Hidden Influence Networks In Your Workplace

70% of change initiatives fail to deliver their promised business benefits (McKinsey, 2024). This is the current trend, and no, this is not referring to underperforming initiatives or initiatives that take longer than expected. This is the percentage of initiatives that Fail completely.

While you are studying organisational charts and mapping formal reporting lines, the people who will actually determine your transformation’s success or failure are operating through an entirely different network. A network that does not appear on any diagram you have seen.

This is neither a technology problem nor a strategy problem. This is a fundamental influence problem that most organisations are completely unprepared for.

While leadership teams focus on communication cascades and training programmes, the people who will make or break adoption are asking themselves much deeper questions:

• Who in my actual work network thinks this change will help us?
• Which colleagues I trust are excited about this, and which are sceptical?
• Who do I go to when I need real advice about whether something is worth the effort?
• If I struggle with this, who will actually help me figure it out?

Here is the thing that should concern us: these informal influence networks are invisible to traditional change management approaches. Yet research from Harvard Business School, tracking 68 change initiatives across the UK’s National Health Service, proves they are the single biggest predictor of adoption success or failure.

Where Traditional Change Management Is Falling Short

Most organisations are treating adoption like a communication and training challenge. Which involves:

• Mapping formal authority structures and reporting lines
• Designing communication cascades from leadership down
• Creating comprehensive training programmes for new capabilities
• Establishing project steering committees and governance structures
• Expecting adoption to follow logical, hierarchical patterns

But influence does not flow down org charts.

Unlike previous organisational changes that primarily affected processes and procedures, think new expense systems or updated reporting structures, today’s transformations directly challenge something much more fundamental: how people actually get work done and who they trust to help them succeed.

Recent research from Deloitte reveals a staggering disconnect: 79% of leaders recognise their responsibility to create value for workers, but only 27% of workers feel their employers are making meaningful progress (Deloitte, 2024). This gap exists because formal change approaches miss the networks where real influence operates.

When you implement a new system, people might resist because of workflow disruption. When you implement a fundamental change in how work gets done, people resist because their trusted advisers, work allies, and influence sources are sending mixed signals.

The Hidden Influence Barriers:

Network Isolation: Change champions identified through formal hierarchy may have limited influence in the informal networks where daily decisions get made.

Conflicting Signals: Mixed messages from informal influencers create uncertainty that traditional communication cannot overcome.

Trust Gaps: People trust colleagues with whom they have genuine working relationships more than formal authorities, regardless of title or position.

Invisible Resistance: The most influential resistance often comes from respected informal leaders who are never identified by traditional change planning.

Traditional change management was not designed for these challenges. You cannot communicate your way past fundamental trust and influence realities.

Some Organisations Are Getting It Right

Despite widespread adoption failures, some organisations are achieving remarkable 90%+ adoption success rates. Not through better technology or bigger training budgets, but by acknowledging that adoption is fundamentally a network influence challenge.

What they are doing differently:

Success Pattern 1: Network Intelligence Before Change Design

Rather than starting with formal stakeholder analysis, these organisations map actual influence networks first. They identify who people really go to for advice, who gets early sight of new information, and who others watch to gauge whether something is worth their attention.

Example: A financial services firm implementing new AI-powered analytics tools started by surveying employees about their actual information networks: “When you need to understand whether a new tool is worth using, who do you ask?” The results revealed that influence was concentrated in 15 people across different departments, only 3 of whom appeared on the formal project stakeholder map.

The message was not “use this because leadership says to.” The message was “the people you trust most have tested this and here is what they discovered.”

Success Pattern 2: Boundary Spanner Strategy

MIT research tracking technology adoption across 2,118 employees found that adoption by boundary spanners, people who connect different groups has exponentially greater impact than adoption by formal managers (Tucker, 2008). Organisations getting adoption right identify and prioritise these connectors.

Example: A healthcare system implementing new patient management technology identified nurses who regularly collaborated across departments, administrative staff who coordinated between clinical and operational teams, and senior consultants who influenced both peers and juniors. Result: 87% adoption within 6 months compared to 34% in divisions that focused only on department heads and formal training.

The strategy was not “train managers to cascade information.” The strategy was “ensure the people everyone actually talks to understand the value and can help others succeed.”

