Getting Smarter About Seasonal Demand: The Holiday Shopping Season Shouldn’t Start in Summer
The kids are back in school. Time to roll out the holiday decorations.
The break between summer and winter holidays feels shorter each year. However, with the start of this school year — paired with Halloween, Thanksgiving, Black Friday, Cyber Monday, Christmas, and New Year’s — the second half of the year is peak season for retailers. There's a lot at stake. The National Retail Federation (NRF) expects back-to-school and back-to-college spending to reach $83.6 billion this year, a 10 percent increase over 2016. And with consumer confidence slowly growing, retailers hope to improve upon last year’s holiday sales of $655.8 billion.
While the raw sales projections might sound promising, they don't tell the whole story behind what's happening during the major shopping seasons. Large retailers continue to face headwinds in an industry that's undergoing a very difficult transformation. Consumers might be spending more money than in years past, but they also have more places and methods to spend it — not to mention a wealth of information about products and stores sitting in the palms of their hands.
Traditionally, the solution has been to stay ahead by throwing more seasonal inventory at consumers earlier and earlier in the year. This creep took holiday shopping from a November and December event all the way back to mid-September, according to Nielsen Sample Store Auditing data. Any earlier and the winter holiday shopping season would overlap with back-to-school.
Part of the reason for throwing more seasonal inventory at consumers earlier and earlier is simply the cost of doing business. It's not practical to build distribution centers specifically to hold holiday inventory. And with heavy promotions centered around Black Friday, Cyber Monday and the general holiday rush, retailers often plan the season’s assortment a year or more in advance. Longer lead times help secure better prices, and align suppliers, factories and logistics providers in a way that helps ensure products arrive on time. Getting ahead of the holiday game also helps offset the unexpected (but not uncommon) disruptions that happen across the un-networked supply chain. The last thing a retailer wants to hear is that a port strike, factory fire or inclement weather resulted in empty shelves and lost sales.
So, while a lot rides on back-to-school and the holiday season, there's also plenty of risk. And while you may never be able to stop the major shopping seasons from blending with one another, there are several ways retailers can take more control over the complex challenges these seasons bring. It starts with greater connectivity and visibility across the supply network, improved forecasting and automation through machine learning, and comprehensive analytics to find weak spots and new opportunities across the value chain.
Connectivity Leads to Visibility
We broadly acknowledge that 80 percent of the data relevant to a retailer’s supply chain exists outside the four walls of the enterprise. The biggest companies comprise dozens, if not hundreds, of different stakeholders, each with its own role in getting the right products to the right place at the right time. It's a complex and highly nuanced process. As a result, 75 percent of retailers rely on manual reports and phone calls to locate inventory across the supply chain. This process that can take three or more days to complete. Greater connectivity across the supply chain can help. By digitally connecting the supply chain network, retailers gain access to real-time information on product flows and the ability to locate goods anywhere in the world.
Continuous Improvement Through Machine Learning
The network effect breaks down silos and increases visibility across the supply chain. What's done with that information is typically where retailers struggle to find a business case. Supply chain visibility is good to have, but it's only the first step in building a responsive, adaptable supply chain. By combining end-to-end visibility with the power of machine learning, retailers dramatically increase responsiveness to any unforeseen challenges. Not only does AI help retailers make better, more profitable decisions right now, real machine learning that goes beyond time-series data or “pick best” techniques enables continuous improvement in forecasting over time.
Analytics Turn Insight Into Opportunity
Connectivity sets the stage for supply chain visibility and continuous improvement. The next step is to turn all that information into a competitive advantage. Implementing business intelligence capable of bringing all of that data into one platform is the key to improving omnichannel inventory placement and assortment decisions. Real machine learning can parse text to find new attributes and trends, execute A/B testing, and cross-apply learnings from one scenario into others with similar characteristics to improve omnichannel inventory placement and assortment decisions. Don't let imperfect data get in the way of progress. Take advantage of the insight it provides for your customers, your people, and the future of your business.
Matt Jones is senior director of retail strategy at Infor Retail, a cloud software provider for retailers.