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Turning Data into Actionable Insights

Actionable Insights
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Big data is both a gift and a challenge. Today, businesses have access to mountains of information ripe for interpretation. Without a strategy for data analysis, organizations will spend time and money on a fruitless search for meaning. According to a recent survey of 1200 companies by DNV, only 23% had developed plans for interpreting and applying insights from data.

Missing out on data-centered decision-making will place a business behind the competition. However, amassing the most data does not guarantee success. The goal is to turn relevant data into actionable insights.


From Raw Data to Information

Any kind of measurement can become raw data. The number of widgets your company sold last Tuesday is one piece of data. The number of chairs in your office is another. A spreadsheet full of data points will not lead to actionable insights on its own. Before data can be useful, it must be delivered as information.

Information is processed data. It may take the form of written reports, bar graphs, and other visual representations. Moving toward information also means putting aside data that is not pertinent.

From Information to Insight

Information is easier to interpret than raw numbers, but it has not yet reached the level of insight. The report must be placed in the broader context of the business. Your team may have sold 600 widgets last Tuesday. Is that an unusual number for a Tuesday? Does that number represent a single order by a widget enthusiast or 600 separate orders? Information linked to contextual concerns yields an insight.

What are actionable insights?

Not every insight will be an actionable insight. Sometimes, insights pulled from data will simply confirm that a strategy is on the right track. You had a flash sale on widgets last Tuesday, and the increased sales numbers show that it worked.

Processes like data segmentation might yield actionable insight. Most of last Tuesday’s sales went to people in their 20s. There is an untapped widget market, and your marketing team will now adapt the next campaign accordingly.

Steps to Develop Actionable Insights

Turning raw data into full-fledged data insights is an intentional process. Businesses must work so that data becomes a tool they can use rather than a time-consuming burden.

Start with a Question

You want data collection to help your team make informed decisions. To that end, it best to start with a question or decision that the data will inform. Knowing that you are focused on the sales of a single product will limit the amount of data you need to analyze. Seeking to learn information about your average client will have you poring over a different set of data points. Keeping things specific will help you focus your efforts and lead to meaningful insights.

Look for Trends

An unexpected number may be interesting, but it is less helpful for decision-making than a series of data points. You do not want to base your company’s future on a number that may have come from an unusual day. Trends of growth, decline, or other changes over time need your attention. For the health of your business, it is better to respond to a long-term trend than to react to a single data point.

Examine the Context

If data is the What, context establishes the Why. Once a trend shows up on your radar, it is time to examine the factors causing it. In most cases, your business strategy will not respond to the data but the forces that fuel the trend. Changes in sales data might reflect changes in consumer culture, a potential new client base, or the growth of a competitor. When you know the reason for the trend, you can address it systematically.

Share the Information

Psychologists will point to common issues that come up in data analysis. Analysis performed in a vacuum is subject to confirmation bias. Analysts look at the data only to find that it confirms what they already believe. Limiting your analysis to one or two leaders may also subject the process to cultural, age, or gender bias. A diverse group of people analyzing the data can prevent these effects.

The Data-Centered Organization

New data analytics and reporting tools make data interpretation accessible to all your employees. A business shaped by responding to data trends will make its decisions ahead of competitors. A few practical steps will help you make the transition.

Eliminate Data Silos

Older business models tended to limit data access. Integrated software makes it possible for everyone to see the same data reports, making it easier for the whole organization to work with meaningful information.

Keep It Relevant

Work with your teams to see what data is relevant to their area of expertise. Later on, they may ask for data from other groups to seek out connections. In the beginning, you do not want to overwhelm people with data they will not use.

Share Insights

Encourage people to share their data insights with others. This practice will help people see that you take data seriously and welcome their input. Every team should approach this process by asking, “What are actionable insights?”

Helping You Move from Data to Action

At the Leonard Productivity Intelligence Institute, my goal is to help entrepreneurs and other business leaders move toward their goals. If you need help transforming raw data into informed decisions, I would be happy to work with you. Contact me today for more information.

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