Implementing and Sustaining the New Operating Model

8.1 Converting the Target Model into an Implementation Roadmap

The target operating model should be translated into an implementation roadmap before the design phase is considered complete. A roadmap connects each approved design choice to the actions required to make it operational. Without this step, organizations frequently move directly from executive approval to broad communication, leaving individual functions and teams to interpret how the new model should work.

The roadmap should begin by decomposing the target model into implementation workstreams. Typical workstreams include organization and leadership, roles and decision rights, governance, portfolio and funding mechanisms, development processes, resource management, performance measures, systems and data, and change enablement. Each workstream should contain specific deliverables rather than broad aspirations.

For example, “implement portfolio governance” is too general. The underlying actions may include appointing the portfolio forum chair, confirming membership, approving the charter, defining prioritization criteria, creating the standard decision pack, migrating the current portfolio into the new segmentation, establishing a meeting calendar, assigning data ownership, and conducting the first review. The operating model is live only when these mechanisms function together.

A practical roadmap should capture:

• Design decision: the approved element of the target operating model.
• Implementation actions: the concrete steps required to put that design into operation.
• Accountable owner: the executive or workstream leader responsible for delivery.
• Dependencies: decisions, systems, appointments, or other changes that must occur first.
• Timing: the expected sequence and implementation milestone.
• Evidence of completion: an observable condition demonstrating that the change is operational rather than merely documented.

Implementation should be organized around operational outcomes. An organization-design action is not complete because reporting lines have been announced; it is complete when leaders are appointed, role charters are understood, affected employees have transitioned, and critical interfaces operate under the new model. A stage-gate redesign is not complete when new templates are published; it is complete when programs use the new criteria and governance bodies make decisions accordingly.

The roadmap should distinguish changes that must occur before launch from those that can mature after launch. Leadership appointments, decision authority, reporting relationships, and critical governance mechanisms often need to be clear on day one. More sophisticated dashboards, automated capacity models, or supporting systems may reasonably follow after foundational processes are stable. Insisting that every component be perfect before launch can delay benefits and encourage unnecessary complexity.

Dependencies should receive particular attention. A new portfolio forum cannot make effective resource decisions if resource ownership remains unclear. A new organization structure may not improve accountability if role charters and decision rights lag several months behind. New metrics may fail if systems use inconsistent program definitions. The roadmap should therefore show the logical relationships among changes, not merely their calendar dates.

Active development programs create an important implementation constraint. Leaders must decide whether existing programs migrate immediately to new processes, transition at defined milestones, or remain on legacy mechanisms until completion. A blanket conversion can create unnecessary disruption, while allowing every program to remain on old processes can postpone adoption for years. Migration rules should reflect program maturity, risk, and the benefits of switching.

Resources for implementation should be explicit. Transformation work competes with ongoing R&D responsibilities, and assuming leaders will implement the new model in spare time often produces delays. Critical workstreams need named owners, sufficient analytical and program-management support, and access to decision makers. Where implementation depends on HR, finance, IT, quality, or other corporate functions, their commitments should appear in the roadmap.

Risks and contingency actions should also be incorporated. Potential issues include loss of key talent, delayed leadership appointments, disruption to major launches, incomplete systems changes, disagreement over new authority, or unexpected regulatory implications. The roadmap should identify the highest-consequence risks and establish mitigation actions rather than treating implementation as a deterministic sequence.

For joint ventures, the roadmap must distinguish changes that venture management can implement directly from those requiring shareholder, board, or parent-company action. A new governance model may depend on amendments to reserved matters, service agreements, resource commitments, or intellectual-property arrangements. These dependencies should be identified early because formal approvals can determine the critical path.

The implementation roadmap becomes the management instrument for the transition. It should be detailed enough to show ownership and dependencies but concise enough for senior leaders to use. Its purpose is to make the target model executable, not to create an exhaustive project plan detached from operating outcomes.

8.2 Sequencing Organization, Governance, Process, and System Changes

Operating model elements are interdependent, so sequencing matters. Implementing them in the wrong order can create contradictions in authority, disrupt active work, and force teams to operate simultaneously under incompatible mechanisms. The sequence should establish enough organizational clarity to support new behaviors while avoiding an extended period in which design decisions exist only on paper.

Organization and leadership changes typically require early resolution because they determine who owns subsequent implementation. If a new platform structure, central R&D function, or business-unit model is being created, leaders need to know who will head those units and what authority they will possess. Leaving key leadership positions unresolved while asking teams to implement governance and process changes creates uncertainty and slows decisions.

Decision rights should follow closely. Reporting lines alone do not establish how the new organization will operate. Leaders should clarify authority for critical portfolio, technical, resource, and program decisions as organizational units are launched. Where possible, role charters and accountability maps should be available when leaders assume their positions rather than months later.

