Sales Enablement Maturity Model: The Complete Guide to Assessing and Advancing Your Function

Disclaimer: This article was created in collaboration with GTM Buddy, who sponsored this content. I’ve partnered with them because I genuinely value their AI-native, in-the-flow enablement approach that helps reps where they work. The article contains affiliate links, meaning I may earn a small commission if you book a demo or make a purchase, at no extra cost to you. These partnerships help me keep the blog free and sustain the creation of practical, high-quality resources for the revenue and enablement community.

Introduction

I spent many months – and more than a few sleepless nights – turning in my bed, trying to bring order to everything I’d learnt about enablement.

Every conversation, every framework, every article I’d written or read added a new layer of insight.

Yet, when I looked across them all, something was missing – a clear way to connect it all together.

Over the years, I’d spoken with hundreds of enablement leaders through my blog. Each had a unique story, but their challenges often traced back to the same root cause: knowing where their team stood in its evolution, and what to prioritise next to drive meaningful business impact.

After months of work – even more long nights, whiteboard sketches, and more revisions than I can count – I built what I’d been searching for: a comprehensive enablement maturity assessment (available inside the Enablement Edge Network) that brings structure and clarity to an otherwise fragmented field.

This article introduces the model behind that assessment – the framework that maps how sales enablement functions evolve and mature over time.

At its core, I believe maturity is about integration – how every element of enablement works together as part of a coherent system that strengthens your sales strategies. Content, training, coaching, operations, technology, and cross-functional collaboration all reinforce one another to create measurable business impact.

The enablement maturity model helps you see that system clearly. It shows how different areas grow at different speeds, how they interact, and what separates organisations that react from those that proactively adapt.

In the next sections, we’ll explore the seven elements that make up the model, the stages that define progression, and how you can use this lens to evolve your enablement function – one deliberate step at a time.

Note: For simplicity, I’ll refer to the model as the “sales enablement maturity model” throughout the article. However, the framework itself applies equally to contexts where terms like “revenue enablement maturity model” or “go-to-market enablement maturity model” are more fitting – especially if your remit spans the entire revenue organisation, not just sales.

The sales enablement maturity model at a glance

As I already discussed in length in my sales enablement guide, enablement is a strategic discipline that is constructed as a system of interdependent elements that, when working in sync, help revenue teams perform at their best.

The sales enablement maturity model I propose comprises seven core components:

1. Sales process & methodology – how consistently your sales motion aligns with the buyer journey.
2. Content services – how relevant, accessible, and measurable your enablement content is.
3. Training services – how structured, role-specific, and outcome-focused your learning programmes are.
4. Coaching services – how consistently and effectively managers and enablers reinforce behaviours and develop capability through coaching.
5. Enablement operations – how effectively governance, data, and processes support enablement execution and scale.
6. Enablement technology – how integrated, data-driven, and adaptive your tech ecosystem is.
7. Cross-functional collaboration – how well enablement aligns and executes alongside Sales, Marketing, Product, Customer Success, and other relevant departments.

To make this system more organised and easier to interpret, the maturity model also groups these components into three broader domains.

The first is execution and capability, bringing together sales process & methodology, content, training, and coaching. These are the sub-disciplines that shape day-to-day performance and give teams the clarity, abilities, confidence, and consistency they need to deliver a strong customer experience.

The second domain is systems and infrastructure. This includes your enablement technology and your operational foundation – governance, production, and analytics. Together, they provide the scale, structure, and insight that make enablement repeatable, measurable, and supported by reliable workflows rather than just individual effort.

The third domain consists of alignment and orchestration, where cross-functional collaboration ensures that Sales, Marketing, Product, and Customer Success move in the same direction. When these teams share goals and information, enablement – often in partnership with RevOps – becomes a unifying force across the entire revenue motion.

At the centre of the model sits the shared outcome that binds everything together: customer value and business impact.

Customer-facing teams and their managers are the primary recipients of enablement’s work, and their effectiveness shapes, to a large extent, how much value buyers and customers experience.

At the same time, other teams such as Product and Engineering contribute to creating the value that the whole go-to-market unit helps bring to market.

In turn, sustained customer value fuels business impact, and the two reinforce each other in an ongoing cycle.

Running through the entire structure is strategic direction and leadership sponsorship, which acts as the backbone of the model. Those aspects ensure clarity of purpose, protect focus, and create the conditions for each component – and each domain – to operate and evolve efficiently and effectively.

As most seasoned enablement professionals know, without a clear strategy and committed sponsorship, even the most capable sales enablement teams struggle to create lasting, meaningful impact.

Such a proposed model aims to show enablement as it truly works: not as a sequence of disconnected activities, but as a coordinated system designed to help customer-facing teams perform at their best and deliver value that the business can clearly feel and measure.

Sales enablement maturity stages

Now that we’ve defined the seven components and the structure that holds them together, the next question is how each of these areas develops over time.

This is where the sales enablement maturity stages come in.

Each component evolves through four progressive stages that reflect how intentional, structured, and impactful your enablement system has become:

1. Random → activity exists, but it is ad hoc, inconsistent, and reactive. Teams rely on individual effort rather than shared processes. Success depends on intuition, not structure. There is little alignment or measurement, and outcomes vary widely.
2. Organised → foundations are documented, repeatable, and partly measured. The team begins to bring order to the chaos. Processes are defined, ownership becomes clearer, and early measurement appears. Work becomes more deliberate, although it remains manual and uneven across teams.
3. Scalable → processes are embedded, data-backed, and reliably executed. Systems now support consistency. Processes flow across teams, technology starts to connect the dots, and decisions rely increasingly on data. Feedback loops strengthen, collaboration becomes rhythmic, and enablement can finally support growth without burning out.
4. Adaptive → systems are predictive, intelligent, and continuously improving. The function becomes dynamic. Insights surface early, systems adjust quickly, and teams learn faster than the environment changes. Technology and operations work together to anticipate needs, not just respond. Adaptiveness becomes a real capability and competitive advantage.

It’s important to recognise that maturity doesn’t progress evenly across elements.

A team might have highly structured training but still operate with fragmented content or inconsistent coaching. Another might excel in process and methodology while still struggling to build cross-functional alignment.

This shouldn’t be seen as a weakness, but rather a signal.

The model is designed to reveal these differences so that teams can focus their effort where it creates the biggest ripple effect.

And this brings us to a crucial point: you cannot meaningfully label an entire enablement function as “Organised” or “Scalable.”

Maturity is not a single score.

Each component develops at its own pace, influenced by your business model, resources, leadership, and growth stage.

Your real maturity picture is the pattern that emerges across the seven components – not one column you place yourself in.

Think of the model less as a scorecard and more as a map. It shows how the different parts of enablement work together, where progress is building, and where friction still exists.

And it’s worth remembering: maturity isn’t the goal in itself. You don’t need to perfect every dimension for its own sake; what matters is progressing in the areas that genuinely support your organisation’s priorities.

Every company has its own context, pace, and priorities. The model and assessment should be used to align enablement maturity with business maturity – so progress in one fuels progress in the other.

In the next sections, we’ll unpack what the seven model components and the four maturity stages mean in practice, and how to recognise the signs of progress as each area matures.

For now, though, I’ll leave you with a very high-level snapshot of how each component typically progresses across the four maturity stages – a simple overview to help you visualise the journey before we explore each area in depth.

You don’t have an enablement problem. You have a revenue activation problem.

GTM Buddy uses AI to orchestrate content, learning, and coaching – activating sellers in the flow of work.

LEARN MORE

Sponsored: I may earn a commission if you purchase through this link. I only partner with tools I’ve personally used or rigorously tested, and that I genuinely trust.

Sales enablement maturity components deep dive

As we outlined, the maturity model rests on seven core areas grouped into three macro domains. Each one shapes how your function performs day to day, and how well it scales.

Below, I explain what each category means in practice and how it typically evolves. I’d invite you to keep it contextual. Use this as a lens through which you can look at your revenue organisation and sales enablement function.

Sales process & methodology

Sales process & methodology represent the foundation of sales execution – how your organisation defines, aligns, and reinforces how it sells.

The sales process provides structure – a clear framework that outlines the sequence of steps a sales team follows to turn a prospect into a customer. It’s the operational backbone of a sales organisation, bringing order, predictability, and a shared rhythm to what might otherwise feel like chaos.

The sales methodology, on the other hand, shapes how those steps are executed. It offers the mindset, principles, and techniques that guide sellers’ interactions with buyers at each stage of the process.

The two are deeply interconnected. The process gives sellers the “what” and “when.” The methodology adds the “how” and “why.” When well integrated, they form a cohesive system – structured enough to scale, yet flexible enough to adapt.

To understand how this area matures, it helps to look at how process and methodology evolve together over time.

At the random stage, every rep sells differently. Sales success depends on personal style, intuition, or luck. There’s little consistency across teams, and buyers often experience fragmented interactions. The CRM is rarely used as a guide; it’s more of a reporting tool than a selling tool.

As the function becomes organised, the fog begins to lift. The sales process is defined and documented. Stages and exit criteria start to appear, even if not everyone follows them perfectly.

A methodology, like MEDDPICC or Challenger, may enter the picture – but adoption tends to vary, and reinforcement is inconsistent.

Teams are beginning to align with the buyer journey, though gaps still exist between sales, marketing, and customer success. Measurement exists but remains basic: activity levels, not outcomes.

Reaching the scalable stage means the process and methodology are no longer theoretical. They’re more aligned with the buyer journey, embedded in daily workflows, reinforced through training and coaching, and supported by integrated tools.

Reps receive prompts and guidance directly within the CRM or other relevant sales enablement tools, managers use data to coach more effectively, and the buyer experience feels more cohesive from first contact to close.

Cross-functional collaboration strengthens, with marketing and customer success operating from the same playbook. Metrics mature from activity tracking to impact – win rates, sales cycle length, average deal size, and overall sales velocity.

At the adaptive stage, everything becomes dynamic.

The process evolves continuously, informed by AI-powered analytics and real-time feedback from across the organisation – call data, CRM insights, buyer engagement data and more.

The methodology becomes part of the organisation’s DNA – not just a sales language, but a shared framework across the entire go-to-market motion (check out this article for the most popular sales methodologies to choose from).

Predictive insights highlight where deals slow down, which behaviours correlate with success, and where buyer engagement drops off. Instead of reacting after the fact, teams can intervene early – adjusting messaging, coaching focus, or resource allocation before issues compound.

Workflows evolve in near real time. Playbooks and tools get updated in agile ways when market dynamics shift, while managers may receive AI-curated prompts to focus their coaching where it matters most.

The line between process and performance starts to blur. Enablement, operations, and leadership operate as one cohesive system – constantly refining how value is created and delivered.

Reaching this stage is never about perfection or permanence. In reality, no organisation ever “arrive” here in a fixed sense – and that’s the point.

Maturity at this level continues to be fluid. It’s about building a system that keeps learning, adjusting, and improving rapidly as conditions change.

Content services

If sales process and methodology define how your teams sell, content services are a big part of what they sell with.

When it comes to sales execution, content acts as the connective tissue between strategy and execution – the substance that enables reps to communicate value, credibility, and trust. When it works well, it doesn’t just support sales conversations; it shapes them.

For simplicity, content can be viewed through two lenses: internal-facing content, which equips sellers, and external-facing content, which engages buyers (I’ve explored this distinction more deeply in my sales enablement content guide and my article on types of enablement assets).

At its best, content helps sellers communicate value with clarity and confidence. It gives shape to your story – helping buyers see not just what you offer, but why it matters to them.

When content is relevant and easy to access, it brings alignment and momentum to the entire sales motion.

But when it’s scattered, outdated, or buried in folders no one visits, it becomes a silent drain on productivity and consistency – as we all know too well in enablement.

At the random stage, content lives everywhere and nowhere. Assets are scattered across drives, tools, or old Slack threads. Some are outdated; others contradict the current narrative. Reps spend precious time searching, repurposing, or recreating what should already exist.

There’s little structure, no clear ownership, and almost no link between what’s being used and what’s actually working. Content isn’t aligned to sales stages, personas, or buyer needs; it simply accumulates. Feedback from the field is anecdotal, and performance is unmeasured.

As teams mature, the first signs of order appear.

At the organised stage, content starts to feel coherent. There’s a central repository, clearer ownership, and a process for creation and updates.

Content is fresher, more role- and stage-specific, and partially aligned with buyer personas. Internal-facing materials (like battlecards or playbooks) are distinguished from external-facing assets (like case studies or business cases). But while structure exists, consistency and optimisation are still works in progress.

Governance may be informal. Collaboration between enablement, marketing, and product happens, but not rhythmically. Measurement often stops at usage metrics – downloads, clicks, or views – without clear linkage to outcomes.

The next major shift happens when structure gives way to system.

Reaching the scalable stage means that content services become a living ecosystem.

Every asset has a defined owner, purpose, and performance measure. Internal and external materials are aligned to distinct moments in both the buyer and seller journeys. Tools like CRMs, digital sales rooms, or AI assistants surface the right content at the right time, reducing friction and improving consistency.

Analytics go beyond engagement – tying content to sales impact through metrics like win rates, sales cycle length, or deal size. Governance is formalised, collaboration is continuous, and feedback loops close the gap between creation and usage.

From here, the system has an opportunity to gain further predictive intelligence at the adaptive stage.

AI and advanced analytics don’t just track what performs best; they anticipate what sellers and buyers will need next. Recommendations, updates, and retirements happen proactively, driven by real-time usage patterns and buyer engagement data.

Content evolves continuously rather than cyclically. Playbooks, talk tracks, and case studies are refreshed automatically as messaging shifts or new insights emerge. Reps and managers no longer have to search for the right asset; it finds them, contextually, within their workflow.

Governance remains in place, but it’s largely automated with tight human oversight. Tagging, version control, and review cycles are managed through intelligent systems that maintain accuracy without too much manual effort.

At this level, data closes the loop between creation, enablement, and outcomes, showing precisely which narratives and assets move deals forward.

Just like in sales process and methodology, no organisation ever reaches a final state here. Adaptiveness isn’t an end point, but an ongoing capability – the ability to stay continually relevant to your users and the wider business.

You don’t have an enablement problem. You have a revenue activation problem.

GTM Buddy uses AI to orchestrate content, learning, and coaching – activating sellers in the flow of work.

LEARN MORE

Sponsored: I may earn a commission if you purchase through this link. I only partner with tools I’ve personally used or rigorously tested, and that I genuinely trust.

Training services

Training is often where sales enablement begins – and where its maturity may be easiest to measure.

It’s the mechanism that initiates the building of knowledge, skills, confidence, and consistency across the sales organisation.

In its early forms, training tends to be reactive: a session here, a workshop there, a quick fix for a new process or product launch.

But true maturity comes when training evolves into a structured, data-informed system that supports readiness, performance, and long-term revenue growth.

Training maturity is also closely tied to technology. Without tools like an LMS, readiness or broader enablement platforms, enablement teams often rely on live sessions, recorded meetings, and manual tracking.

This approach can work on a small scale but limits repeatability and makes it difficult to measure impact as the commercial organisation grows.

The goal, as training matures, is to move from simply delivering training content to designing a learning system that develops people continuously, reinforces skills in the flow of work, and links learning to performance (you may find my piece on sales training best practices useful).

At the random stage, training exists, but without consistency or structure.

Sales onboarding is minimal or improvised, often dependent on whoever happens to be available that week. Sessions cover general topics, but not the specific competencies that matter most for each sales role.

Learning materials live in scattered folders, slides, or recordings, and there’s little visibility into who’s been trained or whether it made a difference. Here, training feels like an event – a one-off moment rather than an ongoing system.

As teams start to bring more order into their approach, the function moves into the organised stage.

There’s now a defined onboarding programme with clear goals and early attempts at role-specific training. Sessions follow a plan, and managers take a more active – though still inconsistent – role in reinforcement.

The use of mixed modalities increases: live workshops, virtual sessions, e-learning modules, peer learning groups, scenario-based exercises, micro-learning, and guided role-plays all start to appear.

Training content becomes centralised, but measurement remains basic – usually tracking attendance or completion rather than behavioural change.

Training is still heavily manual, but it now has direction. It moves from improvised to intentional.

And as this structure settles in, something important begins to shift. Training is no longer just a set of disjointed events that happen occasionally. The pieces start to connect: design informs delivery, delivery feeds reinforcement, reinforcement highlights gaps, and those gaps shape the next round of design.

When those links become visible and reliable, the organisation starts to enter the scalable stage

Role-specific learning paths are clearly defined, multi-modal, and data-driven. 

Onboarding and continuous development follow a consistent rhythm, supported by technology like LMSs or AI-native training and coaching tools.

Feedback loops strengthen, with training design evolving based on performance data, surveys, and manager observations.

Measurement links learning outcomes to commercial metrics such as time-to-ramp, win rates, or quota attainment.

Playbooks and job aids created through training are embedded into daily workflows – often integrated into CRM, conversational intelligence, or other enablement tools.

Sales managers are fully engaged in reinforcing learning through coaching activities, and training shifts from a programme to an engine that continually strengthens performance.

Eventually, the organisation reaches the point where training becomes dynamic and self-adjusting – the hallmark of the adaptive stage.

Learning content updates automatically – though still with human oversight – as messaging or product information evolves. AI identifies skill gaps early, recommends tailored learning paths, and surfaces relevant resources in real time.

Onboarding adapts dynamically to each individual’s needs, while analytics provide instant visibility into knowledge retention, skill adoption, and performance correlation.

Training-derived playbooks are fully integrated into sales systems, surfacing at the moment of need rather than being searched for.

Managers act as strategic coaches, guided by insights that show who’s ready for what, and where interventions will have the highest impact.

At this level, learning is no longer an isolated function. It’s a living system that evolves with the business, building capability not just for today, but also for what comes next.

Coaching services

If training builds the foundation – the knowledge and baseline skills people need to sell effectively – coaching is what turns that foundation into mastery (my piece on sales training vs sales coaching may be helpful here).

Coaching is one of the main bridges between learning and performance, where skills are refined through practice, feedback, and real-world application. I like to share that training may light the spark, but coaching is what keeps it burning.

Through consistent and intentional coaching, knowledge becomes confidence, and confidence becomes capability. It’s how teams can increase the likelihood of sustaining the desired behaviours after the workshop ends.

Yet, in many organisations, coaching remains the weakest link in enablement. It’s talked about often but practised rarely – and when it does happen, it’s inconsistent, unstructured, and disconnected from the skills it’s meant to reinforce.

When coaching is done well, it develops both sellers and managers. It builds accountability, strengthens culture, and embeds learning in the daily rhythm of work.

But when it’s done sporadically, without direction or intent, it becomes a tick-box exercise – another meeting on the calendar that fails to build lasting capability.

At the random stage, coaching is exactly that: sporadic and unstructured.

Some managers might run an occasional session, but there’s no clear purpose, rhythm, or framework guiding those conversations. Coaching happens reactively, often as part of deal reviews or performance issues, not as a proactive tool for development.

Managers rely on instinct rather than structure, and most lack training in how to coach effectively. There’s little visibility into whether coaching happens, let alone whether it helps. Tools like conversation intelligence or AI co-pilot platforms are rarely used, and no link exists between coaching and commercial outcomes.

