Brendon Ford my Home of thoughts on the web

The Hidden Headwinds

What No One Tells You About Partnering with Microsoft

If you’re a tech company looking to scale, the allure of partnering with Microsoft is undeniable. With one of the world’s most powerful sales engines, a global footprint, and a vast customer ecosystem, it seems like a no-brainer. You sign up as a partner, align your solution to their cloud, and watch the leads pour in… right?

With over 25 years of working with Microsoft as a partner this is so far from the truth!

This post is about pulling back the curtain. As someone who’s spent years in and around the Microsoft ecosystem, as a partner, as a customer, and as a leader how has built strategic alliances I’ve seen both the gold and the gravel.

While partnering with Microsoft can absolutely unlock game-changing growth, it’s not as simple as flipping a switch and you have to keep reinventing yourself. Let’s talk about why.

Partnership ≠ Pipeline (At Least Not Right Away)

One of the most common misconceptions about partnering with Microsoft is the belief that doing so instantly translates to revenue and that every other partner is getting leads all day every day.

After all, Microsoft touts a massive partner network, co-sell programs, marketplace opportunities, and joint go-to-market initiatives. But the truth is, becoming a Microsoft partner is just the starting line, not the finish. And the path forward? It’s winding.

First, you need to understand that “Microsoft” is not a monolith. There’s Microsoft Corp (a.k.a. Redmond HQ) and then there’s Microsoft Subsidiaries (the regional field sales orgs). These two groups operate with very different priorities, and forging strong ties at Corp won’t automatically win you love (or pipeline) in the field. In fact, one of the biggest mistakes new partners make is investing heavily in Corp-level relationships, only to realize the local Subsidiary they’re trying to sell with doesn’t even know who they are.

Even more critical: if you don’t know what both Corp and the Subsidiary are measured on, you won’t know whether you can (or should) align. Microsoft’s priorities change every fiscal year, think Azure growth, security SKU attach, Fabric or Copilot adoption, and if your solution or service offering doesn’t map to the current targets, getting traction will feel like swimming upstream.

The Reality Check: You Have to Pay the Microsoft Partner Tax

Here’s a hard truth that’s rarely spoken out loud: if you’re not ready to “pay the Microsoft partner tax,” you won’t get much in the way of traction or engagement.

So what is the Microsoft tax?

It’s not a literal fee. It’s the investment, time, people, and money, that’s required to play the game at a level where you’re taken seriously.

Here’s what it looks like in practice:

You’ll need certified people on your team, especially those with Azure and security credentials.
You’ll be expected to show tangible cloud consumption, which often means becoming a CSP (Cloud Solution Provider) or at least working closely with one.
You’ll need to be present—at Microsoft events, in Microsoft Partner Center, at regional GTM calls, and often flying globally to make face-to-face connections.
You’ll need to build strong up and down relationships with Subsidiary teams in every market you operate in (and each country will be different).
Your senior leadership needs to show up, consistently. Not just once a year, but as a regular drumbeat of visibility and decision-making presence.
You may even need to commit on the spot, sponsoring an event, jumping on a joint marketing campaign, or funding a proof of concept, just to stay top-of-mind.
You might have to bet on bleeding-edge Microsoft products—investing early in developing skills, pitch muscle, and delivery experience for a solution that isn’t quite ready for primetime. And if you do win those early lighthouse deals, be prepared: they can often be painful, margin-squeezing loss-leaders as you wrestle with immature tooling and shifting product roadmaps.

All of this typically happens before you see much return. That’s why many companies dabble, but few go deep enough to win.

The Strategic Shift: Partnership is a Motion, Not a Moment

To succeed with Microsoft, you have to treat the partnership like building a second sales engine, not just slapping a logo on your deck. That means:

Aligning your value to Microsoft’s annual scorecard: Know what moves their needle this year and tailor your messaging, demos, and integrations accordingly.
Learning the rhythm of their fiscal year: Budgeting, planning, co-sell cycles, and performance metrics are all tied to this calendar.
Building field relationships intentionally: You’ll need local champions, joint account plans, and consistent syncs to stay relevant.
Committing leadership bandwidth and resources: Your CEO and senior execs need to be in the loop and visibly invested.

Proof in Practice: How Some Partners Make It Work

The partners who win with Microsoft don’t just show up, they build parts of their business around the ecosystem.

