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The 1-10-100 rule: The real impact of poor data

1-10-100 rule - Addressy

Data is important regardless of the time of year, but seemingly even more so as the holiday season and new year get closer, and communications and deliveries are critical. It is a valuable asset to any company – regardless of sector. So, why is it that so many businesses fail to keep their data clean? With bad data leading to failed deliveries, poor communication with customers, missed opportunities and lack of compliance to name just a few examples, it is vital that businesses start to really asses the quality of their data.

Rather than risk overestimating your data quality, a good idea is to follow the 1-10-100 rule. This useful rule was developed by George Labovitz and Yu Sang Chang in 1992 and is great for any business to follow in order to assess the impact of dirty data.

In phase one of the 1-10-100 rule, $1 equates to the amount it costs to verify data in the first instance. This is the cheapest and most effective way of ensuring you capture clean and accurate data. In phase two, the amount increases to $10 – a significant rise compared to the $1 in phase one. This $10 signifies the increased cost that incorrect data has on your business the longer you leave it.  In the third and final phase, the initial $1 rises dramatically to $100, and this figure represents the amount of money businesses will have to pay after doing nothing at all to clean their data.

Bad data leads to poor decisions, communication and efficiency, which can have serious impacts on your business. So, instead of overestimating the quality of your data, take a moment to consider the real consequences poor data may leave you faced with. Rather than paying a hefty sum trying to clean data further down the line, tackle the issue from the very beginning by validating at the point of capture.

In our recent study, we discovered that two thirds (66%) of retailers believe that  address accuracy is critical to their business. However, 80% of retailers suggest that customers often don’t realize that failed deliveries are due to them mistyping their own address. Data that is entered incorrectly at the beginning is certain to lead to numerous future issues. 

So, using tools such as address verification to validate addresses at the point of entry will ensure that not only will you save money in the long run, but will also help strengthen customer relationships, brand reputation and business efficiency. High quality data is not just for the holiday season – it’s for life.

Interested in learning more about the impact of data quality? Download our report Fixing Failed Deliveries: Improving Data Quality in Retail.

 

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