Mr. Douglas stood at the front of the boardroom, anxiously bracing for the barrage of challenging questions about why his marketing strategies failed. Only 18 months ago, he had entered this very room after being appointed as the highly touted new CMO, confident in his vision for growth.
Now, as he reflected on his journey, the once-promising growth prospects had not materialized. Douglas had done his due diligence, built a smart team, and overseen strong brand assets. He had paid close attention to executional details and trusted in data-driven analytics. He had done everything right, yet the plans had gone surprisingly wrong. Why? How? What had he misjudged?
As he finished his coffee, a line of serious faces filled the room. Douglas sensed that his replacement might soon be sitting in his seat, possibly doomed to suffer a similar fate.
The CMO in the story above is a semi-fictional character. In today’s challenging and ultra-competitive markets, many readers may empathize with the truth of Doug’s story. We are all Dougs, in a myriad of different strategy, marketing, and sales roles.
Let’s explore Doug’s journey in more depth. He was brought in to turn around a popular snacking brand that was facing slowing sales and market share erosion. He directed his team to undertake several major initiatives to revive growth. His leadership team showed high confidence in the new strategy, and strong organizational alignment and commitment to execution.
A year later, however, the brand’s trajectory proved anemic and market share had not grown meaningfully. Leadership demanded answers. Following all the shoulder shrugging, finger pointing, and arm-chair hypothesizing, a committee was commissioned to conduct a post-mortem exercise. Six weeks later, and contrary to the prevailing wisdom, it did not find any one catastrophic failure. The results revealed a more complex and nuanced answer. On the positive side, it found that Doug’s team followed many individual best practices and executed diligently. Despite these positive actions, however, other factors undermined their efforts, causing in-market sales to fall far short of their target.
Let’s review some examples to bring the situation to life.
Team members took many principled actions to rejuvenate the core brand. Through rigorous analysis, they measured brand performance, strengths, and gaps objectively. Investments in insights and analytics helped them understand consumer trends and market dynamics. The team strengthened brand positioning and messaging to double down on the brand's core equities – great taste and party fun. Close collaboration with key retail customers helped optimize their on-shelf presence. Moving from strategy to action, they translated opportunities into concrete executional roadmaps. Yet, the brand met with mixed success.
One critical decision mattered. The brand faced rising product, packaging, and operational costs, but high consumer price sensitivity and competitive dynamics cautioned against a price increase in an inflationary environment. Instead, team members proposed swapping out some ingredients to preserve margins. They made a calculated bet that core heavy consumers would not notice or care about the product changes and were not motivated by quality or health considerations that might have been affected.
The benefits and risks of changing ingredient quality were discussed in product development and marketing strategy forums. However, the issue was one of several dozen decisions occupying management attention. The responsibility was delegated to a smaller committee that lacked the knowledge to evaluate the risks well. Furthermore, the rationale for the decisions was not rigorously documented, leading Doug to miss asking critical questions. He ultimately approved the cost-cutting decision without sufficient scrutiny.
Despite positive changes in marketing and execution, enough taste-savvy consumers disliked the product changes, leading them to reduce consumption or switch brands. The brand lost penetration and market share.
The innovation team designed and launched a premium product to reach new users and occasions. They revamped product formulation, assortment, and packaging, and conducted agile testing before execution to refine product attributes, positioning, and messaging. They supported the positioning with incremental spending.
Despite these sound foundations, two incidents revealed problems—ultimately contributing to why the marketing strategy failed. First, a knowledgeable category manager was consulted about the innovation at an early stage before executional details were set. After she changed roles to a different team, she was no longer part of decision forums. She expressed surprise upon learning about plans to place the product in a different aisle, but her lack of authority relegated her concerns to ‘hallway talk.’ Second, an innovation expert provided input on product health and nutrition claims. He worried that the clean label ‘absence of negatives’ claim might not be sufficiently differentiating. He recommended head-to-head testing in the context of a different consumer and snacking occasion. Under deadline pressure, however, Doug trusted a passing grade from basic acceptance testing with current users. By the time the expert raised the question again, it was too late. The launch was in motion already.
Discerning consumers in the new competitive context did not find the innovation meaningfully better than their current choices. The innovation failed to reach a sustainable trajectory, and repeated attempts to bolster growth depleted support from other portfolio brands. Declining sales velocity led to a spiral of distribution losses with key retailers.
Understanding why marketing strategies fail often requires looking beyond marketing itself—as the financial planning process showed. During the AOP process, the finance team set portfolio growth objectives to drive profitable growth commensurate with industry peers with similar country and category mix. Resource allocation decisions were made without timely input from sales and marketing, and without adequately accounting for the causal drivers behind brand performance. Instead, the process focused mostly on solving for a pre-determined number. Doug’s efforts to explore more flexible and pragmatic scenario planning never saw the light of day.
The process led to unrealistic constraints and misallocation of marketing support, leading the brand to overlook opportunities to adapt strategies to changing circumstances.
With the benefit of hindsight, Doug’s team did many things well in its attempts to drive growth while balancing risks and opportunities. However, individual decisions, no matter how sound, collectively failed to deliver because they were not connected effectively with each other. The company lacked a decision intelligence ecosystem. Decision Intelligence (DI) represents a transformational approach for teams to function more effectively. Simply put, it’s a technology that allows organizations to structure, connect, and automate decision processes digitally. Decision Intelligence software enables the team to ask better questions of the right people, use more insightful metrics in a timely manner, and receive better guidance on areas to focus on. Centralizing decisions and underlying data-based rationales provides transparency and the ability to track and learn from prior experiences. Think of it as a co-pilot, akin to what NASA’s mission control space center is to an astronaut. Modern decision intelligence software makes this level of support possible.
Let's look at how things might have gone differently for Doug if he had access to decision intelligence software to accompany him on his snacking misadventure:
Many readers will recognize similar strategic stumbles and missed opportunities in their own experiences. Some may aspire to have decision intelligence software to drive more favorable outcomes. Yet, one may feel skeptical. The examples above may come across as naively suggesting that Doug should have anticipated every risk, analyzed every possible decision more rigorously, consulted everyone earlier, made all the right decisions, in other words to have acted like some omniscient God with unlimited time and resources. However, this is not the idea.
The benefit of decision intelligence in real life is not for the machine to know all the right answers. The technology cannot anticipate every issue or solve every problem on its own – it's not magic. However, well-implemented decision intelligence software enables teams of human leaders to improve their odds of making better quality decisions with the support of structured processes and predictive AI built on the collective wisdom of the organization. It applies what decision intelligence technology does best (lightning-fast, structured, AI-driven pattern recognition at scale) to supplement what humans need most (automated and objective advice that combines organizational knowledge and experience).
The research underscores what Doug's story reveals. Companies using decision intelligence software are seeing dramatic improvements in their decision-making capabilities - making choices 2-4 times faster while reducing analytics costs by 30%. This explains why Gartner predicts that by 2026, the majority of global enterprises will adopt these practices, transforming how they track and learn from business decisions.
Doug will undoubtedly approach his next role better equipped and wiser with the help of decision intelligence.
For more information on how decision intelligence can help your business, contact Cloverpop.