![[first_data_person_animal_shelter_five_essential_tips.png]] As the first data person at [People For Animals](https://pfawildlifehospital.org/), I was a bit like a [rabbit caught in the headlights](https://www.collinsdictionary.com/dictionary/english/someone-is-like-a-rabbit-caught-in-the-headlights). I had talked my way into the job, but had absolutely no idea where to even start. I knew data of course, but I had no clue about how a shelter operates. There was also very little technical support for me from volunteers at the shelter as the shelter was fairly new to the idea of using data effectively for its operations. In this post, I summarise five key tips that I wish I knew when I first started. ## 1. Identify Quick Wins - Explore the data early and explore it well. - Start with small, achievable data projects that can quickly show benefits, such as preliminary analysis of data at hand - These quick wins can build trust and open doors for more complex data initiatives. ## 2. Understand the Non-Technical Environment - Spend time understanding the shelter's operations, challenges, and goals. Recognise that this is key to success. - This context is crucial for identifying areas where data analysis can be most impactful, such as tracking animal adoption rates or identifying patterns in animal intake. - Understand that you are the first person to use technical concepts. Be mindful and respectful of others' knowledge gaps and help patch it by being open and friendly. Be a mentor. ## 3. Simplify Data Presentation - Use visual tools like charts and graphs to present data insights in an easily understandable way - Avoid technical jargon and focus on how the data can directly benefit shelter operations. ## 4. Be Patient & Persistent - Change takes time, especially in a non-data-centric environment. - Be prepared to gradually introduce data-driven practices and demonstrate their value over time. - Be ready for an outcome where none of your findings are implemented. When this happens, identify what parts of your suggestions were too hard for the shelter to take on. And refine your findings. ## 5. Communicate Effectively - Regularly communicate your findings to the team, ensuring that the insights are relevant and actionable. - Be honest. If the data quality is bad, let the stakeholders know this and work with them to put in place a process to make it better. - Use storytelling techniques to make data more relatable and engaging. If you don't know where to start, check out [[Unleash the Power of Storytelling for Engaging Technical Presentations]] If you would like to chat more in-depth about any of these, feel free to reach out at [email protected].