Success Pattern 3: Authentic Network Engagement

Harvard’s study of 68 NHS change initiatives revealed that successful change agents had one critical characteristic: they maintained genuine relationships across the informal network, including with people who were initially resistant (Battilana & Casciaro, 2013).

Example: A retail organisation implementing new customer service protocols identified that their most influential adoption accelerator was a store manager who had built genuine relationships with sceptical long-term staff. Instead of avoiding resistance, he engaged directly: “I understand why this feels unnecessary. Let me show you how it actually makes the difficult customers easier to handle.”

This level of honesty actually increased adoption rates by 65% because people trust authentic engagement over corporate messaging. People can handle difficult truths much better than they can handle feeling patronised or misled.

The Network Advantage

Organisations that successfully navigate complex change share one critical characteristic: they have built network-aware adoption capability.

Network-aware adoption is not just about identifying informal leaders. It is about developing the organisational intelligence to understand how influence, trust, and adoption actually flow through your people, regardless of formal structures.

Key Capabilities (5 Elements):

1. Network Intelligence Understanding who influences whom in practice, not just in theory. This includes mapping information flows, advice networks, trust relationships, and early-adopter communities within your organisation.
2. Influence Strategy Designing adoption approaches around actual influence patterns rather than formal authority structures. This means engaging the people others watch and trust, not just the people with titles.
3. Boundary Spanning Identifying and empowering the connectors who naturally bridge different groups, departments, and perspectives. Research shows these individuals have disproportionate impact on organisation-wide adoption.
4. Network Communication Creating information flows that leverage natural relationship patterns rather than fighting them. This includes peer-to-peer sharing, informal mentoring, and colleague-to-colleague success story transmission.
5. Relationship-Based Support Providing adoption support through trusted connections rather than solely through formal channels. When people struggle, they want help from colleagues they know and trust, not anonymous helpdesks.

Building Network Intelligence Requires a Different Approach

You cannot mandate network awareness. You cannot train someone into informal influence in a two-day workshop.

But you can create the conditions where network intelligence develops naturally.

Approach 1: Network Mapping Before Implementation

Instead of assuming formal stakeholders represent actual influence, map the real advisory networks first. Survey people about who they actually ask when they need to know whether something is worth doing. This reveals influence patterns invisible to organisational charts.

When people understand the broader network context of change, they are more likely to see individual adoptions as informed decisions rather than corporate mandates.

Approach 2: Boundary Spanner Identification and Engagement

Research consistently shows that people who naturally connect across groups, departments, or hierarchical levels have exponentially greater influence on adoption than formal authorities. Identify these connectors and ensure they understand, experience, and can advocate for the change before broad rollout.

This works because people trust colleagues who bridge their world with others more than they trust managers when it comes to practical advice about whether new approaches actually work.

Approach 3: Network-Based OKRs

Instead of measuring adoption through system usage statistics, measure it through network engagement indicators.

Consider establishing OKRs (Objectives and Key Results) that focus on relationship-based adoption rather than just compliance:

Objective: Build network-driven adoption momentum for [transformation]

• Key Result 1: 80% of identified boundary spanners can demonstrate value and help others succeed
• Key Result 2: 60% of departments have peer-to-peer success story sharing happening naturally
• Key Result 3: 75% of employees can name a trusted colleague who uses the change successfully
• Key Result 4: 90% of adoption challenges are resolved through colleague assistance before formal support

These network metrics tell you whether you are building sustainable adoption or just forcing surface compliance.

The Practical Steps That Make the Difference

Building network intelligence is not abstract. Here are the specific actions that successful organisations take:

1. Network Survey Implementation Survey employees about their actual advice networks: “When you need to understand whether a new approach is worth adopting, who do you talk to?” and “Who in this organisation do you watch to see how they handle new challenges?” Map these responses to identify true influence patterns.
2. Boundary Spanner Analysis
   Identify people who regularly interact across departments, hierarchical levels, or functional areas. These connectors often have informal influence that exceeds their formal authority and can accelerate adoption across organisational boundaries.
3. Influence-First Pilots Run initial pilots with identified network influencers and boundary spanners first, regardless of their formal roles. Ensure they experience genuine value and can articulate benefits in language their networks understand and trust.
4. Peer-to-Peer Success Documentation Create mechanisms for informal influencers to share their adoption experiences with their natural networks. This includes success stories, practical tips, and honest acknowledgment of challenges they overcame.
5. Network Support Integration Embed adoption support within existing trust relationships. Train network influencers to provide initial help and guidance, creating adoption assistance that feels colleague-to-colleague rather than corporate-to-employee.

