You’ve succeeded in a major achievement – Implementing your Product Information Management (PIM) system, but that’s not the finish line. It’s go-live is where the real work begins. The long-term value of your PIM is determined not just by astute configuration choices, but by how confidently and consistently your people can use it on a day-to-day basis.
Organisations of all stripes must have a clear post-implementation training strategy to avoid the most common risks of omitting it:
- Sluggish and uneven user adoption
- Variable and even declining data quality
- The creeping onset spreadsheet reliance and manual workarounds
In other words, precisely what you invested on a PIM to avoid! That’s why we’ve written this article, to examine how best to train, support, and enable your teams to ensure sustained PIM success once it’s gone live.
Why post-implementation training is a must-do
Initial PIM training typically focuses on the basics of the new system: navigation, core workflows, and launch readiness. Once people begin using the system in real conditions, a number of new challenges commonly rear their heads:
- Edge cases that don’t fit standard templates
- Bottlenecks in approval workflows
- Confusion over data ownership
- Inconsistent data entry practices
- Underutilisation of advanced features
If you don’t address these, user confidence becomes unsteady and the smooth adoption you wanted simply stalls. It’s this post-implementation training which bridges the gap between technical launch and operational maturity, so that PIM becomes embedded in your business’s everyday processes rather than being treated (or perceived) as a one-off project.
Shifting the focus from “how” to “why”
After go-live, training should move beyond button-clicking and focus more on impact.
Your teams need to understand:
- How their data affects downstream channels
- Why validation rules and governance exist
- How errors propagate across systems
- The dire commercial consequences of incomplete or inconsistent data
If users are able to see that a single attribute powers filters, comparisons, compliance checks, or distributor feeds, then data stewardship becomes a role with a purpose, not just a procedural nicety. This mindset shift helps to engender a greater attitude of ownership and accountability across the organisation.
Delivering role-based, scenario-driven training
As we all know from experience, generic training quickly becomes irrelevant. In this case, you need to tailor post-implementation enablement to real roles and real–life workflows.
A few examples of where these roles sit:
- Product managers: attribute ownership, lifecycle changes, and taxonomy updates
- Marketing and eCommerce teams: enrichment workflows, consistency across channels, and efficiency techniques
- Data stewards: validation rules, audits, and quality reporting
- Local or regional teams: localisation, translations, and regional compliance
- Administrators: governance processes, change management, and system optimisation
Using live products and current workflows makes training immediately practical and reinforces appropriate product data-oriented behaviours.
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Reinforce data quality continuously
Quality data does not stay that way by itself. Moreover, automation, as great as it is, only amplifies both good and bad practices. Ongoing quality reinforcement is essential.
Effective post-implementation strategies include:
- Refresher sessions on attribute definitions and standards
- Training on common data quality errors
- Explaining validation messages instead of treating them as annoying obstacles
- Linking completeness scores to business outcomes
Dashboards and reports are also powerful teaching tools, highlighting where improvements are needed and where teams are doing the right things.
Align training with governance
Data governance will only work if everyone understands it and why it’s crucial. Your post-implementation training should clearly explain:
- Who owns which data
- How approvals work
- How new attributes or categories are introduced
- What happens when standards change
- How exceptions are handled
If the governance framework is transparent, it will enable clarity among users, rather than turning into a source of friction. Good training both demystifies the rules and builds trust in the system.
Build a network of PIM champions
It’s unfeasible for central teams to support every user ad infinitum. That’s why a provenly effective approach is to establish PIM champions within departments or regions.
What do PIM champions do?
- Provide first-line support
- Reinforce best practices locally
- Help onboard new users
- Feed usability issues back into improvement cycles
- Promote consistent standards
Training these champions in greater depth enables you to create a scalable support model as well as reducing user dependency on IT or external partners.
Learning is embedded in daily work
Again, thinking back to our own learning experiences. We probably found that the most effective training isn’t delivered in seemingly endless theory-heavy sessions but by being embedded into our everyday activity.
Putting this into practice, typical techniques include:
- Contextual help within the PIM interface
- Short video walkthroughs for specific tasks
- Clear documentation linked to attributes and workflows
- Regular tips or data quality reminders
- Using dashboards to highlight improvement areas
Using this approach allows you to ‘walk the walk;’ in terms of offering continuous learning, and all without disrupting productivity.
Measuring, adapting, and evolving
Treat post-implementation training as a living, ongoing, rolling programme.
You can establish useful KPIs like:
- Data completeness and accuracy scores
- Reduction in manual corrections
- Faster product onboarding
- Fewer “how do I?” support requests
- Increased use of advanced features
By regularly reviewing these metrics, you’re in a better position to refine training content where needed, as well as identifying new skills and knowledge needs as the business’s circumstances evolve.
Final words
By focusing on role-based learning, clear governance, continuous feedback, and embedded enablement, you can protect data quality, drive adoption, and ensure the PIM platform, in which you’ve invested money and expectations, delivers value which lasts well into the future. Teams who are well-trained are those that have the confidence and competence to turn PIM from being an excellent technical platform into a truly enduring competitive capability.
If your PIM is live but adoption, data quality, or confidence is in the doldrums, get in touch with us today at Start with Data. We’re seasoned experts in supporting organisations with post-implementation training, governance frameworks, and ongoing enablement – in fact, all the elements to guarantee that your PIM will deliver real value to your business in the long term.