Poor-quality data can have serious consequences, affecting costs, revenue, and customer loyalty. Data quality is a critical factor in corporate success, and operational systems suffer greatly from toxic data. 

It also undermines business intelligence tools, leading to flawed decisions that may result in financial losses, damaged customer relationships, and harm to a company’s reputation. As data becomes a strategic asset, organizations are holding leaders accountable for ensuring the accuracy, reliability, and quality of their data. 

Major Impacts of Toxic Data 

• Customer Dissatisfaction 
• Lost Sales Opportunity 
• Loss of Business Reputation 
• Incorrect Business Decision 
• Decrease in Revenue 

How Data Quality Can Adversely Affect Your Organization? 

Inefficiencies in Data-dependent Business Operations are Caused by Poor Data Quality. 

Companies use data in almost all business processes in one form or another. Data plays a crucial role in client order input, billing, reporting, and business analytics. Even with flawless execution of every business function, inadequate data can cause major disruptions. These inefficiencies lead to highly costly rework attempts to “fix” the data to satisfy different expectations of the processes. 

For instance, inadequate data quality and a lack of data validation in financial transactions may result in losses. There’s a chance that the bank amount in the books and the amount in the bank may not match. Payment of duplicate invoices could result in losses of money. When there is a significant of money owed to the vendor by that company, payments to them may be made. There’s a chance the discount amount was computed improperly. Remittances might be recorded in the incorrect amount. 

Insufficient Data Quality Can Result in Flawed Decision-making.  

A choice can only be as good as the data on which it is based. Businesses should ensure that their data accurately depicts reality because important decisions based on faulty data can lead to grave consequences.  

Recently congressional investigators revealed that a flawed database used by two-thirds of the US health insurance industry under-compensated patients for their visits to doctors outside the insurer’s network. This calculation error causes exaggerated medical costs for Americans, amounting to billions of Dollars. 

Poor Data Quality Breeds Mistrust

Poor Data Quality can undermine customers’ confidence in a company. If the data is incorrect, organizations can waste time, money, and their reputations. Some studies indicate that acquiring a new customer costs four times less than losing an existing one due to staff expenditures and advertising expenses. 

According to a recent survey conducted by Experien’s marketing services division, US companies acknowledge that improper customer data management costs them 7.3 percent of their sales. The survey further states that 77% of businesses that admit to having poor data quality also recognize that this flaw hurts their bottom line. 

Some Real-life Consequences Businesses Can Face 

Conclusion

Achieving data quality requires constant work and cannot be done quickly. According to the Japanese Kaizen concept, individuals can make small everyday gains that add up to significant benefits over time. The accuracy, completeness, consistency, conformance, and timeliness of a piece of data, along with how the organization stores and transfers the data, all fall under the general phrase “data quality”. Businesses will vary the definition and specifications of data quality, but in the end, what matters is that the data is “fit for a purpose”. Companies must be able to use data as an asset to support their ongoing expansion. 

Read Whitepaper Toxic Data: Hidden Threat to Your Organization’s Performance