Veeam doubled down on Azure integration and CSP alignment, earning credibility with Microsoft field sellers by driving tangible cloud adoption.
Nintex aligned with Microsoft’s Power Platform narrative by integrating their automation tools and extended offerings, even though, on the surface, Power Automate could be seen as a competitor. This bold move turning Nintex from a potential rival into a complementary solution.
Elastic earned trust by delivering consumption-heavy scenarios that field sellers could easily plug into Azure deals, making them a multiplier, not a distraction.

What do these companies have in common? They aren’t afraid to make bold, ongoing investments, and they never stop turning into Microsoft’s evolving priorities.

It can be Worth It, But Only If you Invest

Partnering with Microsoft can be transformative, but it’s not transactional, it’s a commitment. You’re entering a relationship where alignment, visibility, and relentless execution are required.

Key Takeaways

Understand the difference between Microsoft Corp and Subsidiary, and why both matter.
Know what Microsoft is measured on before you try to align.
Accept that “partnering” means paying a real-world tax, in certifications, cloud consumption, travel, time, and senior commitment.
Build local and global field relationships proactively. This is a human game.
Stay agile. What worked last year may not move the needle this year.

Why SIs Should Embrace Channel Partnerships for Growth

In today’s ever-evolving technology landscape, being a successful systems integrator (SI) is no longer just about writing code or delivering projects. It’s about shaping end-to-end business outcomes, delivering scalable solutions, and creating long-term customer value. One of the most powerful levers to drive that growth? Becoming a channel partner for leading technology vendors. Whether it’s Microsoft, AWS, Salesforce, or emerging AI startups, aligning with the right partners can accelerate your business in ways that go far beyond reselling licenses.

This post will unpack the strategic why behind partnering, cover what makes for a high-functioning SI–ISV alliance, and offer some hard-won advice to avoid common pitfalls along the way.

The Problem: Growth Is Harder When You Go It Alone

Many SIs today face a common problem: they want to grow, but the path forward is crowded and competitive. Whether you’re a boutique consultancy or a regional powerhouse, the pressure is on to expand your services, win bigger deals, and deepen client relationships. But how do you scale when your current offerings are tapped out or lack the technical depth that clients increasingly expect?

Maybe you’ve built a killer automation practice, but you’re missing cloud-native AI expertise. Or perhaps you’re great at building bespoke solutions, but clients are asking for packaged IP. This is where the right technology partnership can help fill the gap and unlock new revenue streams.

The Solution: Strategic Channel Partnerships

Let’s start with what becoming a channel partner really means. It’s not just about getting a discount on licenses or slapping a logo on your website. Done right, it’s about mutual growth: the vendor grows their reach and adoption; you grow your services pipeline, win more deals, and improve your margins through differentiated offerings.

Here’s how that plays out across a few standout ecosystems:

Microsoft: One of the most mature and partner-driven ecosystems in the world. SIs benefit from co-sell motions, marketing development funds (MDF), and technical enablement. Whether it’s Power Platform, Azure, or Copilot, there’s a constant stream of customer demand—if you’re a preferred partner, you’re in the running for it.
AWS: Focused on technical excellence and specialization. Partnering here gives you access to APN programs, migration acceleration initiatives, and most importantly, credibility. AWS customers often only look for certified partners.
Google Cloud (GCP): While a bit leaner on channel maturity, GCP rewards innovation and AI-centric solutions. Their partner portal and sales alignment processes are improving, especially in AI and data workloads.
Salesforce: The AppExchange and consulting partner model creates a rich ecosystem for SIs to resell, build, and support. The Trailblazer community is particularly strong in verticals like finance, health, and public sector.
Nintex: A powerful process automation partner for SIs focused on digital transformation and workflow. Their clear partner tiers and technical enablement allow SIs to stand out with certifications and use-case IP.

Now add to that a wave of new AI-native companies like:

Anthropic (Claude), OpenAI, and Mistral AI – all with growing ecosystem and partner programs for integrating models or creating fine-tuned solutions for enterprise.
Cohere – especially if you’re focusing on retrieval-augmented generation (RAG) and privacy-sensitive deployments.
Aible – who offer partner-friendly AI solutions with low-code automation and business integration layers.

Business Outcomes: Growth, Differentiation, and Filling Gaps

So why jump in?

