Great salespeople—the truly talented rainmakers—are about as rare as unicorns and just about as mythical, too. In many cases, they own their customers more than their employers do.

A few years ago I was making calls with a top-notch electrical supplies rep. As we pulled up to a major manufacturing plant, he said, “I took this account from $5,000 to $250,000 in one year.”

“Wow!” I said. “How’d you do that?”

“Easy,” he shrugged. “I used to work for another distributor and did $250,000 a year with this customer. They laid me off, their competitor hired me, and I just switched their sales over.”

No wonder many electrical distributor reps make so much money. If you own an account base worth millions and can take it to any distributor in town, you’re going to spark a bidding war for your services.

But look at what actually moved. Not a price file. Not a stocking program. What moved was his knowledge of those buyers: who signs, who stalls, what they run on the floor, what it would take to make them switch. All of it lived in his head, which is exactly why it left with him.

Around the same time I rode with another rep whose customers trusted him so much that plant engineers called him in to diagnose their technical problems. We spent three hours at one plant while he taught two engineers what was going wrong with a motor control system. He’s not an engineer. He never went to college. But he’s in his mid-60s and he’s been selling plant automation for four decades. He doesn’t just know where the bodies are buried. He buried them.

He was also unhappy. He was six months from retirement and management still hadn’t assigned anyone to take his place. “How can I teach someone about my accounts if they haven’t chosen anyone yet?” He loves his customers and wants them to succeed even after they stop being his responsibility. His own leadership had made it impossible for him to do right by them.

That’s the part that should bother you. Not the retirement. The waste.

Until Recently, You Couldn’t Have Fixed It

To be fair to leadership, the tools that have made it easy to capture what’s trapped in a veteran’s head didn’t exist until recently. The state of the art was putting the replacement in the truck for a few months and hoping he was savvy enough to ask good questions before the clock ran out. That’s not a process. That’s a prayer.

What changed is that you can now hand an enormous, messy pile of unrelated data to a Large Language Model  (LLM) and get back something organized. Your enterprise resource planning (ERP) transaction history. Customer relationship management (CRM) notes. Quote and bid history, including everything you lost. Customer service call recordings. Contracts and rebate agreements. Payment behavior. If you use our tools, DemandRX and Customer ExperienceRX, you can add category-level potential and satisfaction data on top of all of it.

But the most valuable thing you can feed it isn’t in any system. It’s one or more, recorded, sit-down interviews with the rep who’s leaving, plus the customer service people, inside sales reps and drivers who serve those accounts. Your ERP can tell you what a customer bought. Only the interviews tell you why the veteran did what he did. Judgment is the part that walks out the door, and judgment has never been in a database.

Think about what this used to require. Pull a dozen reports. Schedule, record and transcribe interviews with the rep, the CSRs, and the drivers. Put an analyst on trying to figure out the right business intelligence (BI) queries to surface a trend buried in six years of transactions, instead of just handing over all six years and asking what’s in there, which is what you can do this afternoon.

The old way was a project. Nobody launches a project every time a rep retires. Which is precisely why nobody has been doing this at all.

Try It This Week

Pick a rep who’s leaving. Better, pick one who might leave in the next two years. Gather what you can and paste this in:

You’re a senior sales operations consultant with deep experience in wholesale distribution. I’m transitioning a territory from a departing rep to a new one. Everything I’ve attached is the source material: [list it].

Rules: use only what I’ve given you, cite the source behind every factual claim, and mark what you don’t know as unknown. A blank is useful. A plausible guess about a real customer is a liability. Where my interview transcripts and my system data disagree, tell me about the conflict instead of smoothing it over. That gap is usually the most useful thing in the file.

First, analyze the territory. Revenue and margin trends, concentration risk, and a brief on each of the top 25 accounts covering who really decides, what they buy from us, what they’re clearly buying somewhere else, and the one thing a new rep would get wrong. Rank the specific customer-plus-category opportunities and show me your logic. Flag the at-risk accounts, including the ones that look fine in the numbers but not in the interviews. Tell me our service strengths and weaknesses in customers’ own words. And for every major account, tell me who besides the departing rep our customer could name at our company. If the answer is nobody, say nobody.

Then stop. Before you write any training material, give me your best clarifying questions ranked by how much the answers would change the program, tell me what data is missing, and write the interview guide for the follow-up conversation you’d want with the outgoing rep.

After I answer, build a 90-day onboarding curriculum with a knowledge check and answer key for each module, all written from real situations in this territory. Include a one-page day-one crib sheet and a first-90-days call plan sequenced by risk and opportunity rather than revenue. Finish with a gap register listing every open question and unverified claim.

Then argue with what comes back. Good prompting is a conversation, not a transaction. Ask it what other data would sharpen the analysis. Ask it to write the interview guides for the people you still need to talk to. Ask it to build the tests, then argue with it over the questions it wrote. Treat these systems like elite consultants: they give you better answers when you give them better material, and they’ll tell you what they’re missing if you bother to ask.

Two rules, though. Make it cite a source for every claim about a customer and state plainly what it doesn’t know, or you’ll get fluent, confident, wrong statements about real accounts that your new rep repeats in front of the buyer. And make the departing rep read the whole thing. He’s your fact-checker, and a playbook he signed off on carries authority with his successor that a generated document never will.

None of this replaces the ride-along. It makes the ride-along worth something because the new rep shows up already knowing which questions matter.

Start Before the Notice

Veterans slow-walk transitions when a clean handoff costs them income, and no prompt ever written solves that. Pay for the overlap. Tie a bonus to whether those accounts are still yours a year and two years later. Make mentoring a paid part of the job instead of a favor you’re asking for.

The balance of art and science in selling really is shifting, but the art was never really art. It was expertise nobody bothered to write down. We finally have a practical way to document expertise and pass it down, and the distributors who use it will start the process of owning their customers more than their reps do.

For more state of the art information on coaching and leading sales, don’t miss our upcoming webinar, State of Distributor CRM and Sales, Wednesday, August 26^th, 9AM PT, Noon ET. Leading sales training expert, Mike Kunkle, will join Jonathan Bein, Ph.D. from Distribution Strategy Group, to review best practices and deep research data about how to get better results and productivity from your sales force.

The post The Balance of Art and Science in Selling Is Shifting appeared first on Distribution Strategy Group.

