What are the most effective ways to measure business outcomes from data reporting?

The most effective ways to measure business outcomes from data reporting is to understand the follwing fact ''Don't start with data but start with business outcomes.'' Business outcome is the apex of the value pyramid and data is right to the bottom. Hence , get to the data and figure out the least amount of information that can make the biggest business impact.In short it is important to link data to business outcome.

The most effective ways to measure business outcomes from data reporting are: Define SMART goals that are specific, measurable, achievable, relevant, and time-bound. Collect feedback from the intended audience and users of the report. Feedback helps understand how the report was received, used, and acted upon and what value it added to the business. Feedback can be collected through various methods, such as surveys, interviews, focus groups, or online platforms. Monitor the outcomes that are directly or indirectly influenced by the report. Outcomes are the changes or results that result from the information, such as increased sales, reduced expenses, improved customer loyalty, or enhanced innovation. #BusinessOutcomes #DataReporting

Feedback is one of the most crucial aspects of helping businesses with data. We need to understand that data science models do not run businesses. They exist to help businesses and thus a greater amount of effort needs to be put to understand the customer and their needs. As it is already mentioned, the data analytics project lifecycle doesn't end with a delivery. If the project exists and serves the customer, it needs to be revisited time-to-time to check the balance and see if the needs have changed. Data Analytics is not a concrete wall to be paved and rest, it should be flexible and open to changing ideas to run the businesses effectively.

Being able to monitor change over time is critical in seeing how effective changes to business processes are. Having an initial baseline of compliance, for example, will help teams understand if their policy changes improve, do not change, or negatively impact compliance each month. The more time data you have, the more robust your analysis can be on effectiveness. Additionally, teams need to use the same metrics to monitor effectiveness. Changing the policy measure of being inconsistent with the policies your monitoring means you’re comparing apples and oranges. Having a robust set of metrics that can be expanded on as policy processes are created in the future will be more effective than measuring different metrics each month.