Governance forums can then be activated using the new authority model. Some organizations attempt to launch all governance mechanisms simultaneously. A more practical approach is to prioritize the forums that control the most consequential decisions, such as enterprise portfolio allocation, major technical authority, or development progression. Lower-level routines can then be aligned around them.

Process changes should be sequenced according to the maturity of programs and the consequences of conversion. A new development pathway can often be applied immediately to newly approved programs while active programs migrate at natural milestones. Critical handoffs, however, may warrant earlier intervention if the current process is causing significant quality, manufacturing, or regulatory problems.

Systems should generally enable the operating model rather than dictate it. Organizations sometimes delay implementation until a new portfolio platform, resource-planning application, or workflow system is configured. Basic operating mechanisms can often begin with simple tools while system requirements are refined through experience. Automating a process before its rules are stable can lock unnecessary complexity into technology.

A phased sequence might therefore follow four broad stages:

1. Establish accountability: appoint leaders, confirm organizational units, publish role charters, and activate critical decision rights.
2. Launch core management mechanisms: establish portfolio and technical governance, operating cadences, escalation rules, and basic dashboards.
3. Transition development practices: implement stage-gates, handoff criteria, resource mechanisms, and differentiated pathways across programs.
4. Enable and optimize: automate reporting, refine planning systems, embed advanced capacity tools, and simplify mechanisms based on operating experience.

This sequence is illustrative rather than mandatory. A company facing severe portfolio overload may need to implement prioritization and capacity governance before completing organization changes. A regulated business with major quality concerns may prioritize process controls. Sequencing should reflect the problem the redesign was intended to solve and the risks of delaying each element.

Leaders should also define temporary operating arrangements. A transition may require an interim portfolio committee, temporary reporting relationship, or provisional decision authority while permanent roles are filled. These arrangements should be explicit and time bounded. Otherwise, temporary mechanisms can persist and create an additional layer of governance alongside the intended model.

Communication should follow the sequence of decisions rather than precede them with vague transformation messages. Employees need practical answers: who they report to, which priorities apply, which processes change, what authority their role possesses, and when the change takes effect. Broad statements about becoming more agile or collaborative provide little guidance during a structural transition.

The sequencing plan should also protect major development commitments. Programs approaching regulatory submission, validation, launch, or critical customer milestones may require temporary stability. Leaders can preserve existing program structures for these initiatives while implementing the new model elsewhere, provided exceptions have clear end dates.

The essential principle is to sequence changes so that authority, governance, process, and information reinforce one another as quickly as possible. The organization should not spend months operating with a new structure but old decisions, or new processes governed by leaders whose roles have not been clarified.

8.3 Integrating Acquired R&D Teams, Labs, and Development Programs

Acquisitions create a distinctive operating model challenge because the organization is integrating not only people but also different technical capabilities, development practices, portfolios, laboratories, systems, and decision cultures. The goal should not automatically be full standardization. Integration should preserve the capabilities that justified the transaction while removing duplication, resolving accountability, and establishing enough common mechanisms for the combined R&D system to operate coherently.

The starting point is the transaction thesis. Leadership should identify what value the acquisition is expected to create through R&D. The value may come from access to technology, a stronger development pipeline, specialized talent, new products, intellectual property, laboratories, geographic capabilities, or combinations of these assets. Integration choices should protect the sources of value rather than treating conformity with the acquirer’s existing model as the primary objective.

A practical integration assessment should examine organization, portfolio, capabilities, processes, sites, governance, systems, and culture. For each dimension, leaders should decide whether to adopt the acquirer’s model, retain the acquired model, combine the strongest elements of both, or allow deliberate variation. These choices should be explicit rather than emerging through incremental negotiation.

Organization integration should clarify leadership and reporting authority early. Employees need to know which teams remain distinct, which are combined, and how functional and program responsibilities will change. Delayed decisions can increase attrition among the people the acquisition was intended to retain. At the same time, moving too quickly without understanding specialized roles can eliminate critical expertise or break informal networks essential to development.

Portfolio integration requires a common view of all active programs. Acquired initiatives should be assessed using the combined company’s strategy and capacity constraints rather than automatically added to the existing portfolio. Some programs may be more valuable after the transaction because they can use the acquirer’s channels, platforms, or resources. Others may duplicate existing work or no longer fit the combined strategy.

Program decisions should consider customer commitments, regulatory obligations, contractual rights, and the disruption created by changing development processes midstream. A late-stage program should not be forced into an unfamiliar stage-gate process simply to achieve procedural consistency. The organization can establish a transition rule while requiring new programs to use the target model immediately.

