5 direct impacts of poor-quality data

Poor data quality has eroding properties, slowly eating away competitivity, profits and in the long run business growth.

In an environment where business processes are increasingly dependent on accurate and reliable data, the capacity to link occurring business impacts with their data related causes and the capability to act accordingly, gives organization an edge over the competition.

Newton's third law states that “For every action, there is an equal and opposite reaction”, also “For every data quality issue, there is a business impact”.

Data and business are interdependent, so a problem in data will always impact business.

These impacts may be in the form of:

1. Lost revenue, sales, or business opportunities, including:

• Lost sales opportunities.

• Failure to do product cross-selling.

• Impairment in properly identifying customer’s needs.

• Failed marketing campaigns.

• Invoicing problems, either resulting in an inability to properly bill the customers or in additional costs in the billing process.

• Missed B2B opportunities or inefficient procurement due to the incapability to accurately analyse the market.

2. Customer dissatisfaction and service costs, including:

• Loss of a dissatisfied customer, that besides the direct cost related with the customer lifetime value added to the costs associated with new customer acquisition, can also imply indirect costs, as the customer can work as a market influencer, leading to the loss of prospects.

3. Operational inefficiencies, including:

• Poor resource planning.

• Increased operational costs, either on system workloads or work hours spent on data quality related issues.

4. Regulatory compliance, including:

• Inability to comply to regulatory compliance. In some industries where regulatory compliance is essential, poor data quality has a significant impact on the capability to comply with the regulatory obligations, resulting in heavy monetary penalties or even civil or criminal proceedings.

5. Poor decision making, including:

• Inability to make correct long-term decisions.

• Incorrect forecasts.

• Inaccurate customer profiling and segmentation, leading to decreased sales and customer retention.

In an environment where business processes are increasingly dependent on accurate and reliable data, the capacity to link occurring business impacts with their data related causes and the capability to act accordingly, gives the organization an edge over the competition.