“With more suppliers bypassing distributors and going directly to customers, pressure on traditional models will intensify. Distributors can grow alongside the trend, rather than be displaced by it, if they learn from this shift and deliberately use their leverage to integrate into supplier ecosystems, expand digitally without expanding their physical footprint, and reinforce their unique strengths.” 

“Reinforce their unique strengths” is fine advice. The rest boils down to this: manufacturers are coming for your role in the channel, and your best response is to stop investing in the assets that define that role while making yourself useful to the companies replacing you. That’s not a growth strategy. It’s advice on how to hold the door for the people carrying out your furniture. 

Start With the Word “Consumer” 

McKinsey titled this theme “Direct-to-consumer models are continuing to expand, and the lessons haven’t changed.” Read that again: direct to consumer. Distributors don’t sell to consumers. Distributors’ customers are contractors, factories, hospitals, schools, municipalities, and dealers—businesses that buy products to run their operations. Retailers sell to consumers. If a little consumer volume trickles through a distributor’s counter, it’s incidental. Maybe “consumer” is a typo. Maybe it’s a tell. Either way it’s not a small mistake, because D2C is a retail playbook, and using the term imports a decade of consumer-brand ideology—cut out the middleman, own the customer—into channels where the economics are entirely different. 

And that playbook didn’t even work in retail. Nike, arguably the best-funded direct-to-consumer experiment in modern retail, sidelined many of its retail partners in pursuit of higher-margin direct sales. (Nike calls those retailers its “wholesale channel,” which tells you how loosely channel vocabulary gets used even by the companies living it.) Within a couple of years, slowing growth and shelf space surrendered to upstart competitors forced the company to rebuild relationships with the very retailers it had pushed aside. The tier is different, but the lesson isn’t: a manufacturer took over channel functions from its downstream intermediary, discovered it couldn’t perform them as well, and paid to reverse course. 

The exhibit behind the theme gives the game away. McKinsey reports that “more than 50% of supplier sales are already made through direct-to-consumer channels.” Look at what counts as D2C: “via phone” (15%) and “in person” (19%). That’s field sales reps and phone orders—the way manufacturers have managed the big orders going to their largest accounts since before the launch of the interstate highway system. This business has always been sold direct, while distributors handle the fragmented long tail where orders are small and service intensity is high. That’s not disruption. It’s the ordinary architecture of B2B channels with a trendy label stuck on it. And because the exhibit is a snapshot with no trend line, it can’t demonstrate that anything is “continuing to expand” at all. 

Where’s the Evidence? 

McKinsey does present data: 86% of suppliers expect to expand D2C investments, 72% expect direct sales to grow more than 25 % in two years, and 65 % of distributors are “bracing” for at least 10% of sales to bypass them within the next 12 months. 

Every one of those numbers is a survey response about intentions or anxieties—not a shipment. Suppliers have been telling consultants they intend to go direct every time margins get squeezed for as long as I’ve been in this industry. And do the arithmetic on the fear: if distributors actually lost 10% of revenue to direct fulfillment every year, the industry would be visibly dying within three. McKinsey’s own footnote says the opposite is happening: from 2020 to 2025, distributors outperformed many industrial peers—and in several cases the broader S&P 500—with total shareholder returns 2.5 times greater, by the firm’s own analysis. Industries in the middle of being disintermediated do not post historic profitability and market-beating returns. 

Why Direct Keeps Failing 

For simple products bought in simple transactions, three capabilities decide who wins: wide assortment, easy ordering, and fast delivery. A manufacturer selling direct can build easy ordering. That’s one out of three. A single manufacturer can never offer broad assortment—they’re one brand. The only way to fix that is to stock other manufacturers’ products, at which point congratulations: you’ve become a distributor. And manufacturers almost never beat distributors on delivery because they lack the route density and local inventory that distributors spent decades building. 

The economics get worse from there. When multiple manufacturers in a region go direct, each one builds a duplicate cost structure—its own sales coverage, warehousing, credit operation, and logistics—to serve the same customers one distributor serves with a single shared infrastructure. And pooling demand across brands and customers does something no manufacturer can replicate alone: volume grows faster than volatility, which means lower safety stock per dollar sold, smoother replenishment and better service. Inventory pooling isn’t a nice-to-have. It’s the mathematical core of why distribution exists. One distributor in a two-step channel put it to me plainly: there’s a big difference between shipping to and managing credit for a handful of distributors versus doing it for ten thousand dealers nationwide. 

What Customers Actually Say 

Since McKinsey built its case on surveys, let’s compare notes. Their customer survey had 599 respondents. In direct contrast and using our Customer Experience RX platform, we’ve administered more than 31,000 customer surveys across 50 distributors, measuring how much customers value ten distributor capabilities—and how satisfied they are with each one. 

The number one capability customers weigh when choosing a supplier—ranked first of ten, with an importance score of 9.25 out of 10—is inventory availability. The most physical, most capital-intensive thing a distributor does. The precise asset McKinsey advises distributors not to expand. 

Now the uncomfortable part: satisfaction with inventory availability scores just 6.79, sixth of ten. That 2.46-point gap between what customers want most and what they’re getting is the widest in our entire benchmark. Among construction customers, it stretches to 2.70. So the data cuts two ways. It confirms that availability is where distributor value lives—and it warns that distributors are underdelivering it. A gap like that is the open door competitors can walk through. The answer to it is not “expand digitally without expanding your physical footprint.” The answer is to get dramatically better at the thing your customers just told you matters most. 

We see the same picture at ground level. We recently completed channel research in one distribution vertical for its trade association—executive interviews, site visits, and a survey of 202 channel participants, most of them the dealers who buy from distributors every day. They ranked parts and inventory availability as the most valuable thing distributors provide. Asked which capabilities would be most expensive for manufacturers to replicate internally at scale, they pointed to inventory investment and regional stocking. And when we asked what typically happens when manufacturers bypass distributors, “worse overall” was the runaway top answer—almost no one said the channel would work better without distributors. One respondent wrote: “In my 35 years in this industry, no manufacturer has been successful in this area.” We’re about to field similar research in a second vertical for another trade association. I’ll let you know if the story changes. I doubt it will. 

