Product Information Management (PIM) optimization is the process of improving organizational processes and practices to ensure that product master data is accurate and up-to-date. This includes the use of templates, rules-based systems, or external validators to ensure that product information is up-to-date and complete in order to ensure data-driven marketing and exceptional customer experiences across channels.
The purpose of PIM Optimization is to guarantee the accuracy and quality of product data, thus ensuring that all stakeholder in product processes and customer relations are equipped with reliable data. PIM optimization should empower people and processes with accurate, reliable, and up-to-date product information, enabling a seamless and unified product experience, no matter where it originates from.
Typical activities included in PIM optimization include improving your data quality and accuracy, such as by developing templates for product data, introducing rules-based systems to verify data, or utilizing external validators. It also includes activities such as onboarding suppliers, automating data entry, consolidating data from multiple sources, or managing product hierarchies and relationships.
Benefits of PIM Optimization
PIM optimization offers many advantages to organizations, such as improving data quality, digitizing product processes, and increasing accuracy. These advantages and more can be summarized as follows :
- Enhanced data quality
- Improved accuracy
- Faster data entry
- Improved customer experience
- Increased sales
Enhanced Data Quality
Data quality and comprehension can be improved by creating templates for different product types and maintaining complete data sets. This is especially helpful for suppliers and retailers, who require consistent and accurate product information to fulfill their objectives and mission. These templates can also be shared across different organizational teams, enabling collaboration and knowledge-sharing.
Rules-based systems and external validators can help ensure data accuracy, by automatically identifying and addressing any inconsistencies that could lead to errors and inaccurate product information. Automation and external validators also reduce the need for manual processes, allowing more time for the implementation of advanced strategies to maximize data accuracy.
Challenges with PIM Optimization
Optimizing for PIM accuracy and quality is not without its challenges. Below is an overview of some of the potential obstacles that organizations may face in their pursuit of data accuracy.
PIM optimization can be costly, as it often requires investing in new software and additional manpower. Additionally, organizations may need to invest in external validation services or third-party auditing to further ensure accuracy. This can make achieving data accuracy a costly endeavor.
Improving data quality and accuracy is a long-term endeavor that requires time, dedication, and resources. Organizations may need to commit to long-term projects or initiatives to ensure quality data, and they may even need to create custom rules or set-up procedures to ensure accuracy.
Best Practices for PIM Optimization
Below are some best practices that organizations can use to optimize their PIM processes for enhanced accuracy and quality.
Automating data entry and processes can reduce the need for manual intervention and improve data quality. Automation can also help organizations accurately and quickly onboard new suppliers and manage multiple product versions. Utilizing automation can save time and resources in the data entry process.
Internal validation can go a long way towards ensuring data accuracy, but external validation is recommended for organizations looking to absolute accuracy. Services such as third-party auditing can deliver extra assurance to organizations regarding their data accuracy.
Integrating with Existing Systems
Integrating PIM systems with existing systems and databases can help ensure accuracy and data quality. By using existing information and systems, organizations can minimize errors and unwanted duplicate data. Integration is also beneficial for streamlining processes and reducing manual labor.
Overall, PIM optimization is key to guaranteeing accurate and quality data, irrespective of stakeholders or processes. By employing best practices such as automation, external validation, and system integration, organizations can achieve their desired level of accuracy and reliability.