Change Management Best Practices for a MES Implementation

Technological developments in advanced analytics, cloud computing, and AI-enabled automation continue to shape Manufacturing Execution Systems (MES). These capabilities are changing how businesses operate, helping to optimize production processes, ensure quality control, and maximize efficiency.

Implementing a strong MES solution can be a game changer, enabling organizations to put those capabilities into practice. Whether you’re integrating an MES solution into an existing infrastructure or starting from a greenfield environment, your implementation will be a complex journey involving not only meticulous planning and execution but also deliberate organizational change management considerations.  

Because an MES implementation can change how employees work and interact with the production processes, change management should be considered throughout the implementation – not just at the end. Below, we outline our top six change management best practices for an MES implementation.

Change Management Best Practices for a MES Implementation

1. Comprehensive Requirements Gathering + Cross-Functional Collaboration 

Begin your MES journey by thoroughly analyzing your organization’s unique requirements and identifying key pain points and areas for improvement. This analysis forms the foundation for a tailored MES solution that addresses your organization’s specific needs and challenges. They’re also imperative to selecting the appropriate MES vendor.  

An effective MES implementation also demands collaboration across multiple departments and partners. Engaging representatives from all key functions affected by the implementation can enable a more holistic understanding of requirements while facilitating stronger adoption across the organization.  .

2. Clear Communication + Comprehensive Training

Throughout an MES implementation, transparent communication helps stakeholders understand how the change will affect their work. Engaging stakeholders early and addressing their needs and concerns – as well as explaining the potential benefits – can build greater support for the implementation. Just as importantly, employees need to understand “the why” the change is happening and what it means for their role.

Clear communication also fosters understanding and alignment among stakeholders, ensuring a shared vision. Empowering your workforce is essential, and often this empowerment is delivered via customized, role-based training that can show team members how the MES will support their specific responsibilities. Involving cross-functional teams in training promotes collaboration and knowledge sharing and can also help to avoid a siloed rollout.

3. AI Governance + Guardrails  

AI-enabled capabilities are increasingly being incorporated into MES implementations, using real-time data to drive predictive analytics and enable operational efficiency while building data trust amongst stakeholders. Effective integration of these AI-enabled MES capabilities depends on clear governance and guardrails, including establishing appropriate use and decision ownership along with expectations for human oversight, data security, and accountability. These measures can help ensure AI recommendations are transparent, trusted, and aligned with the organization’s operational requirements, including applicable quality and regulatory expectations.

4. Change Champions Support Networks 

It’s crucial to system and process adoption to identify change champions within your organization This is your power team of functional experts who are equipped with in-depth knowledge of business processes and associated data, allowing them to serve as super users, mentors, and leaders of a broader support network. Change champions can create a sense of community and help ease concerns throughout the various project phases, including testing, training, and go-live activities. They can also support training as employees prepare for new ways of working.

For AI-enabled capabilities, change champions bridge the gap between AI-powered features and day-to-day operations. They build trust in the new tools, reinforce proper human oversight, gather feedback, identify opportunities for further high-value AI use cases, and help scale innovation more widely. As AI capabilities evolve, change champions can also help identify additional use cases and support adoption across the organization.

5. Post-Implementation Support 

A scalable and modular MES solution allows for a phased implementation, if appropriate, for your organization, helping to reduce disruption as teams adapt to the new system. Whether organizations launch with a phased or “big bang” approach, post-implementation support is crucial and should be defined before go-live.

To help assist in the transition to a live system and new ways of working, a detailed hyper-care plan should be created. Change champions can support this transition through mechanisms such as dedicated help desks or supplementary training. Organizations should also establish ways for users to provide feedback and use that input to identify potential areas for improvement.  By providing this additional level of support, you will continue to build trust among your end users as they become accustomed to the MES.

6. Continuous Improvement  

After go-live and the initial hypercare period, your organization needs to treat optimization as an ongoing effort. As MES platforms become more cloud-connected, AI-powered, and data-driven, it’s important to consider how the system should evolve with changing business needs. Increasingly often, MES systems are integrated with other key business enterprise applications, making it equally important to coordinate improvements across end-to-end processes.

Continuous improvement can include establishing feedback loops, monitoring adoption and performance metrics, and refining workflows and system capabilities over time. Training should also evolve as your business’s needs change or as new capabilities are introduced. Establishing a Center of Excellence to drive continuous improvement, monitor user adoption, and meet the evolving needs of the business is a key enabler to any organization to maximize the benefits of MES.

Embracing Change Management During Your Implementation 

MES implementations bring a multitude of challenges that organizations can overcome through a strategic approach that focuses on change management from day one. This includes gathering comprehensive requirements and maintaining transparent communication across functions. Organizations should also establish a change champion network and define appropriate governance for AI-enabled capabilities.

But these considerations don’t just end at go-live. Post-implementation support can help users adjust to the new system, while ongoing communication provides a way to surface concerns and feedback. Organizations can then use adoption monitoring and feedback loops to inform continuous improvement over time.

Learn more about our change management consulting and MES consulting services. 

Contributions from Aley Saleh and Spencer Simco

Human-created: This content was ideated, drafted, edited, and approved by a human. AI use, if any, was limited to incidental support.