Companies could face data quality issues over a period of time. These issues usually occur due to lack of adequate MDM practices, or the inability to effectively calculate and refine the on-going data policies. In some cases, business managers leverage their existing CRM platforms, to fulfil the short-term customer data cleansing needs of the company. In other instances, they choose to enlighten business users of the importance of good data, to maintain the balance and uniformity required to support data. These approaches might prove to be a temporary solution; however, they do not deal with the entire issue on a permanent basis. These casual approaches will keep accumulating and result in a larger problem, at the end of the day.
 
So, the core question is- Why do businesses ignore the essence of data cleansing and improvement? Some of the major reasons are mentioned below:
 
Lack or Absence of Resources
Several businesses believe that introducing data quality management initiatives can only add to the workload bearing on resources. And, with no data steward on board, the entire process seems meaningless to them. This is why most businesses choose to overlook these issues. Remember that longer the delay, harder the hit. In the near future, the company will end up spending a lot more, for hiring the staff required to navigate such problematic data, after it faces compliance issues or suffers from below par business decisions.
 
Biased Beliefs
Firms are known to blindly accept the fact that most data quality problems arise due to lazy and uninterested employees, because of which, they go around reinforcing business rules and standards to help them tackle these issues. One must remember that, this may not always be the case. Uncommon errors such as nicknames, duplicate addresses and misspelt names are a few relevant examples of how data quality is not always influenced by human hands. You may order a clean-up of your teams and processes, which is a good habit. But, it may not entirely solve the problem knocking at the door.
 
Lethargy and Ignorance
Businesses know how important data quality is, to their functioning. However, they do not think much about it until a major situation occurs, such as a data warehousing, integration or migration project. The complexity of data quality makes it difficult to calculate when, where and how data quality tools have to be utilized. Of course, data quality tools must be implemented before the records are moved from one place to the next. However, the new system may pose difficulties in the cleaning and migrating of data, from the old ones. De-coupling of MDM initiatives from larger ERP umbrella projects is important.
 
Miscalculated Budgets and Costs
A very common issue faced by most firms, is the struggle to calculate the ROI of the data quality improvement exercise. This is the major reason why they choose to ignore the implementation of such tools in their business atmosphere, and this affects their efficiency and progress in the long run. However, with some domains like item, material and product, calculating hard dollar gains is achievable.
 
Remember, prevention is better than cure. Introduction of data quality solutions today will definitely ensure a brighter tomorrow.
 
Are there any other reasons obstructing your organization’s path to the famed single golden record? Do share below..

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Jessica Banks

Jessica is one of the most passionate marketing professionals in Verdantis. She is a strong proponent of master data management solutions for large enterprises. For her, Data drives Performance.

Latest posts by Jessica Banks (see all)

• Data cleansing- what it does for your business - February 5, 2015
• Tips and strategies for enterprise data management processes - September 12, 2014
• Master Data Governance is Re-shaping the Enterprises - August 22, 2014