Llamasoft: 73% of retailers believe AI can add significant value to their demand forecasting

Llamasoft, a leading provider of AI-powered supply chain analytics software to 750 of the world’s leading brands, has published the results of a global retail supply chain study which revealed that 73% of retailers believe AI and Machine Learning can add significant value to their demand forecasting processes, and over half say it will improve 8 other critical supply chain capabilities.

The research also found that while 56% of overperforming retailers, also known as “retail winners,” use technology to model contingency plans for severe supply chain interruptions, a mere 31% of retailers who are not overperforming do the same. Overall, 56% of retailers surveyed are struggling with the ability to respond to rapid shifts and the lack of flexibility has cost them during the disruptions such as COVID-19, with many seeing a huge drop in revenue as a result.

In addition, 73% of ‘retail winners’ have the foresight and ability to monitor capacity, which allows them to prepare for sudden shifts in demand and supply, compared to 35% of ‘other’ or ‘under-performing’ retailers. This is a clear indication that retail winners are outmaneuvering the competition by predicting and preparing for the future. However, without the ability to adapt to these sudden spikes and troughs with contingency planning, the forecasting would be of little use. Therefore, the two must be married together to produce a “retail winner.”

COVID-19 has further illustrated that, moving forward, retailers must rapidly adjust to the ‘never normal’ world we find ourselves in and they must act to consistently enable faster responses to succeed. There will always be market variations and disruptions, meaning that retailers must be able to forecast for these changes and adapt quickly. Ultimately, this is nothing new. While COVID-19 has accelerated certain changes, such as the move to e-commerce, retail habits were already shifting and the need to adapt was a pressing concern.

The study found the following when looking at what retail winners are doing to overachieve:
● 53% of “winners” have invested in data scientists that are competent with data analysis and modeling tools, while just 22% of underperforming retailers have
● 80% of “winners” place a ‘high value’ on demand forecast modeling using macro indicators, while just 65% of underperforming retailers have
● 53% of “winners” rank geopolitical issues such as tariffs, trade wars and rapidly changing consumer demand in their top 3 challenges, while just 23% of underperforming retailers do
● Meanwhile, 46% of retailers who are either underperforming or performing at an average level are clinging to the old normal and focusing on cost (at the expense of flexibility), while just 38% of “winners” are

Rather than implementing newer AI and analytic technologies which enable organizations to better prepare for the future, underperforming retailers are struggling to move away from strategies designed to find the lowest-cost point of manufacture on a product-by-product basis. The contrast is clear: those who can prepare for the unexpected win, while those unable to adapt falter.

While some retailers are ahead in terms of their technical ability, the study shows the retail industry as a whole still has much room for improvement. For example, more than 50% of all retailers surveyed said their current systems were causing a ‘big’ or ‘somewhat’ of a problem in all 10 supply chain capabilities presented to them, yet 13% of retailers have not even planned to invest in technology.

“In the shadow of COVID-19, without a vaccine or successful treatment, shoppers will tire of hunkering down at home and start to visit stores as they re-open across the globe in phases, but in far different ways (and in far fewer numbers) than pre-outbreak. So, retailers are in a ‘new never normal’ environment,” said Brian Kilcourse, Managing Partner, RSR. “With such unpredictability, the ability to be agile and model potential outcomes becomes even more important. Retailers need AI-enabled predictive models for things such as labor and transportation costs across the supply chain or finding optimal DC-to-customer locations to lower costs while still satisfying rapidly changing customer needs. AI isn’t even the future anymore; it is already here.”

With retail habits changing, a process accelerated by the impacts of COVID-19, the current winners in retail are prepared to overachieve once more. Shopping behaviors are rapidly shifting to that of e-commerce, a change which will undoubtably contribute to fluctuations in demand and supply. Retailers with the technology to forecast these changes, model contingency plans and options, and quickly adapt their supply chain strategy to meet new demand and avoid excess supply will win. Those that cannot, risk being left behind with below-target sales figures and losses incurred from waste.

“Retailers and other businesses across the world should now embrace that we are in a ‘never normal’ world. Being prepared for uncertainty, such as continued disruptions from COVID-19, Brexit, trade wars, new market entrants or changing customer preferences must be part of company core competencies,” said Sandra Moran, Chief Marketing Officer of LLamasoft. “However, accepting this is not enough: retailers must act to prepare for the unprecedented. This research demonstrates there are clear performance variations between retail winners who have leveraged predictive technologies and enterprise decision platforms to deliver faster and smarter responses to disruptions and new opportunities, and those that have not.”

Survey methodology
For this research, conducted online by Retail Systems Research (‘RSR’) between February 2020 and March 2020, senior figures within the retail industry were targeted, with answers coming from 82 retail executives. Download and read the full report with RSR’s recommendations: [url=https://llamasoft.com/retail-benchmark-report/]https://llamasoft.com/retail-benchmark-report/[/url]

*In RSR benchmark reports, RSR frequently cites the differences between over-performers in year over-year comparable sales and their competitors. RSR finds that consistent sales performance is an outcome of a differentiating set of thought processes, strategies and tactics. They call comparable sales over-performers “Retail Winners.” RSR’s definition of these Winners is, assuming industry average comparable store/channel sales growth of 4.5 percent, they define those with sales above this hurdle as “Winners,” those at this sales growth rate as “average,” and those below this sales growth rate as “laggards,” “also-rans,” or “all others.”