At this stage, coaching feels optional – something that happens “if there’s time.”

As this service matures into the organised stage, coaching evolves from scattered conversations into a more deliberate practice.

Frameworks appear, and managers begin to receive basic training in core coaching skills such as agenda-setting, questioning, feedback, and goal-setting. Cadences become clearer, and coaching begins to occur more regularly – though still inconsistently across teams.

Sessions start to follow a plan – whether focused on pipeline reviews, deal discussions, or skill development – and clear expectations for managers begin to take hold. Basic tracking, often manual, is introduced to capture participation and focus areas.

This is where the organisation starts to recognise coaching not as a side activity, but as a core part of sales management and leadership. Yet, measurement remains limited, and while coaching may happen more often, its impact is still hard to quantify.

Progressing into the scalable stage, coaching becomes structured, consistent, and measurable.

Frameworks are refined and applied across teams, with clear cadences supported by sales leadership.

Coaching evolves from being encouraged to being expected. Managers are now equipped not only to coach but to coach effectively – tailoring sessions to each role, from SDRs refining prospecting outreach to AEs improving discovery, demo, or negotiation.

Technology begins to amplify impact. Conversational intelligence tools, AI feedback systems, and structured coaching dashboards bring visibility and discipline. Managers use insights from calls, pipeline data, and deal outcomes to personalise sessions and focus on the behaviours that drive results.

Measurement also matures, linking coaching activity to performance indicators such as win rates, quota attainment, or sales velocity.

At the adaptive stage, coaching becomes predictive and fully embedded in the organisation’s rhythm.

It’s no longer a scheduled task; it’s a way of operating. Managers coach continuously, supported by AI tools that surface timely insights – from missed opportunities in conversations to emerging skill gaps across the team.

Coaching adapts in real time. Frameworks evolve alongside the business, and development paths adjust automatically as new products, messages, or market shifts occur. Insights flow freely between enablement, operations, and leadership, creating a closed loop that connects behaviour change directly to commercial outcomes.

Accountability is cultural, not enforced. Managers see coaching as part of who they are, not something they have to do. Predictive analytics reveal where intervention will have the greatest impact, helping leaders focus their time where it matters most.

Ultimately, the continuous improvement at the adaptive stage is marked by a committment to strive for excellence in how the commercial organisation supports and develops its talent.

Enablement technology

So far, we’ve looked mostly at the services enablement delivers – process & methodology, content, training, and coaching.

Enablement technology – along with enablement operations, which we’ll cover in the next section – forms the foundation beneath all of this.

I like to think of it as the nervous system of the function: the set of tools, integrations, and data flows that either make it easy for enablement to scale, or silently hold everything back.

When technology is immature, even good programmes feel heavy and manual. As it matures, the stack becomes more intentional, more connected, and more intelligent – turning tools into an ecosystem that supports better decisions, faster execution, and, eventually, predictive insight.

To see how this evolves in practice, it helps to look briefly at how enablement technology progresses through the four maturity stages.

At the random stage, the tech stack simply “happened” over time.

Different teams have bought tools for specific problems – a learning platform here, a content repository there, maybe a conversational intelligence tool – but they sit in silos. Some are barely used. Others overlap in functionality.

There is little integration and almost no clear ownership.

Reps log into several systems, often manually copying data between them. Adoption is patchy and hard to measure. Support for these tools is minimal, and there is no structured way to decide what stays, what goes, or what needs to be added.

Analytics exist inside individual tools, but no one brings them together to inform strategy. AI is either non-existent or limited to basic, unused features that came bundled with a license.

At this point, the real work is diagnostic and foundational: understanding what you have, what you actually need, and where technology is creating friction rather than solving it.

Then, as you reach the organised stage, the stack starts to make sense.

Someone has taken the time to audit what exists, remove obvious duplication, and focus on a core set of tools that truly matter for enablement – often across areas like training, content delivery, and call insights.

Usage guidelines and basic standards appear.

Reps know which tools to use for which tasks. Managers begin to reinforce expectations. Foundational training is offered so that people can move beyond superficial usage. Basic documentation, quick-start guides, and short internal enablement sessions support adoption.

Some integrations are in place – for example, syncing a content platform with the CRM, or pushing training data into a central system. These integrations reduce manual effort and create more coherent workflows, even if they are still relatively simple.

Data and feedback loops exist, but they are still underused. You can see who is using which tools and how often, but you are only starting to ask what that means and what should change as a result.

Here, technology stops being a loose collection of tools and becomes a set of shared platforms with clearer ownership and intent.

And this progression continues into the scalable stage – the point where technology shifts from a set of shared platforms to a connected system that supports the entire commercial engine.

Tools are integrated across the core systems that matter – CRM, CMS, LMS, conversation intelligence / AI co-pilots, digital sales rooms, and more. Data flows reliably between them. Manual exports and spreadsheet stitching begin to disappear.

Usage becomes role-specific and more advanced. SDRs, AEs, AMs, CSMs, managers, and enablement each interact with the same platforms, but the experience is tailored to their needs, workflows, and levels of responsibility.

Reps receive in-context support. Managers access dashboards that bring together adoption, activity, and performance. Enablement can finally see patterns, not just isolated metrics.

Analytics mature as well. Dashboards now show more than logins and completion rates. You start to link tool usage and programs to outcomes – e.g., whether teams that got certified in a specific skill area actually improved win rates, or whether specific content shared through your enablement platform shortened deal cycles.

AI moves from experimentation into everyday work.

Rather than being a novelty, AI features start to support real use cases: e.g., recommended content for specific opportunities, automatic call summaries, suggested next steps for coaching, or spotlighting deals that need attention.

Some organisations at this stage formalise an internal “centre of excellence” around AI and enablement technology – a small group that curates use cases, shares best practices, and helps teams turn capabilities into habits.

Technology now greatly supports productivity and scalability.

Finally, we reach the adaptive stage where the enablement technology ecosystem becomes highly dynamic and predictive.

Here, the stack is not just well integrated; it is actively shaping how the organisation operates.

Data from across the tools is unified and analysed in near real time.

AI-powered systems surface leading indicators and recommendations rather than lagging indicators and historical reports.

The organisation can see emerging risks and opportunities early – where skills are lagging, where deals are likely to stall, or where certain messages resonate more strongly with specific segments.

Reps and managers experience this as guidance in the flow of work: content recommendations that adapt to buyer behaviour, coaching prompts generated from recent calls, or nudges that highlight the next best action in a deal.