The Real Predator 

None of this means distributors are safe. Share is shifting—just not to manufacturers. Amazon Business went from $1 billion in 2015 to $60 billion today, by Amazon’s own announcement, and it wins exactly where the three capabilities are the whole game: simple products, simple transactions, no human touch required. But losing share to Amazon Business is not disintermediation. It’s losing to a better intermediary—one that out-executes on assortment, ordering and delivery at a scale no regional player can match. Go back to that satisfaction gap: Amazon Business grows in the space between what customers want and what distributors deliver. McKinsey looked at a real wound and named the wrong predator. The competitive threat to distributors is intermediary versus intermediary. Manufacturers going direct is a sideshow—with one important exception. 

How Manufacturers Actually End Up Direct 

Manufacturers don’t build direct channels because consultants tell them to. They end up direct because someone encourages them to build the capabilities. And too often, that someone is their distributor. 

Here’s how it happens. A distributor, looking for superior returns on working capital (often PE-backed and obsessed with ROIC), tells a supplier…” I want you to ship the rest direct for me.” It feels like smart inventory management. But look at what the distributor just did: they asked the manufacturer to invest capital in pick, pack, ship, and small-order logistics—the exact capabilities the manufacturer hadn’t refined, and the distributor’s margin depended on. Once that investment exists, the manufacturer starts looking for ways to improve its return. And the shortest path to better utilization of small-order fulfillment capacity is selling on Amazon Business, where third-party sellers already account for more than half the volume. 

Our vertical research caught the motive from the other side: when we asked manufacturers what tempts them to go direct, the top answer was margin pressure—not distributor failure. They see your margin. They don’t see your costs. The manufacturers I talk to who understand those costs tell me they’d rather participate on Amazon Business through their distributors, or with a 3PL, than build the capabilities themselves—because Amazon’s performance standards demand distribution muscle as strong as a great distributor’s. The barrier protecting distributors isn’t the platform. It’s the operational capability. Every direct-ship request chips away at that barrier using the distributor’s own volume as the training program. 

McKinsey Refutes McKinsey 

Here’s the strangest part of the article. The body of McKinsey’s own direct-to-consumer section says leading distributors are “doubling down on what makes them unique by expanding their assortment, building their technical expertise, expanding their logistics infrastructure, and deepening their customer relationships.” Expanding logistics infrastructure is expanding physical footprint. The section’s only case study is a distributor that stopped a supplier’s direct move cold by pointing to more than $50 million in accessory inventory held locally—inventory the supplier’s customers couldn’t keep projects on schedule without. And the article’s fifth theme, “trust is the new premium,” lists product availability first among the things customers expect distributors to deliver. All of that is correct. All of it refutes the theme-four prescription. The exhibit says don’t expand the footprint; the evidence underneath it says the footprint is the leverage. 

Louis Stern and Adel El-Ansary laid down the governing principle in their classic Marketing Channels back in 1977: the value-added functions of a wholesale distributor—inventory holding, bulk-breaking, credit, market coverage, technical support and the rest—will be performed by someone in the channel. You cannot eliminate them. You can only reassign them. And whoever performs them gets paid for them. 

That’s why “expand digitally without expanding your physical footprint” is a polite way of saying “perform fewer functions.” We already know what a distribution business that performs few functions and holds no inventory risk is worth, because it exists: it’s called a manufacturer’s rep. Reps earn a fraction of distributor margins and sell their firms for roughly one year’s commissions—because they own no inventory, no credit book and no logistics assets. Strip the inventory out of a distributor and you haven’t created an asset-light innovator. You’ve created a rep with an ecommerce site. 

What to Do Instead 

First, hold onto your functions—and perform them better. Inventory risk isn’t a burden to engineer away; it’s the price of admission and the source of the margin. The 2.46-point availability gap in our data is not an argument for carrying less inventory. It’s an argument for carrying smarter inventory—better forecasting, better analytics, better positioning—because customers have told us definitively that availability is why they choose distributors.  

Second, watch the drift. Before you ask a supplier to direct-ship your tail, ask what they’ll do with that capability once they’ve built it. You already know the answer. 

Third, fight the real fight. Amazon Business wins on simple, and it keeps using AI to reclassify complex as simple. Your defense is deepening complexity—services, integration, technical depth, being embedded in the customer’s operations—faster than technology commoditizes it. 

Manufacturers rarely disintermediate distributors. Far more often, distributors do it to themselves—one shed function, one direct shipment at a time. 

The post McKinsey Is Wrong About Manufacturers Going Direct  appeared first on Distribution Strategy Group.

Amazon Business launched in 2015 and made about $1 billion in its first year. Today’s announcement puts it at $60 billion, up from $35 billion just four years ago. (That’s gross sales volume flowing through the platform, including third-party sellers, not Amazon’s own revenue. The press will conflate the two; you shouldn’t.) I read that number as a warning to the distribution industry: A new business model is replacing the old one, but only in some sectors and only for some transactions and distributors.

For simple products bought through simple transactions, three capabilities decide who wins: wide assortment, easy ordering, and fast delivery. Nobody beats Amazon Business on those three across as many categories and geographies. For complex products and transactions — where the customer needs selection assistance, fabrication, kitting, cutting, technical support, jobsite coordination, or commissioning — traditional distributors still offer the best solution, and it’s not close.

The line between the two models is human involvement. Amazon engineered its model, so people rarely touch a transaction. People are variable cost, and Amazon is built to avoid variable cost — or, better yet, to charge someone else for it. Amazon has said more than half of Amazon Business sales come from third-party sellers.

Amazon keeps the information flowing, the customer relationship, the data, and the commission, and passes the physical flow and its costs to the seller. And when Amazon does handle fulfillment, it doesn’t absorb the variable cost; it sells fulfillment back to the seller as a service, at Amazon’s price. Amazon split the transaction in half, kept the profitable part, and turned the other half into a revenue stream.

Here’s something most distributors get wrong. For 30 years I’ve watched distributors chase online sales as though a higher share of website revenue was automatically better. It isn’t.

Ask a harder question: How much of your revenue comes from self-service orders of products anyone could stock? That number is a proxy for your vulnerability to Amazon Business because those are the orders where the customer needed your inventory but didn’t need you. Digital sales embedded in the customer’s operations — managed inventory, VMI and jobsite logistics — are a different story. The channel isn’t the moat; being inside the customer’s workflow is, though today’s announcement shows Amazon is filling in that moat, too. You absolutely need state-of-the-art digital capabilities. That’s table stakes now. But when distributors dumb down their value propositions to drive up online sales, they move their businesses into the bull’s-eye of where Amazon is strongest.

