It is not breaking news that organizations are dealing with data growing at exponential rates. What the headlines fail to reveal, however, are the deeper challenges that companies face as a result of wading through this sea of data. As data volumes grow, IT struggles to keep up, forcing business units to dig into data themselves to try to address critical questions. However, they simply do not have the time nor the resources to both process the data and craft a story around their findings. By skipping the latter step, organizations are left with reports addressing a narrow subset of questions that fail to tell the whole story.
It is not enough to provide users access to reports or dashboards that just inundate them with more, albeit refined, data. A data story wraps metrics and visuals in context and helps facilitate a deeper understanding, driving insights. The development of a good data story is a healthy mix of art and science and can be time consuming to create. Given that your users typically need answers yesterday, how do you balance requirement gathering, data processing, and development with limited time and resources?
In most cases the answer is not cut and dry, however, we have successfully helped our clients navigate this challenge by following a few guiding principles.
5 Key Factors to Tell a Compelling Data Story1. Know your Audience
- Who will consume the report?
- How do they consume data today? Are they satisfied with the current reports?
- What are the most important business questions to each audience group? At what level of data?
- What is the segmentation of the group consuming the information?
Knowing your audience is equivalent to knowing what type of story an author is trying to tell and the level of detail needed to support it. An analyst might desire an encyclopedia of information whereas an executive might seek the headlines of the novella. It is the most important (and underestimated) factor in telling a compelling data story. When you know your audience, you can successfully determine and answer the questions the data consumer didn’t realize needed to be asked.
2. Business Questions
- What business questions are we looking to answer?
- What business units or teams are invested in understanding the answers? To what degree?
- Are the answers to the business questions actionable? If so, who takes the action?
Knowing what questions to answer is considered the plot and the second most important factor. Asking the business to outline their decision-making process will drive the chapters we are seeking to write by providing a natural outline to the data story. Understanding where we want the consumer to end up on their data journey allows us to work backwards and fill in the path to get there.
3. Data Driven Actions
- What follow up questions may be asked and answered?
- How might business decisions change as a result of the analytics?
To build on the decision-making process, another important, often overlooked factor is the action associated with answers to the business questions. Insights without actions are viewed merely as a pile of interesting information that needs to be sifted through, whereas actionable insights contain information that drives change. Understanding what action is taken is essential to the approach of the data story, as it allows you to predict your audience’s next question and then present the answer for them.
4. Industry Standards
- Are there benchmark reports that indicate industry standards for analysis?
- How do the emerging firms or proven leaders in your industry analyze their data?
Although unique corporate cultures drive how companies approach business, there are industry standards that can be leveraged in reporting. To your business this may mean benchmarking against regulatory standards, best in class reporting, or including competitor analysis. For example, if sales are down for the year it would be helpful to know if sales are down for the industry and where your firm falls in the ranking. Comparing against others in the industry can uncover areas of improvement or highlight trends that are affecting the entire industry.
- What data is available to use for analysis and at what granularity?
- At what cadence is it refreshed?
- Is it trusted from the source or is there manual intervention needed to clean, translate, and join?
- Are data volumes expected to grow steadily or exponentially?
- How many sources will be added in the future?
Finally, a story must have a main character – the data! We help clients work through how the main character should be portrayed. If you are writing a short story, an executive summary, or a trilogy, the underlying details should support the plot for that story. This means considering what details/descriptions you offer about your main character. Doing this supports quick refresh of the data and optimal performance of the report. Remember that data is only one of the five factors that goes into this process - the four that come before it are essential to supporting the main character and the rest of the story.
Keeping these five factors in mind when approaching the analysis of your data will help your team tell an impactful data story, facilitate quicker understanding, and accelerate the time to insight. Each organization has a unique company culture naturally yielding a custom approach to these questions. Clarity Insights has worked with industry-leading companies to customize a process that empowers their teams to quickly answer key questions with answers that drive their business. Find out how we can make your business intelligence smarter!