Most organizations that deploy a communication platform end up sitting on a large volume of engagement data — read rates, response rates, participation trends by site and shift — that never gets used for anything beyond a monthly slide. The data collection problem gets solved; ...
Read the post"Workforce analytics" and "workforce intelligence" are increasingly used as if they're interchangeable — two labels for the same dashboard. They aren't, and the difference isn't semantic. It's the ...
"Workforce analytics" means two genuinely different things depending on who's asking. HR and finance leaders usually mean strategic people analytics — headcount planning, attrition modeling, pay ...
You hear it constantly in frontline tech conversations: “We need a better distribution solution.” As if distribution is a feature on a roadmap, something you spec out, build, ship, and check off.
Most organizations think about frontline communication technology as a cost to evaluate, something that might pay off, depending on how the numbers shake out.
In machine learning, “ground truth” is the verified, accurate baseline a model is trained and evaluated against. It’s the known answer, the data point you can actually trust. Without ground truth, a ...
Here’s how the frontline AI ROI conversation usually goes: someone shows the model, capabilities, accuracy, benchmark results. Someone else asks how much it costs. Then someone asks if it’s worth it. ...
Simple question: what’s the maximum wind speed to safely cater an aircraft?
We thought we had a solid ROI model. We’d done the math, built the framework, grounded everything in real usage data. The number was real and defensible.
There’s a version of the frontline AI story that goes like this: buy the AI, train it on some documents, give workers access, and it starts answering questions. Simple, fast, transformative.
It’s 2 a.m. A nurse at a senior living facility has a question about a resident’s prescription. The answer exists somewhere in the organization’s documentation, the care plan, the medication ...
You built the model. Maybe you fine-tuned it, built an agent layer on top, gave it tools and context. It answers well. The demos are solid. Your team should be proud.
At Argentum in Nashville, a rep from Synchrony Pharmacy stopped by our booth. We were running a live demo, Shelbe connected to a Trilogy senior living community’s real data, showing how the AI was ...
The AI industry is converging on a truth that’s uncomfortable for a lot of vendors: the model is commoditizing.
There’s a number buried in most AI deployments that doesn’t get nearly enough attention: the fallback rate. The percentage of questions the AI answers from something other than your organization’s ...