Complexity Is a Moving Target

The wallet-share erosion isn’t easy to measure. Customers cherry-pick. They keep buying complex items from you while the easy orders shift to Amazon. That high-margin, tail-spend business is funding your delivery route density and absorbing your fixed costs. You’ll lose the profitability of the account long before you lose the account.

One more thing: The complexity line doesn’t hold still. AI moves it every year, and Amazon is a technology company that happens to sell products. Product selection that used to require a rep’s expertise is increasingly handled by software. Amazon is building those tools right now. Complexity is a moat for you only if you keep deepening it. The good news is that AI cuts both ways. It’s also the best tool distributors have ever had for delivering complex, high-touch service at a cost the model can finally afford.

No one has credibly sized the U.S. wholesale market by complex versus simple, but in an $8 trillion industry, both categories are enormous. Expect Amazon to keep adding AI-enabled capabilities — configurators, virtual technical support, and tools we haven’t seen yet — that reclassify “complex” as “simple,” making a growing share of the total easy to order online.

Today’s announcement names the tools already shipping: an AI buying assistant, AI-driven savings insights, spend-anomaly monitoring, and guided buying. And it’s not only software. Amazon is rolling out dedicated business delivery fleets with scheduled windows and palletized drop-offs, attacking the physical complexity that used to belong to distributors alone.

Scale Changes the Equation

Amazon Business has one more scale advantage. Most distributors operate in one country or a few. Amazon Business is active in 11, a combined wholesale market worth double-digit trillions. And that scale compounds. Amazon amortizes every dollar of technology and AI investment across 11 markets at once, while most distributors amortize theirs across one. That’s why the capability gap can widen even while you’re investing. No wonder Amazon is pursuing this opportunity so aggressively.

So, what should distributors take from today’s number? Keep it in perspective. Sixty billion dollars is still a small slice of a multitrillion-dollar industry. But it was $1 billion 10 years ago. Three moves matter:

• Build state-of-the-art digital capabilities, including AI, not to maximize online revenue but to meet customers wherever the transaction belongs.
• Make complexity your strategy, not your legacy. Add services, integration, and technical depth faster than technology commoditizes them.
• Watch your mix. If self-service sales of undifferentiated products are your fastest-growing segment, you’re growing the part of your business Amazon takes first.

The distributors that thrive alongside a $60 billion Amazon Business will be the ones that stopped trying to out-Amazon Amazon and made themselves too complicated to replace.

The post What a $60 Billion Amazon Business Means for the $8 Trillion Distribution Industry appeared first on Distribution Strategy Group.

At the time of this writing, NVIDIA’s market capitalization is $4.31 trillion — 4.8 times the combined value of all 94 publicly traded distributors we track. 

Let that sink in. One AI chip company is worth five times the public equity value of a massive swath of the distribution sector. It is dramatic. It is unprecedented. And it is fueling an increasingly common question: 

Are we in an AI bubble? And if so, what happens to distributors if it bursts? 

Why Volatility Could Be Amplified 

One reason the “AI bubble” concern is not irrational is the degree of financial interdependence inside the AI ecosystem. The major players are not just customers and suppliers. In many cases, they are customers, suppliers, and investors in one another. 

Consider the structure: 

• NVIDIA supplies the high-end GPUs that power AI training and inference. 

• Microsoft, Amazon, and Google buy those chips in enormous quantities to build hyperscale data centers. 

• The same hyperscalers provide cloud infrastructure to companies such as OpenAI. 

• Microsoft is also a major investor in OpenAI. 

• Amazon and Google are investing billions in their own AI model development while simultaneously serving third-party AI companies on their clouds. 

Revenue concentration is real. A meaningful portion of NVIDIA’s growth is tied to a small number of hyperscale buyers. 

Layer on top of that, the fact that these firms are committing tens of billions of dollars annually in capital expenditure, often justified by projected AI demand growth. 

When customers, suppliers and investors are this intertwined, sentiment shifts can cascade: 

• If hyperscalers slow capital spending, chip demand drops. 

• If chip demand drops, revenue growth expectations fall. 

• If model monetization disappoints, cloud growth assumptions weaken. 

Markets do not unwind these relationships gently. Instead, they often fall like dominos — not necessarily because the technology failed, but because expectations reset across a tightly connected system. 

That does not mean a collapse is inevitable. It does mean that if volatility arrives, it could be multiplied by the very structure that fueled the surge. And that is a financial market dynamic, not an operational one inside distribution businesses. 

Financial Shock vs. Operational Reality 

Two different conversations are happening right now: 

• Financial markets 

• Operating businesses 

They are related, but they are not the same. 

In financial markets, concentration risk is real. Valuations are stretched into parts of the AI ecosystem. And because of the financial entanglements between leading players, if sentiment turns, stocks could fall sharply. Pension funds, exchange-traded funds, and individual investors would feel that. 

But distribution leaders do not run portfolios. They run businesses. From an operational standpoint, the calculus looks quite different. 

The Scale of the Sector 

According to the U.S. Census Bureau, wholesale distribution in 2025 generated $8.4 trillion in annual revenue. That is not a niche sector riding on speculative capital. It is a foundational component of gross domestic product. 

Distributors move product, extend credit, manage inventories, provide local service, generate and aggregate demand, break bulk and solve problems. That means even if NVIDIA’s stock were cut in half tomorrow, HVAC contractors would still need compressors, electrical contractors would still need breakers, and industrial customers would still need bearings. Factories would need automation and maintenance, repair and operations products, and companies would still need janitorial and sanitation supplies. 

The real economy does not pause because equity multiples compress. 

The Dot-Com Parallel 

We have seen this before. In the late 1990s, internet stocks soared. Then from 2000 to 2002, the Nasdaq composite fell 80%. 

It was brutal for investors. But the internet did not disappear. Amazon did not go away. Digital transformation did not reverse. 

After the bubble burst, the internet became more important, not less. Capital became more disciplined. Weak businesses failed, but strong operators doubled down as the technology matured. Companies that learned to use it gained structural advantages. 

That is a more relevant lesson for distributors than worrying about NVIDIA’s valuation. 

What Would Actually Change? 

Assume the pessimistic scenario: 

• AI stocks fall sharply. 

• Venture funding slows. 

• Some startups fail. 

• Headlines declare an “AI bust.” 

What changes for a distribution CEO? Extraordinarily little. 

Competitive dynamics do not disappear: 

• Margin pressure remains. 

