Preparing your PIM project in advance using the Quable and Datal approach ensures a successful roll-out

A PIM (Product Information Management) project is not simply about the technical roll-out of a new tool: above all, it is about transforming and adapting the organisation and management of product information. That is why success is achieved when the PIM system becomes second nature, seamless and useful for everyone, well beyond the project itself.

At Quable, a provider of PIM & DAM solutions, and Datal, a brand specialising in data projects, we share the conviction that a successful project relies above all on rigorous preparation and a clear vision of business objectives.

Going far beyond the project specifications, it’s about preparing all business and technical teams for change, because behind the tools, there are people.

In this article, we’ll share our combined experience to help ensure the complete success of your PIM project.

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In practical terms, why are you launching a PIM project?

It is crucial to understand why a PIM is necessary:

• To save time in organising, centralising and searching for product data
• To reduce reliance on Excel spreadsheets
• To minimise errors in data entry and updates
• Expand into new channels and new markets
• Automate the production of marketing materials

Listing all the general pain points will help to define the key actions to be taken when rolling out the PIM solution. This list will enable us to challenge the issues and understand their causes alongside the business teams.

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Involve the right stakeholders and establish the right organisational structure from the outset

A PIM project is successful when all stakeholders are involved, as PIM solutions are strategic and cut across the organisation.

Based on projects it has carried out, Datal recommends appointing key, committed individuals:

• A project manager: their role will be to lead, organise and plan tasks, monitor deadlines and manage the budget.
• A business liaison officer for each department – such as procurement, marketing or communications – to centralise actions and decisions so they can be shared with other staff members.
• A technical lead: a key figure in guiding technical choices and resolving constraints.
• The Managing Director: to communicate key information. This will also enable updates on the project’s progress and KPIs to be shared.

This varies depending on the company, but here is the ideal team for a PIM project. Beyond the core team, it is essential to be able to share information via project committees.

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Assessing, supporting and understanding the business teams

First and foremost, a comprehensive analysis of business pain points, limitations and requirements is essential. Depending on the company, the following stakeholders are generally involved:

• Marketing: to adapt, enrich and classify products across the various channels.
• Communications: to list the media and files used in production.
• Purchasing: to share data sent by suppliers and current constraints.
• IT: to list current tools, their performance and any limitations encountered.
• Suppliers: essential if they can, in future, automate and facilitate the transmission of data to the new solution.
• Customers: they are best placed to provide you with concrete, constructive feedback on the state of your data and products.

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Audit the current data model and build the future foundation

For Datal, this phase – which is very often overlooked – is nevertheless the one that will save a considerable amount of time during the solution’s integration.

Indeed, there are several questions that need to be addressed in order to properly frame a PIM project:

• What data needs to be integrated into the solution?
• What is the current data format? Does it pose any problems?
• Who is responsible for validation?
• How are products categorised across the various channels?
• What are the groupings and how are they organised?
• What are the associations?

Datal also recommends preparing an initial data dictionary, as this work is essential for listing attributes, their formats, their assignment to objects, their roles, and so on. Clients who start a PIM project with an initial data dictionary save over 50 per cent of the time required for data modelling.

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Anticipating workflows, integration and automation

A PIM is always part of a wider ecosystem: ERP, DAM, CMS, e-commerce, marketplaces, translation tools or print publishing tools.

Datal recommends mapping these workflows right from the preparation phase and understanding their current limitations in order to adapt the integration. This enables you to prioritise integrations, choose the right connectors and plan for data exchanges.

Quable, through its open API and native connectors, facilitates these integrations and ensures data consistency across the entire digital ecosystem.

And what about data migration? Indeed, today’s tools are already well established and contain data; the aim is to capitalise on this existing data. However, the data is often not ready for integration and requires standardisation; it is during this preliminary phase that we will define the strategy for data control and migration.

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Planning and managing the PIM project in a realistic and phased manner

Most PIM roll-outs completed in under six months rely on effective project management. So whether the approach is agile, waterfall or hybrid, the aim is to set the pace, challenge assumptions and steer the roll-out schedule.

At the outset, all project tasks must be defined: participation in workshops, contributions from buyers and marketing teams between workshops, development of data flows by the IT team, and adaptation of systems (ERP, e-commerce sites). Next, determine the time each contributor will need to spend on the project. The idea of a RACI matrix with time allocations can be useful, provided the tasks are clearly segmented.

And for day-to-day project monitoring, weekly management meetings with monitoring committees and coordination sessions are required. Beyond the methodology itself, active listening, transparent communication and a determination to keep moving forward are essential – in short, more than just ‘skills’ 😉.

All of this must be masterfully orchestrated to free up time for the teams and allow them to work calmly and efficiently; the aim is not to create additional difficulties.

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How Datal supports its clients

At Datal, our approach has been carefully developed based on feedback from the field and the integration projects we’ve carried out. This approach has been refined over more than five years through work on data and digital projects.

1. Understanding and analysing: interviews to understand current limitations. This is followed by a thorough and detailed analysis of your digital ecosystem, tools, data and roles to identify initial avenues for action.
2. Scoping and prioritising: through practical and objective workshops, Datal helps to define the scope and prioritise tasks, whilst also challenging assumptions using best practices in data management and drawing on real-world experience regarding usage patterns and the limitations encountered by other organisations.
3. Recommend and prepare: finally, the aim is to provide a comprehensive response to limitations and challenges through organisational and technical recommendations, whilst presenting and prioritising the action plan.

From the audit through to scoping, drafting the specifications and integrating solutions, Datal offers comprehensive support to help you maximise your ROI.

About Datal

Datal is an independent brand specialising in product data management projects (PIM, DAM, MDM) thanks to its cross-functional and versatile expertise. Datal supports businesses in three key areas: consultancy, solutions and performance, to align strategy, processes and technologies around reliable and controlled product data.

Through a pragmatic and results-oriented approach, Datal helps brands, retailers and manufacturers to take full advantage of their data ecosystem: project scoping, data structuring and integration, training and continuous improvement.

Contact Datal here

The aim: to make product data a genuine driver of efficiency, consistency and sustainable growth.