How can analytics be used to optimize your retail supply chain to peak efficiency?
Beneath the surface
Retail is a lot like a swan or an iceberg: what we can see on the surface is just a fraction of the amount that’s going on out of sight. You might have the best in-store experience in the world, one that customers travel from all over the world to visit. You could have queues out the door of customer waiting to purchase your product. But if you don’t have a well-run supply chain, it can all be for nothing. All those people queuing up to buy your product will be spending their time queuing, not buying your products. With a well-oiled supply chain operation, you could be developing a way to reduce queues and customer wait times.
Analytics provides a means to not only keep your supply chain running, but to also provide predictions and projections that can allow you to tackle problems pre-emptively and run your operations at peak efficiency.
Analytics is a fantastic way to ensure that you are getting the right amount of stock in rotation through the supply chain, to help the retailer make sure they are meeting demand, and are not wasting resources on excess stock. Food retailer EAT partnered with cloud-based analytics provider, Blue Yonder to reduce food waste by 14% (ComputerWeekly). They did this by analysing customer demand compared to external variables such as the weather, or local events for each store.
A similar strategy was implemented by the American department store chain, Stage, who utilized analytics of customer purchases to develop stock projections for individual stores based on the most popular sizes and styles of clothing (Forbes). Stage made sure that the shelf space was occupied as much as possible by clothing that customers would actually buy.
These optimizations don’t just mean that EAT are spending less money on wasted food, or that Stage are using their shelf space more efficiently. They are saving money on indirect costs, such as production, transportation, and storage of goods. If a retailer is only ordering the correct amount of stock to meet demand, then that means there is less excess being produced, which means that less transportation and warehouse space is required for both the raw materials and produce.
Once you’ve refined your supply and stock requisitions, you can start optimizing the individual components of the supply chain. At every step along the supply chain there are places where inefficiencies can occur. Analytics can not only be used to identify any steps where movement through the chain is slowing, but can even make suggestions on how to optimize the process. For example, data insights could suggest quicker routes and schedules for shipping, or could be used to optimize the flow of manufacturing processes.
But it doesn’t have to stop at optimizing the flow through the supply chain, data analytics can help to find potential solutions if there is a problem with the supply chain. Analytics can identify any potential external shocks to a supply chain, and then provide ideas about how suggested work-arounds may be implemented based on previous trends and data points.
Do you know where your stock is?
Data analytics enables companies to create real-time visualizations of their supply chains – letting them see the big picture of their data – through word clouds or dynamic graphs and charts. In order to develop these real time data pictures, trackers can be used all the way along the supply chain, which can provide up to date progress reports of goods on their journeys.
As well as keeping track of your supply chain efficiency, these trackers can also be used to aid with quality control, allowing you to cut losses on spoiled or damaged goods. This can be especially beneficial for perishable goods, as their quality can be tracked in real time. With these tools, you can forecast shelf life in a much more efficient and accurate manner, and even predict when and where you could need a resupply.
Once this system is running at an optimal level, it could be completely automated, as the trackers send out reorders for goods as soon as they’re required. Rather than wasting time waiting for the low or spoiled stock to be noticed and the reorder sent out and processed, the sensors can detect when the shelves are getting empty, or when perishable goods are nearing expiration, and send out orders straight away.
In the past, calculating a single day’s costs for an entire supply chain could take over a week. Often, this is far too slow for companies to take effective action in responding to any raised issues or making quick changes that could save tangible cash. Thankfully, analytics can provide a solution. Intelligence engines can provide a calculation of a day’s costs to a degree of 99% accuracy, within a single day (Logistics Viewpoints). Along with real time visualisations, companies now have the resources available to react almost instantaneously to any issues. Problems can be tackled as soon as they appear, or even, in the best case scenario, before they even occur at all.
With these tools in place a retail supply chain can become a well-oiled machine, as goods glide all the way along from manufacturer, right through the supply chain and into the customer’s hands.
We’ve just published a whitepaper on how Predictive Analytics is changing the retail experience, download it here: http://www.c24.co.uk/wp-content/uploads/2016/08/C24-Predictive-Analytics-in-Retail-Whitepaper.pdf
C24 is pleased to announce their latest whitepaper on Predictive Analytics in Retail.
What’s in the whitepaper?
We look at how analytics is changing the traditional shopping experience – and how in-store operations are being integrated with online e-commerce practices.
Why should I read it?
If you want to stay up to date with how analytics, and more specifically predictive analytics is influencing the retail experience, then download the whitepaper today to find out more.
Why has C24 written this whitepaper?
C24 is heavily focussed on business analytics – we have a product called Bi24 which we deliver to businesses across the country, especially to the legal sector who use the analytics tool to better manage their operations. We also work heavily in the hospitality and retail sector, and see some of the technology coming down the line in the retail sector as a big opportunity for retailers looking to capitalise on big data within their organisations.