• Labor costs do not fall. 

• Customer expectations do not decline. 

• Private equity firms do not stop asking about productivity. 

If anything, tighter capital markets typically increase pressure on efficiency and cash flow, making operational leverage more important, not less. 

AI is not just a speculative asset class. It is a productivity tool. Those are quite different things. 

Speculation vs. Application 

When people talk about an AI bubble, they usually mean: 

• Semiconductor valuations 

• Hyperscaler capital spending 

• Venture funding 

• Public equity multiples 

Distribution leaders should be focused on: 

• Automating repetitive back-office processes 

• Enhancing sales enablement 

• Improving forecasts 

• Reducing error rates 

• Increasing throughput per employee 

• Serving customers faster and better 

The stock market can overshoot, and it does not change these operational imperatives. Even if AI stocks dropped 50%, distributors that effectively apply AI to reduce selling, general and administrative costs, improve inventory turns or enhance service would still widen their competitive gap. 

Financial shock does not change operational reality. 

The Real Risk: Distraction 

Ironically, the bigger danger may not be a bubble burst. It may be paralysis. 

If leaders delay action because they fear the cycle turning, treat AI as a speculative fad instead of a structural productivity shift, or wait for valuations to settle before experimenting, they risk falling behind competitors who are quietly learning. 

During the dotcom bust, companies that continued building digital capabilities emerged stronger. The same pattern is here. 

Perspective Matters 

Public markets can be volatile. Distribution is large, durable, and economically embedded. 

An AI bubble bursting would be painful for investors heavily exposed to AI equities and could slow some capital spending at the margins. But it would not reverse a fundamental truth: Companies that use technology to increase productivity outperform those that do not. 

That was true before AI, and it remains true regardless of market sentiment. 

What Distribution Leaders Should Do 

Focus on application, not speculation. 

Ask: 

• Where can AI remove friction? 

• Where can it reduce labor intensity? 

• Where can it improve decision-making? 

• Where can it accelerate growth? 

If AI valuations fall, the tools will not vanish. They may become more affordable and more accessible. Operational realities will continue, and the opportunity for competitive advantage may grow. 

Distribution leaders are not paid for time technology cycles. They are paid to build durable businesses. 

Call to Action 

If you want to explore what practical AI application looks like inside distribution — beyond headlines and stock prices — join us at Applied AI for Distributors, June 23-25 in Chicago. The focus is not market capitalization. It is execution. 

Learn more and register at AppliedAIforDistributors.com. 

Because whether markets are booming or bust, the warehouse still must run. 

The post How Bad Would an AI Bubble Burst Be for Distributors?  appeared first on Distribution Strategy Group.

“We’re not going to lay people off because of AI. We’ll let headcount come down naturally through attrition.”

It’s a comforting idea. It implies that job losses tied to AI productivity gains will be humane and gradual. It signals responsibility. It lowers anxiety. And it feels like a reasonable compromise between innovation and compassion.

There’s just one problem: the math eventually stops working.

Not because leaders are insincere. Not because employees are irrationally fearful. But because AI changes the structure of the labor market over time in ways that quietly undermine attrition-based workforce strategies.

What looks humane in theory can become an attrition trap in practice – just not all at once.

Why Attrition Works—At First

In a normal, pre-AI labor market, attrition is predictable. Most companies experience 15% to 20% annual voluntary turnover, and two-thirds of that comes from people leaving for other jobs. Retirement and personal reasons – family, education, relocation – account for the remainder. The bottom line is simple: most people leave because opportunities exist elsewhere.

In that environment, attrition is elastic. If you slow hiring, headcount naturally declines. Leaders have relied on this dynamic for decades.

The key assumption, however, is that someone else is always hiring. For now, that assumption often still holds.

Why Early AI Adopters Can Still Rely on Attrition

AI adoption doesn’t happen everywhere at once.

In the early stages, companies that move faster on AI can still rely on a functioning labor market because slower-moving firms continue to hire. Employees who feel uncertain, mismatched, or simply ready for a change still have somewhere to go.

In this phase:

• Attrition continues to work.
• Headcount can decline gradually.
• Workforce transitions can remain voluntary.

Ironically, this is exactly when AI adoption feels least threatening – and when attrition feels safest as a strategy.

How AI Gradually Breaks the Assumption

AI changes hiring behavior long before it shows up as layoffs. As productivity rises across more firms:

• Open requisitions get canceled.
• Backfills stop being automatic.
• Growth no longer requires proportional headcount increases.
• Hiring slows, then freezes, across larger parts of the market.

None of this feels dramatic in isolation. But as AI adoption spreads, the labor market begins to change systemically. What starts as an advantage for early adopters becomes a shared constraint.

When Attrition Loses Its Power

As AI adoption becomes widespread, job-to-job mobility begins to stall:

• If Company A isn’t hiring, Company B’s employees can’t leave.
• If Company B isn’t hiring, Company C’s employees can’t leave.
• The job-switching engine that drives voluntary attrition weakens.

At that point, attrition doesn’t disappear – but it shrinks to a non-functional minimum.

Instead of 15% to 20% annual turnover, organizations may see attrition fall into the low single digits, driven primarily by retirements and a smaller number of personal or family-driven exits. Voluntary moves to other employers disappear – not because people are happy, but because there’s nowhere to go.

This is where the “we’ll manage this through attrition” plan quietly stops working. Headcount stays flat. Work changes anyway. Roles blur. Expectations rise. Anxiety increases. And leaders are left wondering why their humane strategy suddenly feels brittle.

The Attrition Trap

This is the attrition trap:

Leaders delay explicit workforce decisions because attrition used to work – and because it still works just enough to feel safe. But as labor mobility declines, that strategy loses effectiveness without announcing its failure.

AI doesn’t force layoffs immediately. It rewards early adoption with optionality – and penalizes delay with rigidity.

Eventually, organizations reach an uncomfortable moment:

• Productivity gains are real.
• Role requirements have shifted.
• Some work no longer exists in its old form.
• And headcount hasn’t adjusted meaningfully at all.

At that point, transitions tend to be late, reactive, and far less voluntary than they would have been earlier.

The Real Takeaway

I’m pointing out that labor market mechanics change over time, and that strategies built for a fluid market become unreliable as that market tightens.

The most important insight isn’t that leaders should act harshly – it’s that timing matters.

