As any good procrastinator knows, an urgent deadline is an excellent motivator. The problem is, fire drills distract people from real problems—and for companies that embed analytics, dashboards and reports tend to fall into the “real problems” category.
Why do application teams find themselves in emergency analytics situations? It’s not because they’re all procrastinators. It’s because they are working under the assumption that dashboards and reports will always be “nice-to-have” features.
Without a direct consequence—an unhappy customer, plummeting revenue, a spike in customer churn—embedded analytics are left to languish until something demands change. But by then, it’s sometimes too late.
Application teams that understand the risks are more likely to prioritize analytics now instead of putting updates off to the next release. Here are the top three risks of analytics emergencies:
The Quick Fix
Companies scrambling to fix their analytics often invest time and money in a Band-Aid tool, such as bolt-on analytics that can’t be customized or scaled. This might relieve short-term problems, but in the long term, you’ll be trying to maintain a bad solution—and you’ll never accomplish what you wanted to do in the first place.
The Rip-and-Replace Cycle
Anyone who’s had to rip and replace something in their application knows how painful this decision can be. Companies incur technical debt that may never go away, or they have to go back to the beginning and face a much longer cycle to successfully add a new feature. A single rushed decision can impact your organization for years.
The Late Comer
The longer you put off modernizing your embedded analytics, the more chances your competition has to swoop in. Did you know that 68 percent of commercial applications charge more for their product when they embed analytics? Out of the companies that don’t charge more, nearly half say their hands are tied because their competition already has a stronghold. At this point, they’re beyond gaining an edge—they’re desperately trying to keep up or catch up.
So, how do you avoid ending up in one of these emergency situations? Look out for early indicators of trouble—such as declining average sales price or increased customer churn. And don’t assume you’ll have plenty of time to address it in one of your next release cycles. Analytics failure is not a slow decline: It’s a cliff. If you don’t act early, you risk falling straight off it.
Learn more in our ebook: 5 Early Indicators Your Embedded Analytics Will Fail >