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Category: Data Storytelling

Actionable Insights: Missing Link Between Data And Business Value

November 17, 2020

You’ve no doubt come across the phrase “actionable insights.” Every analytics or business intelligence solution promises to unlock a tidal wave of them for your company — maybe even in “real-time” if you’re lucky. With many companies struggling to make sense of their data and create measurable value with their data investments, the promise of actionable insights sounds wonderful. Forrester reports 74% of firms say they want to be “data-driven,” but only 29% are actually successful at connecting analytics to action. Actionable insights are the missing link for organizations that want to drive business outcomes from their data.

While the promise of actionable insights is alluring, I’m concerned that the phrase is fast becoming an empty buzzword as it is being overly misused by technology marketers. Often what’s really being offered by many analytics solutions is just more data or information — not insights. Data, information, and insights are not synonyms.

There’s actually a hierarchy pyramid with data at the foundation, information in the middle, and insights at the pinnacle. In order to better understand what actionable insights are, it’s important to understand the subtle differences between these key analytics terms.

image representing insights pyramid

Data is the raw and unprocessed facts that are usually in the form of numbers and text. Data can be quantitative (measured) or qualitative (observed). Data primarily exists in computer-friendly formats and mostly lives in databases and spreadsheets. Information is prepared data that has been processed, aggregated, and organized into a more human-friendly format that provides more context. Information is often delivered in the form of data visualizations, reports, and dashboards. Insights are generated by analyzing information and drawing conclusions. Both quality data and information set the stage for the discovery of insights that can then influence decisions and drive change.

As an example, my Fitbit watch gives me all kinds of activity data: steps, BPM (heartbeats per minute), miles, calories, and so on. At this moment, my watch says I’ve taken 7,442 steps today. This single fact is fairly useless, especially without more context. My Fitbit app includes a number of data tables and visualizations (information), such as a weekly steps report where I can see how many steps I completed each day. When I analyze this trended information, I can see my current trajectory is ahead of what I accomplished the past few days and with a little extra effort in the evening, I can reach my daily target (insight: I only need 2,558 more steps in the next five hours).

fitbit data visualization - data - information - insight to action

While we’re happy to obtain as many insights as possible from our data, not all of the takeaways will be actionable. You may not know what to do with some analytics insights and choose to ignore them. For example, you’ll notice on the chart above that I was very active on the previous Friday (18K steps!). Whatever I did on that day, I should probably just replicate the same behavior all the time. Unfortunately, while it’s an interesting data point, it was a short-lived aberration or outlier. I was on spring break vacation with my family, and I can’t spend every day walking around Disneyland — that’s not realistic or actionable for me.

image representing actionable insights pyramid above information and data

Key Attributes of Actionable Insights

key attributes of an actionable insight

Actionable insights sit at the apex of your data pyramid. An insight that drives action is typically more valuable than one that simply answers a question — especially an insight that makes you rethink something and pushes you in a new direction. They’re the highly treasured output of all the work that goes into collecting, preparing, and analyzing your data. Maximizing the actionable insights you receive from your analytics investments is important to your data-driven success. For this reason, I’d like to examine more closely what makes an insight truly actionable. I refuse to surrender the term “actionable insight” to becoming just another hollow, meaningless buzzword. Please consider the following six attributes when examining how actionable your data insights are:

An insight that drives action is typically more valuable than one that simply answers a question—especially an insight that makes you rethink something and pushes you in a new direction.
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1. Alignment

When an insight is closely tied to your key business goals and strategic initiatives, it’s more likely to drive action. If you don’t know how to react to a particular metric when it significantly increases or decreases, you might be looking at an unnecessary vanity metric. Insights based on key performance indicators (KPIs) and other key metrics inherently engender a sense of urgency that other data won’t. It’s easier to interpret and convert strategically-aligned insights into tactical responses because they often relate directly to the levers in your business that you control, influence or are focused on.

