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Does it feel like technology stands in the way of getting the information you need?
The numbers are locked up in the wrong place and there aren’t the resources, coordination, or buy-in to wrangle your tech and get it into the right format. Getting the answers your systems were supposed to provide seems too complicated or expensive so you make do without.
The good news is that there’s probably a shortcut when you question your assumptions about what you need and rethink how to get there.
At the core, there are only a few key elements that go into actionable reporting:
- A shared understanding of what the report means to the business
- End numbers that are derived in a consistent manner
- Accessibility for the people who need it
- A plan for putting the new information to use
When you examine each of these steps more closely, you may find that technology is not the limiting factor.
Unpacking the four steps
1. Business Definition
The first step is a shared understanding of what you would like to measure in business terms. This may be very close to—but typically not quite the same— as the technical definition. We recommend using a simple business glossary as a shared source of truth for each term that you define. This can also hold information about subsequent steps.
2. Technical Definition
The business definition is not typically precise enough to know *exactly* how a certain number is calculated. The technical definition is the place to specify details (filters, which values are aggregated and how, etc), and should live next to the business definition in your business glossary. This step is easy to gloss over when your reporting tool provides the final number because the logic is embedded in the report.
Without a centralized place where criteria are defined, it’s easy to end up with inconsistent reports. They may share a business definition but each person building the report defined technical criteria in a slightly different way. In addition to setting up a good foundation for consistent reports in the future, an explicit technical definition should allow a non-technical user to understand how a report is created and generate consistent results—even if the report requires multiple steps to calculate.
3. Accessibility
The next step is to determine how to ensure the numbers get to the right people on a timely basis. Live data feeding a unified dashboard is great, but if you have clearly defined how a number is derived this can be done manually. And if you’re thoughtful about how the data goes in, you can have a flexible dataset that lets us change how you sort, filter, and aggregate the manual numbers.
Here are a few examples based on the reporting tools you might use:
CRM
If most of your reporting originates from your CRM, create a new table to hold the data you’d like to incorporate; you can even name it “External Metrics” to indicate that it has originated from a different system.
For example, to add digital advertising data to an existing marketing dashboard, use the following fields:
-
- Date
- Ad Spend Last 7 Days
- Impressions Last 7 Days
- Clicks Last 7 Days
- Platform [picklist: LinkedIn, Meta, Google, etc]
Every seven days, someone takes a few minutes to create a new record for each system running ads. You then have a history that can be aggregated, filtered, and grouped within your existing system with minimal technical overhead.
Note the decision to use weeks as the finest level of granularity—this is plenty of detail for the dashboard, and limits data entry to a weekly task.
Excel
Excel is a nice example because it’s so ubiquitous and easy to drop numbers into any cell you’d like. This also means that what goes into Excel isn’t always easy to work with if you want to change the timeframe you’re looking at or apply a new filter.
To add depth to reporting compiled in Excel, use the same principle outlined above for adding external numbers to a CRM. Focus on adding more data as new rows to one tab and using calculations on another tab to filter, aggregate, and even visualize what you have.
Business Intelligence Tool
Most BI tools let you upload or connect to spreadsheets, as well as a variety of other data sources with varying levels of complexity.
Power BI has a ‘Scorecard’ feature that can use either data generated by a report or numbers you type in manually; you can start with manual data entry and pivot to automated if/when the report becomes available. Adding updates will create a trend and automatic visualization, and it comes with some nice features like status and conditional coloring.
4. Action
The value of all this work comes when it drives decisions and actions. Be clear on who is responsible for each metric, and ensure there’s a regular cadence for checking in with the right people to review and discuss any changes that need to be made.
The next action might be to gather more information if the number is new or unexpected; you need to better understand the change before making a decision. If you’ve made a recent change based on a hypothesis, new numbers might confirm or deny that you’re on the right track so you modify your approach accordingly.
You might even realize that the next step isn’t clear-cut and raises new questions. This is not a failure! You’ve leapfrogged the technical problem of how to build the report, and can now dig into deeper questions about what the data means and what to do next.
Distilling what’s important
There’s value in unified data and streamlined reporting. But we live in a world of tradeoffs, and can more effectively reach our goals when we’re thoughtful about where to put resources.
If we take a step back and think critically about the information that will be the most helpful to us, we might discover that thoughtful design and a solid process can circumvent a technology roadblock.
