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I’ve just published our paint-by-numbers guide for building a dynamic machine-learning model inside Power BI—no heavy coding required. 👉 https://lnkd.in/eyA6uDxa #PowerBI #DAX #MachineLearning

“The system would work fine if people just used it correctly.” I hear this all the time. After designing systems for dozens of companies, I’ve learned that poor adoption and messy data usually come down to three things: 𝐈𝐧𝐜𝐞𝐧𝐭𝐢𝐯𝐞𝐬 - Too many systems are built for management, not for the people who have to use them daily. If it doesn’t help users win, they won’t use it. 𝐅𝐫𝐢𝐜𝐭𝐢𝐨𝐧 - If it’s hard to enter data correctly, don’t be surprised when people don't. 𝐅𝐞𝐞𝐝𝐛𝐚𝐜𝐤 - People will make mistakes. They need clear signals to fix them when they do, the sooner the better. Bottom line: if your system doesn’t compensate for human weaknesses, 𝘵𝘩𝘰𝘴𝘦 𝘸𝘦𝘢𝘬𝘯𝘦𝘴𝘴𝘦𝘴 𝘸𝘪𝘭𝘭 𝘴𝘪𝘯𝘬 𝘺𝘰𝘶𝘳 𝘴𝘺𝘴𝘵𝘦𝘮. What to do instead: ✅ 𝐑𝐞𝐝𝐮𝐜𝐞 𝐢𝐧𝐩𝐮𝐭 𝐞𝐟𝐟𝐨𝐫𝐭. Design for someone in a hurry: defaults, autofill, forgiving formats, and fewer required fields. ✅ 𝐍𝐮𝐝𝐠𝐞𝐬 > 𝐜𝐨𝐧𝐬𝐭𝐫𝐚𝐢𝐧𝐭𝐬. Avoid rigid rules that block work. Use prompts, inline tips, and gentle validation that guides without stonewalling. ✅ 𝐌𝐚𝐤𝐞 𝐢𝐭 𝐯𝐢𝐬𝐢𝐛𝐥𝐞. Dashboards or “data hygiene” leaderboards turn quality into a game and create a clear to-do list when it slips. What’s one small change you’ve made that boosted adoption?

£𝟐𝟓𝐦 𝐭𝐨 £𝟏𝟎𝟎𝐦+ 𝐫𝐞𝐯𝐞𝐧𝐮𝐞 𝐢𝐧 𝟑 𝐲𝐞𝐚𝐫𝐬. 𝐇𝐞𝐫𝐞'𝐬 𝐭𝐡𝐞 𝐡𝐢𝐝𝐝𝐞𝐧 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝐭𝐡𝐚𝐭 𝐦𝐚𝐝𝐞 𝐢𝐭 𝐩𝐨𝐬𝐬𝐢𝐛𝐥𝐞: Most businesses plateau because they're flying blind. Data scattered across a dozen systems. Sales teams manually tracking leads. Marketing campaigns with no clear ROI. Operations drowning in busywork. In 2022 one client of ours was stuck there. Today they’re on the FEBE Growth 100 for the second year running. That doesn’t happen without talent, hard work and a bit of luck, but the biggest change was how they leveraged their data. Here’s the 4 step framework we used: 🧪 𝐓𝐞𝐬𝐭, 𝐭𝐫𝐚𝐬𝐡, 𝐫𝐞𝐩𝐞𝐚𝐭 – Before building rigid systems, we created cheap prototypes. If it didn’t perform we were ruthless at scrapping it and pivoting.   ⚡ 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐭𝐢𝐦𝐞 𝐬𝐢𝐧𝐤𝐬 - We focused on automating the biggest drains on people’s time, reducing errors and freeing people up to focus on high value activities. 🔗 𝐔𝐧𝐢𝐟𝐲 𝐝𝐚𝐭𝐚 - We built a model that connected everything  (CRM, Databases, Emails, Calls, Excel files, everything) and gave real time visibility across the business for the first time. 📊 𝐅𝐢𝐧𝐝 𝐭𝐡𝐞 𝐧𝐞𝐞𝐝𝐥𝐞-𝐦𝐨𝐯𝐞𝐫𝐬 – We found the numbers the connected actions and results, created new KPIs and put them in the hands of decision makers. The results speak for themselves: • 𝟏𝟑𝟕% 𝐢𝐧𝐜𝐫𝐞𝐚𝐬𝐞 𝐢𝐧 𝐚𝐯𝐞𝐫𝐚𝐠𝐞 𝐬𝐩𝐞𝐧𝐝 through focused customer targeting. • 𝐒𝐚𝐥𝐞𝐬 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐛𝐨𝐨𝐬𝐭𝐞𝐝 𝐛𝐲 𝟒𝟐% with personalized, data-driven coaching recommendations. • £𝟑𝐦 𝐫𝐞𝐜𝐨𝐯𝐞𝐫𝐞𝐝 by through automated opportunity alert system. It’s not about more data: it's discovering which numbers will drive results.   If you’d like to talk about how to find those key drivers for your business, my DMs are open!