10 Rules for Creating Insightful Metrics and Actionable Reporting

We‘ve all been there – sitting in a conference room, staring at a colorful but confusing chart splashed across the screen, trying to decipher what the numbers actually mean for the business. The head of sales is arguing that the dip in revenue is due to not enough feet on the street, while the head of marketing is sure her latest campaign is to blame. The meeting ends with a whole lot of finger-pointing but very few insights on what‘s really going on or what to do about it.

Sound familiar? If so, your company likely has a metric and reporting problem. But don‘t worry, you‘re not alone. According to research by Domo, 74% of business leaders say their organization is not effectively using data and analytics to drive business decisions.

The issue is that most companies focus their reporting efforts on simply presenting the numbers – how many widgets were sold, how many leads were generated, what the customer churn rate was. But while this type of "what happened" reporting has its place, it does little to uncover the "why" behind the numbers or provide guidance on how to act on them.

To unlock true insights that drive meaningful action, you need to go deeper with your metrics and reporting. Here are 10 rules to follow to do just that:

1. Focus on ratios and percentages, not just absolute numbers

Absolute numbers, like total sales or leads, provide little context on their own. They need to be benchmarked against targets, prior performance, or industry standards to be meaningful.

Let‘s say your sales in Q4 were $10M. Is that good or bad? It‘s impossible to say without more context. But if you said sales were 20% below target, that tells a clearer story that points to a problem that needs investigating.

Percentages and ratios are even more powerful. Instead of total sales, look at sales growth percentage vs last year. Instead of total leads, calculate marketing qualified lead (MQL) to sales qualified lead (SQL) conversion ratio. Metrics like these give much richer insight into where trouble spots and opportunities lie.

2. Segment, segment, segment

Averages lie. Or at least they obscure the real story. Overall company metrics typically aren‘t granular enough to uncover aha moments or eureka insights.

That‘s why segmentation is critical. Slice and dice your data across every relevant dimension – region, product line, customer segment, marketing channel, etc. Identify your best (and worst) performing segments and drill into them further to figure out what makes them tick.

For example, if website traffic conversion is dropping, segmenting by traffic source may reveal that paid search visitors are bouncing at a much higher rate than before. Now you have a specific problem to solve vs a vague one.

3. Visualize the data

A picture is worth a thousand words, especially when it comes to data. Visuals like charts and graphs make it much easier to spot trends, outliers and relationships between data points vs staring at a grid of numbers.

But visualizations need to be designed with purpose. Strive for simplicity and clarity above fancy animations and stylistic flourishes. Always include clear titles, labels and legends. Use color intentionally to draw the eye to what matters most.

Interactive visualizations with drill-down capabilities are even better. They allow end users to explore data on their own, following their natural curiosity to interesting nuggets they may have never thought to look for in a static chart. Domo found companies using interactive dashboards were 24% more likely to discover previously unknown insights that drove new actions.

4. Connect metrics to actions

A metric is only as valuable as the decisions and actions it influences. Too often, metrics live in a vacuum, disconnected from the operational levers a business can pull.

Before including any metric on a dashboard or report, ask "so what?" What will the end user do differently if this metric goes up or down? How does it connect to a fundamental business action? If you don‘t have good answers, the metric may not be worth tracking.

For example, overall customer satisfaction score is a common metric, but not a very actionable one. Breaking it down by key touchpoints in the customer journey (sales, onboarding, support, etc) provides more granular insights teams can act on to improve specific parts of the experience.

5. Make reporting a team sport

Insight generation shouldn‘t be a solo sport or an ivory tower exercise conducted by the analytics team in isolation. The best insights often come from cross-functional collaboration and diverse perspectives.

Establish a regular cadence of bringing together stakeholders from across the business to review metrics, discuss trends, and brainstorm actions. Encourage active participation and questions. Value business context and qualitative observations as much as quantitative analysis.

Also, strive to democratize data access and analytical capabilities as much as possible through self-service tools, training, and support. Empowering teams to explore data on their own is a force multiplier for insight discovery.

6. Automate what you can, but don‘t overdo it

With today‘s business intelligence and analytics tools, it‘s easier than ever to automate the production and distribution of reports and dashboards. This is a huge time saver and helps ensure stakeholders always have access to current data.

However, automation is not a panacea. Applying human judgement is still important for insight generation. Automated alerts can spot major anomalies, but they can‘t tell you why an anomaly occurred or what to do about it. Augment automation with regular human analysis and insights.

Be judicious in what you automate. Dashboards that provide an overall pulse on the business are good candidates. But one-off analytical projects are usually better done manually. Just because you can automate something doesn‘t mean you should.

7. Standardize KPIs, but allow for customization

For company-wide alignment, it‘s important to have a core set of standardized metrics or KPIs that everyone rallies around and consistently interprets. These create a common language for performance discussions and make cross-functional collaboration easier.

However, different teams and business units inevitably have unique needs too. A one-size-fits-all approach to metrics doesn‘t work. Allow room for teams to track supplemental metrics specific to their function and goals. Just make sure they connect back to the company‘s overall strategy and KPIs.

