In today’s business world, we’re drowning in data. We track nearly everything, constantly analyzing the numbers. Yet, the sheer volume of data can be so overwhelming that it often leads to a shortage of actionable insights.

All that data is worthless—or worse—if we don’t produce thoughtful analysis and carefully craft communication of our findings in ways that enable decision-makers to react to the data rather than try to analyze it themselves.

To navigate the data deluge and extract meaningful insights, I’ve found a framework that consistently produces effective analysis. It’s all about achieving F.A.M.E., baby!

We need to focus on four key attributes: Focused, Actionable, Manageable, and Enlightening.

Focused

A focused finding is fact-based, clear, and easily summarized in a succinct format similar to a newspaper headline. It’s OK to augment the main headline with a sub-headline that adds further clarification, but anything more complicated is not nearly focused enough to be an effective finding.

Example: “New Brand X running shoes converting 23% lower than prior model.”

Sub-headline: “Contributing factors include an unclear value proposition, irrelevant landing pages, and a high number of first-time visitors.”

This headline provides a clear, specific insight, allowing decision-makers to grasp the issue quickly. Supporting data should directly relate to this headline, excluding any irrelevant information. Remove the clutter so the main points are as clear as possible.

Actionable

Effective findings must be specific and narrow enough that decision-makers can quickly develop a plan of action. For example, the finding "Brand X running shoes are converting 23% lower than the prior model" should be paired with actionable recommendations like "Modify landing pages to include more relevant messaging about performance innovations, testimonials, and styled images."

Less appropriate would be a vague finding like “Customers from Google search terms are viewing more pages than those from email campaigns” accompanied by an equally vague recommendation to “Consider ways to reduce pages clicked by Google search campaign visitors.” Is viewing more pages good or bad? Why? The recommendation insinuates it’s bad, but it’s not clear why. What’s the benefit of taking action in quantifiable terms?

Truly actionable analysis doesn’t burden decision-makers with connecting the data to executable conclusions themselves. The thought put into the analysis should make the diagnosis of problems clear so that decision-makers can get to work on determining necessary solutions.

Manageable

The number of findings in any set of analyses should be contained enough that the analyst and anyone in the audience can recite the findings and recommendations (but not all the supporting details) in 30 seconds. Sometimes, less is more. This constraint helps ease the subsequent communication that will be necessary to react to the findings and plan and execute a response. Conversely, information overload obscures key messages and makes it difficult for teams to coalesce around key issues.

Enlightening

Last, but most certainly not least, effective findings are enlightening. Effective analyses should present—and support with clear, credible data—a view of the business that is not widely held. They should, at the very least, elicit a “hmmm…” from the audience and ideally a “whoa!” They should excite decision-makers and spur them to action.

The F.A.M.E. attributes are not always easy to achieve. They require a lot of hard thought, but the value of clear, data-supported insight to an organization is immense.

The most effective analysts I’ve seen achieve FAME on a regular basis. They have a thorough understanding of the business’ objectives, and they develop their insights to help decision makers truly understand what’s working and what’s not working. And then they lay out clear opportunities for improvement. That’s data-driven business management at its best.