5 direct impacts of poor-quality data

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.

Estelle Onyekachi Mbadiwe MPharm, MSc

Founding Partner at DUCIT BLUE SOLUTIONS, Kofi Annan Global Health Leadership Fellow

4 年

This is accurate, including for the business of quality healthcare provision ...

要查看或添加评论,请登录

Jose Almeida的更多文章

  • DW is not dead

    DW is not dead

    Discussions around modern data architectures often bring up a recurring question: Is the data warehouse dead? With the…

    1 条评论
  • Data Is Not a Business Requirement

    Data Is Not a Business Requirement

    For years, organizations have treated data as just another box to check - a business requirement that needs to be…

    3 条评论
  • AI’s Dirty Secret: It’s Only as Good as the Data Behind It

    AI’s Dirty Secret: It’s Only as Good as the Data Behind It

    Artificial Intelligence (AI) is often painted as the ultimate game-changer - capable of automating processes, driving…

    6 条评论
  • 5 Use Cases for Master Data Management (MDM)

    5 Use Cases for Master Data Management (MDM)

    Mastering data is no longer optional - it’s essential for business success. As organizations generate and rely on vast…

  • The AI Paradox

    The AI Paradox

    The explosion of AI tools in the last year has been nothing short of remarkable. Organizations across industries have…

    10 条评论
  • The Most Important Skill for Data Professionals? It’s Not What You Think

    The Most Important Skill for Data Professionals? It’s Not What You Think

    I’m often asked by young data professionals: What technologies or tools should I learn next? They expect me to list the…

    2 条评论
  • Making Data Quality Everyone’s Job

    Making Data Quality Everyone’s Job

    Data is no longer the sole responsibility of IT or data teams—it’s the foundation of every modern business decision…

    3 条评论
  • Turning Chaos into Clarity

    Turning Chaos into Clarity

    Every organization—big or small—is swimming in data. But without a clear plan to manage it, this valuable asset can…

    3 条评论
  • ESG Data in Banking

    ESG Data in Banking

    Environmental, social, and governance (ESG) factors have shifted from being a secondary consideration to a core driver…

    1 条评论
  • How to Make Data Governance Sexier

    How to Make Data Governance Sexier

    Let’s face it—data governance isn’t exactly the most thrilling topic in the room. It often gets lumped into the “boring…

社区洞察

其他会员也浏览了