Storytelling with data simplified; how to overcome your writer’s block when storytelling with your data
Storytelling with data is an essential tool for communicating the data we have analyzed. After all, it is the insights that are the end product of Data Analytics. It is usual to get stuck when trying to communicate the best possible, brief, and concise report for your audience.
This writer’s block does not mean we are confused and can’t communicate the best possible report but because we are trying not to be biased and not leave out all charts that make up a valuable part of KPIs
Let’s have a look at these 4 ways on how we can overcome this hurdle;
Trends
We should not compromise on trends but instead, build our analysis and reports around them since they communicate a valuable part of the data we have. In my view, it is the most valuable part of data analytics.
Trends include Time series, Patterns, Increases, Decreases, etc, best explained by Area Charts, Trendlines, and sometimes Column and Bar Charts. Storytelling with trends is best done by the following steps:
1. Explain the cause of the trend
2. Explain underlying factors for the cause of the trend
3. Explain the source of the underlying factors
4. Always start with inherent/primary factors down to the least, which can be ignored in case of a brief report
Creating insight around context
Reporting data based on where something is FROM, where it has BEEN, and where it is going is a powerful tool in both Analytics and Data Science.
It is mostly used in predictive analysis where as an analyst, you should investigate the pattern, capture the data, and create some convenience for the consumer by communicating insights. In predictive analysis proceed to write a formula, and predict when the occurrence is gonna happen again in the future.
Things out of the ordinary should be noted and the sphere of influence given much focus.
Relationship and clustering
In large data, Instead of monthly trends, we can go with YEARLY trends and just highlight peak months as well as the frequency of data. This will simplify key metrics and weigh down on jargon.
Demographics
We should center our demographics around 3 key factors:
1. Gender
2. Age
3. Age groups
This will capture key metrics in an all-rounded manner and communicate insights that are inclusive and concise.
In conclusion, when telling Data stories, we should be able to engage the target audience, explain the data, enlighten them with KPIs and key trends, and seek to change their perspective by inspiring action. Connect with people's experiences and explain things like why people continue to appreciate a trend yet it’s costly.