We are living in the era of Big Data. There is an ocean of information waiting at our fingertips.
A crucial part of running a business is the ability to wade into that ocean of data and pull out what is relevant and impactful to inform business decisions. Finding insights can be challenging but there is a learnable art to uncovering them.
An insight is an interpretation of data that uses business knowledge to make an observation or argument. Good insights are not just sets of data, nor are they unsupported assertions or facts with a spin added to them. We at The Spur Group have a framework for identifying insights
At The Spur Group we have developed a framework for uncovering insights. In this blog we will guide you through our process by explaining how to understand as much as possible, figure out what matters, and explain why the data matters.
This blog is the conclusion of a three-part series on data and dashboards. In part one of this series, we discussed how to design a dashboard, part two focused on evaluating your dashboard with three simple questions, and this blog will cover translating dashboard data into useful insights.
Part 1: How to design a dashboard
Part 2: How to evaluate the effectiveness of your dashboard through key questions
Part 3: This blog focuses on how to translate the dashboard data into insights
1. Understand as much as possible
Businesses are complex and the amount of information at your disposal can seem unwieldy at times. While it may be impossible to know and understand all aspects of your business, we have identified three steps to help manage this section of our framework.
- Collect facts, data, and anecdotal evidence. Figure out the things that you personally own and that affect your business. This list of responsibilities will guide the information that might be helpful for you to collect. If you’re in sales, you’ll want pipeline data, win/loss analysis, actual sales data, and likely some connections to the sales or channel teams getting credit. If you’re in marketing you’ll be more interested in the campaign data, but you might also list out the pipeline and sales data, so you can do some correlation. Unfortunately, just because you want the data doesn’t mean it’s available or reliable. Once you have your list of potentially helpful data points, work with appropriate teams in your organization to determine what data you can get access to programmatically, and which data you may need to use more qualitative approaches for.
- Determine what drove the identified data points. Once you have the data, start doing some basic classification on the forces that drove the outcome. There are active and passive outcomes that you will have to consider. If you think — “the outcome was a result of a business action taken” — then that is an active outcome that was pursued and intentional. On the other hand, if you think — “the outcome was a result of an outside force” - that's passive. For example, a campaign a marketer designed and ran resulting in higher lead generation would be an active outcome, while benefiting from a related campaign run by another company would be a passive one. By determining the driving force of a result, you can select the appropriate data representations to include in your reports. The goal is to show causality. It instills confidence in your audience when you can demonstrate that you understand the causes and effect in the bigger picture.
- Identify blind spots and distinguish what’s certain from what’s speculative. As we’ve said, there may be information that you wish you had that you don’t. Carefully consider this and determine how impactful that gap may be. In many cases, you can still make strong conclusions based on other relevant information, but it is still important that you’re able to speak to these blind spots. You’ll need to either defend why you don’t have the data or explain how you’ve approximated what it might be. This will be important as you document your final insights. You might say, “we don’t have visibility into this information but from what I see, it appears that <this> happens”. Speculation is okay as long as you're very clear about it when you present your data analysis.
2. Decide what matters
Get down to what your team or business really cares about. Different audiences in an organization have varying perspectives and types of information they need and don’t need, so tailoring your insights to them is crucial.
- Know your audience. We originally brought up knowing your audience in the first blog of this series, and we bring it up again because of how important it is. What do the people you are presenting the information to care about? What is their role, level, or department in your business? Is part of your audience a corporate vice president known to be interested in the number of customer adds? Then include customer adds in your report. Insights can only be delivered if they pertain to your audience and help answer their questions and guide their actions. Any other information is background noise to them and may lead to more confusion than insight.
- Think about business priorities. Focus on the most important items. Depending on the audience; budget, scorecard metrics, items needing executive decisions, best practices, risks, and issues could all be priorities. While these might not constitute a complete list of items that an executive or business teams might use, if you focus on these examples they will help you to zero in on what data matters.
- Anchor to contextual metrics (4 T’s). Trends, targets, triggers, and totals are another group of concepts we would like to reinforce from the 3 steps to building dashboards that get used blog. Tether your insights to the data. Keep your connections focused by articulating the specific pattern that is relevant:
- Totals are aggregate numbers that summarize a point (often related to targets). While great on a dashboard, unless you relate it to one of the other T’s, referencing a total alone may not prove overly insightful.
- Trends are patterns over time. They may indicate something you need to pay attention to or may support the argument that it’s no big deal. If the pattern is towards or away from the desired goal it should be examined.
- Triggers are thresholds at which point something happens. Insights around this may include the impact that was observed when the triggered action happened, or that you are approaching a designated trigger point.
- Targets are the point by which end success may be measured. It’s not just whether you’re going to hit the target that matters. The insights presented should be about how close to the target you are in relation to the time needed to attain it.
3. Explain why it matters
Providing important information is only half the battle in delivering insight; making it relevant is the other half. Insights can only be gained if the right people receive the right amount of information to answer their questions.
- Consider perspective. Try to use the format of “know, feel, do” when thinking about your audience. First, determine what you want your audience to know when you provide them the data. Next, think about how they should feel about the insight (optimistic, concerned, anxious, etc.). Finally, consider how to tailor a message to the data with what you want them to go and do.
- Start with a framework. Deliver your information to your audience in a logically ordered framework. A good framework to start with is one that has an assessment (data that shows what happened), causality (links between data points showing why that thing happened), and action to take (data that leads to a ‘now what?’ conclusion).
- Keep it concise. After you put all your information together, edit it down to the appropriate level for your audience. Provide only the necessary context so that the audience can readily consume and understand the insights you deliver. This may be about trimming information, or it may be about ordering it appropriately. For executives, this often means a series of high level data point summaries, followed by a few deep dives into the findings.
Providing insights that add value to business decision making is much more than collecting and distributing information.
It’s about doing diligent research and interpreting data to decide what matters.
It’s also about the way you present the data to create an informed opinion explaining why things are the way they are and to provide recommended actions to take. Using our framework, you can manage the flood of information constantly thrown your way, uncover key insights, and deliver them to your audience with full confidence that you and your team will make the right business decisions thanks to your efforts.
Check out the other blogs in the series: