Lets assume a situation where you were going to send a marketing premium to some customer and ironically the incorrect address was recorded and you mistakenly sent the premium to some other person. The original client calls in for a complaint and then you have to send the premium again. What was the reason behind this? If we look closely at the scenario then it might occur to you that there were several business losses due to a low quality or incorrect data.
1. The call centre cost in terms of agent time which occurred due to the customer’s complaint call
2. The cost of data correction i.e. correcting the wrongly recorded address
3. The cost of sending the premium again since the first premium is considered scrapped
This is just many of the examples that arise due to the faults in accuracy and quality of the business data. You might miss an opportunity when your sales representative finalizes the deal only to find out that the credit card score is below your requirements so you end up wasting your time and efforts which could prove more fruitful if the data had been of good quality.
There are three types of business losses due to the low quality of data.
Direct losses occur when a core business process is effected due to the errors in the data. For example if you enter invalid zip or area code and you have to send a product on that address, your staff might have to correct it before sending the product. These kinds of direct losses arise from the data quality in the core operations or processes of a business.
There can be time, money and efforts of your employees spent on checking, inspecting and verifying the quality and accuracy of data which could undermine the efficiency and effectiveness of business processes. Data quality inspection can undermine your ability to achieve your goals in time.
When a business process is severed due to the bad quality of the data, it needs to be prevented and improved. The time and efforts spent in fixing the business process could affect the results and business objectives.
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