Best Practices Summary:

• Data teams created a single source of truth for data to reduce conflicting reporting and analytic insights

• Analysts gained alignment with customers of reports on the data and insights required before prototyping. An intake request form helps facilitate this process. 

• Analysts continually iterated with their customers to ensure that all key questions are answered by the reporting/dashboards.

Case Study:

A division of an online real-estate marketplace company struggled to identify operational and promotional improvement opportunities due to the confusion caused by conflicting dashboards and reports. Business stakeholders in operations, marketing, and sales needed more accurate insight on rental property transactions, the impact of promotions on sales, and tracking of rental cancellations. Operations, data science, and finance teams each frequently provided reports and insight, however each team used different data sources leading to differing data, analysis, and interpretation. In addition the disparate data sources, parameters, and assumptions used to develop reports and analytics lacked explanation. The analysts were tired of explaining why results were different. The stakeholders in operations, marketing, and sales who made decisions for the business had low trust in the insights they received. Executive leaders wanted to be able to see the real and accurate numbers in order to better manage the business. The lack of trust led to limited adoption of the teams' reporting and insights. 

The Senior Manager of Sales Operations Analytics identified these challenges and convened a task force to drive alignment on solutions. The group met and agreed on creating a single source of truth for the data that could be used across the operations, data science, and finance teams. Senior leadership were informed of the challenges and bought into the need for improvements. The challenges were experienced strongly enough that analysts were willing to adopt new ways of working. New steps included adding steps to produce collateral explaining parameters (such as filters and business rules) for the data and the difference between old calculations and new calculations. Analysts worked with stakeholders to get more buy-in on the reports they were producing even before prototyping dashboards. An intake form was instituted that asked who would use the data, how often, and what actions would be taken based on the insights in order to drive more thoughtful asks from the business as well.  The analysts iterated the dashboards with their internal customers to ensure they thought through all the questions that might need to be answered. 

In the end, these changes drove much more trust in the data and reports from stakeholders. Data coming from the operations, data science, and finance teams now agreed with each other. The company could now more confidently understand their rental sales, marketing, and operational progress and make decisions and changes with greater confidence. Ultimately the group was able to grow their business based on the more trusted insights.