Business / Consumer Goods
Business signals: regulation, strategy, macro links, and market structure. Topic: Consumer-Goods. Updated briefs and structured summaries from curated sources.
Innovation Reignited: C-Suite Insights into the State of Innovation
Full timeline
0.0–300.0
The webinar discusses the current state of innovation, highlighting the need for consumer insights to drive true innovation rather than mere renovation. Industry leaders emphasize the importance of tracking innovation as a growth engine and the dual role of AI in this process.
- Todays webinar focuses on new insights on innovation from industry leaders, emphasizing the importance of consumer insights in driving true innovation
- Innovation is viewed as essential but is not being prioritized adequately, with much of the current innovation being merely renovation
- Tracking innovation like a growth engine is critical for success, as highlighted by the upcoming data presentation
- AI is discussed as both a catalyst for innovation and a potential pitfall, stressing the need to navigate its use carefully
- The webinar is part of the Innovation Reignited series, created to address the decline in true innovation and provide practical tools for attendees
- The session features accomplished speakers, including Richard Davies, who has extensive experience in innovation and brand strategy, and Olaf Lensman, who focuses on insights and product execution
300.0–600.0
Innovation is identified as the top priority for growth among C-suite leaders in sectors like CPG, retail, and healthcare. However, many leaders express concerns about their effectiveness in generating and executing innovation, with expectations of modest revenue contributions from these efforts.
- Innovation is the number one priority for growth among C-suite leaders, particularly in CPG, retail, and healthcare sectors
- % of leaders expect innovation to become more important to their growth strategy over the next three years
- A majority of leaders feel they are not effective at generating and executing innovation
- Two-thirds of leaders anticipate that innovation will account for less than 20% of their revenue in the next three years, indicating modest expectations
- There is a disconnect between companies claims of successful innovation and the actual results they achieve
- Many organizations do not measure innovation effectively or set targets for its contribution to revenue
600.0–900.0
Companies must define innovation based on its consumer impact rather than solely on technological advancements. High performing companies generate around 20% of their revenue annually from innovations launched in the previous 12 months.
- Every company must define innovation for itself, considering its impact on consumers rather than just technological advancements
- High performing companies generate around 20% of their revenue annually from innovations launched in the previous 12 months
- Companies often lack clear innovation targets and fail to integrate innovation into their strategic planning
- Three quarters of innovations are renovations, with only 26% being true new product launches
- A Mintel report from 2024 indicated that only 29% of new product launches were true innovations, the lowest since 1996
- Renovation can effectively protect existing brands, but may not drive significant growth
900.0–1200.0
Leaders are encouraged to take smarter risks rather than bigger risks, balancing renovation with breakthrough innovation. The definition of innovation should prioritize consumer impact over mere technological advancements.
- Leaders should focus on taking smarter risks rather than bigger risks to avoid sacrificing long-term differentiation for short-term gains
- Renovation can be beneficial if the resources invested are proportional to the returns generated
- A balanced innovation funnel should include both renovation and breakthrough innovation to prevent resource allocation solely to short-term activities
- While renovation is often easier and can be prompted by retailer requests, it is crucial to simultaneously work on larger innovations that may take longer to develop
- Innovation should be evaluated not only on technological advancements but also from the consumers perspective, emphasizing the importance of consumer-centric definitions of innovation
- It is acceptable for innovations to fail in the funnel, as long as there is awareness of their low success potential before market launch
1200.0–1500.0
Innovation is hindered by a lack of consumer insights, with less than half of leaders reporting their innovations stem from such insights. Successful organizations invest in internal marketing to enhance awareness and accessibility of insights.
