In late March, we published a number of articles that focused on the use of data and technology in the retail operations and logistics space.
There was a guest-authored piece from Mikko Kärkkäinen, group CEO of Relex, which argued that making the right IT investment decisions now has to become a priority. In addition, Matt Hopkins, retail director at Blue Yonder, spoke to eDelivery editor Sean Fleming about the use of machine learning algorithms to cope with the increasing volume and complexity of data.
At the time, several eDelivery readers contacted us to share their views, especially when we invited opinions on the role of tech and data. We also asked people to tell us what that oft-used phrase big data means to them.
Stuart Simms is CEO of Fits.Me which provides retailers with tools that allow customers to quickly browse through clothes that are the right fit for them; according to one of its customers, the shirt maker Pink, conversion rates are 21% better when shoppers are able to check fit details.
“Big data (or the ‘right’ data as we refer to it) provides unique customer and behavioural insight which, on top of allowing for a more personalised experience for shoppers, enables retailers to amend supply chains and manufacturing outputs to that of their consumers which is important for making savings on stock and reduces the amount of wasted products,” he says.
“In apparel retail, fit preferences are highly personal data which, when combined with other data assets, provide a rich and insightful picture way beyond the near-meaningless ‘size’. The concept of fit preferences encapsulate the truism that two otherwise identical people will, more likely than not and for reasons only they know, prefer to wear different size garments. Such preferences change according to the type of garments being considered, and the context in which the shopper expects to wear them.
“For the apparel retailer this data is gold and relatively easily obtained (with full customer participation and permission), well understood, and straightforward to repurpose for beneficial purposes.
“In fact, in conjunction with shopper and garment measurements, and other data such as purchase history and location, fit data creates an opportunity for retailers not only to curate each and every customer experience at each and every touchpoint, but to fundamentally change the way shoppers search for, discover and buy clothes.
“This can then all be fed back to the very start of the process to ensure only clothes that will be sold are provided – ending the dreaded ‘end of season’ sale where all unwanted sizes are left.”
Tom Jeffrey, head of ecommerce and development at fashion retailer Jules B, says big data is part of the company’s purchase processes.
“Jules B use the big data philosophy over a variety of different data sets. This enables us to purchase more effectively, predict product and brand opportunities and ensure our stock quantities are reflective of the potential demand. It also enables us to engage with our consumer more effectively, thus ensuring we don’t run out of stock, anticipate demand, ensure stock comes in and offers are rolled out at the correct times.
“We believe the term means utilising and consolidating a variety of different data sources (sales, online demand, marketing cost, bottom line contribution value) to actively forecast future demand and capitalise and pre-order stock in advance whilst ensuring that we are constantly monitoring trends and consumer’s reactions to existing stock ensuring were achieve the expected sell-throughs.”
Jason Tavaria, head of direct at fast delivery experts Shutl, issues a reminder that technology is a tool, not an end goal in itself.
“Big data is a buzz word and like most buzz words is over used and misquoted. The truth, in my opinion, is that it is more important to start with business value and use technology to help, then to start with technology and then look for business value.
“Companies can use their own data to profile customers in ways often only available to large media firms or governments. More organisations have opened their data to enable companies to leverage this against their own data and provide real time insight never before achieved.
“These limitless opportunities need to be considered carefully so the right priority is placed toward the most effective use of big data and that drives the greatest business value. All too often firms get stuck into the how and don’t focus enough on the why and what.
“There are smarter ways the logistics industry can utilise assets. This might be a single carrier fleet or possibly the industry itself. Sharing delivery address data might help reduce re-deliveries of ecommerce orders. Sharing potential / fraudulent customer data might help reduce claim costs. Using GPS and ecommerce platforms can deliver real time delivery updates to customers and more advance in-flight changes.”
Patrick Gallagher, CEO at On the dot says whether or not you are working with big data, you can only hope to offer services customers want if you understand customers’ needs and expectations.
“Using customer data – big and small – to understand purchase context is vital for getting convenient delivery right. In 2016, On the dot research found that 10am and 6pm are the most popular times in the UK for specified hour delivery. But these times become less important for items that customers need more urgently or for a specific purpose. This is when delivery at any time, as long as it is speedy, is most convenient.
“With purchase context playing such an important role in what convenience means for today’s consumer, retailers cannot afford to second guess customer needs. Instead, they should leverage all data from customer journeys to understand why and when customers require convenient delivery and make predictions for future purchases.
“Big data in particular can help retailers track trends that apply to their entire customer base; but even simple cues, such as ticking the gift wrapping option, can tell retailers a lot about a purchase and the most suitable delivery options to offer.”
Southard Jones is VP of product strategy at business intelligence consultancy Birst. He sees two potential obstacles where the smarter use of data in retail operations and logistics is concerned.
“The first challenge is how to bring data from across the supply chain so that it can be used for managing operations more efficiently. This is difficult because it relies on pulling together information from multiple sources and systems, and then making it usable across procurement, logistics and operations.
“A good example would be looking at how spending is managed. For the supply chain team, monitoring that budget is spent with approved suppliers and terms are being met will be critical areas to track.
“But on the logistics side, order management and SLA tracking will be more important. Looking at these areas together, it’s possible to significantly reduce costs and improve service.
“The second challenge is how logistics and supply chain operations link into the wider business picture. Too many times, decisions made elsewhere within the business can lead to unexpected and higher costs around supply chain management. Areas such as marketing rarely share data with the supply chain team, yet a successful campaign can lead to more goods being shipped or products ordered. If supply chain and procurement teams are involved from the start, they can supply data that can make marketing even more effective.”
This is a topic we will continue to return to here on eDelivery, so if you have an opinion you’d like to share please join in the conversation. You can leave a comment under this story, you could send us a tweet, or email us direct.
- By DARPA (Defense Advanced Research Projects Agency), Public domain, via Wikimedia Commons, link