5 Common PIM Mistakes to Avoid for Retailers and Distributors
As more product-related data is available for retailers and distributors, manually managing this volume is becoming unmanageable for businesses which want to be truly competitive in crowded digital markets. That’s why Product Information Management (PIM) systems have become a go-to solution for agile management of large amounts of product data. However, replacing a legacy system and implementing a PIM is a challenging and complex endeavour, and the potential for getting it wrong can lead to poor data quality, inefficiencies, and lost revenue.
Our insight article outlines five common PIM pitfalls to avoid for retailers and distributors.
1. Not defining data governance policies
A common mistake in the implementation of a PIM is a failure to define data governance policies. A fit-for-purpose data governance framework should define the rules and protocols which determine who is responsible for managing product data, and who has permission to access different categories. It should also establish how it is collected, stored, and updated. Without clear data governance policies, the business runs the risk of using inconsistent, duplicated, inaccurate and out of date information. The consequent errors and confusion have a material impact on efficiency and bottom line.
2. Failure to integrate with existing systems
Another common mistake is not integrating your PIM system with existing ones such as ERP, CRM, and e-commerce platforms. Doing so is crucial for ensuring that the same pristine, ‘single source’ data is used across the organisation to ensure consistency and accuracy needed for omnichannel success. Without integration, data ends up being manually entered into multiple systems – at best, a duplication of effort and at worst, a use of inconsistent data.
Download our Benefits of a PIM consultant guide
3. Overlooking cleansing legacy data
Before the PIM system implementation project goes ahead, it is essential to carry out an audit of your product data to audit, normalise, and cleanse existing data before migrating it to the PIM. This generally includes removing duplicates, standardising formats, and ensuring there is a quality standard in place to ensure uniformity. If you don’t clean up ‘dirty’ data, you are exposing yourself to a world of pain once you feed it into a new PIM system – the adage “Junk in, junk out” exists for a reason.
4. No PIM training provision
A PIM system requires a new mindset and new practices, so it’s essential to train all users who will interact with the system. A failure to provide adequate training will lead to some employees not using the system correctly, causing inefficiencies and an inconsistent approach to what should be a new ‘regime’ of product data management. severely affects the PIM’s capacity and will stymie effective collaboration in enriching data to make it channel ready. A comprehensive training initiative should cover all elements and features of the system, including data onboarding, storage, enrichment, syndication, and reporting.
5. Failure to implement continuous improvement for data quality
Retailers and distributors should be looking for continuous improvement in their product data quality. That means processes and protocols in place for systematic quality monitoring to identify and correct errors, as well as to update data rapidly. A PIM solution is multi-faceted, so failure to ensure data quality is of the best possible standard impacts not only on the degree of use you can put the PIM to, but also operational efficiency and the information you provide for potential customers, Using analytics with data of inconsistent quality will also impact on more strategic decision-making.
Implementing and operating a PIM system doesn’t need to be further complicated by failing to factor in what we have mentioned above. As retailers and distributors, you have invested in a PIM to ensure product data accuracy, consistency, and quality, so that your customers enjoy the best possible experience, and the likelihood of conversions rises significantly. The best way to do that is by defining data governance policies, integrating with other systems, cleansing existing data, providing suitable training, and continuously improving data quality – that way, you can maximise the ROI on your investment not just now, but well into the future.
Without the guidance and support of experts in PIM implementation projects, with a proven track record of success, the complex journey to getting your PIM online and operationally efficient risks getting derailed en route. Installing the best technology is only half the story – maintaining legacy practices and attitudes will no longer cut it, so organisational change is needed. Start with Data’s team of experienced consultants can ensure your journey to data-driven is as smooth and value-generative as possible. We can help you to enhance your organisational effectiveness and increase your revenue, so contact us for a more in-depth conversation about your requirements.