Software Works (Usually). Your Adoption Strategy Does not

Mar 17, 2026

Software Works (Usually). Your Adoption Strategy Doesn’t

Software doesn’t fix chaos. It industrializes it.

Mat Witte | March 17, 2026 Subscribe for More Final Mile Insights

Key Takeaways

Software doesn’t fix chaos. It scales it.

If the operating model is broken, the tool just helps the company fail faster, with cleaner dashboards.

Buying software is not the same as installing change.

Vendors sell motion; operators still have to own the handoffs, standards, and behavior change.

Customer Success is support, not a control system.

If adoption depends on vendor staffing staying stable, the buyer has built a dependency, not a strategy.

AI will not rescue bad execution.

In routing and dispatch, it can speed decisions, but without governance it will just scale the same old bottlenecks.

If you’re buying new software or replacing your current system hoping it will save your operation, stop. Software doesn’t fix chaos. It industrializes it.

You’re not buying transformation. You’re buying an amplifier. And if your adoption strategy is weak, that amplifier turns today’s bottlenecks into tomorrow’s, only faster and more expensive.

This is not an anti-software take. It’s a pro-reality take.

The Uncomfortable Truth Bu y ers Don’t Sa y Out Loud (But Act Like It’s True )

Buyers and sellers both talk about software like it’s a forklift.

Buy it, drop it on the floor, train a super-user, and the building magically moves product better. That’s historical inertia.

If your operating model is disciplined, software makes you dangerous. If your operating model is sloppy, software makes you faster at being sloppy, with better dashboards.

The SaaS Sales Model Is Old. Like , 1880s Old

A point from the book B4B should make every operator sit up straighter:

“The B2B operating model most often practiced today was actually designed in the 1880s, more than 125 years ago.”

Different century. Different technology. Same fundamental operating model: sell the deal, move on, repeat. That doesn’t make software companies “bad.” It makes them… software companies.

And it means buyers must stop confusing a sales motion with a transformation plan.

Sales 101 Isn’t Operational Truth

Here’s a dynamic most technology buyers misunderstand:

SaaS companies are conditioned to find the problem you told them you have, then attack it. That’s sales. That’s not malpractice.

And it’s why most discovery stays strategically general: if a vendor tries to unpack every internal handoff, incentive, and bottleneck you’ve accumulated for years, the sales cycle explodes, and the deal dies. Delayed deals blow up the forecast, which directly and negatively impacts their model.

That’s why buyers must bring the operational truth to the table, because sellers can’t afford to.

“Customer Success” Is Not Your Adoption S t r a t e gy

Operators love the idea that a technology vendor will “partner with us” to drive adoption.

That partnership can be useful, but it is not a control system. Vendor Customer Success does not own your P&L, your service failures, or your compliance exposure.

And here is the boardroom reality. Customer Success coverage is variable, and when SaaS business conditions tighten, it is often one of the first functions to be resized.

If your adoption plan depends on stable vendor staffing, you do not have an adoption plan. You have a dependency.

Welcome the vendor help. Use it. Structure your program so it still succeeds if the team changes next quarter.

Now Add AI to the Mix (and Watch the Confusion Get Expensive)

AI is showing up in every release note, every roadmap, every demo.

And right now, it’s not just changing products. It’s paralyzing buying behavior. On new purchases, nobody wants to sign a multi‑year deal for “AI routing” or “AI dispatch” while the definition of “AI in production” is still moving.

That hesitation is hurting SaaS companies. It’s also shifting leverage back to buyers: more pricing flexibility, shorter terms, tougher language, and harder ROI gates.

But leverage isn’t the main point. The main point is this:

Buying software for alleged AI functionality creates two predictable problems. Problem #1: Tech Vendors Are Still Figuring Out What “AI in Production” Really Means

Even conservative analysts are forecasting a high cancellation rate for agentic AI initiatives because costs, value clarity, and risk controls aren’t mature.

Translation for operators: don’t pay a premium for a promise you can’t govern.

Problem #2: AI will amplify your bottlenecks, especially in a strategy/execution gap environment Serious thought leaders have been saying the same thing in different words:

This isn’t about layering tools onto broken workflows. Real value comes from process redesign, not the tool. So if you already live in a world of unclear ownership, exception-driven operations, and functional turf wars, AI won’t rescue you. It will accelerate the chaos.

Here’s the operational trap: today’s advanced routing optimization doesn’t just optimize routes. It changes decision velocity. If you haven’t cleared the bottlenecks, you’re basically pouring jet fuel into the same old constraints.

