Buying BI

What to Do When Your Analytics Go Bad

By Michelle Gardner
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Once you’ve realized your analytics are outdated, starting from scratch can seem like a daunting prospect. Where do you start? Do you simply replicate your current dashboards and reports in a new tool? Augment your existing tool? Or replace your analytics solution altogether?

>> Related: The Definitive Guide to Embedded Analytics <<

Each scenario comes with its own challenges and best practices. But determining where your company sits will go a long way in helping you to navigate your BI “breakup.” Here’s how to choose a course of action when your analytics go bad:


Companies in a Replicate Scenario are usually predicting an issue in the future or experiencing the first pangs of a larger, long-term problem. This scenario presents the smoothest transition for your end users. If you’re replicating your analytics one-to-one from an old to a new tool, then your rollout can look the same (presentation wise) as the original solution.

Replicating means you can add new capabilities or make changes to the interface over time. This is great for end users and customers because they won’t have the rug ripped out from under them. As far as they’re concerned, the update may have some minor changes to analytics, but it mostly looks and feels the same as before.

To determine if you’re in a Replicate Scenario, assess your existing reports to see what’s already working and decide if there’s anything you have to change. The strongest indicator is that it will take several questions to get to a strong user objective. You’ll inevitably face some areas of dissatisfaction, but overall user satisfaction should be relatively high for your current solution.


In a Replace Scenario, you’re likely feeling the pain of an urgent overhaul of your application’s embedded analytics. Whether your end users are clamoring for new capabilities, your security has become too much of a pain to manage, or the cost of your old tool has spiraled out of control, it’s time to make a change—and fast.

This scenario is more common than replicating analytics, but it will also be more jarring for your end users. A Replace Scenario demands a careful balance between changing too much too fast, and not changing enough to please your unhappy customers (whether they are paying customers or internal teams). Similar to the Replicate Scenario, you want to avoid ripping the rug out from your end users all at once.

Note that the Replace Scenario and the Replicate Scenario aren’t mutually exclusive. You may have a handful of mission-critical or beloved reports that you have no choice but to replicate. Never build an analytics solution without your most popular or critical features. At the same time, you’ll inevitably have new projects you want to integrate into the new solution.

The best tactic in this case is to take a phased approach. Start by replicating everything your users absolutely need from the old solution, and replace anything critical that’s no longer working.


Companies in an Augment Scenario realize that one analytics tool may not solve all their needs. Instead, they’ve decided to use multiple BI solutions—usually two or three—for different end-user groups with competing needs.

The Augment Scenario is not recommended for every organization, but it may be a good path for some specific use cases. For example: You have different groups of users with totally different needs. Perhaps your marketing team is happy to export their data into a standalone data discovery and visualization tool, but your sales team may need robust reporting capabilities embedded in their CRM.

Modern analytics platforms will support every use case, so many companies in this scenario may still prefer to choose one tool to meet both needs. But if not, you may decide to use two different analytics tools that can co-exist.

If your old solution offers unique capabilities you aren’t willing to give up (and are not offered in your new BI tool), it may be cost-effective enough to maintain both solutions. This gives you the functionality and scalability you need without upsetting your users.

For further detail on upgrading your analytics, read our ebook: How to Break Up With Your BI Solution.


Originally published January 4, 2018

About the Author

Michelle Gardner is the Content Marketing Manager at Logi Analytics. She has over a decade of experience writing and editing content, with a specialty in software and technology.