The Consequences Of Poor Data Quality
Do you know that very few enterprises trust their data and use it confidently? More than 90% of businesses have no confidence in the effectiveness of their data. Accurate, clean, and correctly formatted data always gives value to your business. On the contrary, low-quality data can pose a risk to your business.
Organizations that do not enter proper data and maintain it pay for data management. It involves both direct and indirect costs. The direct one refers to the cost of resources essential for maintaining the data. What is the indirect cost? Data quality problems result in the loss of business. There is also a risk of making inappropriate decisions.
Let us now briefly discuss the problem you can encounter due to low-quality data maintained in your ERP system.
Damaged reputation
Have you contacted a particular prospect or customer several times without strong reasons? It can result in a bad reputation in the digital and physical worlds. Your potential customers will think that you are inefficient.
Poor decision making
Poor data results in inaccurate analysis which results in inefficient decision-making. This can have an adverse effect on business performance. There will be a failure in predictive data analytics as well.
Loss of revenues
The biggest problem with using low-quality data is revenue loss. Because of the poor data, Organizations will not be able to target/promote customers with appropriate offers which can lead to customers moving out to using competitor’s products. On the contrary, poor data also results in giving high discounts and gifts to undeserving customers.
Missing potential opportunities
Incorrect buyer personas lead to missed opportunities. Knowledge about prospects’ behavior and interests is important to devise appropriate sales and marketing strategies. Sales and marketing teams may not be able to reach that prospect in time due to incorrect buyer information. The data should be comprehensive and should provide answers to all the relevant questions. Another important thing is the consistency of data because inconsistent data results in misplaced and mismatched data which in turn leads to missed opportunities.
Lowered customer satisfaction Bad data negatively impacts the customer experience. Misspelled names, undelivered messages, delayed services, inaccurate product suggestions, errors in transactions, and all such things spoil the customer experience. These experiences lead to lower customer satisfaction and may eventually end up losing out on this customer forever.
Increased operational costs Bad data increases operational costs. Bad data leads to business process breakdowns which significantly increases the time to manufacture a product or deliver it to the right customer. Identifying and correcting the bad data also consumes time and effort of our resources.
You can make an informed decision with the availability of real-time and accurate data. Your systems should provide up-to-date information to be competitive in the market. Quality data also has a high level of integrity. Without this attribute, your data will be useless. Your customers may think of you as unreliable.
