PIM Implementation: Project Plan, Requirements and Checklist

A PIM implementation brings together product data, responsibilities and technical integration. A useful project plan therefore defines more than the software launch date. It specifies which products and channels are included at launch, who owns the data and how the team will assess a successful handover.

This guide from apollon, the provider of OMN PIM, covers six phases. It includes concrete deliverables, examples of testable requirements and a checklist to transfer into your project plan. The sequence is a planning aid; activities can overlap and are tested in the pilot.

For the full background on data model, migration, interfaces, roles and costs, see the PIM implementation guide.

Jump to: Project phases · Requirements · Time and budget · Checklist · FAQ

When a PIM implementation makes sense

A PIM can help when product information needs structured maintenance across channels, languages or teams. Start by identifying where work or errors actually arise:

• The same technical value is maintained in several files and reaches the shop, data sheet and trading partner in different versions.
• Launching a channel requires people to find, rename or supplement information repeatedly.
• Variants, images and documents cannot be linked reliably.
• Approvals depend on individual people, and the current approved data cannot be identified clearly.

Collect concrete examples. A high return rate alone does not demonstrate a product-data problem. Check whether incorrect dimensions, unclear variants or missing information actually contribute. For a limited need, clearer responsibilities and improvements to the existing process may be sufficient.

The fundamentals of Product Information Management help define the scope. The decision to add a system should follow from the workflows you need.

The PIM project plan in six phases

Use the phase deliverables as checkpoints for the next increment. Record open decisions and assign an owner to each.

Phase 1: Define objectives, scope and the business case

Describe the problem through a workflow, such as approving a new product variant for the shop. Measure current effort, waiting time and corrections. Define what should improve and how you expect the volume of data to develop.

Set the initial scope: product groups, variants, languages, channels and connected systems. Record what will follow later as well. The project lead, business owners and budget owner should share the same understanding of the launch scope.

Deliverable: an agreed project brief covering baseline measurements, objectives, responsibilities, scope and open assumptions. A savings target is initially a hypothesis to test in the pilot.

Phase 2: Assess data sources and quality

Select representative products: simple items, variants, sets, incomplete supplier records and language-specific content. Map where identifiers, technical attributes, text, images and documents are stored. Record duplicates, inconsistent units, missing required information and unresolved media usage rights.

Identify the authoritative system for each data area. For example, an import must not accidentally overwrite approved marketing copy in the PIM with an older supplier version. Document how items are created, changed, blocked or discontinued.

Deliverable: a source inventory with data owners and a prioritised list of data issues. Missing values remain visible as gaps; plausible guesses do not replace them.

Phase 3: Design the data model and maintenance process

Define the product hierarchy, variant relationships, attributes, data types, units and permitted values. Separate requirements by product group, language and channel. A field can be required for one channel without being appropriate for the entire assortment.

Clarify roles too: who supplies a value, who may change it, who checks its accuracy and who approves publication? Specify which checks must be repeated when approved data changes.

Deliverable: a documented data model and maintenance/approval workflow that the team has tested with the selected products. Assess the technical limits of candidate systems early; the model should remain connected to implementation feasibility.

Phase 4: Evaluate systems against your requirements

Turn the findings into a requirements catalogue. Separate essential functions from later extensions and add a test case for important requirements. Ask vendors to demonstrate the same workflow with your sample data: import, correct, approve, publish and propagate a subsequent change.

Also assess roles, logging, data export, operations, support, included modules and integration services. A successful export during a demo does not yet prove that the production channel can process the data.

Deliverable: a documented evaluation with evidence, open issues and effort estimates. Our PIM software comparison adds selection questions; as a PIM vendor, we also discuss our own solution.

Phase 5: Implement the pilot, integration and migration

Implement a bounded workflow from the source system through to the target channel. Keep the pilot small enough to investigate errors while including important exceptions. Test identifiers, field mapping, units, variants and media relationships.

Migration requires a trial import, record-count reconciliation, documented transformations and a process for subsequent changes. For interfaces, also test rejected records, interrupted transfers and repeated runs. Define who receives and resolves errors.

Deliverable: a documented test run with business validation in the receiving system, resolved issues and a plan for the actual data transition. Imported does not yet mean complete, correct or approved.

Phase 6: Accept, launch and hand over to operations

Agree acceptance criteria and owners before go-live. Ask future users to carry out typical maintenance tasks. Determine whether open defects block launch, who can approve exceptions and what fallback is available if the transition fails.

Plan training, support, continuing quality checks and interface maintenance. After launch, compare the same workflows and metrics with the baseline. Schedule further channels and product groups as additional increments.

Deliverable: documented acceptance and named operational responsibility. The implementation can be completed as a project; data maintenance and development continue.

Data model: a concrete variant example

Simplified planning example, not a customer case: A manufacturer sells a product family in several sizes and colours. One description applies to the family, while dimensions and item numbers differ by variant. An image shows one particular colour; installation instructions apply to several variants.

