Facing pushback on new data quality protocols can feel like hitting a wall. First, get everyone on the same page by showing how the new protocols will make their lives easier. Speak their language and relate it to their day-to-day challenges. Next, involve the team early on. Ask for their ideas and concerns. When people feel heard, they're more likely to get onboard. Training is key, too—nobody likes change when they don't know how to handle it. Make sure everyone's comfortable with the new process. Lastly, be patient. Change takes time, and a little encouragement and a few quick wins can go a long way.

When implementing new data quality protocols, I’ve faced resistance due to concerns about workflow disruptions and increased complexity. To overcome this, I focused on aligning the new protocols with our team's current pain points—demonstrating how improved data quality enhances downstream processes, like more accurate predictive analytics. Involving key stakeholders early and incorporating their feedback into the protocol design fostered buy-in. Additionally, I provided targeted training sessions, leveraging real-time examples using actual project data to make the benefits tangible. This approach helped streamline adoption and minimized disruptions while ensuring long-term engagement with the new protocols.

Data drives the operation, weather good or bad it's what organizations use to monitor performance. The resistance to new protocols partly comes from change, potential fear within analyst to rely on the new way to use the new data protocols and leadership's ability to properly interpret and align the data to drive results towards KPI's.

In my experience, the argument of reduced workload appeals most to employees. We need to show that if we follow established protocols when entering data it will result in more work at the beginning of the process. On the other hand, we will save a lot more effort at the end of the process building reports or analyzing data. In sum, there will be less work.