Data Quality – 5 reasons why it should matter to you

Data – the word is all around us. It is being shouted about from rooftops and is being whispered about in hushed tones; it is being talked about as a panacea and is being reviled as just another fad that will pass. Whatever be your thought about it, the fact remains that data is ‘in’ today. You need to be aware of it, and be using it in your organization, if you want to be in with the times. However, what use is data if you don’t have confidence, and you can only have this confidence if you are sure that data quality has been taken care of.
Now what I am saying is nothing exceptional – everyone knows data quality is important, and companies are putting in millions for making sure it is up to the mark. But a recent report by Experian Data Quality has thrown up numbers that will make you stop, pay attention, and maybe re-evaluate the way you approach data quality.
Here are 5 insights that will definitely force you to think –


  1. Lack of Reliability – You might be surprised to know that 92% of respondents believed that their organization’s data is inaccurate in some way or another. This betrays an amazing lack of trust in the company’s own data. Interestingly, this can also be seen as a sign of people becoming more aware about their data and its importance. Either ways, such a high level of distrust is not a good sign for those particular organizations.

  3. Simple, entrenched errors – The most common type of errors in data were found to be Incomplete or Missing Data (51%), Outdated Information (48%), and Inaccuracies (46%). The worst part about these numbers is the fact that each of them point to a human error that could (and should) have been detected and rectified. This is the reason why a comprehensive master data management effort is becoming essential for organizations with each passing day.

  5. Apathy – This was perhaps the most disheartening number thrown up by the survey. A full 43% of respondents said that their organization was wither ‘unaware’ or ‘reactive’ about their data quality. Even with the increased awareness regarding the criticality of data and data quality, such a large number not paying heed to it seems strange, to say the least.

  7. Lack of strategy – Respondents whose organizations did care about data quality had a different sort of problem. 63% of those surveyed believed that their company did not have a coherent, centralized approach to their data quality strategy. This is a common phenomenon, especially in situations where data quality is not considered a business issue, but is rather seen as an IT problem. Such an approach leads to piecemeal solutions and ineffective implementation of master data management and data governance solutions.

  9. Some good news – After all these scary figures, it is time for something completely different. If you are on the fence about a data quality initiative, you should know that 53% of the respondents from companies having a central data quality approach said that their organization has seen a significant increase in their profit in the last 12 months.


Whatever might have been your stance on the issues raised in the survey, the fact that data quality and data governance are critical is quite evident and the responses should give you food for thought. Let me know what your thoughts are in the comment section below.


Further Reading:

Blog – Single Version of the Truth – What it means for data quality?

White Paper – Material Data Quality Project Handbook – Avoiding Pitfalls

Case Study – Material Master Data Management for a leading Oil and Gas Company

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Vipul Aroh

Vipul Aroh

Vipul Aroh is a part of the Marketing team at Verdantis. Although relatively new to the field of master data management and data governance, he is fascinated by the topics and is becoming more passionate about them by the day. Vipul holds a Master’s in Business Administration from Sydneham Institute of Management, Mumbai.

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