eCommerce Product Data Governance: Why Does It Matter?

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eCommerce Product Data Governance Why Does It
Matter?
According to Gartner, organizations hold poor
quality data as the cause of an estimated 15
million worth of losses per year. The consulting
giant also points out that approximately 60 of
businesses do not measure their annual cost of
bad data quality. For brands trying to
streamline their online sales, maintaining
complete and accurate data is the most critical
element to succeed. However, achieving this goal
requires a robust product data governance process
in place that delivers actionable frameworks.
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What Is Product Data Governance? Product data
governance is one of the most crucial processes
for a business to succeed in the digital age.
Having accurate balances and checks for product
information of any item sold in the marketplace
is more important than ever. TechTarget defines
data governance as the process of managing the
availability, usability, integrity, and
security of the data within enterprise systems,
depending on internal data standards and
policies controlling data usage. Although the
concept sounds complicated, it is relatively
simple in practice. Data governance allows
enterprises to know their data, the datas
accuracy, and where its overlapping. The data
governance practices ensure secure data storage
and privacy, structured data availability,
product data analytics, and accurate data across
multiple channels. When it comes to product
data governance, ongoing maintenance is critical
to prevent unforeseen consequences. It requires
a robust Product Information Management (PIM )
platform to centralize product data along with
data practices. Continuous product data
governance ensures the best governance practices
are sustained. All in all, product data
governance is not a one-time solution its an
ongoing procedure that consistently gives you
clean, coherent, and consistent product data.
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• Data Management Vs. Data Governance
• Data governance is often mistaken for data
  management and vice versa. It is essential to
  understand the differences in using these two
  strategies where applicable.
• According to DAMA, data management is a set of
  processes used for planning, identifying,
  facilitating, designing, developing, retaining,
  utilizing, archiving, saving, managing, and
  cleaning data.
• Contrarily, data governance is just a process of
  data management. It oversees procedures that an
  enterprise sets to ensure the security and
  quality of data in possession and operation.
• The Product Data Governance Framework
• Businesses handling vast volumes of eCommerce
  data should be able to visualize the bigger
  picture when it comes to product data governance.
  For that, using an ideal data governance
  framework that helps with data collection, data
  management, distribution, and storage is
  important.
• The product data governance framework entails
  some basic steps leading enterprises to a smooth
  and agile implementation
• Defining goals and analyzing benefits
• Evaluating the present condition and conducting
  delta analysis
• Developing the roadmap based on the findings
• Preparing a budget and ensuring the action plan
• Introducing and organizing a data governance plan

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• Practically, each enterprise should have its
  customized product data governance framework in
  place.
• What Makes Product Data Governance Important For
  eCommerce?
• The global product data governance market crossed
  the 2.1 billion mark in 2020. As it stands,
  more and more enterprises are advocating its
  innate benefits for eCommerce services.
• Heres why businesses should invest in intrinsic
  product data governance strategies
• Cost Saving
• Characteristically, the supply chain involves
  designing, planning, sourcing, production,
  logistics, and distribution. In each stage, a
  large amount of data is transferred between the
  external and internal stakeholders. Incompetent
  data management could cause data asset loss,
  biased demand forecasts, etc., leading to a
  long-term cost burden.
• In the data designing phase, a structured data
  plan can reduce developmental costs. A cohesive
  product data governance strategy ensures relevant
  data is carefully stored in one central location
  so that other users and systems can consume it
  all while adhering to security and accuracy.
• Data Streamlining
• Product data governance ensures appropriate data
  storage and eliminates incorrect dataset
  referencing. Establishing enterprise-wide data
  quality and data-centric views assists in the
  transition of an information-centric industry
  into a digitally empowered entity.

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• Transparency
• Data governance fosters a transparent and trusted
  environment. A centralized workflow-driven data
  management system brings together the key
  components of an asset, such as product
  configuration, change control, etc. It also
  considers the technical aspects of the parts of
  a product, its attributes, and supplementary
  documentation. It is equipped to supply accurate
  data having role-specific visibility with
  additional permissions to ensure data management
  and governance.
• Putting Milestones Metrics In Place
• Product data governance allows you to put tools
  and processes together with a set of
  well-defined milestones and metrics. As a result,
  it ensures data reliability. Without planned and
  thoughtful business rules and diligent data
  governance, enterprises would only work on
  flawed and skewed datasets. Often, the data
  flowing across divisions may not be synced
  properly due to the lack of a centralized hub.
• To that end, data governance aids in defining
  processes and metrics to ensure data accuracy,
  reliability, and quality. This initially involves
  collaboration across supply chains to decode the
  common issues, data validation, cleaning, and
  data monitoring control. Besides that, product
  data governance ensures that enterprise-wide
  standardized data and processes function as one
  unit.
• Risk Identification
• With broader supply chains and multiple
  stakeholders, there has been an exponential rise
  in information exchange through both authorized
  as well as unauthorized networks, suggesting
  that the risks persist. Inefficient data
  governance may lead to many unforeseen risks,
  such as misuse of sensitive data.

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Its also noteworthy that data management
provides internal and external members of an
organization with access to relevant data.
However, robust security infrastructure is
critical to ensuring data is protected from theft
and cyber incidents. A comprehensive governance
strategy that can define data point checks and
controls and further monitor data location
deviances is one way to mitigate risk. Proper
data governance gives access to trails of data
audits that monitor and track the retrieved
data. This also downsizes the expensive
errors. Final Word The new technology-powered
data systems collect, analyze, and streamline
data to make it more intuitive, easy to use, and
accessible. Here, by implementing product data
governance policies, companies can ensure high
data quality, regulatory compliance, auditing
and lineage, accuracy and consistency, increased
efficiency, etc. This bodes particularly well for
eCommerce, for it heavily relies on data-driven
decision-making. At EnFuse, were always working
to foster innovation and drive substantive value
out of data governance initiatives. Explore our
offerings here. Read More Product Data Is The
Cornerstone Of B2B eCommerce