Wikis in High School
Last month, Vinson wrote about the use of wikis in school projects, and it reminded me to dust off some notes I took from a conversation with my daughter Sean…
Driving Participation and Contributions on Internal Blogs and Wikis
It's much easier to install the software than it is to get participation ... you need to put some thought into the why? and the who? ... Why are we…
What’s the Difference between Announcements, Blogs, Discussions, Wikis?
Alternate Title: Battling Collaboration Memes As mentioned previously, we are trying out SharePoint where I work, and I'm finding it interesting, maintaing 3+ blogs, including this one. Actually, the focus…
More on (sic) experience with wikis
no, that's not a typo ... Preamble: This starts out sounding like a diary entry, but some interesting wiki-focused observations are found below - including metrics! Catching up on old…
The Law of Large Numbers – or, why Enterprise Wikis are Fundamentally Challenged
Some will be taken a bit by surprise to read the title of this post; we have implemented a wiki in our group at work, and I have the evangelist…
AI Readiness Assessment: What Does Good Look Like?
Most AI readiness assessments measure technology. The AI Readiness Assessment measures your organization - across Five Building Blocks, with honest self-evaluation and real benchmarks.
Operations and AI Readiness: The Discipline You Can’t Skip
Operations brings the lean discipline that AI implementations desperately need. Waste elimination, metrics culture, and daily standups matter more than algorithms.
Product Development and AI Readiness: From Widgets to Intelligence
Product Development is the only team that can answer the question "what should AI do for our customers?" That conversation - from widgets to intelligence - is where new revenue lives.
Sales, Marketing, and AI Readiness: Voice of the Customer
Sales and Marketing sit on the richest unstructured data in the company and have spent their careers mastering the art of change. Those aren't peripheral skills for AI readiness - they're the core challenge.
Finance and AI Readiness: Speaking in Facts
Finance has been speaking in facts - insisting on data rigor, measuring value, building structures that survive turnover - since before AI was a boardroom topic. Those aren't peripheral skills for AI readiness. They're foundational.