What are actionable insights and are they really in-sight?

Luka Škorić
Feb 24, 2019 · 3 min read
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Does the term “actionable insights” feel like a business buzzword to you? It does to me. Most of the time, only big data and data science nerds really understand what it means and the power it illustrates. But what it represents is crucial to the future of your business.

Actionable insights have two main characteristics:

1. They are borne from the partnership between conscientious reporting and focused analysis.

2. They drive action which leads to results.

A connection between reporting and analysis

As we all know reporting delivers results. It shows the „what“, such as data changes. Analysis delivers the answers to the „whys“, or the cause of the said change. Actionable insights are found when reports trigger questions and analysis answers them. The analysis also requires context. Reporting can be done in a closed environment, but without any real information on what the reported data means, reporting is useless. Analysis broadens the picture and gives the meaning of the report, where actionable insights are born from.

Not everything is actionable

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 insights and choose to ignore them. Don’t immediately get your hopes up if you see a change in the customers’ behavior through your data. For instance, if your customer is using a running app (like the Nike app) and he usually clocks about 2–5 thousand footsteps a day. One day, let’s say Saturday you see a change in the behavior, he made 20000 steps that day. Don’t be reckless and jump into conclusions, first process and analyze the data. It could be a short-lived aberration, maybe the user just went on a hike with his family. What I’m trying to say is don’t act on that data as if you think there is a change in your customer behavior, wait a bit, follow it closely, then when you have more data decide if the behavior was actionable or not.

Key attributes of actionable insights

1. Alignment

When the insight is closely tied to your key business goals and strategic initiatives, it’s more likely to drive action. Insights based on key performance indicators (KPIs) and other key metrics inherently cause a sense of urgency that other data won’t.

2. Context

It is hard to move forward on an insight if you are lacking ample background to appreciate why it’s important or unique. You need a benchmark or comparison to give your data the proper context. Without accompanying context, an insight can end up raising more questions than action.

3. Relevance

A single insight can be both a strong signal for one person and just more noise for another. 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 will not receive the attention they deserve.

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. If an insight doesn’t adequately help to explain why something occurred, it’s not yet actionable. As I said earlier don’t act on it until you’re sure it’s actionable.

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. We become numb to certain insights if we feel as though they reinforce rather than challenge or evolve our current knowledge and beliefs.

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. The right data visualizations and messaging can help explain insights so they are more easily understood and correctly interpreted. However, poor communication can cause the signal to be lost in the noise.

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