Can you put a value on quality data? Definitely! But how?
Who better to ask than Kristin Otter Rønnevig and Espen Hjelmeland? They both dedicated their master thesis to explore this topic with really interesting results. Their thesis "An Investment Perspective on Data Quality in Data Usage" asks "How can an organization optimize its investments in data quality?"
To answer the question Kristin and Espen posed three Research Questions:
- What are the main drivers for willingsness to pay for data quality?
- What part of data quality aspects should one invest in to maximize opportunities and minimize risk?
- How can the quality of data be improved, and what are the costs?
Here are some of their key observations, I found particularly interesting:
- Increasing confidence in data in order to enhance company operations is one of the
motivations for willingness to pay for data quality. - A greater level of knowledge in data quality gives a higher willingness to pay for data quality.
- Demonstrating to the customer how quality improvements may enhance profit at each step
of the value chain contributes to the willingness to pay for data quality. - Prioritizing improvements are based on the time and cost of the particular improvement. A way to reverse-engineer the impact of various improvements
can help to identify how to improve the quality. - It is critical to invest in a professional, highly skilled team environment to succeed
in data quality investments. - To cope with data quality, it is necessary to invest in security.
- To know whether the organization is investing in data quality optimally, it will need a deep understanding of the business and experience with it.