Across all industries, the race is on for firms to differentiate with data — through data-driven products; enhanced customer acquisition and experience; reduced risk; or streamlined operations (cost-out). C-suite executives have the aspiration and vision to win with data-driven insights, yet most are dissatisfied with the cycles consumed in producing data-driven insights. The time it takes for a business to deliver a quantitative insight from when an internal stakeholder or external customer needs it — let’s call that a firm’s Data ID, short for Data Insight Delay.
Data Storytelling is an essential skill of of any data scientist that makes data come alive. It is a structured method for turning data insights into action through analysis, design, and narrative. It is an art that brings interpretation and clarity while engaging the audience towards action. The Framework defines the art of data storytelling, as well as provides guidelines for how to do it successfully.
Data is something everyone uses and needs to do their job. When people don’t trust their data, organizations have a big problem on their hands and it won’t go away overnight.
The only way to fix a lack of trust is to build trust. Getting employees to buy in to a new way of using data is a process of building trust. Just taking the spreadsheets away won’t work. People are more dedicated to their culture than any strategy.
While there are very tactical and very specific steps to take, it starts with the approach: understanding that data is a business problem, not an IT problem. From there we can focus in, all the way from brand, mission, and operating model, down to the key performance indicators to measure success. This is a process that takes time. Many organizations desire to follow a business-driven approach to data, but find quickly (and surprisingly) they are still treating it as an IT problem and they have a tougher time measuring success than they thought. This is the vital work we love to partner in.