Category: Decision making
Approaches for improving business decisions through structured reasoning, analytics, and optimization.
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Pattern-Driven Analytics: The Mirage That Can Mislead
Misidentified patterns can produce serious analytical errors. Valid pattern recognition requires an inductive approach that starts with a hypothesis explaining the underlying mechanism, tests observed patterns against it, validates results using external evidence, and confirms conclusions with a problem expert. Decomposing complex problems into simpler components improves validation reliability.
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Smarter Inventory Management with Advanata
Advanata redefines inventory management by taking a customer-driven approach that allows for easy usage by a non-specialist, quick addition of custom inventory goals, and incorporation of inventory structure. A detailed example is given for a garage that wants to balance profits and lead times along with descriptions for other applications.
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Can Data Ever Be Trusted?
Data can never be objective since its construction requires the use of preconceptions. This increases usability for users but decreases objectivity. As content is transformed into more usable forms, it becomes more complex and less available. Advanata simplifies problems thus reducing the need for complex content and increasing its availability.
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The Secret Recipe for Smarter Pricing
Advanata provides an optimal solution to the problem faced by businesses needing to change prices while maintaining other subjective goals. A detailed example is given for a restaurant that wants to change menu prices in order to increase profits while maintaining customer loyalty. Other applications are also briefly mentioned.
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How to Identify the Hidden Value of Data: Useful or Useless?
Content is essential but varies in value across users. The same document serves different needs, demonstrating content’s polymorphic nature. Effective transformation requires analyzing problems to meet specific requirements. Advanata employs a structured approach to tackle analytics issues, emphasizing customer-driven solutions and the necessity of clear problem definition.
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Why We Need Information, Not Just Data
It is important to emphasize the importance of transitioning from viewing data as the final product to recognizing the necessity of information. We discuss the classification of content, the biases involved, and how Advanata utilizes information in analytics for more effective problem solving. By prioritizing information, businesses can better address challenges.
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Why You Don’t Need Another Dashboard
Dashboards often distract from effective problem-solving in business operations, focusing on data volume rather than actionable insights. While useful for reporting and transparency, their complexity can hinder decision-making. Analytics, like those enabled by Advanata, are essential for addressing real business challenges and fostering survival in an evolving marketplace.
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Don’t Fall for the Correlation Trap
Correlation does not imply causation; many analysts erroneously conflate the two. Collaboration between data analysts and customers, who possess domain expertise, is crucial for accurate conclusions. Employing an inductive approach allows for clearer identification of causation, improving efficiency and outcomes in analytics. This balance enhances the analysis process and results.
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Business Problems: What are they?
Business problems deliver the optimal actions a customer needs to reach their goals without any excess data or analysis. Most real-world problems are in fact of this type. Business problems are a structured form of analytic problems with the additional identification of goals, options and resources.
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Data Effectiveness: What is it exactly?
Let’s start from the very beginning. Who, What, Where, When, Why, and How are the basic questions for analyzing any problem. Things get far more interesting when we combine these basic questions! Combining Who and What allows for comprehensive Identification. Combining Where and When allows for describing Location. Going one step further, we can combine…
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