Organizations that adopt AI earlier can:

• Capture productivity gains sooner.
• Rely more on voluntary attrition while mobility still exists.
• Reduce the likelihood of forced headcount reductions later.

Those that delay may find that when they finally need attrition to work, the labor market no longer cooperates.

A Leadership Imperative

AI doesn’t create an attrition crisis overnight. It creates an attrition illusion—the belief that yesterday’s workforce math will still apply tomorrow. Leaders who understand this can move faster, communicate earlier, and preserve flexibility while the labor market still allows it.

Those who don’t may discover – too late – that their most humane intentions have left them with the fewest humane options.

If you want to learn more about how you can be an early-mover with AI – and how AI is likely to affect jobs and training – be sure to sign up for our upcoming conference, Applied AI for Distributors, June 23-25 in Chicago. In addition to more than thirty technology companies showing how distributors can achieve new levels of productivity and profits with AI-enabled tools, we’ll have leading speakers, including Matt Sigelman, CEO of The Burning Glass Institute. Matt is an expert on how AI affects jobs and will be a featured keynote speaker at the event. Go to www.appliedaifordistributors.com for more information and to register.

The post The AI Attrition Myth appeared first on Distribution Strategy Group.

Consider:

• Your income is 100% commission.
• Your contracts with the manufacturers you represent are only guaranteed for 30 days, meaning you effectively must earn your renewal every month.
• The value of your company is typically no more than a single year’s commissions—compared to the multiple of earnings that some other businesses command.

There’s very little margin for error in the rep business, so it’s no surprise that in my more than 40 years in distribution, I’ve found agency principals to be some of the sharpest, hardest working, and savviest business leaders anywhere. In fact, if I want to know what’s going on in a distribution channel, I call my manufacturer’s rep friends because they are more plugged in and informed than just about anyone else.

These views were reinforced in October from the 20th to the 23rd when I had the honor of emceeing the 53rd Annual Conference of the Association of Independent Manufacturers Representatives, or AIM/R, in Scottsdale, Arizona. The quality of attendees, presenters and networking was top-notch and while I was there to help manage the event as the emcee, this experience wound up becoming a major learning occasion for me.

You Must Take Time to Sharpen the Saw

The theme of the conference was “Working on your business and not just in it.” We’re all familiar with this advice, but it’s difficult to make time for working on your business when you’re swamped with day-to-day challenges, opportunities, and surprises. Arguably, attending any industry conference helps you work on your business, but some events are better than others. The AIM/R 53rd Annual Conference was among the best I’ve seen, starting with the lineup of speakers.

• Gino Wickman, the founder of EOS® Worldwide and the author of Traction: Get a Grip on Your Business, and other books designed to help entrepreneurs succeed, led a 3.5 hour workshop to kick off the conference. Wickman is the world’s leading authority on how to run a business effectively and he did not disappoint. In clear, compelling, and entertaining fashion, Wickman delivered a masterclass in entrepreneurial management.

• AIM/R firms sell primarily in the plumbing and heating, ventilation and air conditioning (HVAC) sectors, and the organization provided two major distributors to take the stage at various times during the meeting:
  • Hajoca: Steve Ferry, Division Manager and Sean Kelly, President and General Manager of Emco, a Canadian subsidiary of Hajoca.
  • Winsupply: Steve Coen, Director of Business Development and Luke Muszynski, VP, Vendor Relations.

These are among the largest and best-run distributors in their industry, and it was fascinating to hear the constructive and direct dialogue between these individuals and the reps at the meeting.

Other speakers included:

• Economist Chris Kuehl, Ph.D., with Armada Corporate Intelligence, who (as always) delivered a fascinating update on the economy.
• Inside Sales expert Mark Peck, who described how an effective outbound inside sales program can build sales productivity and results.
• Branding and marketing expert Teri Slavik-Tsuyuki of tst ink., on “How to Build Your Brand + Stand Out in a ‘Sea of Sameness.’”
• CoMetrics CEO Paul Giudice, who updated the group on a new performance benchmarking service his company is providing AIM/R. This provides invaluable data so principals can understand how effectively their companies are operating vs. peers.
• Brooks Hamilton and Tim McLaughlin with AI Strategy Advisors, who led a fascinating workshop on artificial intelligence and how it can transform your business.
• In addition, there were outstanding breakout sessions on, “Buy/Sell: The Good, The Ugly & The Exciting;” “From Founder to Future: Tailoring your Succession Plan;” and “Employee Benefits to Attract and Retain.”

In addition, the entire AIM/R executive committee took the stage for an extended town hall. And, of course, the conference featured awards, memories, and a preview of next year’s event, which will be in Napa Valley.

My Takeaways as Emcee

As emcee, I had a front-row view of the extensive planning that went into this event. I was honored to work with Conference Chair Jeff Blair, President of Barclay Sales, Stacey Woldt, Executive Director for AIM/R and others. This was one of the best-planned events I’ve ever been involved in, and it showed in Scottsdale with both in the quality of the program as well as how smooth the event was.

The bottom line is that the hard work in advance of the conference paid off. 2025 – 2026 AIM/R Chair and President of Preferred Sales Inc., Michelle Lewnes-Dadas told me, “The AIM/R Annual Conference is truly the highlight of my year. It’s one of the few times I can step away from the day-to-day demands of running our agency and focus on working on the business instead of just in it. Many of the foundational elements of our business have been shaped by insights gained at this conference—it’s an investment that pays dividends year after year.”

2025 Conference Chair Jeff Blair, President of Barclay Sales Ltd., was justifiably pleased with the event and is already focused on next year. “It was an honor to see the results of all the volunteers who came together to make this a great learning and networking experience. I look forward to seeing everyone in Napa in 2026 to share what we have done to improve our businesses and get new ideas!”

Stacey Woldt, Executive Director of AIM/R, pointed out that the organization, “Has intentionally developed and expanded the annual conference in recent years. During the last decade, the event has grown from 250 to more than 600 total attendees. Sponsorship support from all sectors of the supply chain has increased tenfold. Each year, we close the conference wondering what in the world we will do next year to top this year’s experience.”

The 2025 event will be hard to top. But I believe that if the attendees at this event apply the lessons they learned, they’ll be sharing a lot of success stories at the 2026 event. And isn’t that what a great association meeting should accomplish?

The post AIM/R Reps Take a Break from Working in Their Businesses to Work on Them appeared first on Distribution Strategy Group.