Drive Top-Line Revenue: If you’re growth-oriented, there’s no better way to scale than by tapping into a vendor’s brand equity and customer base. Microsoft, Salesforce, and AWS all generate inbound leads for certified partners. That said, it takes real effort to make these partnerships pay off. I’ve spoken with many partners who feel like everyone else is getting more leads than they are, but that’s rarely the case. Success often comes down to consistent engagement, internal alignment, and patience.
Fill Offering Gaps: If you’re missing security, observability, or AI expertise in your offering, partners like Datadog, Anthropic, or Microsoft help you round out the solution.
Showcase Differentiation: Becoming a certified partner signals to customers that you know your stuff. If you’re a GCP Premier Partner or a Microsoft Solutions Partner, that badge means something and also it often is required to tap into funding.
Combined Selling Power: When co-selling is in play, everyone wins. The vendor wants to land a new customer. You want to grow your services business. Working together through combined account teams can build real momentum and reduce sales cycle friction. That said, be mindful, sometimes, you’ll need to walk away from a deal. For example, if Microsoft brings you into an account to shift workloads off AWS, but the customer shows no interest, and you pivot aggressively to selling AWS instead, you could risk burning a bridge. Strategic alignment matters just as much as short-term opportunity.

What Great Partnerships Look Like

To maximize the value, you’ll need structure, on both sides. The most successful SI partner models include:

An Executive Sponsor: Someone internally who can clear roadblocks, approve investment (like getting your team certified), and show your commitment to the partner.
A Sales or Alliance Lead: This person builds the relationship, finds co-sell opportunities, and evangelizes the partner internally and to clients.
A Hands-On Delivery Champion: Someone who deeply knows the tech and can prove your team can actually implement the solution well.

Don’t overlook your internal comms either. Having a structured partner enablement plan—like monthly capability sessions, shared go-to-market (GTM) assets, and use-case examples, can help you scale faster across your teams.

Pitfalls to Avoid (And How to Fix Them)

Of course, not all partnerships are smooth sailing. Watch out for these traps:

Lack of internal alignment: If your execs see partnership as “just another vendor relationship,” it won’t get the internal muscle it needs. Assign clear roles and make sure someone owns success.
Over-commitment without ROI: Some programs require expensive certifications or quota commitments. Be honest about whether the opportunity justifies the investment. Start small, prove value, scale up.
Mismatched goals: Vendors are focused on license growth; you’re likely focused on services margin. Clarify early how you both win, and track joint KPIs like pipeline generated, deals closed, and service attach rate.
Under-leveraging resources: Many vendors have pre-sales engineers, marketing funds, and partner incentives, but you have to ask for them. Build a quarterly plan and activate those benefits.

Wrapping It Up: Play Bigger, Together

If you’re a systems integrator looking to grow, don’t go it alone. Channel partnerships can open doors to new clients, richer offerings, and higher-margin services. The key is picking the right partners, structuring internally for success, and avoiding the common traps that dilute value.

Next Steps:

Identify your offering gaps and see which vendor can help fill them.
Choose a strategic partner to start with and nominate your internal sponsor, sales lead, and delivery owner.
Build a 90-day GTM plan that aligns your goals with theirs.

If you’re not sure where to start? Look for ISVs that are your “plus one”. What do we mean by that? Simply put, find a partner that enhances what you already do, rather than requiring you to build an entirely new offering from scratch. Partnering is most effective when it’s an extension of your strengths, not a reinvention of your business. Unless you have deep pockets or strong internal buy-in, avoid partnerships that pull you too far out of your lane. Launching a successful partnership takes time, focus, and commitment. If your executive team isn’t aligned or patient with the ramp-up, you risk half-hearted execution and limited results.

About me

Understanding Token Math

Turning Ideas into Hard Numbers

There’s no shortage of hype around generative AI. From dinner table debates to executive boardrooms, people are abuzz with talk of AI transforming everything, from coding to customer service, risk analysis to recipe generation. Across industries, leaders are feeling the pressure to “do something” with AI. But what exactly?

As businesses look for ways to improve productivity and reduce costs, inference-based solutions can offer a smart entry point into the generative AI era.

Modernizing Legacy Applications

Organizations should be actively exploring how inference-based functionality can be integrated into their existing line-of-business (LOB) solutions. Done right, this has the potential to be a genuine game changer, not just another flashy demo.

To move beyond a generative AI proof of concept, leadership teams need to shift the conversation toward what it actually costs to run these solutions at scale. Without that clarity, operationalizing AI remains out of reach

From Cool Demo to Scalable Reality

Let’s talk about the hard part.

Once you move beyond a clever prototype and start considering inference in a production setting, several challenges appear. First, there’s latency and performance, your model needs to return results fast enough for real-world use.

Then there’s infrastructure. Do you run this on CPUs? GPUs? Where? And let’s not forget model size, fine-tuning, and security.

Today, I’d recommend starting with inference before diving into fine-tuning. But one question tends to dominate stakeholder discussions. What does it actually cost to run?

