Report

The Business Resiliency Playbook

Decoding the signals and shocks that shape consumer behavior

Report
The Business Resiliency Playbook

Decoding the signals and shocks that shape consumer behavior





Where is the economy heading?

And how will consumers respond?  

These questions are undoubtedly top of mind for manufacturers and retailers as they face a global economic landscape marked by an extraordinary degree of uncertainty. But in our quest to forecast what’s coming, are we overcomplicating what really matters for building business resilience?  

From shifting trade policies and geopolitical tensions to volatile financial markets and evolving consumer behaviors, today’s environment is more unpredictable now than at any point since the pandemic five years ago. This uncertainty is not an abstraction—it’s a daily reality, shaping the decisions of businesses, policymakers, and consumers alike.  

For business leaders, this unpredictability presents a challenge: Decisions about pricing, hiring, supply chain investments, brand positioning, and innovation pipelines must be made in the face of incomplete information and rapidly changing conditions. Traditional models and former precedents may no longer provide reliable guidance, making it difficult to chart a clear path forward. Yet, choosing not to act—delaying key decisions or defaulting to the status quo—is also itself a decision, one that can leave organizations exposed to risks and missed opportunities.  

In a 2022 report, McKinsey found that the actions a company takes before any sort of economic shock—for example, what it does to prepare or where it invests—could account for as much as half of the gap in shareholder returns between leaders and those who lag behind. 

In this context, business resiliency planning isn’t just advisable—it’s essential. The manufacturers and retailers best positioned to navigate uncertainty are those that have proactively developed strategies to withstand shocks and adapt to new realities. But before crafting a resilient plan, it’s crucial to first understand the potential scenarios that could unfold over the next couple years. This requires a rigorous assessment of both the risks of the current environment and a thoughtful exploration of how similar risks played out in the past. 

For this report, we’ve designed an analysis to give business leaders the insights they need to anticipate and prepare for a range of possible futures. By mapping out distinct scenarios for consumer spending, we aim to provide a framework that enables agile decision-making and strategic foresight. Our goal isn’t to predict the future, but to help organizations develop robust plans that can adapt as conditions evolve.  

To do this, we draw on experiences of the past to help calibrate what the next couple years might hold. Historical episodes—the stagflation of the 1970s, the significant recession of the early 1980s, the mild recession of 1990, the soft landing of the mid-1990s, and the oil/geopolitical shock of 2022—offer invaluable lessons in how consumers respond to economic disruptions and uncertainty. During such periods, consumer priorities often shift rapidly, with spending on essentials taking precedence over discretionary purchases, and brand loyalty being redefined by perceived value and trust

Importantly, our analysis suggests three key findings:  

“Our goal isn’t to predict the future, but to help organizations develop robust plans that can adapt as conditions evolve.” 

The outlook for the US economy over the next two to three years is unusually uncertain, with several plausible scenarios—each carrying different implications for growth, inflation, and consumer spending.  

Despite volatility month to month, real consumer spending is still up nearly 1% since last October, and real durable goods spending is up nearly 2%. A largely stable labor market has been supporting the consumer (although recent data suggests signs of weakening), while wages and income growth have grown faster than inflation, providing some support to consumer purchasing power despite persistent price pressures. Inflation is still slightly elevated but has come down from the unusually high levels (e.g., 7–9%) of 2022.  

Consumer sentiment and broader economic indicators are mixed, however. The Consumer Confidence Index and University of Michigan’s Survey of Consumers have both shown a rebound since their lows earlier this year; however, consumer attitudes are still down from late 2024. Meanwhile, preliminary results from NIQ’s annual Consumer Outlook survey indicate overall increased levels of optimism since a year ago; however, concerns about the potential for rising food prices, economic downturn, and geopolitical conflict remain top of mind for most—illustrating just how challenging it is to keep up with consumer mindsets during this time.  

Economic growth has also been mixed: Real GDP growth was negative in Q1 2025 but beat expectations, at 3%, in Q2. Even with this bounce back, average growth over these first two quarters was still only 1.2%, down from 2.5% in 2024. There also could be upward inflation pressure and labor supply contraction over the next year, depending on evolving US policies (e.g., trade, immigration, Federal Reserve prime rate, reconciliation tax package).    

