The supply chain landscape is undergoing rapid transformation, driven by technological advancements and evolving leadership paradigms. Enhanced human-machine interactions and Industry 5.0 technologies are significantly improving resilience and operational efficiency. Artificial intelligence is revolutionizing supply chain operations at an unprecedented pace. Today, organizations are increasingly empowering teams to harness the potential of AI, big data, and analytics to optimize daily operations and enable data-driven decision-making.
Despite significant efforts—including robust project management frameworks, stakeholder engagement strategies, and adoption roadmaps—most organizations continue to struggle with a 70% failure rate associated with large-scale, people-centric transformations.
A critical question arises: Are organizations overlooking essential data that could drive program success? How can change managers effectively harness the hidden potential of informal networks that exist beyond formal governance structures? While stakeholders such as subject matter experts (SMEs), core project teams, and change agents are explicitly defined in transformation models, it is essential to recognize the role of “invisible networks”—undocumented local influencers who maintain extensive social ties and can significantly impact change initiatives.
Organizational change is inherently dynamic, rooted in relationships and operating within contexts of uncertainty. Mapping these relationships is crucial, as it illuminates information flows and provides tangible measures of transformation success.
Case Study: Unstructured Influence in IBP Implementation
In a recent Integrated Business Planning (IBP) implementation for a global leader in the food and dairy industry, spanning three regions, the formal project structure faltered during the “Build” phase. However, key stakeholders emerged outside official roles—individuals not tagged as SMEs or change agents—who played critical roles in driving change impact analysis and influencing key design decisions.
When visualized through a social network lens, employees can be represented as nodes, with connection strength defining their relationships. These informal groups, developed through trust and shared affinities, represent untapped social capital. Through organizational network analysis (ONA), hidden structures can be uncovered, enabling companies to leverage their workforce strategically, enhance decision-making processes, and align interventions with cultural realities.
The Role of Network Theory in Change Management
Traditional governance models often focus on formal hierarchies; however, it is essential to identify informal connectors—individuals who bridge silos or control information flow within the organization. In the IBP case study, initial appointments of change agents were based on formal roles. By applying social network analysis and graph theory, peripheral influencers were discovered whose innovative behaviors and peer trust accelerated adoption efforts.
Key strategies for leveraging these networks include:
1
Enhancing Network Connectivity: Strengthening ties between isolated groups to foster collaboration and information sharing.
2
Leveraging Diversity: Integrating cross-functional insights to refine adoption strategies tailored to diverse stakeholder needs.
3
Building Trust: Engaging informal leaders through targeted communication efforts to amplify organizational commitment and support for change initiatives.
Best Practices for Harnessing Invisible Networks
1
Ethical Clarity: Clearly define network analysis objectives and methods to maintain transparency and stakeholder trust throughout the process.
2
Mixed-Method Rigor: Combine qualitative insights (e.g., interviews) with quantitative metrics (e.g., centrality scores) to validate findings and ensure comprehensive understanding.
3
Contextual Visualization: Utilize intuitive tools like sociograms to map networks effectively while interpreting results with nuance to avoid oversimplification or misrepresentation of data.
Organizations are far less rigid than traditional models suggest; viewing them as dynamic networks of relationships can unlock efficiencies, sustain meaningful change, and enhance adaptability. The future of transformation lies not only within formal structures but also in recognizing the invisible threads that bind an organization’s social fabric together.
Priya Doshi
Manager – OCM
Bristlecone
