D. Justhy's Blog

"Getting to Yes, Now!"

Get Rid of Poor Data Quality Once and for All

The impact of poor quality data is felt both in terms of revenue as well as the reputation for organisations. Data quality issues cost businesses $600 billion per year according to a report by TDWI (The Data Warehouse Institute). A 2016 report by IBM estimates that the losses caused by poor data quality are almost $3 trillion annually.

Organisations also incur damage to their reputation which can vary from minor to major. One example is the roll out of Maps by Apple in which most of the data was inaccurate and not usable. Reputation damage also has a direct impact on revenues.

Striking the balance

While many businesses realise the criticality of data quality, they are not effective in striking the right balance in allocating resources to address data issues. Although businesses respond to regulatory demands to invest in data management, return on investment is a subject that eludes CFOs and COOs.

According to a report by KPMG, 84% of CEOs are not confident about the quality of data they are basing their decisions on. Two out of three executives are overwhelmed by the quantity of data that need to be analysed. In the digital era, technologies including Internet of Things and automation are leading to exponential growth of data. To be able to stay ahead of the competition, managing the data quality is becoming increasingly important for businesses.

A 10% increase in data accessibility can boost the net income by $65m for Fortune 1000 companies. Simplifying the data deluge management process with the right tools, methods, people and processes is basic to solving data quality issues.

The solutions

The first step to getting rid of poor data quality is to understand the relative importance of data. Focusing on the most important person-centric data, followed by products and services is critical to managing data quality.

  • The person-centric data should be of the highest quality and also well managed to enable businesses to run efficiently. In this context, businesses should know the relationship between Business Strategy-Business Model-Business Process-Data.
  • The most critical data for the business needs to get 100% in terms of quality. Before getting into big data analytics, it is crucial to get the quality of person-centric data right. The cost of not managing the quality of person-centric data can run into billions or trillions for businesses.

The Data as an Asset (DAAS) Index is a tool that helps create transparency required to address and manage data quality.  Just like in the industrial age – ZERO DEFECTS – is a possibility.

Patience and discipline is the basic foundation, though.

In the midst of burgeoning technologies.