Drawing on both current data and historical parallels, we can outline five principal scenarios that could impact the US economy and challenge business resilience over the next few years:

  1. Stagflation
  2. Mild recession
  3. Deep recession
  4. Soft landing
  5. Geopolitical shock

Note that these are not intended to cover all possibilities, nor are they mutually exclusive. A recession may be “stagflationary,” for example, while geopolitical shocks may underpin all of them. The direction the economy ultimately takes will depend on the interplay of monetary and fiscal policy, the trajectory of inflation, the evolution of global trade and geopolitical risks, and the resilience of consumer demand. 

In a soft landing, we would expect current consumer trends to continue and not see a huge break from present-day behaviors. But how does consumer spending for different goods respond under the other macroeconomic scenarios? 

To assess this question, we share two layers of analysis:  

  • The first looks back historically at periods that align with the macroeconomic scenarios laid out above and calculates how real consumer spending (inflation-adjusted Personal Consumption Expenditures—or PCE—from the US Bureau of Economic Analysis) changed over the subsequent two years.1 We show the results for four of these periods relative to the soft-landing period that began in January. PCE categories cover all monthly consumer spending, including services, but lack the detail to answer important questions—for example, the ability to distinguish within categories among different brands.  
  • In the second analysis, we use NIQ data to dig more deeply into some of the most historically sensitive product categories, which allows for more differentiation between products and high-frequency detail. 

1 Full results of the analysis are in the chart labeled “Full historical real PCE consumer goods analysis.” In summary, the analysis calculates the percent “gap” of monthly real consumer spending per capita for each of nearly 200 PCE categories against trend. “Trend” here is calculated as the Hodrick–Prescott (HP)–filtered trend of log real spending per capita for each category with a band-pass window of 20 years (equivalent to an HP smoothing parameter of roughly two million). The calculation of trend allows the analysis to account for long-run consumer preference changes. The change in the gap shown in the chart for each historical period is the average percentage point gap over the second year out (13–24 months from the beginning of each period) minus the average gap over the 12 months ending with the period start (the month of the period start itself plus the 11 preceding months). 


The outcome of our first analysis suggests a perhaps surprising result: To prep for consumer behavior under one outcome is to be well-prepared for the other outcomes as well. In general, across all economic shocks we evaluated, consumer behavior followed similar patterns. 

During times of economic stress—regardless of its classification or cause—consumers tend to pull back on bicycles, cars, sugar and sweets, and photographic equipment, among other goods. Few goods are left unaffected—although some are affected less (e.g., tobacco). Unsurprisingly, “nice-to-haves” are more affected than “need-to-haves” when consumers have to pull back—the exception being a small treat or affordable luxury that can substitute for bigger savings (e.g., an increase in spending on meat in the face of a recession likely reflects that consumers are no longer going to restaurants and are instead buying more to cook at home). 

Interestingly, as the continuation of our chart below shows, some categories actually saw increases in spending—including watches and “pleasure aircraft.” This may suggest that luxury spending can hold up relatively well during times of change, as more well-off consumers remain insulated from economic swings.   

Although the stress response across scenarios is similar, the scale and speed of that response is likely proportional to the magnitude of the shock. In other words: The more severe the disruption, the faster and more pronounced the behavioral shifts will likely be. A major recession may trigger swift and widespread pullbacks, whereas a mild downturn or stagflation might result in more gradual or limited adjustments. Similarly, some geopolitical shocks could rival the economic impact of traditional recessions, depending on their scope and consumer visibility. Understanding this scaling effect is critical for anticipating the depth and duration of demand shifts across categories. 

Especially in periods of change, building business resiliency means being prepared and staying attuned to the data to see trends as they emerge. Unfortunately, this can pose a challenge for several reasons: 

Regardless of category, fast-moving consumer goods (FMCG) data makes an ideal use case for pulse checking the state of the consumer. Given its high turnover rate, variety of purchasing channels, and opportunities to trade up or down, we can see even slight behavioral shifts that, in combination with our historical analysis and consumer sentiment data, might signal larger emerging trends. By regularly monitoring overall market and category data—especially those that are historically sensitive during economic shocks—businesses can anticipate needed price adjustments and promotions, right-size their product portfolios, and adjust marketing strategies and budgets. 

“Our goal isn’t to predict the future, but to help organizations develop robust plans that can adapt as conditions evolve.” 

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