Opportunities of "Why": Utilizing Real Business Intelligence, From Signals to Actions | Technology Trends

True business intelligence goes beyond just seeing the numbers—it’s about understanding the story behind the numbers.

In the UK, your retail team wants to know why members abandon their bookings at checkout; in Germany, your manufacturing team is asking why machine efficiency dropped by 12% on Tuesday; and across Europe, your customer experience leader wants to understand why French business travelers prefer different hotel service products compared to Nordic guests.

These are not hypothetical questions, but real challenges occurring daily across various business lines. However, by the time analysts manually correlate information between customer relationship management data, Internet of Things sensors, booking systems, and customer feedback, the optimal moment for action has already passed. That personalized hotel offer? The meeting is over. That supply chain adjustment? Negotiations have already begun. In today’s world, the shelf life of opportunities is getting shorter, and insights can’t wait for the next dashboard refresh.

This is not just about asking more questions; it’s about empowering every team with intelligence so they can act swiftly and confidently. Yet, most companies remain trapped in chasing static dashboards, buried in reports, or relying on analysts for delayed answers to address current challenges.

Imagine if every business user could easily ask “why” and receive trustworthy answers within seconds—answers that integrate structured data, unstructured content, and real-time context, transforming into clear, actionable intelligence, all while ensuring explainability, accuracy, and governance. This is the future of business decision-making: not more noise, but sharper signals.

The future is here, as the recent comprehensive launch of Snowflake Intelligence enables leading enterprises to move from insights to tangible impact, achieving democratized access to intelligence and gaining confidence in action based on trust.

Toyota Motor Europe’s Journey Towards Simplified, Faster, and Smarter Insights

Product planners at Toyota Europe are continuously exploring how to integrate the voice of the user more closely into the core of design. They are responsible for shaping the future automotive strategy: from defining model specifications to predicting customer needs, all of which rely on insights hidden within over 100 disparate systems—covering a variety of information from vehicle data to sales records.

In the past, planners relied on dashboards for analysis, but the depth and complexity of their analysis limited flexibility. They needed a smarter solution: one that could understand natural language and replace traditional dashboards with an AI assistant. This assistant needed to embody the team’s deep industry knowledge and complex logic, reducing the time to gain insights from hours or even days to seconds.

Initially, they built a fully customized solution, but due to complex business rules, the process took months and required significant investment to achieve acceptable accuracy. Subsequently, the team turned to Snowflake Intelligence, achieving the same level of accuracy and functionality in just about a month.

With Snowflake Intelligence, TME enables product planners to understand patterns and trends across disparate data sources while ensuring governance, accuracy, and scalability. Snowflake Cortex Analyst can map the relationships between data and business concepts, while validated queries and custom instructions are responsible for interpreting user intent and adhering to business rules Snowflake Cortex Search also enriches contextual understanding through a business glossary to handle domain-specific terms and synonyms. Finally, by selecting appropriate tools and standardizing outputs through an orchestration layer, it ensures that the generated responses are clear, well-structured, and ready for direct use by users.

The key to success lies in starting small and gradually scaling up after validation. Trust is also a critical factor in the user adoption process. In controlled evaluations, this solution achieved an 87% business accuracy rate, demonstrating a deep understanding of business scenarios and terminology, while maintaining a high level of consistency in response results. Planners can transparently view the reasoning process and source basis behind the answers, which is crucial for promoting usage and for future generative AI projects. Ultimately, migrating to Snowflake Intelligence means that the TME planning team can focus more on business outcomes, linking customer feedback directly to vehicle production over the coming years with faster and more reliable decision-making.

The potential of AI begins with AI-ready data. By building robust semantic models in Snowflake, TME successfully transformed data into intelligence, turning business scenarios into real value.

Achieving Greater Value with Stronger Contextual Processing and Capabilities

From smarter product decisions to faster market pivots, new revenue opportunities require action at every level of the organization, from the CFO's office to the marketing team. To act confidently, you need validated third-party data, trusted industry benchmarks, and analytical tools, all of which must be accessed instantly without compromising security, privacy, or compliance. Snowflake connects an ecosystem of publishers, providers, and applications directly to your data, accelerating the transformation process from concept to new revenue streams in collaboration with partners.

Why This Matters

Intelligent self-service analytics not only accelerates the analytical process but also enhances the quality of every decision, empowering faster action. When fresh insights can flow in real-time at the speed of emerging questions, your competitive advantage is no longer hidden in disparate data sources but returns to where it belongs: delivered to those closest to the customer, most familiar with business operations and market dynamics.

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