After determining the business questions you are trying to answer, collecting the relevant data, and analyzing it, presenting data and results to your audience in a way that resonates with them is not always easy. Decision makers come to the table with varying levels of technical expertise and differing expectations. In order to actually improve decision making, insights from data analytics must be presented simply, concisely, and with clear actionable takeaways.
At Edgeworth Analytics we achieve this by staying client oriented, practicing good communication, and developing simple, yet effective visualizations. Our end goal is to be able to explain complex concepts simply and explain the intuition behind the results. To do that, we think carefully about how to present ideas and results to our clients so that their business can take advantage of the insights we provide.
Below we share some of the practices we rely on when communicating results to clients. These same practices can be applied when presenting data internally to business stakeholders.
- Know the Takeaway: What question does the analysis answer? What are your actionable insights? Does your visualization provide insight into the question you set out to answer? What questions remain or what can your analysis not answer.
- Simplify: Identify your key insights and action items and drive them home. Avoid results that, while interesting to you are not related to the key takeaways. Even when it comes to visualization, simple is often more insightful. Don’t try to do too much!
- Avoid Jargon: While data and methodology are important, avoid communicating in heavy jargon. Communication often comes down to explaining a concept to someone in simplest terms and adding detail as necessary. It is important to spend time determining how you are going to convey the work that you did and any important findings without getting stuck in the weeds.
- Be prepared for questions: Your audience will have questions, especially if your results are inconsistent with their prior expectations. Be objective, transparent, and systematic when answering questions. Present validations or intuitive examples to backup sophisticated models. Finally, be sure to know all the details even if they are not initially presented.
Communicating results is as important as preparing the results. It is part of the process, not an afterthought. Boiling down work to a precise answer is a sign you did your job well. The process may be complex, but its presentation can be simple!