If I had to describe life in one word, that word would be CHANGE. Constant and inevitable, change is woven into every experience, shaping our perception of the world and what’s happening around us. Each new experience is a testament to the relentless and inescapable nature of transformation. While change is ever-present, it is not always easy to manage.
In large-scale transformation projects, the success of organizational change management (OCM) hinges on maintaining a clear focus on people readiness. However, when OCM team members become overly absorbed in the technical aspects of a project, such as system debugging or technical troubleshooting, people readiness activities are commonly deprioritized.
Waiting for data is like waiting at the gate with no plane in sight.
Artificial intelligence is no longer a distant concept. It’s here and is reshaping the way organizations operate and deliver value. In higher education and government, where innovation is expected but resources are stretched, AI creates opportunities to streamline operations and elevate outcomes. But unlocking the full potential of AI requires more than just tools. It requires strategy, alignment, and the right partner.
Even the most successful partnerships face challenges early on. Before winning six NBA championships, Michael Jordan and the Chicago Bulls endured years of playoff disappointments and internal clashes. Similarly, Steve Jobs didn’t transform Apple into one of the world’s most valuable companies overnight—he actually resigned in 1985 due to internal tensions, only to return in 1997 and lead a historic turnaround.
Often, organizations complete lessons learned sessions after a project, but don’t always know how to leverage these as they move to the next initiative. They can get lost in the shuffle, quickly forgotten, or overshadowed by other concerns. I once heard a client call them “lessons documented” since many times they are captured but not learned.
For more than 20 years, I’ve had the privilege of working in management consulting. Today, I help lead a data analytics and AI practice focused on empowering our clients with meaningful insights. One of the most rewarding aspects of this journey is connecting directly with customers at conferences like NACUBO, where conversations on the expo floor often reveal the real, urgent challenges institutions face.
How many times have you spent hours building the perfect dashboard, only for it to be used once, maybe twice?
Data analysts love to produce engaging reports that generate end user collaboration. To drive solution adoption, data teams may need to meet users where they’re at in sharing reporting. Microsoft Power BI not only enables data analysts to build compelling visualizations to drive data storytelling, but it also offers flexibility in accessing content either through the Power BI service or embedding content directly into an organization’s own web application. For instance, embedding allows government organizations, nonprofits, or higher education institutions to share their data insights alongside related information all on one page for external users to consume. In this blog, we’ll explore some of the capabilities, approaches, and best practices for embedding content with Power BI Embedded Analytics.
Power BI is Microsoft’s platform for data visualization and discovering business insights. Its flexibility allows you to visualize limitless iterations of your data and generate insightful reports, but what happens when that data needs to make its way out of the dashboard and onto your desktop?