Oh No – Not Another Data Groundhog Day

It’s Groundhog Day, a time when the nation gathers to watch a bushy-tailed rodent peek its head outside a burrow to observe whether or not it sees its shadow. If it does, winter sticks around for six more weeks. If it doesn’t, we can expect an early spring. Or so they say.

But Groundhog Day has another meaning, too. Popularized in the 1993 movie of the same name, Groundhog Day describes events or circumstances that occur on an endless loop, often without meaningful change or progress. It’s a situation where change feels out of reach, despite your best efforts to break free. 

In the movie, aptly named protagonist, Phil Connors, relives the same day - February 2nd - over and over again. Phil wakes up each morning in Punxsutawney, PA, the town where the famed groundhog “Punxsutawney Phil” resides, and must confront his decisions and their implications – both good and bad – in a repetitive cycle. 

Now, you may be wondering what, exactly, Groundhog Day has to do with data. The answer is a lot, actually. Imagine this scenario.

Senior leaders of your company are meeting to discuss the strategic plan for the upcoming fiscal year. The CEO wants to map out the company’s growth strategy, so the meeting begins with a discussion of the current customer base. The CFO confidently states that the company has 1,300 active customers which represents an 8% growth rate year-over-year. The head of sales pipes up, disagreeing with the CFO by stating the company has 1,350 customers, which represents a 12% growth rate. At this point, the inevitable data brawl ensues, and the meeting quickly dissolves into a debate about the quality of the data, not a productive discussion of the insights it provides. And if we had to speculate, this isn’t the first time this team had this discussion. 

Answering the question “how many customers do we have” shouldn’t be this challenging. Caught in an endless loop of inconsistent, inaccurate, and disconnected data, companies continue to make poor decisions, waste resources, and overlook valuable opportunities. Like Phil Connors, they face the same challenge on repeat: duplicate records, incomplete or outdated information, and misaligned metrics that lead to faulty decisions or customer experience errors. And until they fix their underlying data, they’ll be doomed to repeat their mistakes.

We call this Data Groundhog Day. And the problem is more common than you may think. 

In a rush to operationalize their data, companies implement traditional master data management (MDM) technologies that serve as yet another data repository with its own flashy set of APIs. But despite their investment in MDM, their challenges persist. And the reason these companies failed to realize value from their MDM investment is because they didn’t follow the right path. Instead of assessing their data, improving its quality, and reviewing it with users, they jumped straight to the last step in the journey - operationalization. 

The better approach is to follow the MDM Journey. Instead of remaining caught in the endless loop of bad data, the MDM Journey provides a path for companies to improve their data before they operationalize it, enabling them to avoid facing Data Groundhog Day. Said differently, it’s a way to make forward progress on the perennial challenge of mastering key data entities.

When companies follow the MDM Journey, not only can they finally trust their data, but they can also confidently answer questions like “what is our customer count,” “which suppliers deliver the specific set of products and services I need,” or “what markets should I explore to grow the business?” And because these companies follow the steps to improve data quality before they operationalize it, they see higher degrees of success. 

The MDM Journey

1. Assess: know where you are…and where you want to go

2. Improve: make your data trustworthy by cleaning and enriching it

3. Review: put your data in front of end users to gather feedback and build trust

4. Operationalize: turn your data into a mission-critical asset by connecting it to key business systems

If you’re ready to break free from the endless loop of bad data, download our ebook The MDM Journey: From Trusted Data to Operationalization. Then, schedule a free data assessment with a Tamr expert to provide you with insights into the state of your data and the next steps you should take to finally escape Data Groundhog Day.