historical data, we would expect a continued rise into 2022-23. But obviously, that’s not actually happening.

That being said, habits learned during Covid will still exist to an extent. Plus, monkeypox is on the horizon! The changing macro factors like Inflation and Unemployment compounded due to global political developments and other factors including pricing and distribution come together in each channel to impact consumer purchase behaviour.

Even the best human data analyst would have trouble integrating all those factors in an Excel spreadsheet.

A new AI & ML based forecasting technology designed for direct business

Singular Intelligence uses multiple machine learning algorithms along with real-time data to run multiple potential scenarios across the whole value chain, making predictions for use by every department, from marketing to distribution, to sales.

A single product like Singular Intelligence can provide monthly predictions. Even quarterly predictions take a lot of time, manpower, and money. The volume of data provided by machine learning would simply be impossible with a human team. And by using SIngular Intelligence in-house, you can make predictions specific to your business almost instantly without communicating with - or paying for - a middle man.

With AI, there’s no betting on a single number being correct - rather, your e-commerce or FMCG business can work with a prediction that takes into account potential changes in global supply chains, customer psychology, weather, and much more, taking a granular view across the market structure.

Practical Uses For Singular Intelligence Software & service

As prices rise and some products become scarce, it will be more important than ever to reduce waste, price products competitively while taking into account price changes across the board, forecast coming shortages, and move towards increasingly intelligent supply planning.

Ultimately, it is likely that margins for FMCG and retail businesses will be squeezed in the coming quarters. Reliable demand forecasting - without having to employ an entire team to make it happen - could mean the difference between profit and loss.

Learn more:

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