Whether you’re using OpenAI’s GPT models, your own LLaMA instance on Azure, or Hugging Face models via containers, the real question is, What’s the dollar cost per inference? And more importantly, what’s the cost per business transaction?

Three Paths to Inference Deployment

Let’s break down the three most common paths for running inference:

Option 1: API-Based Inference (Token-Based Services)

How it works: You consume a model via a managed API (like OpenAI, Azure OpenAI, or Cohere). You pay per token used.
Pros: No infrastructure overhead, rapid setup, great for experimentation and burst workloads.
Cons: Limited control over performance, latency, and data governance. You’re locked into model choices and pricing.

Option 2: Containerized Inference (Self-Hosted Models)

How it works: You run models like LLaMA or DeepSeek in your own cloud (or even on-prem) using GPU VMs.
Pros: Full control over the model and tuning, consistent performance, and easier cost predictability at scale.
Cons: High setup complexity, need for ML engineering expertise, GPU cost volatility, and you carry the burden of uptime and scaling.

Option 3: Hybrid Model (Burstable Inference)

How it works: You run a base level of dedicated GPU capacity and burst to an API when demand spikes.
Pros: Balances cost and performance, reduces latency under load, and provides fallback capacity.
Cons: Requires orchestration logic and potentially dual billing models, with added complexity to monitor.

What’s the Cost Per Business Transaction?

This is where it gets real.

An API request or a GPU inference run is not a business outcome. To justify the investment to leadership, you need to tie this back to actual workflows.

Use Case: Construction Site Safety Inspection with AI

Here’s a process you could automate with generative AI:

A construction site photo is uploaded.
A 10MB safety policy document is ingested.
The model identifies any safety violations in the image by comparing it against the policy.
A risk register is generated with identified issues and proposed mitigations.
Tasks are created for the site manager to resolve each issue.

As a ballpark estimate lets say it costs on average of $250 to perform a site inspection and takes about 3 hours per visit.

What would it look like if you could automate most of this and do it daily across every construction site and only send a human when high-risk sites are identified ?

Token Math: Estimating Inference Cost with Real Data

Let’s get into the numbers. A quick and dirty way to estimate inference costs is what I call “token math.”

Assumptions,

Policy document: ~10MB of text → ~40,000–50,000 tokens
Photo (analyzed for context): ~500–1,000 tokens
Prompt: 100–300 tokens
Output (structured data, tasks, risk register): 500–2,000 tokens

That gives us a total token count per job of ~11,000–53,000, depending on prompt structure and policy complexity.

Now let’s look at the cost,

Containerized GPU run (e.g., LLaMA 8B on Azure low-end GPU VM): ≈ $0.72 per scan at the high end of token usage
API-based inference with a similar model ≈ $0.05 per scan

This doesn’t include supporting cloud infrastructure (storage, networking, orchestration), but those are relatively predictable costs that most teams already model.

So even at the higher end, $0.72 vs. $250 per inspection? That’s an eye-popping reduction. Even if you only automated part of the process and cut site visits in half, the ROI becomes clear.

What’s the Takeaway?

As you consider deploying generative AI in production, especially for inference-heavy use cases, the deployment model you choose has a dramatic impact on cost and flexibility.

APIs are great for speed and scale
Containers give you control and cost predictability
Hybrid models offer balance, if you’re ready for the complexity

But no matter the tech stack, the business case is won or lost on how clearly you map tokens to transactions, and dollars to outcomes.

Links to head over to if you want to read some more

Hugging Face Inference Endpoints – Hugging Face

Read about responsible AI if you are interested Responsible AI: Ethical policies and practices | Microsoft AI

If your want to build workflow solutions and inject GenAI check out CoPilot Studio https://www.microsoft.com/microsoft-copilot/microsoft-copilot-studio

If you want to build with AI check out

About me About me – Brendon Ford my Home of thoughts on the web

Demystifying the ISV Partner Channel

Why Partner Ecosystems Matter for ISVs

For Independent Software Vendors (ISVs), scaling beyond a direct sales model is no longer a luxury, t’s a necessity. In today’s competitive SaaS landscape, partner ecosystems serve as powerful growth engines that enable global reach, faster customer onboarding, deeper market penetration, and scalable service delivery.

Whether you’re just starting to explore indirect channels or refining a mature partner strategy, one truth remains: not all partners are created equal.

