I’ve been writing on data quality for over a year now and it remains one of the most fascinating tasks of my work week. It’s an industry that’s new, always changing, and is quickly becoming the most important aspect to a company’s chances of thriving in the digital age. But for the tens of thousands of words I’ve written since I jumped into the data quality space, it’s really the numbers that do the talking. If I could tell business leaders why data quality is crucial to their business’s success, here are the data sets I’d choose to present to the man or woman at the top.
Poor Data Quality Costs Everyone Money
The statistic that made the biggest impression on me in 2017 involved one extremely large number with numerous negative implications. Earlier this year, IBM suggested that poor data quality cost U.S. businesses a staggering $3.1 trillion dollars in 2016. Imagine for a moment all of the efforts businesses take to minimize unnecessary costs. And then think that $3.1 trillion is evaporating into thin air due to wasted time, resources, and opportunities. It boggles the mind that such waste has been happening, but it shows why adopting data quality processes have become highly prioritized industries across many industries.
Data Quality Wastes Time
We live in a knowledge-based economy, and this knowledge in which we deal is based entirely on data. To overstate the importance of useful, accessible data in the modern business age would certainly be a tall task. The goal of data quality solutions is to make this data as clean and effective as possible. But the best solutions go further. They focus on speed as well. Why? Because poor data means wasted time; lots of wasted time. In fact, data scientists waste as much as 80% of their time addressing simple data quality issues. Imagine your smartest, most valuable people spending just 20% of their time delivering insight, finding opportunities, and identifying areas of your business to cut waste. Terrifying, isn’t it?
Want to Increase Your Profitability? Address Data Quality
A statistic that is new to me, but no less impactful, is that the cost of bad data to a company is somewhere between 15% to 25% of revenue. According to this research, data quality is a measurable reality for most mid-to-enterprise level organizations. Wasted time, costs, and resources, not to mention missed opportunities have a huge impact on businesses. Isn’t it time you took ownership of your data and started making meaningful change?