Despite more data being available than ever before, many organizations still find themselves struggling to turn it into action. According to Forrester, nearly three-fourths (74 percent) of firms say they want to be data driven, yet only around one-fourth (29 percent) say they’re “good at connecting analytics to action.”
This speaks to the challenge of mining potentially useful insights from stored data as well as figuring out how to evaluate them for quality and using them to fuel decision-making.
So, what makes a data insight actionable? Read on to learn more about closing the gap between having data and acting on it in a way that drives desired business outcomes.
The Distinction Between Data, Information & Insights
It’s useful to first distinguish between information, data and data insights.
As one expert writes for Forbes, it’s helpful to envision a pyramid with data as the foundation, information in the middle and insights as the top peak.
Here’s how he defines each:
While the abundance of data available today is generally a competitive advantage, one possible pitfall is overwhelming employees with information — like metrics about every aspect of performance under the sun. This is why it’s so important to ensure data analytics users can analyze information to reach actionable insights.
Here’s an example of what this looks like in action.
Data: A log of daily products sold, product price and employee ID.
Information: A retail associate creates a chart tracking her daily sales revenue.
Insight: The associate needs to sell $300 worth of products by closing time to stay on trajectory to earn a bonus commission.
Action: The associate prioritizes cross-selling complementary products to shoppers, helping her generate enough extra revenue to meet the daily performance goal.
3 Hallmarks of an Actionable Insight
1. Aligns with Business Goals & Processes
The more closely an insight ties in with specific business objectives, the more likely it is to be useful in driving clear action. Some insights, while undoubtedly interesting, are distant from business goals and processes. This is why it behooves businesses to track lots of metrics as well as establish clear key performance indicators (KPIs) that can tell the “real” story at a glance, i.e. the one most closely aligned with goals and processes.
2. Decision Maker Can Gain Context
Context helps decision makers understand what the numbers are telling them. A sales associate learning they’ve made 25 sales in a day means little without context. If a usual day of sales is five, then it’s likely worth figuring out what helped them multiply their average — and replicate it in the future. Conversely, if a usual day nets 100 sales, it’s worth looking into why the associate is having such a low-volume day.
Interactive data visualizations help provide vital context to ad hoc analyses, allowing analytics users to click around and fully flesh out the meaning and implications of insights before acting
3. Single Version of the Truth
To act on an insight, decision makers must trust its accuracy. They must also feel confident they’re getting the company’s only version of the truth. It’s counterproductive to have different decision makers acting upon conflicting insights from disparate sources.
This is why advanced data analytics platforms enable users to trace data lineage back to the source, and ensure there’s only one consistent version of the truth floating around out there.
Data insights are actionable when they’re relevant to business goals, enriched with context and trustworthy.