This raises at least the following data-model decisions:

• Which information belongs to the family, and which to the sellable variant?
• Which values can be inherited, and which require individual maintenance?
• How are images, documents and their applicability linked to the right product?
• Which texts differ by language or channel?
• What happens to approvals and published outputs when a dimension or document changes?

Keep internal product structure, external classification and exchange format distinct. ETIM and ECLASS classify or describe products; BMEcat is a catalogue-data exchange format. Agree which version and format a trading partner requires. ETIM International also describes ETIM xChange as an exchange format, so “ETIM always requires BMEcat” would be too broad.

Background: ETIM classification, ETIM exchange formats and the ECLASS standard.

Write PIM requirements that can be tested

“Interface available” or “improve data quality” is too vague for acceptance. Add the triggering event and the expected outcome. These examples are test ideas for your requirements catalogue, not promised features of every PIM system.

Set project-specific thresholds for completeness, transfer time and acceptable error counts. Check factual accuracy separately: a completed field can still contain the wrong value.

Plan time and budget on an explicit basis

Product count alone does not establish a reliable project duration. Variant complexity, data quality, integrations, approvals and available staff all matter. A blanket estimate such as “5,000 products means two to four months” does not replace an effort assessment.

For each work package, define the deliverable, owner, required participation and dependencies. Separate effort from elapsed time: a business approval may take little working time but still delay the next task. Review assumptions after the pilot and adjust the remaining plan.

For the budget, include software, configuration, data cleansing, migration, interfaces, training, internal work and ongoing operations over the same period. Identify included services, options and work charged by time. The largest cost item depends on the particular project and contract.

Our guide to PIM pricing and Total Cost of Ownership provides a calculation framework. This checklist helps define the scope needed for comparable offers.

Seven mistakes to address in your project plan

1. Choosing a vendor without clear requirements: describe the workflow you need and check technical feasibility early.
2. Transferring data without quality checks: make problematic records visible before and after migration.
3. Leaving responsibility unclear: assign business data ownership, system operations and approval explicitly.
4. Using only simple products in the pilot: include relevant variant and failure scenarios.
5. Making the launch scope too broad: prioritise requirements and plan later extensions separately.
6. Training only after the switch: let users test real tasks beforehand.
7. Accepting the result only inside the PIM: check processing in the target channel and the subsequent operating process too.

This list identifies project risks. It is not a statistically established ranking of the most frequent mistakes.

Your PIM implementation checklist

Transfer these items to your project tool and add an owner, due date, evidence and status for each. “Discussed” does not replace a documented result.

• Objectives and scope: the baseline problem, metrics, initial assortment, languages and channels are agreed.
• Business case: benefit assumptions, cost items and internal capacity are documented.
• Data inventory: sources, identifiers, quality gaps and authoritative systems are recorded.
• Data model: product hierarchy, variants, attributes, units and channel rules have been checked.
• Responsibility: data supply, maintenance, business validation and approval have owners.
• Vendor evaluation: essential requirements, test cases, scope and open issues are documented.
• Pilot: representative products, exceptions and a complete path to the target channel are defined.
• Integration: mapping, changes, error handling and responsibilities have been tested.
• Migration: trial transfer, reconciliation, subsequent updates and fallback procedures are prepared.
• Acceptance: business outcomes, error thresholds and approval responsibility are agreed.
• Users: training, tasks and launch support are planned.
• Operations: support, quality checks, metrics and the next increments have owners.

Frequently asked questions about PIM implementation

Clarify these questions before commissioning the work and record the answers for your specific project scope.

How long does a PIM implementation take?

A reliable duration depends on scope, data condition, interfaces and available staff. Plan work packages with acceptance criteria and review the estimate after a representative pilot. Product count alone is insufficient for a delivery forecast.

What does implementing a PIM system cost?

Include the licence or subscription, implementation, data work, integrations, training and operations, including internal effort. Compare offers over the same scope and period. A blanket claim that the licence is always the smallest cost item would not be reliable.

Where should I start with a PIM project?

Start with a concrete workflow problem, a limited initial scope and a data inventory. Use these to develop requirements and test cases. Assess technical feasibility and system options accordingly.

Do I need a PIM if I already have an ERP?

Not automatically. Check whether your existing system adequately supports the required enrichment, variant maintenance, media relationships, approvals and channel output. A PIM can complement these tasks; you must define which system owns each data area.

Can I introduce a PIM in stages?

Yes, for example by starting with one product group and one target channel. The pilot should also cover relevant exceptions. Plan shared data and interfaces so that later increments can build on them.

When is the PIM project ready for go-live?

When the agreed business and technical acceptance criteria are met, critical defects are resolved and users and operations are prepared. A successful import or completed installation alone is insufficient.

Assess the project scope with your own data

OMN PIM by apollon supports central product-data maintenance, rights and roles, quality checks and connections to media and output channels. The modules, interfaces and project services you need are determined by your scope.

An overview of your data sources, desired channels and a few representative products provides a useful starting point for a conversation. It helps establish which workflows to demonstrate and which open issues to assess before preparing an offer.

Request a demo for your planned PIM project