8. Design dashboards for specific audiences and goals

There‘s no such thing as the perfect, all-encompassing dashboard. Different end users have different information needs and analytical skills. A dashboard designed for the C-suite to monitor overall company health would be very different than one designed to help the demand generation team optimize paid search tactics.

When creating dashboards, always keep the end user and use case in mind. What questions are they looking to answer? What actions do they need to take? Design the views (high-level vs detailed), KPIs, comparisons, and drill-down paths accordingly. A dashboard is only effective if it drives the right actions for its intended audience.

9. Prioritize data integrity

Insightful analysis is only possible with accurate, consistent, and up-to-date data. Integrated, properly structured data is the foundation of everything in reporting and business intelligence.

Invest the time upfront to ensure data is being captured correctly at the source, aggregated and normalized properly, and flowing seamlessly between systems. The end result will be more reliable and timely insights.

Establishing data governance processes and clear ownership is also key. Everyone needs to be working from the same "single source of truth" when it comes to data and metrics. Multiple, conflicting versions of the truth only create confusion and erode trust in the data.

10. Iterate and evolve

Your business doesn‘t stand still and neither should your reporting. As strategies, priorities and external factors change, so should what you measure and how.

Regularly review your KPIs and dashboards with a critical eye. Do they still align with your current goals? Do they provide a complete picture of performance? What new questions do you need to answer? Don‘t be afraid to retire metrics that have lost their relevance and experiment with new ones.

The same goes for the visualizations, delivery mechanisms, and cadence of your reporting. Just because you‘ve always done things a certain way doesn‘t mean it‘s still the best way. Solicit feedback from end users and adapt as needed.

Companies That Get It Right

Need some inspiration? Here are a few examples of companies that excel at insightful and actionable reporting:

• GoDaddy: The web hosting company has built a robust self-service analytics platform that puts customizable dashboards in the hands of every employee. Teams like customer support and marketing can track core KPIs, dig into drivers, and take data-driven actions in real-time. This democratized approach has led to innovations like proactive customer interventions and highly targeted cross-sell offers.

• Zendesk: The customer service platform provider has taken data visualization to the next level with dashboards that go way beyond basic charts and graphs. In their executive briefing center, a 12-foot video wall displays a dynamic visual of their real-time data pipeline in action, from raw data streams to insight generation. The ability to see the flow of data in such a visceral way has sparked new ideas for data capture and analysis across the company.

• Warby Parker: The eyewear retailer has made data a core part of its culture from day one. Employees across every function are encouraged to be "citizen data scientists" and are given the tools and resources to analyze data on their own. Cross-functional teams meet weekly to review metrics and discuss insights. This collaborative approach has led to breakthroughs like a new inventory forecasting model that cut stockouts by 25%.

Turning Insight Into Action

Inspired to take your own reporting to the next level? Here‘s a simple process you can follow:

1. Assess the current state: Review your existing KPIs and dashboards with a critical eye. Do they still align with current priorities? Do they provide real insight into the why behind the data? Survey end users on what‘s working and what‘s not.

2. Define critical metrics: Based on your current strategies and goals, outline the key questions you need to answer. What metrics would provide those answers? Prioritize those that are most relevant and actionable over vanity metrics.

3. Establish your single source of truth: Define how metrics should be calculated for consistency. Audit your data capture and integration processes to ensure data integrity. Assign clear ownership for each data source and metric.

4. Design insight-driven dashboards: Create focused dashboard views tailored to different audiences and analytical needs. Make insight generation the primary goal, not just data presentation. Use clear, intentional data visualizations. Build in interactivity and drill-down capabilities where possible.

5. Enable broad access: Invest in self-service BI tools to democratize data exploration. Offer training and support to help build analytical skills across the org. Make insight discovery a team sport through cross-functional collaboration.

6. Take action and iterate: Don‘t just generate insights, act on them. Build processes to turn insight into timely business decisions and measurable actions. Close the loop by tracking the results and iterating on the process.

The Future of Reporting

The bar for reporting and business intelligence is only getting higher. As data becomes more abundant and technologies more sophisticated, opportunities to become an insight-driven org will only grow. Here are some of the key trends shaping the future of the space:

• AI-powered analytics: Artificial intelligence will increasingly be used to automate insight discovery and surface unknown unknowns in data. Natural language query and generation will make interfaces more intuitive. Augmented analytics will become the norm.

• Real-time, all the time: With the rise of streaming data and IoT, stakeholders will demand access to insights in near real-time. Latent, backward-looking reporting simply won‘t cut it anymore. Continuous intelligence will be the new standard.

• Predictive and prescriptive: Analysis will become more forward-looking, with machine learning models that predict future trends and prescribe optimal actions to take. Scenario modeling and simulation will be key to strategic planning.

• Insights everywhere: Insights will be pushed to users in context within the apps and tools they use every day vs having to seek them out in separate BI tools. Embedded analytics and event-driven alerting will become more prevalent.

The future of reporting is bright for organizations ready to embrace it. By following the rules laid out here, they‘ll be well on their way to turning data into insights, and insights into action – no matter what the coming years bring.