We recently began offering workshops for distributors on how they can use AI to drive new levels of productivity and profitability. It quickly became clear that people regularly conflate “AI” with tools like “ChatGPT.”

“We use AI all the time,” one person told me. “We use ChatGPT to write most of our emails and it saves us a lot of time.” That’s great but it’s barely scratching the surface of what AI can do for a distributor. That’s like claiming you sell electrical supplies because you added batteries onto your counter displays. Sorry, but that’s a huge exaggeration.

To be clear, ChatGPT is an advanced AI software system. Along with Claude, Gemini, Perplexity and others, “Large Language Models” are bringing enormous new capabilities that any business – including distributors – can apply to gain productivity and improve profitability. But they’re just one form of AI—and there are many AI applications distributors can use to drive much bigger gains in performance.

The prospective AI “stack” for distributors includes transformational technologies that can be applied across your enterprise. From quote to order automation to returns, rebates management and more, these specialized, purpose-built applications use AI in highly impactful and specific ways. Unlike ChatGPT, you don’t have to figure out the use cases for these technologies or try to adapt the tool for the job.

Why the Confusion?

The capabilities of LLMs like ChatGPT are so amazing and impressive that it’s easy to think of them synonymous with AI. But that dramatically undersells AI—just take a look at the “boxes” in the graphic above. This is an incomplete list of areas in your business where you can find AI-enabled applications that will dramatically improve your company’s performance today.

The AI Stack for Distributors

Here’s a little extra detail on how AI can be applied across your company:

• Pricing Optimization: AI analyzes transaction-level detail, customer behavior, and competitive data to recommend price levels that maximize margin without losing business. Instead of one-size-fits-all pricing, distributors can set dynamic, customer-specific price points at scale.

• Demand Forecasting: Traditional forecasting often leans heavily on gut feel or spreadsheets. AI forecasting models incorporate sales history, seasonality, even economic and weather data, giving you sharper inventory planning. The result: fewer stock-outs, less excess, better turns.

• Dynamic Routing and Slotting: AI-driven logistics systems optimize truck routes in real time and rearrange warehouse pick locations automatically. Drivers spend less time on the road. Pickers walk fewer miles. Fill rates improve. Customers get faster service.

• Warehouse Robotics: Robots powered by AI are moving beyond novelty. They are already streamlining picking, packing, and replenishment. When combined with slotting algorithms, you’re not just moving boxes—you’re optimizing labor and throughput.

• Rebate Management: Distributors leave millions on the table every year because rebate programs are too complicated to track. AI can automate accruals, validate claims, and surface missed dollars. That’s pure profit found with almost no incremental effort.

• Quote-to-Order Automation and Cross-Selling: AI can turn quote requests into orders instantly and recommend add-on items based on purchase history or similar customers. That means faster transactions, bigger baskets, and happier customers.

• Marketing and Product Information Management (PIM): AI is transforming how product content is created, translated, and syndicated across websites, catalogs, and marketplaces. Paired with marketing automation, distributors can deliver campaigns that feel personalized at scale.

The Bigger Picture

When distributors conflate ChatGPT with AI, they risk missing the bigger opportunity. Yes, LLMs can save time in drafting emails or summarizing meeting notes. But the most dramatic gains in productivity and profitability come from embedding AI deeper into your processes—where it can handle complexity, scale decision-making, and eliminate manual inefficiencies.

Takeaway

ChatGPT may be the most visible face of AI, but it’s only the tip of the iceberg. The distributors that thrive in the next decade will be the ones who understand and apply the full stack of AI technologies to transform how they operate.

If your AI strategy starts and ends with ChatGPT, you’re missing the real prize. The future belongs to those who embrace the entire AI stack—and put it to work across the enterprise.

We’re producing a live conference on how you can use these applications (and others) to transform your company’s performance. Join distribution and technology thought leaders from across the industry as we convene to learn how to use AI to drive new levels of performance.

The post ‘We Use ChatGPT’ Isn’t an AI Strategy  appeared first on Distribution Strategy Group.

—Eric Schmidt, former Google CEO, and chairman. April 11, 2025, TED2025

The challenge with a sweeping, dramatic new technology like AI is that its effects are extremely difficult to predict. Consider these common contradictions:

• AI is in the Gartner hype cycle and will hit the trough of disillusionment soon. No, it won’t – AI is different; if anything, it’s underhyped!

• AI will take over the world and destroy humans. Nonsense! It’s going to help us cure all diseases, including cancer.

• ChatGPT is amazing! No, it makes mistakes and its writing sounds wooden. Also, it’s bad at math. But wait, its deep research capabilities are incredible!

• AI models are going to need 90 gigawatts of power to keep developing and that’s 90 nuclear plants we don’t have, so it’s going to grind to a stop soon. No – the Chinese developed DeepSeek with more efficient algorithms; that’s the way around the power problem!

• Open-source AI like China is pursuing is the best model. No, it isn’t! It gives too much power to bad actors; the U.S. model of closed systems is safer!

• AI is going to displace hundreds of millions of jobs and we’re going to have an unemployment crisis. Well, that’s only a crisis if you think work is essential for people – how about we establish a universal basic income?

Who’s right in these arguments? I have opinions; you do, too. But no one knows for sure. We’re all speculating. And, I’d argue, very little of what’s in each of these bullet points is under your control. There’s so much capital and energy and computing power and human effort being thrown at AI by so many players around the world – public, private, in every industry and sector – that no one can possibly know what the world will look like with another 5 or 10 years of AI development.

So, while these are interesting topics and, as responsible citizens, we should keep up on what’s happening with AI, as distribution leaders, the most important thing we can do right now is to block out the noise. And focus on:

The One Thing Distributors Must Know about AI

Whatever else happens in the world, your competitors are going to use emerging AI tools to drive performance and efficiency improvements in every part of their business. If you don’t keep up or stay ahead of them, you’re going to erode competitive advantage either through reduced performance or efficiency.

Consider this quick list of current in-market AI-enabled solutions for distributors:

I wrote that table in 5 minutes off the top of my head based on recent discussions I’ve had with technology companies. I’m in the business of understanding how technology can help distributors succeed and I struggle to keep up because it’s all changing so fast. How are you doing with it?

If you’re a distribution executive, you can watch TED talks about the impacts of AI on humanity; you can debate whether AI robots are going to be like R2D2 or the Terminator and you can worry over whether our new AI overlords will eventually look upon humans and pass judgement that favors our existence or not. But if you don’t apply these new technologies as faster or faster than your competitors, you’ll be having those discussions while you’re unemployed because your board of directors will find a more focused and aggressive individual to do your job.