Automation takes over large parts of the operational load – CRM syncs, scheduling, tagging, logging activity, call summaries, generating standard reports, and much more – so that human focus can shift to higher-value work like strategy, experimentation, and deep coaching.

The technology roadmap itself is living and forward-looking.

New tools and features are assessed not only on what they can do today, but on how well they fit into the broader ecosystem and how they support long-term objectives. Feedback from users, leaders, and cross-functional stakeholders shapes ongoing evolution.

When enablement technology reaches adaptive maturity, it stops being “the tools we use” and becomes an intelligent infrastructure – one that provides deeper insight, powers better decisions, and enables more effective support for every other part of your enablement system.

You don’t have an enablement problem. You have a revenue activation problem.

GTM Buddy uses AI to orchestrate content, learning, and coaching – activating sellers in the flow of work.

LEARN MORE

Sponsored: I may earn a commission if you purchase through this link. I only partner with tools I’ve personally used or rigorously tested, and that I genuinely trust.

Enablement operations

After exploring enablement technology – the nervous system that supports how work flows – it’s natural to turn to the structure that holds the entire function together: enablement operations.

If technology provides the tools and connections, operations provide the structure and control that keep everything aligned and running smoothly.

This is the engine room of the function.

The systems, processes, governance, and data foundations that make everything else – content, training, coaching, and even technology itself – consistent, measurable, and scalable.

Without strong operations, even the most inspired enablement strategy collapses under the weight of inefficiency (more on this later).

At its best, enablement operations bring clarity to complexity. They create order where there’s chaos, alignment where there’s friction, and visibility where there’s guesswork. They help teams move with direction instead of noise – doing the right things, at the right time, for the right reasons.

At the random stage, however, that order doesn’t exist.

Enablement operates on instinct. Processes are reactive, improvised, and dependent on whoever happens to be available. There’s no defined governance, no clear ownership, and little alignment with broader business goals.

Cross-functional collaboration is informal, often driven by relationships rather than systems. Marketing, Product, and Customer Success may all be involved in enablement, but without coordination, duplication and inconsistency follow.

Data, if tracked at all, sits in spreadsheets. Decisions are made based on anecdotes, not insight. Technology is either underused or scattered across disconnected tools that create more friction than flow.

At this level, enablement feels busy but not productive – always doing, rarely measuring.

As maturity progresses into the organised stage, structure begins to form.

A governance framework emerges – sometimes in the shape of an enablement charter that defines purpose, priorities, and scope. Roles and responsibilities become clearer. Enablement starts documenting how things get done, from onboarding to content production to cross-functional alignment.

Processes are introduced, though often still manual. Teams begin to map dependencies with other departments and use simple tools to manage projects and communication. There’s an effort to bring consistency – an early recognition that enablement must operate like a business function, not a support team.

Technology adoption improves, and data starts to inform decisions – but only partially. Insights exist, but they’re fragmented. Dashboards might show outputs, yet not outcomes. The function runs more smoothly, but it hasn’t yet achieved the scale or precision needed for real impact.

Reaching the scalable stage transforms enablement operations from functional to strategic.

Governance becomes routine, with clear ownership, accountability, and executive sponsorship. Frameworks and playbooks guide delivery across enablement services – from content creation to onboarding – so nothing needs to be reinvented from scratch.

Processes are efficient, repeatable, and increasingly automated. An enablement intake process manages incoming requests, prioritising those with the highest business impact. Workflows are documented and optimised, supported by project management tools that bring visibility and speed.

Cross-functional collaboration becomes seamless. Marketing, Product, and Sales work from shared goals and timelines. Data is now consistently used to evaluate impact, connecting enablement activity to commercial outcomes such as ramp time, win rates, or deal velocity.

Technology integration accelerates this shift. CRMs, enablement platforms, and project tools speak to each other. Operational data flows in real time, guiding prioritisation and decision-making.

At this stage, enablement operations are structured and efficient – capable of scaling without breaking.

At the adaptive stage, operations become intelligent.

Data doesn’t just report; it predicts. Governance frameworks evolve continuously, informed by feedback and advanced analytics. Automation takes care of repetitive work, freeing enablers to focus on high-value strategy and innovation.

Processes are flexible and modular, designed to adjust to new priorities without disruption. Live dashboards and integrated data streams give instant visibility into resources, performance, and outcomes, allowing leaders to act on insight rather than intuition.

Cross-functional alignment reaches its highest form. Teams operate with shared OKRs, connected systems, and real-time feedback loops. Enablement is now embedded as a strategic partner across the organisation – a function that doesn’t just execute, but shapes how the business learns and adapts.

Technology forms an intelligent backbone that predicts needs and suggests action before gaps appear. Analytics are no longer static reports but dynamic inputs that inform strategy definition, resource planning, and execution in real time.

As the function matures, the enablement team evolves with it. Defined progression frameworks ensure people grow alongside the systems they manage, maintaining both agility and operational depth.

At this level, it’s hard to define precisely how things are because by nature, they’re always changing.

Predictive analytics continue to improve but never reach a fixed end state. The goal isn’t to create a perfectly optimised system per se, but one that reacts instantly, learns continuously, and provides the clearest possible view of what to do next.

Ultimately, operational excellence here means running on real-time intelligence – using live data to guide fast decisions, align strategy with execution, and keep enablement one step ahead of the business it serves.

Cross-functional collaboration

By this point, we’ve explored the services enablement delivers and the systems that enable the execution of those services.

It could be said that cross-functional collaboration is the connective tissue around all of it.

We all know that enablement doesn’t operate in a vacuum. Its success depends on how well it works with Marketing, Product, Customer Success, Sales Operations, and, of course, Sales leadership itself.

When these relationships are weak, enablement becomes isolated, and its work struggles to translate into meaningful business impact.

When they are strong, the revenue organisation moves with shared intent. Teams pull in the same direction, and business impact is achieved more efficiently, more effectively, and with greater predictability.

But collaboration does not mature automatically. It requires conscious effort, and it evolves through its own journey – from informal and inconsistent exchanges to a predictable rhythm, and eventually to a dynamic partnership built on shared goals, real-time insight, and trust.

As per usual, we begin at the random stage where collaboration is mostly accidental.

Teams interact because they have to, not because there is a shared process or purpose.

Requests come in informally – a message here, an email there – and each team has its own priorities.

Marketing runs campaigns without visibility into sales needs. Product shares information late or inconsistently. Customer Success spots patterns in renewals, but they rarely reach Sales or Enablement in time.

There are no regular cadences, no shared goals, and no agreed mechanisms for resolving issues. Feedback, when it happens, is reactive and anecdotal.

