In this short, 5-part blog series, we will explore the crucial role that high-quality, trusted data plays in driving effective business outcomes. In this first part, we will explore the cost of bad data quality
Bad data is expensive. According to Gartner, poor data quality costs organizations an average of $12.9 million annually. For individual businesses, the impacts ripple across every function:
- Decision-Making: Flawed data leads to misguided strategies. Imagine a sales team targeting the wrong demographics because customer records are outdated.
- Compliance: Regulatory fines escalate when data inaccuracies lead to reporting errors (e.g., GDPR or CCPA violations).
- Customer Satisfaction: Duplicate records or incorrect contact details frustrate customers. Imagine running a loyalty program with duplicate profiles, causing a 30% spike in marketing costs and customers receiving repetitive promotion offers.
- Market Efficiency: Supply chain delays, inventory mismanagement, and missed sales opportunities stem from unreliable data.
- Competitive Advantage: Companies with trusted data outpace rivals by acting on insights faster.
The bottom line - maintaining high standards for data quality and trust is crucial for building a reliable and successful business. Without trust in data, businesses operate in the dark—and the consequences are real.
Bad data isn’t just a nuisance—it’s a threat to survival. By decentralizing data quality and fostering a culture of trust, businesses can transform data into a driver of innovation and growth. With platforms like Qlik Talend Cloud, organizations don’t just manage data; they leverage it to stay ahead in a competitive landscape.
