In our continuing series on Symphony RetailAI, I wanted to talk about an area in which we have the longest history of helping FMCG retailers address difficult issues – the retail supply chain.
With so much attention being given to the customer experience, in-store and online, over the past few years, supply chain has taken a bit of a back seat. But once again, it is rightly back in focus, very much front and center, you could even call it “the new black.”
Of course, I work in the retail technology industry, but I’m like any one of you reading this blog. We are all shoppers living in a “I want it now, and I can get in now” environment. When I go to a store (or order online) and they don’t have what I want in stock, I’m more than a bit disappointed. I don’t think or care what the issue may be for the retailer to be out of stock, I’m disappointed and I may immediately contemplate which other retailers may have what I need. A retailer can do everything else right – have the right mix of products, be price competitive, personalize their offers to loyal customers, and much more, but if the product isn’t available when the customer wants it, everything else good can very quickly be forgotten. Customer loyalty starts to erode.
The supply chain is still the lifeblood of retail.
Maintaining a resilient supply chain is crucial to keeping organizational costs down and operating efficiently, all while satisfying the end customer. But the increasing complexity of getting goods to customers in an omni-channel retail environmental has forced the supply chain to continually evolve. And this is where artificial intelligence and machine learning has started to come to the fore.
Half of retail supply chain leaders are embracing AI
We recently commissioned a survey of supply chain leaders at 50 North American retailers, with the majority of respondents from large or mid-size grocery organizations. We announced those findings last month in our “Strengthening the Retail Supply Chain” survey, which shed light on the inability of current technologies to support the supply chain as business grows. Here are some highlights:
- Disparate demand replenishment systems are a significant burden to efficiency. Thirty-six percent of survey respondents indicated that they have separate demand planning, replenishment, allocation and order management systems.
- Retailers struggle to produce accurate, timely demand forecasts, and many third-party systems are outdated and incapable of understanding complex consumer behavior patterns. As a result, 34% of retail supply chain leaders say one of their top supply chain challenges is lack of forecast accuracy.
- Respondents said AI’s greatest potential to improve supply chain management relates to quality and speed of planning insights. One in three professionals surveyed claim to have incorporated AI capabilities into their supply chain management processes, and one in four is working toward that goal.
We’re taking on forecasting accuracy and grocery-specific strategies
Demand forecasting is central to retail success, so getting it as close to actual as possible is key. But it seems like the sheer amount of data required to produce accurate forecasts can feel more like a hindrance than a benefit, unless you have the right tools in place. There’s a reason why 50% of executives are looking to AI – continual data cleansing and machine learning are most helpful in understanding sales patterns and anomalies in the supply chain.
That’s why we launched SR Demand ForecastingAI at our Xcelerate Retail Forum in October, a solution that incorporates AI and machine learning to help retailers significantly improve forecasting accuracy. We also know that many of today’s systems lack the grocery-specific logic required to handle fresh and ultra-fresh categories – so we built the Demand ForecastingAI solution with this in mind. The retail industry is evolving at pace and there is an increased focus on fresh and prepared meals – shoppers have less time, crave convenience, and don’t often plan dinner in advance. In the US, 50% of people say they don’t know what they plan to have for dinner one hour before they expect to eat. So, it’s key that retailers can now better forecast demand for fresh and ultra-fresh grocery items alongside other categories, improving service levels while simultaneously reducing food waste (and cost).
Prior to an early implementation of SR Demand ForecastingAI, one leading grocer had a 20% error rate in its current demand forecast – the solution was able to cut this down to just over 5%!
Keeping momentum in the supply chain conversation
We have a rich legacy of supply chain experience that goes back over 30 years to when we were first known as Aldata and then Symphony GOLD. Over this time, we have worked with hundreds of retailers across the globe helping them manage, optimize and improve their supply chains. In February, our own Patrick Buellet, chief strategy officer, was selected as a “Practitioner Pro to Know” by Supply & Demand Chan Executive. Then this summer, Symphony RetailAI was named to Supply & Demand Chain Executive’s SDCE 100.
Artificial intelligence is poised to improve efficiency across the supply chain, and the key to AI’s power is data. We know that through data, machine learning and AI, retailers can be enabled to make better supply chain decisions.