In Execution Paradox™ terms: AI helps you make trade ‑ offs faster across Profit / Service / Risk. But if you haven’t defined what ‘good’ looks like across those trade ‑ offs, the system will simply operationalize the loudest voice, at scale.

Buyer Demand List ( AI Routing/Dispatch Edition )

If a vendor is selling you “AI routing” or “AI dispatch,” here’s what I’d require before I pay an AI premium:

Define the decision it will make. Not “better routes.” A specific decision in a specific workflow (e.g., re- optimizing after same‑day adds; dispatching under hard cutoffs; handling late picks; managing returns/re- deliveries).
Human-in-the-loop controls. Clear override rules, escalation paths, and “kill switches” when the AI recommendation conflicts; plus plan vs. actual reporting that forces behavior change.
Auditability. You should be able to answer: Why did it make that call? What inputs drove it? Who overrode it? If you can’t audit it, you can’t govern it.
Production proof, not roadmap poetry. A referenceable production use case that matches your complexity, not a lab demo.
Commercial guardrails. Shorter initial term, adoption gates, and pricing that doesn’t punish you for discovering reality.

Wh y Adoption Fails in Final Mile ( It’s Almost Never Training )

After living in this world for decades, I’ll tell you: adoption breaks for four reasons:

No one owns the outcome. IT “owns the system,” Ops “owns the warehouse,” Sales “owns the customer,” and nobody owns whether behavior actually changed.
The field can veto by historical inertia. Not with a speech. With a thousand tiny exceptions. The system becomes optional.
You never defined ‘good’ at the behavior level. Not ‘visibility.’ Real standards: compliance rules, exception codes, dispatch cutoffs, route edits, POD discipline.
You bought configuration when you needed governance. You can configure anything. You can’t configure accountability.

How to Keep Your Current Software Vendor Accountable ( Existing Customers: This Matters )

If you’re already under contract, you have a different lever: accountability through structure. Here’s how to do it without turning every call into a fight:

Write a one-page success plan that defines outcomes (not activity) and names owners on both sides.

Run a monthly value review with a scorecard: adoption metrics, exception trends, root causes, and decisions needed. No slides. No fluff.
Escalate early and professionally. Do it while there’s still time to fix it. Don’t wait until the last month of the term to get serious.

The Operator Adoption Pla y book (What Bu y ers Must Install Alongside the Software )

If you want adoption, treat it like an operating model install, not a tech install. Most teams “implement software” and then act surprised when the field keeps running the business the old way. The tool is not the hard part. The operating discipline is.

If you do nothing else, install these four things alongside the software:

Outcome Owner: One accountable leader with cross-functional authority (not a project manager).
Non-negotiables: 5 to 10 behavior standards the field cannot “exception” their way around.
Cadence: Daily and weekly exception decisions and monthly value realization, not status meetings.
Incentives: Stop paying Sales to promise and Ops to suffer. Align rewards to adoption and outcomes.

I’ll unpack each of these in a future edition with examples you can steal and use.

A Note to Software Companies (Because I Do Want You to Read This)

If you sell into final mile and you want better customers:

Stop overselling “easy.” Start selling “operating discipline.”

And do your part on the front end: ensure your new customer is actually ready for implementation and adoption. Or better yet, take the risk and be a preparation partner, or hire a field expert to do it for you to ensure readiness.

The best customers aren’t the ones who believe your platform will save them. They’re the ones who say: “We’re going to do the hard work. Your tool will help us enforce it.”

Those become your references.

Moving Forward

Every routing and dispatch decision is a trade‑off across Profit / Service / Risk. That’s the Execution Paradox.

Until that’s settled, you’ll keep buying tools to dodge a leadership decision, and calling it “adoption” when historical inertia wins.

Vendors ship features. Buyers drive change. Don’t confuse the two.

Sources ( For Readers Who Want to Go Deeper )

B4B excerpt (AFSMI):

https://www.afsmi.nl/fileadmin/user_upload/Strate g y _Shift_from_B2B_to_B4B_Chapter1_LR.pdf

Bain (customer success / post-sales model mismatch): https://www.bain.com/insights/why-software- companies-customer-success-is-failing-tech-report-2024/

TechCrunch (layoffs by function; references Layoffs.fyi crowd-sourced data):

https://techcrunch.com/2020/05/04/data-shows-which-tech-roles-might-be-most-vulnerable-amid- la y offs/

Layoffs.fyi (roles most affected; opt-in lists): https://la y offs.f y i/2020/05/05/what-roles-have-been-most- affected-by-startup-la y offs/