Dinsdag 20 februari 2024

Technologie & Innovatie

prof. dr. Hinda Haned

DAFI: The Game-Changer in Data-Driven Decision Making

Data-driven decision-making has the power to transform businesses, translating insights into actionable strategies that drive growth, innovation, and enhanced customer satisfaction. However, many organizations fail to fully realize this potential due to insufficient assessment and planning. To address this challenge, we introduce the Data Analytics Functionality Index (DAFI), a tool that empowers organizations to make informed decisions about their data analytics initiatives.

An essential ingredient of successful data-driven decision-making is the ability to assess the potential impact of a given project. However, relying on data- or AI-driven tools for decisions-making is typically a complex process carried out in multiple steps and involving multiple actors and stakeholders; often with different objectives. One consequence of this complexity is that many undertaken projects may fail to deliver on their promise, leading to wasted resources, diminished returns on investment, and missed opportunities. To address this challenge, we introduce the Data Analytics Functionality Index (DAFI), a new tool that empowers organizations to make informed decisions about their data analytics efforts. Similar to the Nutri-Score system that helps consumers compare the nutritional value of food products, DAFI provides a standardized, visual assessment of a project's functionality and potential impact. It considers a comprehensive set of factors, including data availability, complexity, resource requirements, and business relevance. By providing a clear and concise assessment, DAFI empowers decision-makers to identify promising projects that align with organizational goals.

Hinda Haned is a Responsible AI advisor, founder of Owls & Arrows, a company specialized in data science consultancy and algorithmic auditing. She is also professor by special appointment of Data Science at the University of Amsterdam and the Scientific Co-director of the Civic AI Lab, where her research focuses on developing solutions for best practices for safe and responsible data science.

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