DATA ANALYTICS

Stop Chasing Insights. Start Generating Outcomes.

Max Seiden

Five Year Software Engineer at Sigma

Browse the website of any analytics or BI tool and you’re bound to find claims that it will “dredge up insights from the depths of your data lake.”

This is because analytics companies are obsessed with helping you uncover insights. But what exactly are insights and why does everyone want you to have them?

Insights are generally defined as the deep understanding an individual or organization gains after analyzing data. This is vague enough to create an air of mystery around them. It’s as if collecting enough insights together in one place will uncover some lost secret or hidden truth. It’s no wonder then that people tell you your business needs them. Who wouldn’t want to amass a wealth of understanding about their data?

In reality the allure of gathering insights doesn’t always deliver on its promise. Reading Moneyball and collecting the same data isn’t enough to build a winning franchise. Insights alone are not enough.

Insights ≠ Outcomes

Somewhere along the way, the value of insights got blown way out of proportion. Data and BI teams were given the mandate to manufacture insights, as if each is a discrete artifact of equal value that a company could pile up for later use. As a result, report factories started filling with analysts cranking out all kinds of dashboards, visualizations, and ad-hoc reports solely to surface insights.

This misses the point, as generating insights is not the same as generating outcomes. It doesn’t matter how many artifacts are created. Unless the end result of your analyses are clear decisions that ultimately lead to measurable business outcomes, you’re not moving the needle the way you think you are.

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Report Factory Hell

Everyone Is Responsible for Business Outcomes

For many years, the work of data and BI teams was seen as isolated from the rest of the business. Once a report was sent off to the C-suite, the baton was passed and their work was done. But the truth is that anyone performing an analysis is, at some level, responsible for the business decisions it supports. Furthermore, when an analysis is delivered in a static way, (i.e. a report or a dashboard) there’s little opportunity to dig deeper.

The person tasked with making decisions based on a static report can only use what they’re given. If they cannot validate the analysis, don’t have time to ask its author for more details, or simply don’t trust its findings, they may end up making business decisions that at best amount to the flip of a coin.


Just ask JP Morgan. In 2012, an Excel copy-paste error cost the financial giant over $6 billion dollars in trading losses. When catastrophes like that happen, it becomes obvious to everyone that analysts don’t exist in a bubble that’s separate from the business. Their impact is much bigger than anyone thinks it is.

Retooling the Report Factory

Instead of measuring their impact in terms of the number of reports generated or ad-hoc requests closed, data and BI teams should aim for making it as easy as possible for business domain experts to further investigate, independently solve problems as they arise, and make sound data-driven decisions. In other words, it’s not about the number of insights — it’s about the quality, flexibility, and velocity of the analysis.

The role of data and BI teams is changing. Rather than spending time building reports and dashboards they’ll never consume, they’re building data infrastructure and deploying tools and processes that enable their colleagues to become self-sufficient. Teach a person to fish, as the saying goes, and they’ll significantly outperform their quarterly earnings expectations.

Ultimately, companies are realizing that data analysis is less about mechanically generating insights, and more about how these insights can help steer the organization towards success. A modern data practice enables domain experts to better understand the impact of their efforts, accurately measure their teams’ performance against KPIs, and course correct in real-time.

The Role Insights Play in Decision Making

Insights are just a part of the iterative decision making process. The reality is that insights are very small signals in the noise, which can help alert us to where we should direct our powerful human curiosity. They provide glimpses into the operations of a business. They’re narrow, nuanced, and ever changing. What we really need is to see the forest through the trees.

So while an insight can represent a statistical fact, anomalie, or prediction, great decision making often marries that information with human context. There will always be human factors and dimensions to business problems that are difficult to quantify.

Businesses typically focus on conscious knowledge: the things we know we know. These are easy to measure, catalog, and distribute. But we also have unconscious knowledge: tacit wisdom that shapes our decision making.

As we conduct an analysis, personal, institutional, and contextual knowledge come together to influence our decisions. Insights are the conscious knowledge that get the conversation started. Human context is the unconscious knowledge that drives great outcomes.

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A Collaborative, Outcomes-Focused Future

The days of static reports and limited dashboards are numbered. A better future lies in bringing decision makers into the room where the analysis happens.

We envision a world where people are given a starting point from which they can validate, investigate, and iterate on a colleague’s analysis. They aren’t forced to put blind trust in what has been handed to them. They can ask questions, start a conversation, and collaborate to discover the best course of action. This sets everyone up for faster decisions, tighter feedback loops, and better outcomes.

It’s a collaborative approach where all parties are getting more and more involved in the outcome and decision making process. In this world, sound, consistent, data-driven decision-making is operationalized across the entire organization. All of this requires a flexible, shared workspace — a tool that assumes the questions will change, and that people want and need to dig into the data themselves.

At Sigma, we’re focused on building a powerful tool that allows everyone to iterate on analyses, create visualizations, tell data stories, and find answers to critical questions — all within a single collaborative canvas.

Chasing insights doesn’t automatically lead to great outcomes. Thoughtful, researched decisions lead to great outcomes. And one of the best decisions you can make for your organization is to empower everyone in it to collaborate through data using Sigma.

Ready to visualize your data for actionable insights?