Discretionary spending, a crucial component of consumer behavior, continues to mount increasing pressures on supply chains. Staples like bread, dairy products and eggs have seen price increases of 20% to 40% in the U.S. in the last three years, leading to consumers becoming increasingly cautious about their purchases. The perfect storm of rising costs, stagnant incomes, and declining demand for non-essential items is taking its toll on businesses.
The recent example of Starbucks is telling. The coffee company reported weaker-than-expected quarterly earnings and revenue this year, fueled by a surprise decline in same-store sales attributed to – among other factors – cautious consumers. Starbucks, known for its robust customer loyalty and consistent demand, has felt the brunt of shifting consumer priorities. This underscores a broader challenge for organizations, where even well-established brands are not immune to the pressures of changing consumer spending habits.
Consumer packaged goods (CPG) companies are also feeling the pinch. In an effort to stimulate sales, retailers have recently announced price cuts on discretionary products such as new clothes, decorative items for the home, and arts and crafts or hobby kits. For instance, Ikea has slashed prices on hundreds of products.
Despite these price cuts, shoppers have continued to pull back on their spending over the past year. This trend is indicative of deeper economic anxieties and the need for financial prudence among consumers. With the focus shifting towards essential goods, non-essential items seemingly remain on the shelves.
What actions can companies take to tackle these challenges? As consumers tighten their purse strings, it is more crucial than ever to develop agile and responsive supply chain planning strategies to quickly adapt to changing consumer behaviors and weather the economic headwinds.
The ability to pivot and respond to market demands is no longer a competitive advantage but a necessity for survival and sustained success.
Here are some key strategies to consider:
Beyond Traditional Demand Planning and Sensing
To mitigate the challenges posed by fluctuating market conditions, companies are increasingly turning to new ways to leverage artificial intelligence (AI) and machine learning to generate feasible plans that align with their business goals. These approaches go beyond using traditional historical data and market trends to bring together multiple internal and external data sources. With powerful insights into consumer behaviors and preferences, organizations can effectively anticipate shifts in demand patterns and adjust production plans.
Advanced supply chain planning software, for example, enables real-time demand sensing by integrating external sources, enhancing responsiveness to market dynamics. Continuously monitoring demand signals is crucial. For instance, if a consumer sensitivity to price increases is detected, supply chain professionals can recalibrate production plans and inventory levels to align with revised demand forecasts or looking for additional cost efficiencies to help offset increasing costs in other areas of the supply chain.
Embrace Uncertainty
An end-to-end probabilistic planning approach is increasingly vital to help companies effectively manage variability, uncertainty, and supply chain disruptions.
Unlike traditional deterministic models, which rely on fixed forecasts and one-number plans, probabilistic models incorporate a range of potential outcomes based on various key indicators, including economic factors.
The probabilistic approach enables supply chain teams to analyze various economic factors, such as inflation rates, consumer confidence, and credit availability, allowing them to run multiple scenarios and make better data-driven decisions with confidence. For example, if banks cut interest rates, it could signal a potential increase in consumer spending power, boosting discretionary purchases. Conversely, if rates remain high, discretionary spending is likely to stay subdued. By integrating these indicators into the planning processes, companies can better anticipate market shifts and adjust their strategies, forging more flexible and resilient supply chains.
Probabilistic planning is a proactive approach that enables businesses to develop policies to respond quickly to market changes, maintaining supply chain efficiency and meeting consumer demands. For instance, a consumer goods manufacturer facing declining sales in non-essential goods category might use probabilistic planning to forecast the impact of a marketing campaign or a targeted discount strategy. By running these scenarios, the CPG manufacturer can make informed decisions that optimize inventory levels, reduce waste, and improve customer satisfaction.
The Path Forward in Your Supply Chain Planning
As discretionary spending continues to exert pressure on supply chains, companies must be willing to pivot and innovate to stay competitive. The path forward is clear: you must embrace advanced supply chain planning approaches and technology to quickly adapt to changing consumer behaviors and successfully navigate economic uncertainty. These tools equip organizations with powerful capabilities to enhance decision-making, giving companies the edge to respond rapidly in an increasingly complex marketplace.
Let us show you how the Atlas Planning Platform from John Galt Solutions serves as a single platform to orchestrate your end-to-end supply chain processes. With an innovative end-to-end AI-powered probabilistic planning approach and advanced features for inventory optimization, collaboration, scenario planning, and more, supply chain teams have everything they need to unlock new levels of agility and efficiency, to drive long-term success. Take the next step here.