In this environment, enablement often works hard, yet feels misaligned.

Good initiatives stall because key teams were not involved early enough. Other initiatives succeed only because the right individuals made the effort, not because the organisation supported it.

The work at this stage is simple but essential: understanding who needs to be involved, setting a baseline for communication, and creating the first routes for alignment.

Once you reach the organised stage, more formal collaboration begins to take shape.

The right people are now in the room, and regular meetings begin to happen – sometimes monthly, sometimes quarterly – creating a first layer of rhythm across teams. Plans, timelines, and constraints are shared more openly, and ownership becomes clearer as conversations mature.

Small rituals emerge: a standard agenda, a shared document everyone updates, a follow-up note that captures decisions and next steps.

These may seem minor, but they anchor the whole process.

Feedback loops strengthen as well, not yet smooth, but consistent enough to reveal friction early and highlight new opportunities before they slip through the cracks.

Shared metrics begin to appear, often still tracked manually, but they point everyone in the same direction and create a shared sense of progress.

Escalation also becomes more deliberate. Priorities still clash – they always do – but there is at least a known path to resolve tension, which helps teams keep momentum.

Nothing at this stage is advanced or fully refined, but it’s no longer improvised. Enablement becomes less reactive, and collaboration starts to feel like part of the role rather than an extra favour teams offer when they have time.

At the scalable stage, collaboration becomes a system rather than a series of meetings.

Departments no longer align occasionally; they work from shared rhythms that make coordination feel natural rather than forced. Goals are set together, plans are shaped together, and metrics are reviewed together, creating a sense of collective movement.

Processes become predictable, with clearer expectations and smoother handovers. Feedback loops move faster, helping teams adjust without waiting for the next formal checkpoint. Escalation paths also sharpen, supported by SLAs that match the urgency and impact of the issue at hand.

Shared dashboards replace ad-hoc updates and scattered spreadsheets. Teams can now see, in seconds, how content is used, how training lands, and where friction begins to build across the commercial engine.

The tone of conversations shifts as well. Instead of debating opinions, teams anchor discussions in evidence. Instead of reacting to problems once they’ve grown, they spot early signs and address them before momentum is lost.

At this level, collaboration becomes a catalyst for scale. It reduces friction, speeds up execution, and strengthens enablement’s role as a credible, integrated, and strategic partner across the organisation.

At the adaptive stage, collaboration becomes a living, responsive network.

Departments act as partners rather than stakeholders, and alignment happens continuously instead of being confined to scheduled meetings. Insights move across teams in real time, supported by predictive analytics that help everyone anticipate risks and spot opportunities early.

Escalation becomes the exception, not the rule, because issues surface sooner and are handled before they slow anything down. Feedback is no longer something you gather at set moments; it’s woven into daily workflows and shapes decisions as they happen.

Shared goals evolve as the business does. Metrics shift to match emerging priorities, and plans adjust with far more agility, without the disruption that typically accompanies change.

Enablement becomes part of the organisation’s decision-making fabric. It influences how teams learn, how they respond to the market, and how they act on intelligence. Collaboration fuels experimentation – rapid working groups form quickly, cross-team projects advance without friction, and new approaches emerge directly from shared insight.

By this point, collaboration is not something the organisation tries to improve. It becomes the way the organisation thinks, operates, and grows.

Strategic direction and leadership sponsorship: the compass that keeps the function on course

Although the maturity model rests on seven components, none of them can evolve in a meaningful way without a steady strategic direction and the backing of committed leadership.

These two elements don’t sit inside the model; they surround it, giving shape, coherence, and momentum to everything enablement does.

In my sales enablement strategy guide, I describe strategy as the plan that turns scattered activities into an intentional system. A strong strategy doesn’t just outline what enablement should deliver; it clarifies why each initiative matters, where it fits in the broader motion, and how it supports the organisation’s goals.

When this clarity is missing, enablement risks becoming a reactive service desk. Work spreads thin, priorities drift, and teams spend more time responding to noise than building capability or driving impact.

Leadership sponsorship completes the picture; essentially creating the conditions in which strategy can be executed well to deliver impact.

With genuine sponsorship, enablement gains the trust, authority, and visibility needed to operate as a strategic partner rather than an optional helper. Cross-functional teams collaborate more willingly, decisions move faster, and the function has a voice in shaping the GTM direction, not only supporting it.

Here, the direct connection with one of the seven components – enablement operations – becomes important. In fact, it was where I had already hinted at aspects of strategic direction.

Strategy sets the direction. Operations carry it forward.

Without clear governance, processes, and reliable data, even the sharpest strategy remains abstract – especially as company size increases. You can afford to have a basic strategy and a very light operational backbone when you’re an early-stage scale-up, but things can get very messy as the organisation grows.

Enablement ops give strategy a home, acting as the operational pathway through which strategy becomes real in day-to-day work – intake processes, prioritisation rules, project rhythms, documentation, service production workflows, and the insights that guide decisions.

In most cases, the “tool” used to capture the essence of the strategy, explain the scope and purpose of the function, and set the boundaries that help teams concentrate on what matters most, is the enablement charter.

As many enablement leaders highlighted in the article on sales enablement best practices, the charter shouldn’t be a static document. It should evolve as the strategy evolves, keeping expectations, priorities, and decision-making aligned as the business changes.

When strategic direction and sponsorship are strong, maturity accelerates.

When they are weak, progress slows across every component, no matter how good the individual work may be.

I often suggest enablers ask themselves this simple question to help them understand where they stand: “Does our strategy guide our decisions, and do our leaders actively support it?”

If the answer is yes, enablement is likely to have the foundations to grow with intention.

If not, strengthening this layer will unlock more progress than any single component improvement ever could.

How AI accelerates maturity across the model

AI has introduced one of the biggest shifts sales enablement has seen in years.

Not because it adds new responsibilities, and not because it replaces human judgment, but because it changes the speed, quality, and intelligence with which each part of the enablement system operates.

Every component of the maturity model – process and methodology, content, training, coaching, technology, operations, cross-functional collaboration – evolves faster when AI is thoughtfully embedded.

I believe it acts as a cross-cutting accelerant, lifting the ceiling on what’s possible and lowering the effort required to get there.

This is why I often describe AI as the bridge between scalable and adaptive maturity.

Where organisations once relied on manual work, one-size-fits-all programmes, and lagging indicators, AI now helps teams personalise learning, analyse patterns earlier, and surface intelligence in the flow of work.

The result goes way beyond efficiency gains. Here we are talking about better decisions, clearer alignment, and more predictable execution with continuous learning loops.