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2. Context

It’s hard to move forward on an insight if you’re lacking ample background to appreciate why it’s important or unique. We often need to have a comparison or benchmark to give data proper context. For example, if your company generated 1,400 leads this week, your reaction to this result could change entirely with a dash of context. If you know your marketing team typically generates 1,250 leads each week, you might do nothing. However, if your company just sponsored and exhibited at your industry’s major convention last week, you may be wondering why it didn’t translate into significantly more leads. Without accompanying context, an insight can end up raising more questions than action. Having ample supporting details ensures the insight results in action and not unwarranted skepticism and objections.

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3. Relevance

A single insight can be both a strong signal for one person and just more noise for another. There’s a level of subjectivity when it comes to the relevance of insights. In order to be relevant, an insight needs to be delivered to the right person at the right time in the right setting. If insights aren’t routed to the right decision makers, they won’t receive the attention they deserve. If insights aren’t timely, they might be too stale for stakeholders to act on. If insights are trapped in an analytics tool that managers never access or delivered to devices they use infrequently, the insights may never reach the intended audience.

A single insight can be both a strong signal for one person and just more noise for another.
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4. Specificity

The more specific and complete the insight is, the more likely it can be acted on. Sometimes insights based on KPIs and other high-level metrics can highlight interesting anomalies but lack sufficient detail to drive immediate action. For example, knowing your revenue is up 35% this month may be a cause to celebrate, but party planning might be premature without deeper insights. You might discover a massive fraudulent order messed up your online revenue numbers or a big customer win was based on promised product functionality that won’t exist for the foreseeable future. If an insight doesn’t adequately help to explain why something occurred, it’s not yet actionable. Deeper probing may be required before it’s ready for primetime.

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5. Novelty

With so much competing data and information to digest, novel insights will have an advantage over more familiar insights. The first time your company spots a particular pattern will be more interesting and compelling than the tenth time, especially if you feel you already have a good handle on what’s driving the behavior. Curiosity can drive people to test or verify an unusual or unexpected finding in the hope that it sheds new light on a key subject area. This criterion speaks more to human nature than to how valuable an insight actually is. We become numb to certain insights if we feel as though they reinforce rather than challenge or evolve our current knowledge and beliefs.

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6. Clarity

If people don’t clearly understand an insight, why it’s important, and how it can help them, the insight will be overlooked and forgotten. Communicating analytics insights effectively is important to their adoption and fruition. The right data visualizations and messaging can help explain analytics insights so they are more easily understood and correctly interpreted. However, poor communication can cause the signal to be lost in the noise. A clearly communicated insight creates a strong signal that is hard to miss or ignore, and it prepares a pathway for action to occur.

With these six criteria, you can weigh how “actionable” the insights are that you receive from your analytics and business intelligence tools. Regardless of the source of the insights —humans or machines — the more they line up with these attributes, the more actionable they will be for your business. Strategically-aligned tops random; relevant beats extraneous; novel trumps familiar — you get the idea.

Harvesting more insights from your analytics data can yield tremendous returns for your company. However, as author Richard Bach said, “Any powerful idea is absolutely fascinating and absolutely useless until we choose to use it.” While the increased actionability of an analytics insight doesn’t guarantee its adoption or application, it should motivate more individuals within your company to think more deeply about the data and encourage them to act on a more consistent basis. Make sure your hard-earned analytics insights are as actionable as possible so they’re primed to drive value for your organization.

This article was originally published on Forbes.com.

Brent Dykes
About the Author

Brent Dykes is the Senior Director of Insights and Data Storytelling at Blast Analytics. He is also the author of Effective Data Storytelling: How to Drive Change with Data, Narrative, and Visuals. Brent has more than 15 years of enterprise analytics experience at Omniture, Adobe, and Domo. His passion for data strategy and data storytelling comes from consulting with many industry leaders including Nike, Microsoft, Sony, and Comcast. He is a regular Forbes contributor and has written more than 35 articles on different data-related topics. In 2016, Brent received the Most Influential Industry Contributor Award from the Digital Analytics Association (DAA). He is a popular speaker at conferences such as Strata, Web Summit, Shop.org, Adtech, Pubcon, RISE, Crunch, and Adobe Summit. Brent holds an MBA from Brigham Young University and a BBA in marketing from Simon Fraser University.

Connect with Brent on LinkedIn. Brent Dykes has written on the Web Analytics Blog.

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