It’s official. We’re addicted to data.
This was on vivid display in this weekend’s Super Bowl. I’m not an NFL expert, but after watching the game this weekend I can tell you:
- Tom Brady had gone 9 Super Bowls over 2 decades without scoring a Q1 TD
- Patrick Mahomes had never lost an NFL game by more than 8 points
- At halftime, the Bucs had a 90.5% chance of winning the game
- Mahomes ran 497 yards BEFORE his passes or sacks this Sunday
Sadly, when asked to provide insights with that level of granularity and precision about their business, most revenue leaders struggle. Want to test this? Ask an executive if they have cross-functional alignment on the number of customers, revenue and bookings for your business. Sounds simple enough, but the dissonance may surprise you.
So, why is data management so elusive? It’s not due to a lack of data — quite the opposite, in fact. At a basic level, the systems we use to operate our businesses day-to-day don’t speak the same “data language”. And our attempts to integrate and translate data across systems often make problems worse: One day it’s a list of leads imported from an event that creates duplicates to your recently cleaned CRM, and the next day it’s a broken ERP integration that erases three new order requests, never to be seen again.
As a result of all this mayhem, data workers spend 80–90% of their time managing and preparing cross-functional data and only 10–20% of their time performing analysis. All this inefficiency drains a whopping $3.1 trillion dollars out of the U.S. economy every year. And it can cost your businesses up to 15-25% of total revenue.
At Syncari, we’ve given this mayhem a name: the data chaos monster. And we’ve cracked the code on defeating it.
How to slay the Data Chaos Beast
In Greek mythology, not even Hercules could defeat the Hydra, a three-headed monster, alone. He needed a new, powerful tool—a golden sword from Athena—plus the help of many other capable hands to triumph. Similarly, the data chaos beast is too enormous a task for any one person. You need the right technology and a team rallied around you to win the battle.
Hercules finally slew the beast with flame, so new heads wouldn’t grow back each time. Similarly, it’s not enough to fix bad data where it pops up—you need to go back to the original source and understand how bad data is generated in the first place. You need a strategy, a repeatable process, and people who understand the fix.
Data management automation is that flame. If you can find a way to automate data integration and data management, you’re not just stopping the bleeding with an isolated, one-and-done cleanup project. You’re putting structures in place to actually meaningfully fix the root of the problem—and keep it that way ongoing.
Organizations with strong data quality generate up to 70% more revenue, according to SiriusDecisions. That’s why 73% of B2B sales and marketing decision-makers increased their focus on data quality in 2020.
The Danger of SaaS App Connector Overload
The average company uses 137 different SaaS applications. Since each system relies on its own data structure, terminology, and workflows, companies are left without a reliable source of truth to inform their decision-making.
When executives in different departments can’t agree on basic information, aligning on strategy becomes a truly impossible task.
Meanwhile, ops folks are stretched thin putting out fires, often left with no choice but to apply band-aid fixes. While this is important work to keep operations running, band-aid fixes often prevent breaks that would have forced the team to invest in a sturdier long-term fix.
To understand more of the impact of SaaS connector overload, read our previous eBook, The Catastrophic Cost of Bad Data: an Irrefutable Case For Multidirectional Sync.
Data Automation—the only way forward
Data automation is the new tool that makes it possible to defeat the data chaos beast. While the right tools and processes help to minimize human error, without automation, you’re fighting a losing battle—not to mention an exhausting one.
Automation is the only way to cauterize data chaos. Without an ongoing, continuous, and automated system for unifying, cleaning and managing your data, it’s subject to entropy. Customer data decays at a rate of 30% annually, and frequent software updates to your most trusted SaaS systems affect all connected SaaS apps, making clean, trusted data a moving target. That’s why you need an equal and opposite force in place to counteract the inevitable decline.
Data automation may feel like a Herculean task—but trust us, it’s possible.
Download The Definitive Guide to Data Automation to discover clear frameworks and real examples so you can restore your confidence in your data and get on the path to predictable revenue growth.