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Unlock the Power of Actionable Insights

Being data-driven begins with gathering and managing your organization’s data, but the real value comes after you tap into actionable insights.

Jay Matre

Senior Business Architect, MentorMate

Increasingly, many of our clients ask us how they can make their organization data-driven. Yet in searching for the “how,” many companies neglect the “why.” Why do they want to implement data solutions into their business in the first place? I’m here to talk about that “why” and, more specifically, one of the key outcomes that drive value when you successfully harness your data — actionable insights. 

What are Actionable Insights?

Simply put, actionable insights are the result of being a data-driven organization. They are the conclusion of successful data management and analysis that empowers decision-making and planning.

Analytics often uses the concept of an insight funnel to describe how we turn raw data that’s unfriendly to humans into useful and informed decisions based on actionable insights. Insights are the filtered stream flowing from the pooled data and information.

Funnel graph consisting four elements.

How do you get to Actionable Insights?

Generating actionable insights from your data is a question of thorough business intelligence and analysis backed by a holistic understanding of your business and organization’s processes. However, there are two approaches to generating Actionable Insights.

1. Knowing what business question you want to resolve and looking for the answer by analyzing and managing data 

Ideally, you first identify the question you want to answer and work backward from there. Create a measure of success, a dot on the horizon that marks where you want to go and what you want to achieve, then look for the answer in the conclusion of your specific data and information analysis. 

2. Exploring your data to target a valuable question you want to find an answer to 

When there isn’t a specific business question to answer, the process is more exploratory. Starting with the data engineering and management work to generate a clean and coherent data set from the source systems, data experts will then move into activities to explore the data, build models, and evaluate them to test for insights. 

How do you design value into your analytics?

It’s important to find a balance between experimentation and justification when making choices on data investments.  

Balancing scale with experimentation on the left and justification on the right.
Justification

On the justification side of the scale, we have data experiments that always start with a well-vetted business case. That scenario is good for reducing the risk of wasted effort, but it can also kill good ideas that aren’t well-defined. 

Experimentation

On the experimental side of the scale, you may combine and analyze what seem like unconnected datasets. It’s possible to make leaps in understanding and correlation. Still, it can all result in building pools of information with no useful outlet for the insights to flow.

Balance

One way I’ve seen value built up over time is to start the data journey with justified “quick wins,” where it’s easy to measure and understand business value. They help prove your investments and give everyone (stakeholders, business users, data team) good examples that spark creativity.

How Do You Measure Value?

Ultimately, you want to be able to observe how insights and the recommendations they enable impact the business. Understand what “winning” looks like and try to measure it. This is easy in situations like A/B testing an e-commerce website. When the outcomes are ambiguous or hard to measure, it becomes more difficult to identify and set up feedback loops.

Feedback loops are crucial for evaluating the efficacy of the available data and information. I’ve seen many organizations come up with assumptions and then make investments without adding the necessary metrics to understand the effects. As one of my first managers once said: “If it’s important enough to improve, it’s important enough to measure.” Organizations need to build the measurement and associated data gathering into their digital transformation. 

Final Thoughts

Becoming a data-driven organization starts with gathering and managing your data, but the real value comes with being able to put it into action and harness its potential. A report by Forrester shows that 74% of companies want to achieve the goal of being data-driven. Yet, only 29% have managed to put their analytics to work toward achieving the coveted goal. 

Actionable Insights are far more than just a buzzword. They are the key to unlocking the full business potential of companies, regardless of the industry. Understanding the concept and partnering with the right data management and analytics team is all it takes to obtain that key. 

Tags
  • Data & Analytics
  • Digital Transformation
  • Business Intelligence & Analysis
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