Navigating the partner ecosystem can feel like alphabet soup—GSI, NSI, SI, ISV, VAR, LAR, MSP. Each partner type brings different strengths, incentives, and go-to-market (GTM) models. Without a clear understanding of their roles, ISV leaders risk misalignment, lost revenue, or poor partner engagement. This guide breaks it all down.

One Size Doesn’t Fit All

Many ISVs step into the partner world assuming more partners mean more revenue, what it really means is busy work. But quality trumps quantity. A GSI won’t solve the same problems as a VAR. An MSP isn’t going to co-develop your product like an OEM might. Clarity is key.

This post helps you:

Understand the major partner types
Recognize what each brings to the table
Identify which ones are right for your strategy

Let’s look at the partner landscape.

Putting It All Together: Strategy Meets Partner Type (with a Microsoft Ecosystem Lens)

Microsoft’s partner ecosystem is one of the most mature and structured in the software industry, making it a powerful lens through which to understand how different partner types contribute to an ISV’s go-to-market success.

Each partner type aligns to specific business goals within Microsoft’s Cloud Partner Program and Azure Marketplace. Here’s how it typically breaks down:

Partner Type	Ideal For	Example Microsoft-Aligned ISV Scenarios
Global System Integrator (GSI)	Enterprise deals, global delivery	Dynamics 365 or Power Platform transformation via Accenture or TCS
National System Integrator (NSI)	Regional growth, regulated industries	Slalom delivering Azure data solutions to U.S. healthcare orgs
System Integrator (SI)	Ideally industry-focused, but often not. Access to midmarket customers and great for a product that requires services to be successful. Smaller SI’s are often nimble and flexible	SI’s offer a huge range of services from building Microsoft Teams integrations, developing custom software solutions and now building agentic solutions
Independent Software Vendor (ISV)	Product innovation and ecosystem plays	DocuSign integrating with Microsoft 365 or Power Automate connectors
Value Added Reseller (VAR)	Mid-market sales & deployment	CDW bundling Microsoft 365 with cybersecurity solutions
Large Account Reseller (LAR)	Licensing scale & procurement	SoftwareONE reselling Microsoft 365 or Azure consumption SKUs
Distributor	Reach and partner enablement	TD Synnex recruiting resellers for Azure and Defender bundles
Managed Service Provider (MSP)	Operational management & retention	Rackspace offering managed Azure and Microsoft 365 environments

In the Microsoft world, co-sell readiness and marketplace presence are essential. ISVs looking to succeed here often:

Register as co-sell ready in Partner Center
List solutions in Microsoft AppSource or Azure Marketplace
Enable their partners through Solution Workspace and PDM relationships

Mapping your partner mix to Microsoft’s ecosystem could provides both strategic leverage and operational scale. Understanding how these partner types fit into Microsoft’s tiered programs, incentives, and co-sell motions can significantly accelerate your ISV growth.

Real-World Applications: How ISVs Use a Partner Mix

Below are some simple examples

1. ServiceNow

Works with GSIs NSI and SI’s (e.g., Deloitte, Accenture) for enterprise transformation
Builds with ISVs for App Store extensions
Leverages SIs and VARs for implementation

2. Okta

Partners with SIs and MSPs for identity management rollouts
Collaborates with ISVs (e.g., Zoom, Slack) for SSO integrations
Uses distributors to reach smaller resellers

3. Atlassian

Strong ecosystem of marketplace ISVs
Engages SIs for Jira Service Management implementations
Scales globally with distributors like Arrow

Know Your Partners, Know Your Growth

As your ISV scales, your partner strategy must evolve. Understanding the strengths and roles of each partner type ensures you can:

Design effective co-sell and delivery models
Fill ecosystem gaps with purpose
Accelerate growth without adding internal overhead

Next steps:

Map your ideal partner profile by business goal
Evaluate your current ecosystem for coverage and alignment
Explore partner enablement and co-sell plays

Excited for the Power Platform Community Conference!

I’m thrilled to be attending the Power Platform Community Conference on September 18th! 🎉 This event is a fantastic opportunity to connect with like-minded professionals, learn about the latest innovations in the Power Platform, and dive deep into the tools that help shape so many incredible solutions. I can’t wait to see what new ideas and best practices I’ll be able to bring back to my work after attending.

If you’re planning on joining or just curious, check out the event here: Power Platform Community Conference 2024.

Looking forward to sharing what I learn with all of you!

Blog refresh time!

I’m starting again, again. I’ve just moved hosting providers again and also starting a fresh. Over the coming month I’ll be drafting and publishing some new content!

What am I looking to share? At this stage I want to share content about BBQ’ing, tech and life in general,