- The best time to start innovation is now, even if it takes time to develop
- A significant barrier to meaningful innovation is the lack of consumer understanding and insights
- Less than half of leaders report that their innovations stem from consumer insights, indicating a disconnect
- Insights often become siloed within organizations, making them difficult to utilize effectively
- Practitioners struggle to apply insights due to their dispersion across multiple systems
- Technology, including AI, can help make insights more accessible and contextually relevant for users
- Successful organizations invest in internal marketing to promote awareness and availability of insights
1500.0–1800.0
Companies face challenges in making aggregated data actionable during their innovation processes. Over a third of CPG leaders struggle with differentiation, often relying on competitive innovation for new ideas.
- Companies struggle to make rich aggregated data actionable in their innovation journeys
- Technology can serve as a partner in innovation, helping to analyze consumer insights and iterate on ideas
- Differentiation is a significant challenge for over a third of CPG leaders, with many relying on competitive innovation for new ideas
- The irony exists where companies seek uniqueness but often look to competitors for inspiration, risking a me too approach
- Uniqueness is the most critical metric in concept testing, determining whether an idea can enter the innovation funnel
- Being first in innovation is generally advantageous, and companies should focus on compelling claims to avoid being undermined
1800.0–2100.0
Effective communication is essential for innovation to resonate with consumers and prevent competitors from copying. A thorough measurement system is crucial for tracking key metrics related to idea generation and project success.
- Being first with innovation is crucial, but effective communication is equally important to prevent competitors from copying
- Without strong branding and advertising, innovative products may fail to resonate with consumers, wasting the effort put into development
- A complex system requires a balance between innovation and marketing; neglecting one can lead to cultural shortcomings
- Many leaders do not track key metrics related to idea generation and project success, which can hinder growth
- A thorough measurement system is essential for identifying weaknesses and optimizing processes in innovation
- Innovation panels often function as tunnels rather than funnels, leading to the launch of every idea without proper evaluation, which can result in failure
2100.0–2400.0
Companies often underestimate the number of ideas needed to maintain a well-managed innovation funnel. Senior decision-makers must be involved in gatekeeping meetings to ensure that only viable projects receive resources.
- Innovation is a numbers game; companies often underestimate the number of ideas needed to feed a well-managed funnel
- The role of a gatekeeper is to eliminate weaker projects to allocate resources to stronger ones, increasing the likelihood of market success
- Ideas should be assessed with consumers at every stage of the funnel, not just at the beginning, to ensure they meet consumer needs
- Senior decision-makers, including the chief marketing officer and CEO, should be present in gatekeeping meetings to make informed decisions about project viability
- The head of the insights organization must represent consumer interests in gatekeeping meetings, ensuring that ideas align with consumer preferences
- Continuously killing off ideas as they progress through the funnel raises the bar for projects and improves the probability of successful launches
2400.0–2700.0
A significant majority of leaders recognize the importance of AI in driving innovation, with 86% believing it will be very to extremely important. Additionally, 97% of leaders are already utilizing AI in some capacity, emphasizing its role as a collaborator rather than the primary innovator.
- % of leaders believe AI will be very to extremely important for innovation
- % of leaders are already using AI in some form
- AI should be viewed as a collaborator, not the chief innovator
- AI excels at accelerating synthesis, organizing disparate sources, and drafting concepts
- Caution is advised as AI can mislead and create false confidence if relied upon too heavily
- Safe use cases for AI include searching, summarizing, and providing situational context
- AI can help shape brand challenges and synthesize innovation suggestions
- Working with AI on complex tasks requires deeper thinking and prioritization from humans
2700.0–3000.0
AI can enhance initial steps in becoming impactful, but it requires human attentiveness and intentionality. Effective use of AI involves understanding its limitations and grounding it in specific data to achieve differentiation.
- AI can accelerate initial steps in becoming more impactful, but requires human attentiveness and intentionality
- Understanding how to effectively use AI is crucial for all users, including knowing its limitations
- Starting use cases for AI include searching, summarizing, consolidating, and synthesizing information
- Its important to ground AI in your own data to achieve differentiation from others using the same models
- Humans must remain accountable in the use of AI, as it is a tool that requires human ownership
- Validation with real consumers is essential when scaling AI applications