Declutter and Focus

I don’t see any scenario in which the core activities of distributors will be made obsolete by artificial intelligence. Distributors provide this value to the channel:

Assortment convenience: A wide assortment of products from many manufacturers so that customers can consolidate their purchases efficiently and effectively.  

Fast fulfillment and delivery: By holding inventory, distributors can get products to customers quickly.  

Bulk-breaking: Distributors allow manufacturers to produce efficiently in large quantities while allowing customers to buy small lot quantities effectively.  

Demand generation: Distributors use websites, sales reps, email, and other marketing tools to advertise the products of many manufacturers effectively to a large number of customers and prospects.  

Customer service / technical support: When customers have questions, need service or advice, distributors have trained employees who can help them. 

Credit and financing: Businesses like to buy on credit because it’s more efficient and cheaper than using checks or credit cards. It also smooths cash flow for companies that need products for customers who will pay them later. 

Distributors face risks, like retailers entering the industry, manufacturers taking on some of these capabilities, but ultimately someone must provide this set of value-added functions in the marketplace. Nothing I’ve seen from AI fundamentally changes this reality. That means your existential threat from AI isn’t that it’s going to make the distribution industry unnecessary, but that your competitor will make your distribution company unnecessary.

That’s liberating because it means you don’t have to worry about some black swan event wiping out the industry. You can do what you’ve always done and that’s to continue to build a better distribution company, only you need to do it faster than ever and apply much more technology to your problems and opportunities.

When it comes to your business, declutter your mind about AI. Focus on finding AI that makes your company better. Do it better and faster than your competitors.

Where to Start

There is exactly one major distribution industry event about AI and it’s our upcoming conference, Applied AI for Distributors. It’s June 24-26 in Chicago and you have lost your mind if you aren’t attending or sending someone to this two-day immersion in AI. As you can guess by the name, the focus of the conference is to help you understand what AI technologies are available today, how other distributors are using them and how you can apply them to build a better company.

This event is likely to sell out, so sign up soon. We have good discounts for more than one attendee from the same company, so do yourself a favor and bring some colleagues. I hope you to see you there – and not just your competitors.

The post The One Thing Distributors Must Know about AI appeared first on Distribution Strategy Group.

This quest will continue for a long time as models become more powerful and we learn how to interact with this exciting and yet still-mysterious intelligence.  

In our company, COO Brian Hopkins has been the leader in building LLM tools for our team, including overlaying Claude onto our company data in a set of “Projects.” This allows us to complete work faster and better than ever.  

He’s also created “prompt generators” because as it turns out, ChatGPT, Perplexity, Gemini and other tools are better at writing prompts for themselves than we are creating them on our own! I tell the LLM what I’m trying to do, and it asks me a series of questions. It uses the answers as a prompt to give me better, more useful results than I would have gotten if I’d just typed my own question or instructions.  

The key limiting factor in LLMs is that they’re inherently passive. When I ask them questions or assign a task to them, they usually do an amazing job for me. Write a proposal? Claude looks at our previous proposals, considers my detailed request (which it helped to write with a prompt generator), evaluates our company’s capabilities and writes a proposal – complete with pricing – all in a few minutes.  

However, LLMs don’t currently work across applications and datasets and proactively do work for me. They respond to what I ask them to do, always ready, but never interacting with other technologies or jumping in on their own before I ask them to.  

Up Next: Agentic AI 

Brace yourself because the next big thing in AI is coming soon and it’s called, “Agentic AI.” The name comes from AI acting as an agent on your behalf. Here’s a simple example: 

I need to fly to Dallas for a presentation to the American Supply Association on June 18. With Agentic AI, as I’m driving back from the store, I can trigger the voice AI on my phone and say to the agent (which I’ll refer to as AIN – my name, spelling updated to the world of AI): 

“Hey AIN, schedule my June ASA trip.” The agent will book my flights, rent me a car and confirm my hotel reservation. It will know the airlines I prefer, make sure it registers everything with my loyalty numbers, remember that I don’t like my return flight to be less than three hours after I finish speaking and add all the information to my calendar.  

It can generate travel directions, monitor for weather delays and adapt automatically; it can find a gas station for me to fill up the car before I return it. It will even check the dress code and technology requirements for the event and generate a packing list for me. As I travel, it will automatically track my receipts and send in the expense statement afterwards.  

AIN will have access to my travel accounts, Office 365 account, credit cards and work databases. It will know or learn my preferences, watch for any changes that come in by email or voicemail and, in exchange for all this authority, make my travel life easier and better than ever.  

That’s a very simple example. Now think of all the ways you could use this kind of capability in your business, such as: 

• answer customer questions 
• manage your supply chain 
• negotiate contracts  
• watch for customer service issues before you or the customers know they’ve occurred  

Imagine asking your agent to prepare your company as a snowstorm approaches. It will check inventory levels on winter products and report back to you minutes later with specific products and locations where you need to act – or act itself to optimize inventory allocations and order more stock based on manufacturer availability. It will send notifications to your team to watch for travel delays and generate a marketing email to your customers to tell them how you can help them get through the storm.  

The use cases are endless because AI agents will have access to enormous amounts of data, will be able to consider many alternatives, balance many dependencies and – most importantly – act on your behalf. You won’t have to schedule calls; if someone asks for a meeting, you’ll simply tell your agent to set it up and it takes care of it for you. The change from reactive to proactive means agentic AI’s impact on your personal productivity will be even larger than LLMs.  

Challenges in Agentic AI 

Like LLMs, Agentic AI will pose challenges due to its immense intelligence and power. LLMs still hallucinate and sometimes provide wrong answers; Agents will make wrong choices and mistakes, especially when they’re early in the learning curve.  

There are ethical questions to answer. If an agent replies for you, is it really you? Are its agreements legally binding? As these systems become more powerful, it’s harder for us to control them – are we willing to cede that kind of authority to technology?  

Tough questions, to be sure, but we humans tend to adopt technologies that are convenient despite the risks – just look at the early days of commercial air travel; we were flying on jetliners before there was a radar grid and air traffic controllers!  

And keep in mind the differentiating characteristic of AI vs. all previous technologies: It learns. It improves on its own. It gets better at its tasks without human intervention. