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Change management - What are the challenges not to be overlooked in the adoption of Master Data Management #MDM?

Here are 5 of the most commonly overlooked challenges related to the adoption of master data, along with 5 simple steps to address MDM change management. 

When it comes to MDM adoption, most hurdles stem from a fundamental issue: the inability to assess your organization's readiness before starting the project.

It's essential to stay realistic about the state of readiness and prepare accordingly. This means: 

Assess openness and support within management (and those leading data initiatives throughout your organization) 

Our projects begin according to your maturity. We distinguish 2 dimensions. 

#1 Evaluer votre culture organisationnelle / Déterminer la maturité basée sur les données - Change management – Quels sont les défis à ne pas négliger dans l’adoption des données de référence #MDM ? - Blog - Opéra-Conseil

Many MDM projects start as an IT project. That’s okay: in fact, IT should be involved at every step. However, engaging business stakeholders too late can lead to a disconnect with real problems and desired outcomes.

The process must be facilitated by creating a regular cadence of discussion and collaboration throughout the process.

Businesses process enormous amounts of data, and this is growing every year. But not all data has the same value for your business. Additionally, while many realize they have data problems, they do not appreciate the full extent of the associated challenges and process gaps.

The key is to focus on the results of solving your toughest problems; then tailor your data management efforts to those areas.

For example :

  • Examine your processes and try to identify either gaps in the available data or the time and effort required to obtain the data needed to make a decision.
  • Then think about how to capture this information in different contexts and develop models to help decision-makers.
  • Think about what could happen in your industry over the next five years and how you can build confidence in your benchmark data to align with these trends.

One of the keys to MDM adoption is showing the value of the program to the business as a whole.

Data must flow seamlessly across the organization, with analytics capabilities built into the core business. This requires providing access to analytics capabilities and reporting with a platform through which users can easily access data.

Finally, many MDM projects fail because they are unnecessarily complex.

On the other hand, some projects omit features that many users consider essential to their daily work. The key is to find a balance and find the right approach.

One way to address this challenge is to assess the current mindset of your users.

  • Do you know what they think of the system currently in place?
  • Are there any custom features they plan to port over to the new system?
  • Do they understand the why of the MDM initiative?

The mindset assessment will help you set the stage for successful MDM adoption, as will the following five steps for approaching change management.

5 Steps to Start Your Change Management Process

Chaque initiative MDM doit commencer par la définition de vos résultats business. En d’autres termes, quels sont vos objectifs commerciaux de haut niveau et comment des données bien gouvernées et gérées de manière centralisée peuvent-elles vous aider à y parvenir ? La clé de ce processus consiste à formuler une stratégie de données.

Why is a data strategy so important for change management? Because it defines the people, processes, policies and culture that will guide your data initiatives. And it helps your users and business groups work in agreement and alignment, not in silos or opposition.

Then, once you have defined a data strategy, it can be helpful to identify and select an MVP (minimum viable product) that meets your most relevant business outcomes. You can quickly deploy your MVP to show the value of the MDM program.

Consider the impact and risks to your data, processes and systems. Don’t forget to get feedback and suggestions from IT and business stakeholders.

Also, be sure to document and plan expenses in your budget.

Determining ownership is a crucial step.

A simple step is to designate an MDM project owner and sponsor.

These champions will lead the project, remove barriers to adoption, gather support, and make final decisions.

Be sure to create a reasonable schedule and communicate the rationale to business and IT stakeholders. If your MDM launch timeline is too short, you risk not preparing your organization and users. If it’s too long, you risk overwhelming and exhausting the team.

If you know your risks and establish ownership, it should be easier to determine a reasonable schedule that incorporates testing and adequate training without causing tension.

Don't forget: you don't need to manage all your data, for every part of the business, all at once.

Many companies wisely choose to start on a smaller scale, then scale up implementation over time to encourage enterprise adoption.

Having an application that incorporates change management and training is a good start, as it facilitates expanding adoption across multiple business departments, geographic areas, and beyond.

While it's prudent to consider everything that could go wrong (i.e., your risks or challenges), it's also important to remember all that can go right. Adopting a new MDM system should be an exciting time for your business, and it can be when you take concrete steps for successful change management.

L’implication des métiers au cœur des projets de gouvernance des données est essentielle. - Change management – Quels sont les défis à ne pas négliger dans l’adoption des données de référence #MDM ? - Blog - Opéra-Conseil

Opéra implements a specific change management process

  • Corresponding to your maturity
  • Transversal Empowering
  • Identifying the actors and responsibilities
  • Involving a data culture
  • Have a reference for defining your business objects
  • In terms of ROI, the intangible capital that is reference data to controlled quality is important
  • Overhaul (and centralize) business processes – allowing, if necessary, to move towards a Business Process Management approach…
  • Finally being able to have a 360 vision of your business objects through the IS

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