Paul Günther

Special Guest Blog Post written by Parabola Founder & CEO, Alex Yaseen   Operators are under pressure. They’re expected to move faster, do more with less, and somehow keep everything running smoothly while their systems, tools, and data are a mess. Now, AI is adding a whole new layer. On one hand, it’s exciting. The potential is real. On the other, a lot of teams feel stuck. They know they should be using AI, but they’re not sure where it fits into their day-to-day work. These are the five questions I get asked most often—whether someone’s trying to get started with automation, or trying to figure out how AI actually helps. 1. Can we automate this, or is it too messy? This question usually comes from someone deep in a spreadsheet that was never meant to scale. The short answer is: yes, you can probably automate it. But the longer answer is that you’ll need to rethink the process first. AI can help summarize, transform, and clean data—but it won’t fix a broken workflow. That’s on you. The best teams pair structured automation with lightweight AI to get leverage. Think: using rules and logic to standardize a workflow, and AI…

Special Guest Blog Post written by Chris Cunnane with InterSystems   In a world defined by rapid market shifts, volatile supply chains, and unpredictable customer behavior, traditional forecasting methods often fall short. Relying primarily on historical data is no longer enough. To stay competitive, organizations are increasingly turning to demand sensing and forecasting, an approach that blends real-time data, advanced analytics, and AI to anticipate demand more accurately and respond faster to change. This shift is not limited to retail or manufacturing. Demand sensing is transforming how organizations across industries plan operations, allocate resources, and improve service levels. Below, we explore key industry use cases where demand sensing is delivering measurable value, and why businesses should care.   Why Demand Sensing Matters Demand sensing moves beyond static historical trends. It incorporates current, high-velocity data signals such as sales transactions, weather patterns, logistics feeds, economic indicators, and even social sentiment to generate short-term demand forecasts that reflect real-world conditions. The benefit is clear. Organizations gain better visibility and responsiveness across procurement, production, inventory, and distribution. Instead of reacting to outdated forecasts, they can make timely decisions that reduce costs, prevent stockouts, and improve customer satisfaction. FMCG, CPG, Retail, & E-Commerce Fast-moving…