DATABERG
Data can be very valuable to organizations, but data without a deep understanding of its meaning and context is not helpful at all. For the data to be relevant, it must provide a robust picture and in-depth understanding, as well as actionable information.
Information gathered from data analysis should be actionable, that is, managers can recalibrate strategy and operations in response to the findings. Enterprises of all sizes across the world collect data as a part of their routine operations. Then, it’s processed and analyzed to determine trends, customer behavior patterns, best marketing practices, and more other things. With countless companies engaged in data analysis at all times, it’s inevitable that some information doesn’t get translated into ground-breaking outcomes.
How to Develop Actionable Business Insight
In order to maximize the return on data investment, corporations must focus on actionable data. This usually involves some investment into the data-driven analytical approach at the organization. “Actionable” is always the goal, as quality reigns over quantity in the world of data analytics.
The following criteria should be kept in mind when formulating an effective data analysis program.
Alignment
Data should be aligned with the key business metrics, or KPIs, decided on by management as a part of the organizational master plan. When a data insight is closely tied to business goals and strategic initiatives, it is likely to yield action. If an organization lacks key metric sets, it is handicapped in its ability to derive value from the numbers. These metrics should be developed with a cross-functional grouping, and data should be strategically aligned with these KPIs.
Context
All analysis requires proper context. Most data sets are difficult to interpret without a background knowledge of the terms and concepts contained within. Furthermore, trends do not exist in a vacuum. Knowing how changes in data points track to actual events, such as product or campaign launches, provides necessary context to the information collected.
Relevance
Data and analytical resources are limited. Therefore, an effort to target relevant questions and areas is important. Relevant data not only produces the most value, but also drives the most transformative action within an organization.
Specificity
No doubt, it’s always better to have more details. A data insight metric should be specific and tailored according to the goals the management most cares about. Specific achievable outcomes should be established, so that everybody is informed about the expectations.
Novelty
The most value is added from the new techniques, so analysts should feel comfortable to cast a fresh look at old information with a purpose to possibly uncover actionable trends and patterns.
Clarity
Communication is the key to make any data analysis successful. Data needs to be presented in a manner that is easily understood and interpreted by its target audience.
With the right plan and strategy, any organization can transform its data into the actionable knowledge.
