As organizations rush headlong into digital transformation initiatives, a critical factor often gets overlooked: data quality and the resistance to support ongoing data quality efforts. In the race to implement cutting-edge technologies and overhaul business processes, many companies fail to recognize that the success of these efforts hinges on the accuracy, completeness, and reliability of their underlying data. This oversight can lead to disastrous consequences, undermining the very goals that digital transformation aims to achieve.
Read MoreData Literacy: The $100 Million Insurance Policy You're Probably Ignoring
In boardrooms across the globe, executives are gleefully signing off on multi-million-dollar investments in data infrastructure. Big Data! AI! Machine Learning! But here’s the inconvenient truth they’re overlooking. Without a data-literate workforce, these shiny new toys are as useful as a Ferrari in a traffic jam.
Read MoreChange Management in Data Projects: Why We Ignored It and Why We Can't Afford to Anymore
For decades, we've heard the same refrain: “Change management is crucial for project success.” Yet leaders have nodded politely and ignored this advice, particularly in data and technology initiatives. The result? According to McKinsey, a staggering 70% of change programs fail to achieve their goals. So why do we keep making the same mistake, and more importantly, why should we care now?
Read MoreThe Art of Feedback: Reflections on transformative teaching and learning
At its core, effective teaching and learning hinge on meaningful feedback. It’s not just about grading; it’s about investing in each student’s growth, challenging them to think critically, and creating an environment where deep learning can happen. As educators, we nurture this process by providing the guidance and support that transforms education from a mere transfer of information into a transformative experience.
Read MoreWhere Business Meets Technology in the Marketplace of Information
Real estate focuses on governance and value derivation from assets. The Marketplace facilitates value-driven transactions while maintaining order, quality, and trust throughout the ecosystem. BOTH must work TOGETHER.
Read MoreNavigating the Complexity of Data Projects: Lessons from the Rubik's Cube
As someone in the information management space for nearly thirty years, I've seen firsthand how the landscape of data projects has evolved. Understanding complexity is crucial for success. Imagine a Rubik's Cube. Unlike a jigsaw puzzle where pieces fit independently, every move on a Rubik's Cube affects the entire structure. This is the perfect metaphor for modern data projects. They're not just complicated; they're complex.
No stakeholder, risk, or work stream can be viewed in isolation with data projects. Marketing can't operate without considering IT's capabilities, and HR needs to align with data privacy standards. It's an intricate dance of interdependencies that requires a holistic approach.
Read MoreCultivating a Data Ecosystem: A Fresh Approach to Organizational Data Management
Many organizations have recognized the need to enhance their data management capabilities. The traditional response has been to centralize these efforts, often by appointing a Chief Data Officer (CDO). However, this well-intentioned approach often leads to challenges and resistance within the organization.
Read MoreDescribing data consumption to anyone
Visualizing data consumption as a bustling marketplace can help illuminate an organization’s diverse needs. Let’s explore how various business roles interact with data, like shoppers in a busy bazaar.
Read MoreLow and High Quality AI: What's the Difference?
When we talk about "low-quality AI," we're referring to AI systems that are less sophisticated, less accurate, or more limited in their capabilities. These systems, interestingly, can sometimes lead to more critical and independent thinking from users.
Read MoreThe Double-Edged Sword of AI in Education and Work: Lessons from the Frontlines
As adjunct faculty, I get a front-row seat to the AI revolution in education and the workplace. What I've observed is both exciting and concerning, a paradox that we must navigate carefully as think about our future work.
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