Retail surgery: How can I forecast levels of supply chain demand?

As online traffic increases dramatically, retailers are struggling to meet the increasing expectations of shoppers. So how can they overcome this obstacle and accurately forecast demand to maximise sales and avoid running out of stock?

Retailers are investing heavily in big data to help predict demand and adjust buying strategies accordingly.

It is therefore key for retailers to invest in a data analytics strategy in order to capitalise on insights and make the consumer mindset measurable.

“Combining disparate datasets across channels can help in the identification of patterns,” says Anant Sharma, chief executive of ecommerce agency Matter Of Form.

“This is increasingly instrumental in the survival and success of retail organisations, who are suffering increasing pressure to compete on price and fulfilment.”

Demand planning for retailers is becoming ever more complex as the variety of influences on shoppers increases.

Factors ranging from social network conversations through to celebrity endorsements and weather can drive sales up or down and retailers need to be aware of that.

“In order for retailers to be truly successful they need to look at the bigger picture and consider the other factors prior to getting carried away with the data,” says Sharma.

“By acting across the whole customer journey, brands can use every interaction to help inform the next. This will enable them to map the consumer journey more accurately and as a result, gain an in-depth understanding of which products will be in high demand.”