Many of these monsters are culture-based, so they can be overcome through conversations and accountability. That’s good and bad news, since your management and leadership are what will right the ship, but it might take months of conversations and new layers of accountability.

(If you’re wondering what these awful beasts are, please meet The Six Data Sea Monsters.)

Step 1: Start scheduling meetings to discuss data.

Don’t wait for a data-driven culture to evolve on its own; actively create it by working to incorporate it into regular team meetings. Initial meetings can be about how they’re currently using data and how they’d like to use it, with meetings to follow about the tool inventory in Step 3, and all ensuing steps.
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Step 2: Determine which metrics most closely align with your business objectives.

These will most likely be metrics that contribute to bottom-line numbers such as customer acquisition cost (CAC) and lifetime customer value (LCV). It’s crucial to do this before Step 3, so you’ll know what you want and need to measure, independent of whether or not your current tools can measure it.
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Step 3: Get an inventory of all tools, platforms, and systems you’re currently using.

Include all the data-gathering tools you have, even if nobody remembers how to log into them and use them. Each item should have a summary of the metrics it tracks, which of those metrics it’s especially good at tracking, how far back it can gather data (possibly filling gaps in data), and how it gathers and presents reports. The summary should also include the known/unknown status of login credentials, tool usage, and training completion, as well as any subscription/renewal/upgrade information.
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Step 4: Select your systems.

Determine which of the items from the inventory best measure the most critical metrics for your business. If there are any gaps between tools/systems and metrics, consider investing in additional tools. Also, investigate if you’re getting the most out of the tools you have; many tool providers offer additional benefits such as training and customized reporting.
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For the tools that don’t make the cut: If there’s no cost involved in using the tool and its security and functionality are solid, allow it to keep gathering data. This can be useful for double-checking the accuracy of the tools you’ve chosen.

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Step 5: Get all the relevant people trained on all the tools.

This could be the most demanding step, as it will require an investment of time and money, and might seem redundant at times. However, this step is crucial to breaking down silos, maintaining institutional knowledge, getting the best return on your tool investment, and furthering a data-driven culture.
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Step 6: Centralize all relevant metrics into one data stream.

As you and your team have gone through this process, you’ve probably gained much greater insight into how each metric ties into the overall customer journey. You might have re-evaluated your attribution model and extended your data-gathering into post-purchase activity, customer service, renewals and upgrades, and other aspects of the customer lifecycle. Now it’s time to put that data together into one consistent, end-to-end model that clearly depicts the meaning and impact of each metric.
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Now that you’ve got data you can trust, you can begin harnessing it for real insights. Our next post will show you a three-step framework for approaching your clean, trustworthy data.