Adapt or die, they say. Keeping up with rapidly changing industry trends is the name of the game in most industries, but it’s particularly challenging in the retail realm.
Consumer preferences change seemingly overnight, buying behaviors become more unpredictable, and new products flood the market making it difficult for manufacturers to figure out what products and how much of them to make. To keep pace, supply chain partners — retailers, vendors, and manufacturers — have individually begun fully embracing the Big Data movement in hopes of gaining a competitive advantage.
But like many things data-related, silos always seem to diminish the value of that information and retailers are quickly realizing that keeping insights confidential and not enriching or cross-referencing the findings with data from other supply chain partners limits the usefulness of those insights.
Instead, forward-thinking retailers are eagerly seeking new ways to share data and knowledge to gain a 360-view of the entire supply chain that drives more sales, minimizes time-on-shelf, and protects against out-of-stock or excessively overstocking.
Why many retailers don’t share their data.
Despite the obvious advantages to sharing POS data, challenges remain. It’s easy for retailers to guard their findings out of a desire to keep the competition in the dark. But hiding that information can come at the expense of their sales partners.
For example, retailers have an intimate understanding of the products they sell and what flies off their shelves, versus the ones that languish for weeks or months. Similarly, suppliers may have knowledge of stock levels not reflected in the information accessible to retailers, creating an information gap that could inhibit both partners’ success.
Of course, there are a number of reasons beyond sheer unwillingness that retailers don’t share their information.
- Most retailers lack the appropriate technology to centrally store and easily distribute data. Many still rely on manual tools such as Excel spreadsheets, PDF reports, and flat files that take an eternity to update, standardize, and share.
- Retailers don’t have the right analytics capabilities to identify the connection between customer demographics and transactional data. Manually creating analytics models is beyond most retailers’ core competencies and limited resources. Reporting from third-party point solutions provide superficial metrics and no way to turn those metrics into action.
- Data sharing isn’t an enterprise-wide mentality. When sharing data with retail and supply partners does happen, it’s usually confined to an individual or a single department instead of a company-wide effort. Without a top-down mandate to share information, sharing data becomes an afterthought and produces a supply chain of siloed partners and isolated stores of information.
- Many retailers and suppliers want to monetize their data. The easiest way to stave off requests for sharing data is charge for it. Many companies believe that the effort, time, and resources that went into collecting the data makes it a valuable asset that should also produce revenue. But businesses — particularly supply chain partners — feel they already have high enough cost of doing business and aren’t willing to pay for information, despite its obvious value.
Solutions for easy data sharing.
Data sharing has been shown to play a central role in delivering an enhanced customer shopping experience. In fact, nearly 90% of companies listed the customer experience as their primary competitive differentiator in 2018, and other recent studies show that 9 in 10 retail leaders believe they can better use POS data.
In an interconnected world, retailers can’t afford to operate as in years past. Enabling access from web-connected devices to select parties in the supply chain is a foundational component of successful data sharing. Still, only 53% of field sales teams have access to POS data on their mobile devices, though 81% of brands surveyed said their teams would benefit from such insight.
To easily and reliably share rich data among supply chain partners, retailers need to implement software-driven workflows that aggregate data from across its operations into a central data warehouse. Not only does consolidating data sources streamline and simplify reporting, it also dramatically enhances it.
Combining POS data with other data streams such as time-on-shelf reports, inventory levels and projections, and sales projections creates more comprehensive and meaningful context to each partners’ performance. Once collected, the data needs to be analyzed at scale using artificial intelligence (AI) and machine learning models to slice and dice massive volumes of data quickly and enable partners to query data in any context for complete view of business operations.
4 big advantages of sharing POS data
Collecting, analyzing, and sharing data makes it easier for retail partners to share discoveries and projections about their business. Specifically, sharing POS data can help to:
- Improve inventory and merchandising strategies. Retailers can make data-driven decisions on purchases based on the projected demand, placing larger orders during peak sales periods to take advantage of bulk discounts while lowering quantities when sales are projected to slow down or decrease.
- Gain deeper insight into local and regional performance. If one store in a region is drastically underperforming, the supplier has the ability to identify an issue that may have gone unnoticed. And data compilation and analyzation bring greater accuracy when predicting seasonal trends.
- Increase sell-through. Using performance analytics removes the guessing game of shelf placement and helps retailers arrange products to maximize sales.
- Increase sales promotions effectiveness. Running a promotion without confirmation the distributor has sufficient product in stock is a retail disaster waiting to happen. But when data’s shared, retailers, distributors, and manufacturers benefit from perfect alignment, allowing for attractive and timely sales promotions.
Collaboration is the highway to success
When it comes to sharing data, retail supply chain partners have historically been reluctant to partake for a variety of reasons.
But many forward-thinking retailers are coming around, recognizing that brands adopting data sharing practices and pairing them with powerful AI and machine learning tools will enjoy increased efficiency and enhanced analysis, will gain deeper insights into the health of their businesses, and operationalize the intelligence they’ve gathered for stronger sales and healthier margins.
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