Technical capability integration should distinguish valuable redundancy from avoidable duplication. Two laboratories performing similar work may provide resilience, geographic access, or genuinely different expertise. Alternatively, they may exist because the organizations developed the same capability independently. Decisions should consider technical quality, utilization, strategic importance, talent, equipment, location, transition risk, and future demand.

Site roles should be clarified as part of the combined network. Acquired laboratories often retain broad mandates because leaders are reluctant to disrupt them immediately. Over time, this can produce overlapping centers of excellence, duplicated platform ownership, and competition for global mandates. Each major site should receive a clear role in the future R&D network, including what work it owns and which businesses or platforms it serves.

Governance integration should focus on the decisions that require common treatment. The organization may need one enterprise portfolio process, shared technical authorities, common development controls, or coordinated resource allocation while allowing different team-level practices. Leaders should avoid retaining duplicate executive reviews indefinitely merely because both legacy companies used them.

Systems and data integration can be phased, but information needed for management decisions should become comparable early. Program definitions, milestones, spending, resource demand, and technical risk may be recorded differently in the two organizations. Leadership needs a common fact base before it can make credible portfolio and capacity choices, even if underlying systems remain separate temporarily.

Retention and cultural considerations have direct operating implications. Acquired scientists and engineers may interpret increased governance as a loss of autonomy, while the acquirer may view informal practices as inadequate control. Leaders should identify which aspects of the acquired model contributed to speed or innovation and distinguish them from practices that simply reflect smaller scale. The objective is disciplined integration, not cultural victory by one organization.

Joint ventures differ from acquisitions because the parent companies intentionally retain separate interests and authority. The operating model cannot assume that one party can simply impose its structure, systems, or technical standards. The venture may need its own decision architecture while relying on capabilities supplied by both parents. Governance should clarify access to experts and labs, program prioritization, intellectual-property boundaries, funding commitments, technical authority, and escalation between owners.

Integration is successful when the combined R&D organization can make coherent portfolio and technical decisions while retaining the distinctive capabilities that created strategic value. Organizational neatness is not the objective. The objective is a functioning development system in which people understand authority, resources can be deployed deliberately, and critical programs continue without unnecessary disruption.

8.4 Piloting, Refining, and Scaling the New Ways of Working

Not every operating model mechanism should be deployed across the entire R&D organization immediately. Pilots can test whether a proposed governance process, stage-gate, resource model, dashboard, or cross-functional interface works under real operating conditions before the organization commits to broad rollout. Piloting is particularly useful when the design introduces materially different behaviors or when implementation assumptions remain uncertain.

A pilot should test a defined hypothesis. “Pilot the new development model” is too broad. A stronger objective might be to determine whether a risk-based gate process reduces approval burden for lower-risk programs without increasing downstream rework, or whether a new resource forum can allocate scarce engineering capacity within five business days rather than relying on executive escalation.

Pilot selection matters. The chosen area should be representative enough to generate useful learning but manageable enough that implementation can be observed closely. Extremely unusual programs may produce findings that do not generalize, while politically protected pilots may not expose the real difficulties. Selecting two or three different program types can sometimes provide better evidence than a single showcase project.

Before launch, the organization should define baseline performance and success measures. These may include decision lead time, governance hours, milestone predictability, resource-allocation speed, handoff rework, or user understanding of decision authority. Baselines enable teams to distinguish genuine improvement from enthusiasm associated with a new process.

Pilots should preserve the essential elements of the target model. If teams are permitted to bypass every unfamiliar requirement, the pilot tests only the old way of working under a new label. At the same time, participants should be encouraged to identify where the design is impractical. The purpose is to validate and refine the model, not to prove that the original design team was correct.

Feedback should be specific and evidence based. Statements such as “the new governance is cumbersome” should be translated into observable issues: which review duplicated another decision, which information was unavailable, how much preparation time was added, or which authority remained unclear. These findings can then be addressed through design changes.

Refinements should distinguish problems with the model from problems with adoption. A stage-gate may be well designed but poorly understood because training was insufficient. A portfolio forum may appear slow because members have not yet delegated authority as intended. Changing the design prematurely can institutionalize old behaviors. Implementation teams should determine whether the mechanism itself is defective or whether users need clearer guidance and reinforcement.

Scaling should occur through defined waves. Programs, sites, business units, or regions can transition according to readiness and risk. Each wave should apply the lessons of the previous one and use a consistent implementation package containing role guidance, governance charters, process definitions, templates, training, and support.

Local adaptation should be controlled. A global model may legitimately vary where regulatory conditions, product risk, customer requirements, or organizational structures differ. However, allowing each unit to customize basic decision rights, metrics, and governance mechanisms can quickly recreate fragmentation. The organization should define which elements are mandatory and which can be adapted locally.

