How Accelerated Analytics Can Improve Restocking and Consumer Experience
Accelerated analytics can be used to process data to stay up to speed with supply and demand.
Today, retailers can’t afford to overlook the power of real-time data. With ongoing turbulence in the global supply chain, the unpredictability of the world economy and the evolving demands of consumers, it’s challenging for retailers to succeed today without adopting a data-driven business approach. Todd Mostak, CTO and co-founder of HEAVY.AI, shares how accelerated analytics can help companies gain an advantage.
Before the pandemic, most retailers were operating on a low-inventory, lean manufacturing model, which allowed them to stay nimble while minimizing costs. For decades, U.S. companies have been reducing inventories to increase growth in their return on assets. According to a recent study conducted between 1981 and 2000, companies have cut inventory by an average of 2% per year. However, the Just-in-Time (JIT) model for inventory management can be risky, especially when there’s a global supply shortage or other major disruption, such as a pandemic or geopolitical conflict. Due to these massive global disruptions, the JIT approach to manufacturing, shipping and restocking shelves is proving to be an unsustainable path forward for many businesses.
To stay competitive in today’s market, retailers must tap into the data they have available throughout their supply chain from internet-of-things (IoT) sensors on trucks or ships, customer behavior and weather patterns. With this data collected, companies can utilize accelerated analytics to process and visualize large amounts of data in seconds rather than weeks to stay up to speed with supply and demand.
See More: Three Ways Tech Can Make Supply Chain Solutions More Agile
What is Accelerated Analytics?
Accelerated analytics includes interactive visual analytics and data science frameworks that enable companies to uncover opportunities and risks hidden within their data. This real-time application of big data presents a high-level visual interface to retailers. It allows them to anticipate restocking delays and quickly adjust inventory management and manufacturing schedules to meet evolving consumer shopping habits and market disruptions.
Even for someone who doesn’t consider themselves a “data nerd,” the types of decision-quality data being collected and displayed visually are nothing short of remarkable. These insights are make-or-break for companies today amid supply chain shortages and rising global competition.
Opening the Door for Insights Previously Unattainable
Pioneering artificial intelligence (AI) technology and advanced processing techniques make sense of billions of data points from multiple sources to provide supply chain professionals with the information they need to accelerate planning and forecasting. Detailed location, point-of-interest and human movement data are enabling retailers to make more informed site selection, trade area analysis, competitive intelligence, consumer behavior analysis and more to enhance the longevity of their business.
The metrics from the digital world are now being used in the physical store settings with impressive precision, including point of origin, navigation routes and dwell time.
For example, foot traffic data over time can help decision-makers understand changes in consumer shopping habits, while anonymized time and distance data exposes details about how frequently consumers visit the store, total time spent, distance traveled and more. By layering this data with other details, like franchise locations, retailers can see a comprehensive view of how consumers in the surrounding communities interact with their stores.
Big Data, Big Impact
Every point of the supply chain benefits from high-quality consumer data analytics, both getting the merchandise to the store and the staffing needs to unload it or assist consumers. Even before consumers get to the store, analytics enable retailers to target the perfect buyer at the perfect time with advertising that directly impacts buying behavior – leading to a richer shopping experience throughout the entire buying lifecycle.
The changes in consumer online and in-store shopping decisions are so complex that retailers must be able to leverage real-time, accelerated analytics to guide omnichannel strategies and stay competitive. Visualizing the data can help predict potential cross-selling opportunities or elevate trends in curbside orders that help retailers better understand the real-time connection between online and in-store behavior. Once domain experts can interactively explore their data to get a sense of interesting anomalies and correlations, they can then do deeper discovery using native SQL and data science pipelines.
See More: Blockchain: The Way Out Into Supply Chain Integrity
Getting Started with Accelerated Analytics
It’s wise for companies to begin applying modern analytics to their current business model if they want to remain competitive in this dynamic environment. A good first step is to take inventory of the information currently available to them—either proprietary or through third-party or public data. Once that is determined, retailers should look for an analytics solution that not only provides real-time interaction and data visualization capabilities and data visualization of large-scale and high-volume joined datasets from these different sources but also allows deeper analysis via a familiar API like SQL and strong connectivity with other analytics and data science platforms.
Modern analytics solutions offer high-level visual dashboards that lay out all these data points in one place. For example, dashboards allow users to zoom into streets or buildings in the U.S. to analyze foot traffic and other points of interest. This enables brands to test out different scenarios and come to a strategic, data-based decision for their unique business objective.
Today, retailers must be smarter and more strategic about buying and timing deliveries to avoid ending up with an extreme surplus or empty shelves and frustrated customers. Accelerated analytics can provide some clarity here with detailed location data, trade area analysis, competitive intelligence and consumer behavior analysis. Retailers can finally harness the big data available today to gain visibility into supply chain trends and consumer shopping patterns to better navigate these challenges and make data-informed decisions.
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