In practical terms, AI supports enablement by turning slow, inconsistent, or fragmented processes into more responsive systems.

For example, it helps teams interpret signals faster, update materials with less friction, and build coaching conversations around real behaviour rather than guesswork.

It also strengthens the sales process and methodology by bringing structure to what sellers do in real time – prompting better questions, sequencing actions, and providing contextual guidance that supports how the organisation expects deals to be run.

But AI does not create maturity by itself. In fact, it can easily give the illusion of progress.

Many organisations unintentionally fall into what I call AI maturity theatre: lots of tools, lots of interesting features, very little behavioural change. Workflows stay the same, adoption remains patchy, and the stack becomes heavier instead of leaner and smarter.

To avoid that trap, AI needs to be anchored in disciplined enablement practices.

It should strengthen the system you already have, reduce friction, and improve consistency. It should help people do their work better – not automate their thinking away (a very risky thing).

In some cases, it may even replace outdated processes altogether – but only when the underlying logic remains sound, and the change genuinely improves clarity, speed, or reliability.

Here I want to list a few principles that tend to make the biggest difference (I also discussed them in my piece on AI sales agents):

1. Start with outcomes, not tools. AI works best when it’s tied to a clear problem or ambition, not adopted because it looks impressive.
2. Strengthen the process before accelerating it. AI magnifies what’s already there. If a process is unclear, AI will make the confusion faster, not make the work better.
3. Own the prompts, governance, and standards. Who maintains them? Who trains teams? How are they reviewed? This is enablement operations; just in a new form.
4. Track and measure behaviour change, not feature usage. The value lies in better conversations, cleaner data, and stronger execution – not in dashboards showing tool activity.
5. Keep humans at the core. AI should reduce cognitive load, not replace the judgment and emotional intelligence that shape real buyer engagement.

I truly believe that when used intentionally, AI becomes one of the most effective levers for progression across the model.

It shortens learning cycles, sharpens execution, and enables teams to move with more clarity, consistency, and confidence.

For a deeper exploration of how AI supports each component – and dozens of practical use cases – you can refer to my full guide on AI in sales enablement.

You don’t have an enablement problem. You have a revenue activation problem.

GTM Buddy uses AI to orchestrate content, learning, and coaching – activating sellers in the flow of work.

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Sponsored: I may earn a commission if you purchase through this link. I only partner with tools I’ve personally used or rigorously tested, and that I genuinely trust.

How to use the enablement maturity model in practice

If you’ve read this far, you now have a solid grasp of the seven components and the four maturity stages.

But understanding the model alone isn’t what creates progress. What matters is knowing how to apply it in a way that feels realistic, focused, and tied to your organisation’s priorities.

The maturity model is ultimately a decision-making tool. It helps you see where you stand today, identify the gaps that truly matter, and decide where to invest your sales enablement efforts, time, and energy for the greatest impact.

And you don’t want to tackle everything at once. That leads to overwhelm, diluted effort, and slow progress.

So, in this section, I outline a simple, structured way to use the model in practice: how to assess your current state, how to select the few areas that will move the needle most, and how to put in place the governance that keeps progress steady over time.

1. Assess maturity component by component

Start by reviewing each of the seven components on its own.

Avoid the temptation to give the entire function a single stage label, as that hides the nuance you actually need.

Use a mix of inputs: data, conversations, existing metrics, and any artefacts you already have in place (e.g., playbooks, training plans, dashboards, your tech stack, governance notes). Speak with sales leaders, managers, and cross-functional partners to balance perspectives.

Look for honest signs of reality.

Which stage description best reflects today?

What evidence supports that view?

It’s normal to find variation: perhaps your process and methodology feel close to Scalable, while coaching is still at the early edge of Organised. Treat that as insight, not a flaw. These differences highlight where improvement will have the greatest effect.

If you want to fast-track this step, you can also complete my enablement maturity assessment, which turns this evaluation into a structured, guided process.

2. Choose your priorities wisely

Once you see the pattern across the seven components, choose one or two areas to work on first. Trying to tackle everything at once won’t turn out well; focus is key.

Let the business goals guide you.

If the organisation is struggling with late-stage conversion rates, process and methodology may be the starting point.

If reps are constantly recreating materials and wasting a lot of time, content services may likely give you more leverage.

If GTM teams struggle with alignment, improving collaboration or operations may offer the fastest lift.

Focus on the areas that will move the needle in the next 6–12 months.

Define the stage you aim to reach, and outline a small set of initiatives that will get you there. You are not building a perfect system; you are choosing the next step that makes everything else easier.

3. Set governance and cadence so the model stays alive

For the model to work, someone needs to own it.

Usually, this sits with the Head or Director of Enablement, supported by partners in RevOps, Sales Leadership, and other GTM teams.

Create a simple rhythm that keeps the model connected to the business. For example:

• A quarterly review to reassess maturity scores, check progress against the roadmap, and adjust priorities
• A monthly pulse to surface blockers, gather cross-functional input, and maintain momentum
• A one-page snapshot that shows current stages, active priorities, and early signals of change

This cadence links naturally to the governance structure described in the strategy section. It ensures the maturity model informs decisions, secures sponsorship, and helps leaders understand what progress looks like.

Without this rhythm, the model becomes a document rather than an active driver of maturity development and business performance.

4. Measure progress and iterate steadily

Progress shows up in behaviour long before it shows up in dashboards.

Look for signs that teams are working differently: cleaner qualification notes, more consistent coaching, better content usage, smoother collaboration, stronger adherence to process.

Then look at system signals: better workflows, better documentation, more reliable integrations, clearer governance.

Commercial results will follow, though they often take longer to appear. Treat these early changes as leading indicators, and revisit your maturity assessment periodically to see how things have shifted.

Expect the journey to be uneven.

Some areas will move quickly, others will take longer, especially when they involve habits, data quality, or cross-functional coordination. Adaptive maturity is not a finish line; it’s an ongoing commitment to refinement and responsiveness.

The most important principle is simple: move one stage at a time, with intention.

Small, consistent steps beat broad, unfocused effort every single time.

Limitations of the maturity model

Every model simplifies reality, and this one is no exception.

The seven-component structure gives clarity, focus, and a shared language, but it cannot capture every nuance of how enablement operates day to day.

While the model helps you navigate amd make sense of complexity, is critical that you leave room for additional judgement, adaptation, and organisational context.

That said, let’s explore some of the core limitations worth acknowledging:

1. Reality is messier than any framework

Organisations rarely develop in neat stages.

Teams jump ahead in some areas, stall in others, or regress when priorities shift.

