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?

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.

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.

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.

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. 

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.

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.

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.

The ability to craft compelling narratives from complex information is a superpower. Working with graduate students across various sectors, I help communicate how effective storytelling can bridge the gap between data teams and business leaders. Let's explore how to master this art and avoid common pitfalls.