Managing Change Successfully in a Collaborative Workspace

This article is a response to the series of posts from Oleg Shilovitsky about Rethinking Change Management. It argues that a collaborative workspace is more effective than the classic file check-in/check-out mechanism for managing changes.

• Part 1: Orchestrating Complexity Across Systems & Disciplines – (Collaborative Workspace)
• Part 2: From Check-Out/In to Collaborative Processes, Single Source of Truth
• Part 3: Coexistence of New Architectures with Legacy PDM/PLM File-Based Revision Control
• Part 4: PLM Collaborative Workspace Technical Architecture and Sample Workflow

The idea of a collaborative workspace is not new. Google introduced this with their Google Docs and later Microsoft followed with their Microsoft Office. However, with these advancements come new challenges, especially in managing change to product design information across diverse teams and ensuring the integrity of configuration information. In this article, we will explore the complexities of collaborative workspaces and how they can be optimized to ensure configuration information integrity, while not losing the efficiency gains that come with these workspaces.

Challenges in Managing Collaborative Workspaces

Diverse Teams and Disparate Systems:
One of the most significant challenges is orchestrating changes across multiple teams, each using different tools and systems. Mechanical, electrical, and software teams often operate in silos, which can lead to misaligned decisions and inefficiencies. Not to mention a lot of corrective actions to fix all the problems.

Data Integration and Consistency:
Ensuring that data remains consistent and accurate across various systems is not an easy task. Traditional Single Source of Truth (SSOT) models struggle to keep pace with the complexity of modern products, leading to synchronization issues and data silos. On top of that, data is often duplicated in various databases for performance reasons, which increases the risks of synchronization issues across the IT landscape of an organization.

Real-Time Collaboration:
While collaborative workspaces enable real-time updates, they also require robust mechanisms to handle concurrent changes. Without proper controls, simultaneous edits can lead to conflicts and data corruption. People might unknowingly undo changes of a colleague, which can cause serious issues downstream when this goes unnoticed. And what about support for offline work and synchronizing when coming back online. This requires the management of collisions of changes made by different people when synchronizing.

Change Impact Analysis:
Impact analysis of changes is becoming more complex when people can concurrently modify the design information. Most (if not all) impact analysis is based on the latest released. However, with a workspace that allows concurrent changes, managing the changes that are going to be in work needs to be coordinated to ensure you end up with a working product. As products become more intricate, the impact of changes can ripple across the entire organization. Accurately predicting these effects would help minimize disruptions and ensure smooth transitions from one approved snapshot to the next.

Planning
When you concurrently change your design documentation, you will need to ensure that when you create and release a new snapshot, it is complete and results in a working product in the end. This requires planning, not just implementation planning of individual changes, but the planning of the configuration you want to achieve and the effectivity that goes with the new snapshot.

Workflows and Traceability:
Managing approvals in a collaborative environment necessitates transparent and traceable workflows. Ensuring that all changes are properly reviewed and documented can be a bureaucratic nightmare without the right tools and integrations. In a collaborative workspace, you still want to control which changes get implemented and which ones do not. There needs to be a way to verify if the changes done are in line with the approved change requests.

Ensuring Consistency and Integrity of Configuration Information

To tackle these challenges, the organization and its people must adopt a different mindset when it comes to collaboration, planning, and implementing changes. This will not happen overnight, but to enable them to achieve the desired results, several technologies and best practices need to be implemented as well:

Flexible Data Models:
Embrace data models that accommodate the diverse needs of different stakeholders. Contextual representations of data, such as the use case based knowledge graphs based on a unified Enterprise Knowledge Graph, enable tailored views that simplify complex datasets.

Federated Change Architecture and Unified Enterprise Knowledge Graph:
Rather than centralizing all data, adopt a federated approach that connects multiple systems while maintaining a unified view through an Enterprise Knowledge Graph. This architecture allows for real-time changes across different domains without compromising data integrity. And provides a solid foundation for machine learning and applying AI to improve efficiency and integrity.

Robust Workflows:
Implement workflows that support both structured and ad-hoc processes. These workflows should facilitate seamless routing and approval of changes, ensuring traceability and accountability. Instead of expecting everyone to know how the change management tooling works, the tools must be able to guide the user on their change journey.

Real-Time Synchronization and Offline working:
When online, all changes should be synchronized instantly. This eliminates discrepancies and ensures that everyone is working with the most up-to-date information. However, it is not always possible to work online or there are synchronization issues that need to be fixed, this requires a robust way to synchronize the changes at a later stage and be able to deal with the collisions that can occur with other changes made by different people.

CM Baseline Management:
Next to having immutable snapshots of product data (as suggested by Oleg), you need to have a view of all the planned changes as described in my series on the CM Baselines. These baselines provide a reference for tracking changes and maintaining consistency over time. And can help prevent collisions when working on multiple changes at the same time.

Conclusion

The move to collaborative workspaces in change management is not just a technological evolution; it’s a strategic approach that can bring more innovation and efficiency to organizations. But like with every major change in technology, it requires people to embrace this change and tools that ensure the integrity of the product design information as well as robust but flexible processes to accommodate this new way of working. If not addressed appropriately, this change can break more than it brings.

What do you think?