The model gives direction, not a deterministic path.

2. Some activities cut across multiple components

Even when certain activities sit formally within a component – for example, governance and analytics in enablement operations – they still influence several areas at once.

Things like intake, cross-team decision-making, prioritisation, and stakeholder management are similar: they reach beyond any single category and shape how all components work together.

The model separates these elements for clarity, but real enablement work rarely fits into clean boxes.

3. The model focuses on capability systems, not human dynamics

The model maps strategy, structure, process, and execution across the various components – but it cannot fully reflect culture, leadership style, team psychology, or interpersonal dynamics.

These elements strongly affect maturity yet sit outside any formal component.

4. AI reshapes how maturity develops across the model

Another important limitation to acknowledge is how fast AI-driven technology is reshaping the enablement landscape.

AI sits under the “technology” component in the model, but its impact reaches far beyond tooling. Agentic workflows, generative systems, CRM-embedded guidance, and automation that supports reps in real time are redefining what execution looks like.

This has two key implications for the maturity model.

First, technology can now accelerate progression between stages.

In traditional models, maturity followed a mostly linear path: Random → Organised → Scalable → Adaptive.

But today, tech and, more specifically, AI allows organisations to leapfrog steps when the underlying foundations are strong enough.

For example:

• A team with a clear process and solid content foundations may jump from early Organised straight into Scalable execution once agentic workflows or guided-selling AI are introduced.
• A coaching approach and rhythm that previously required months to mature can accelerate rapidly when conversational intelligence and behaviour-based insights enter the flow of work.
• Content operations can move from fragmented to adaptive-level personalisation far faster than before, simply because the mechanics of production and versioning no longer depend entirely on manual bandwidth.

AI does not make the model obsolete; it changes the pace at which teams progress through it.

Second, AI shifts the role of enablement itself.

Enablement no longer supports reps only through training, content, and coaching – it increasingly shapes the workflows, prompts, governance, and behavioural standards that AI agents or co-pilots use.

In other words, enablement now influences both:

• human execution, and
• AI-mediated execution.

This dual responsibility isn’t captured explicitly in the model, because it cuts across every component.

It means the model should be read with awareness that:

• maturity stages describe the system,
• technology can lift the system faster than before,
• and enablement must actively design how AI enhances, reinforces, or automates parts of that system.

This context is important so readers don’t interpret the stages as rigid, chronological steps.

With AI, progress can be non-linear, conditional, and accelerated.

5. Communication and field engagement are implicit rather than explicit

Finally, there is one more limitation worth calling out before closing the model: the important role of sales communications and field engagement, which the model does not fully account for.

When you look at how enablement actually works inside organisations, you quickly realise that the way information reaches the field often determines whether any initiative succeeds. Yet, this area sits between components rather than inside any single one, which makes it less visible in a structured model like this.

Industry assessments (including Gartner’s) sometimes treat sales communications as its own category, and several enablement leaders I’ve spoken with raise the same observation: the flow of information to the field has a direct impact on execution, but it isn’t represented as a formal element in many maturity frameworks.

Sales communications refer to how an organisation:

• Curates, prioritises, and sequences information sent to the field
• Ensures the right people receive the right message at the right time
• Avoids overwhelming sellers with noise
• Creates a predictable, structured cadence for updates
• Aligns messaging from Product, Marketing, RevOps, and Leadership

As you can see, sales communications extend far beyond announcements. Their purpose is to protect cognitive load, maintain clarity, and make sure critical information is actually absorbed rather than ignored.

In many assessments, a communications strategy is seen as a marker of maturity because without it:

• Content becomes scattered, and teams often remain unaware of what exists or where to find
• Training loses reinforcement and fades quickly in the field
• Coaching becomes inconsistent, with managers emphasising different messages
• Process adherence weakens as reps follow conflicting cues
• Cross-functional messaging clashes, creating confusion for both sellers and customers

In other words: poor communication erodes every other component.

So why isn’t sales communications its own component in the model?

I found it difficult to include it as such because it isn’t a standalone component; instead, it is an expression of several systems working together.

Sales communications is the connective layer through which many components reach the field and stakeholders. It is both operational and behavioural, both structural and cultural, which makes it hard to define neatly as a single component.

Perhaps it may be more closely related to the cross-functional collaboration component and could sit there, but even then, it stretches beyond that boundary. 

I think that keeping this limitation in mind should strengthen your use of the model – reminding you to pay close attention to how information reaches the field, how aligned it feels, and how easy it is for sellers to act on. 

You don’t have an enablement problem. You have a revenue activation problem.

GTM Buddy uses AI to orchestrate content, learning, and coaching – activating sellers in the flow of work.

LEARN MORE

Sponsored: I may earn a commission if you purchase through this link. I only partner with tools I’ve personally used or rigorously tested, and that I genuinely trust.

Conclusion

When I first set out to create this model, I wasn’t looking for a perfect framework.

I was looking for a clearer way to make sense of everything enablement touches – and to help practitioners decide, with more confidence, what to do next.

What emerged for me is not a score or a label, but a way of seeing your function as a system: seven components, four stages, and a set of forces around them – strategy, sponsorship, and communications – that either support or constrain how well that system works.

If there is one idea I hope you take away, it is this: maturity is not about doing everything, or reaching some abstract “Adaptive” ideal.

It is about choosing the few areas that truly matter for your organisation right now, and moving them forward in a deliberate, visible way.

You will never have all components at the same level.

You will always have constraints, trade-offs, and organisational realities to navigate.

That is normal.

The power of a model like this lies in making those realities explicit, so you can work with them instead of against them.

So, as you reflect on your own enablement function, you might ask:

• Where are we strong today, and why?
• Where do we feel the most friction?
• Which one or two components, if we improved them, would make everything else easier or more effective?

From there, you can decide how to use this work:

• As a lens for honest internal conversations with leaders and partners
• As a structure for your enablement roadmap and charter
• As a shared language to anchor priorities, investments, and expectations

If you want a guided way to get started, once again, you can use my enablement maturity assessment and the accompanying maturity blueprint (part of my premium enablement membership). They turn this model into a concrete self-diagnosis and a set of focused next steps.

My hope is that this framework gives you not just a clearer picture of where you are, but also a calmer sense of how to move forward – one stage, one component, one decision at a time.

Enablement is still a young discipline.

How we define it, shape it, and lead it over the next few years will have a huge influence on how revenue organisations operate.

This model is my contribution to that journey.

What you do with it – and how you adapt it to your world – is where the real work, and the real impact, will come from.