How much is poor data quality costing your business?

Today’s economy is now fuelled by data and we’re collecting exponentially more data every year. However, not every data set is created equally, and businesses are missing the insights and opportunities their data holds due to avoidable data quality issues. In fact, many executives will say their organisation’s performance is being directly affected by poor data quality.

And it isn’t difficult to see why. Have you ever received an email from a company that had your name wrong in the title? There is no faster way to erode your customers’ trust in your business than by demonstrating your inability to manage their data. But mismanaging customer data is only the beginning of your problems with poor data quality.

According to various studies, the task of assembling and correcting data takes up to 60% of an analyst’s time. This is time they aren’t spending actually performing analysis and creating insights for data-driven decision making. And this extra effort is rarely quantified by businesses, as most executives are unaware of the hidden cost and wonder why they cannot get accurate and timely business insights.

Gartner’s 2017 Data Quality Market Survey revealed that poor data quality is costing organisations up to $15 million on average.  While many leaders are aware there is some kind of problem overall, not many organisations have to the effort of quantifying the effects on the bottom line. But market leaders know how valuable data is, and they are laser focused on ensuring their data quality is enabling them to shore up their competitive advantage.

Even for those businesses who have a great grasp of their customers’ data, they might still be overlooking the costs to their business of inefficient internal processes caused by poor data quality. While these inefficiencies start out small, they are the types of errors that amass into the millions when you combine:

• unsent invoices or payments for goods never received
• deliveries of the wrong product
• overstocking and stranded assets

Misreporting due to incorrect data can also lead to large fines and subsequent falls in share price.

Regulatory non-compliance caused by poorly managed migrations and a lack of effective data quality processes have seen many organisations crippled, and subsequently, many executives and board members falling on their sword.

So, how do we break out of the cycle of endless data quality firefighting and begin adopting a more proactive approach? It’s important to remember where the core competencies of your business lie. Is it in cleaning and correcting data at scale? Probably not.

That’s why it’s important to leverage technology solutions and partners that can bring best-practice data quality management to your organisation. While every organisation’s data is different, there are some common process and technology that can eliminate the data quality burden on your analysts, while developing a more robust and scalable solution for your organisation to become more effective to make better decisions.

About the author:

As the General Manager of InfoCentric, my team and I provide specialised expertise, advisory and implementation services in digital and data analytics to help our clients convert data assets into business insights for competitive advantage with faster, smarter and more accurate business decisions. If you’d like to discuss how your organisation can leverage your data assets to drive operational efficiencies, attract new business, and minimise risk, please feel free to get in touch with me at [email protected].