Dec 26, 2016

5 Points to Consider When Formulating a Proposal for Data Quality

Dec 26, 2016 Data, Data Management

Businesses rely on crucial business data to derive insights to enhance customer experience, streamline operations, minimize business risks, and much more. Data originating from diverse sources is surrounding us, and we are interacting with it through its entire lifecycle. Yes, this provides a great opportunity for businesses to derive actionable insights. However, it is imperative for businesses to make sure that the data you are going to rely on is actually of good quality, and is appropriate for the purpose it is being used for.

Why Is Data Quality So Important?

Data is generated frequently by businesses within their departments. For example, customer related data is often created by customer service executives. This information is then utilized by marketing and sales teams to perform numerous functions, such as targeted promotions, upselling, etc. Also, this data is stored by IT professionals in databases or in the cloud.

Though, so many users access the data for diverse needs, it is up to customer service executives to establish whether or not the data is accurate and of good quality. With too many departments and professionals involved, it’s no surprise that business users might lose track of the data collated. Due to inappropriate measures to maintain data quality and vague understanding of data management responsibilities, valuable customer data can lose its value and turn obsolete.

Luckily, experienced business leaders understand the importance of good quality data.

However, in reality the process of formulating a strategy to make ‘Data Quality’ an integral part of company’s data management process is quite challenging and lengthy. Experian plc (a global information services group) conducted a study recently to understand how businesses have gone about developing a business case for data quality. The primary objective of the study was to understand the challenges faced by businesses, the stakeholders and decision makers involved in the process, how long does implementation take and how it is monitored for results.

Here are five crucial findings from the study:

  • 80 percent of respondents agreed that developing a business case for data quality involves many stakeholders, which in turn delays the process. Also, usually the process of developing a business case becomes over-engineered. So it is best to keep it simple. Create your business case by involving only a few selected IT stakeholders and business SMEs capable of providing measurable impacts of data quality on business goals. According to the study, business case approval and implementation can take up to 18 months or more, so simplifying it can surely reduce the timeline a bit.
  • 20 percent of respondents believed that the data quality should be maintained at departmental level. They further stated that IT department is also responsible for data quality, which also explains as to why it is so challenging to build a case for data quality. As the IT department aren’t essentially using the data, they are probably not in a position to elucidate the impact of data quality on business.
  • 66 percent stated that poor quality data has had a negative impact on their business in the past twelve months. Poor quality data can result in decrease in sales, inefficient processes, wastage of resources and diminishing relationship with prospects
  • 43 percent  of the businesses stated that they faced difficulty quantifying cost incurred by organization due to poor quality data. It is actually impossible to calculate the exact cost. However, study has revealed that identifying compliance penalties directly related to poor quality data is possible. Add to this, an approximate cost of lost business opportunities. It is advised that you take help of latest technology to calculate the cost involved.
  • 47 percent of the most significant decision-makers are at C-level. In order to appeal to them data quality needs to be optimal. Hence, when creating your proposal, it’s imperative that data quality matches with your business objectives, like operational and financial performance, regulatory compliance, etc.

For More Information

We hope that this post helps you in understanding the importance of data quality and data management for your business. For more information on how we can help manage correct, complete and updated database with our Data Cleansing and Enrichment Services, please feel free to write to us at info@suntecindia.com and our experts will get back to you shortly.

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