Joint ventures and external partners may need separate pilots where interfaces cross organizational boundaries. Testing a new transfer process between a venture and a parent-operated manufacturing facility, for example, can reveal contractual or capacity issues that an internal pilot would miss. Scaling should therefore include the external interfaces on which the operating model depends.

The goal of piloting is disciplined learning. The organization should emerge with a simpler, more credible operating model and greater confidence about how to implement it at scale, not with a collection of local versions designed independently by each pilot team.

8.5 Tracking Adoption, Resolving Implementation Issues, and Sustaining the Model

Implementation does not end when the final rollout wave is complete. New operating models frequently regress because legacy behaviors remain easier, leaders continue using old escalation channels, governance forums expand beyond their charters, or new employees learn practices informally. Sustaining the model requires mechanisms that track whether the organization is operating as designed and allow the model to evolve without losing coherence.

Adoption measures should focus on observable behavior rather than communication activity. Counting employees who attended training or received a presentation shows exposure, not adoption. More useful measures examine whether decisions occur at the intended level, whether programs use the correct development pathway, whether portfolio decisions change resource allocation, and whether cross-functional handoffs follow defined readiness criteria.

A practical adoption scorecard might include:

• Decision rights: percentage of sampled decisions made by the intended role or forum.
• Governance: use of approved charters, decision packs, and documented decision outcomes.
• Portfolio management: evidence that starts, stops, and priority changes result in funding and resource movement.
• Development process: percentage of programs following the appropriate pathway and gate criteria.
• Cross-functional interfaces: frequency of incomplete handoffs, late functional involvement, or downstream rework.
• Management system: consistent use of agreed KPI definitions, dashboards, and operating cadences.

Implementation issues should be managed through a defined resolution mechanism. Early problems are inevitable, and not every issue should be escalated to the executive steering team. A central implementation office or designated operating model owner can maintain an issue log, assign owners, distinguish local execution problems from systemic design defects, and elevate only decisions requiring senior authority.

Issues should be categorized before action. Design issues indicate that the target mechanism does not work as intended. Adoption issues occur when teams have not understood or accepted an otherwise workable mechanism. Capability issues arise when people lack the skills or data required to operate the model. Dependency issues reflect unfinished systems, HR, finance, contractual, or organizational changes. Correct classification helps avoid redesigning the operating model whenever implementation becomes difficult.

Leadership behavior is one of the strongest determinants of sustainability. If executives tell teams that decisions are delegated but continue to intervene routinely, the organization will learn to escalate. If portfolio leaders refuse to stop lower-priority work after resource trade-offs, capacity governance loses credibility. Leaders must operate within the same decision rules and governance boundaries expected of everyone else.

Governance mechanisms themselves should be reviewed after several operating cycles. Forums may discover that their cadence is too frequent, criteria overlap, or certain decisions can be delegated further. Refinement is appropriate when supported by experience. However, changes should be controlled so that local exceptions do not gradually rebuild unnecessary complexity.

Ownership of the operating model should transfer from the temporary implementation team to permanent leadership. Responsibilities may sit with the head of R&D, an R&D operations function, portfolio management, or another designated owner depending on the organization. The permanent owner should monitor model health, coordinate future adjustments, maintain core design documentation, and ensure that changes in one component remain consistent with others.

New leaders and employees should be incorporated into the model through role onboarding. A newly appointed program director should understand delegated authority, governance expectations, resource mechanisms, and escalation paths. Relying on informal knowledge makes the model increasingly dependent on the individuals who participated in the original redesign.

Annual operating model health checks can provide useful discipline. These should not automatically trigger another redesign. Instead, management should examine whether the strategic assumptions underlying the model remain valid, whether portfolio complexity has changed, whether decision bottlenecks are reappearing, whether site roles remain appropriate, and whether governance burden is increasing. Specific changes can then be made where evidence justifies them.

Major strategic events may require more substantial reconsideration. Acquisitions, divestitures, entry into new technologies, significant geographic expansion, new regulatory requirements, or changes in product architecture can alter the operating requirements on which the model was based. The organization should be willing to adapt deliberately rather than allow workarounds to accumulate until another full transformation becomes necessary.

Joint ventures require particular discipline because governance can drift as parent-company leaders change or strategic interests evolve. Periodic review should confirm that delegated authority, reserved matters, service arrangements, funding rules, and shared capabilities still support the venture’s operating needs. Where parent organizations repeatedly intervene outside the agreed model, the issue may require governance clarification rather than additional venture processes.

The ultimate measure of sustainability is whether teams can operate effectively without continuous intervention from the people who designed the model. Decisions occur at the intended level, portfolio choices translate into resources, development interfaces function predictably, and leaders can identify and correct problems through established management routines. At that point, the new operating model is no longer an implementation program. It has become the normal system through which R&D is managed.