The Commonsense Supply Chain: Looking at the Impact of Travel Data

On the weekend leading up to the Fourth of July, there were considerably fewer cars on the streets of my town, as well as shorter waits at local restaurants and empty checkout lines at the nearby supermarket. A lot of folks traveled over the holiday break, resulting in less congested commutes and shopping experiences for those of us who stayed in town.

The impact of this temporary – yet significant – population shift is large enough to be felt by businesses along both ends of the travel routes. While you expect that retailers and service providers in destination areas (such as the beach or mountains) to be prepared for an influx of visitors over the holiday break, how prepared were the businesses at the points of origin? My local supermarket, for example, appeared to be overstaffed compared to the lighter foot traffic of that weekend. When looking at the impact of travel data, it’s just as important for retailers at the points of origin to not overstaff or overstock perishables as it is for retailers in destination locations to ensure that they are staffed properly and don’t run out of perishables.

Although travel patterns are predictable to some degree, they can vary considerably in magnitude. That said, there are data algorithms that can capture travel plan specifics, providing a mine-able source of information that companies can leverage to be more prepared to serve their customers. For instance, I can tell that my personal travel itineraries are already being scanned and analyzed by data-mining algorithms by the creepily relevant web ads and recommendations that appear when I am on Twitter or Facebook. If this type of travel information was aggregated across a city (or even by zip code), scrubbed and then presented back to supply chain stakeholders, it would enable them to more properly plan their inventory investments and promotions. Even if the data only captured travel plans for a segment of customers, annual trends could provide companies with valuable information that would enhance their existing forecasts.

The migration from a digitally-enhanced supply chain to a truly digital supply chain is well underway. The JDA customers who are at the forefront of this digital supply chain journey continue to uncover insight-rich data sources that are forming additional inputs into JDA solutions and driving additional value.

Applications for big data are plenty, and JDA’s supply chain management tools remain the ideal medium to capture the impact of how a dynamic demand signal can influence your supply chain plan, allowing you to analyze multiple scenarios to determine available options and select the one that best meets your current objective. JDA’s Consulting Services professionals are trained and experienced in identifying complimentary data sources, as well as in recommending ideal methods for harnessing data into actionable insights. For a backgrounder on the power of the digital supply chain, check out this playbook for digital supply chain success or contact JDA Consulting Services to learn how we can advance your company’s digital supply chain efforts.

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