The Competitive Advantage of Network-Aware Adoption

Organisations with network intelligence do not just handle current transformations better. They handle all future changes better.

Recent AI adoption data reveals this advantage clearly: organisations tracking informal networks alongside formal rollouts are achieving 78% adoption rates compared to 34% for traditional approaches(Worklytics, 2024). When Generative AI tools arrive, they adapt faster. When new regulatory requirements emerge, they pivot more effectively. When market opportunities demand different capabilities, they can move quickly to capture them.

Strategic Investment: The companies that invest in building network intelligence today are not just preparing for current change challenges. They are building the organisational capability that will determine their long-term success in an increasingly dynamic market environment.

The reality is: your current transformation is not the last major change your organisation will face. It is just one of many.

Three Immediate Actions

The research is clear: organisations that invest in understanding their informal networks are 3-5 times more likely to achieve successful adoption (Harvard Business Review, 2013). You do not need to wait for the perfect methodology or comprehensive network analysis tools.

1. Informal Influence Audit This week, identify 10 people in your organisation who others naturally ask for advice about whether new initiatives are worth supporting. Interview them about their concerns and excitement regarding your current change. These conversations will reveal influence dynamics invisible to formal planning processes.
2. Boundary Spanner Engagement Map people who regularly work across departments, connect different levels of the organisation, or bridge internal and external relationships. Ensure these natural connectors experience your change first and can provide authentic peer guidance to their networks.
3. Network Success Measurement Establish tracking for relationship-based adoption indicators alongside traditional metrics. Measure peer-to-peer help, colleague recommendations, and informal success story sharing. Ask: “How did you learn to use this successfully?” Track answers that include colleague names versus formal training.

Goal Clarification: The goal is not to create perfect network maps; that is impossible and unnecessary. Your goal should be to build teams that leverage natural influence patterns, transforming hidden resistance into visible advocacy and isolated initiatives into network-powered movement.

This Challenge Is Not Going Away

Most organisations are still approaching adoption like a training and communication problem. They focus on content delivery and hoping for the best. But the research shows us something different: the organisations succeeding with complex change understand it is fundamentally a network influence challenge.

Building network intelligence takes time, but the alternative is watching your transformation investments fail while your people struggle with each new wave of change. The companies that start building this capability now will find every future transformation easier, faster, and more successful.

This is exactly the challenge M1 is designed to solve. We specialise in change adoption success, helping organisations ensure their transformations actually deliver the promised business benefits rather than joining the 70% that fail to achieve their objectives (Errida & Lotfi, 2021). We understand that lasting change happens when everyone moves as one, especially when it comes to complex transformations where informal networks determine whether adoption spreads or stalls.

Ready to Turn Hidden Networks Into Adoption Success?

Ready to transform invisible resistance into visible advocacy?

Book a 30-minute strategy conversation where we can discuss your adoption challenges and share practical insights about what network-aware organisations do differently. No sales pitch, just an honest conversation about building change capability that leverages your people’s natural influence patterns rather than fighting them.

Book your strategy call here or email hello@wearem1.com

References

1. Battilana, J., & Casciaro, T. (2013). The Network Secrets of Great Change Agents. Harvard Business Review. https://www.hbs.edu/faculty/Pages/item.aspx?num=45076
2. Deloitte. (2024). Harnessing Organisation Network Analysis. https://www2.deloitte.com/us/en/blog/human-capital-blog/2024/harnessing-organization-network-analysis.html
3. Errida, A., & Lotfi, B. (2021). Change Management Statistics. Referenced in: https://mooncamp.com/blog/change-management-statistics
4. McKinsey. (2024). The state of AI: How organisations are rewiring to capture value. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
5. Tucker, C. E. (2008). Identifying Formal and Informal Influence in Technology Adoption with Network Externalities. MIT Sloan Research Paper. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1089134
6. WalkMe. (2024). Change Management Statistics You Need to Know. https://www.walkme.com/blog/change-management-statistics/
7. Worklytics. (2024). Top Organisational Network Analysis Software for Microsoft 365. https://www.worklytics.co/resources/2025-buyers-guide-organizational-network-analysis-software-microsoft-365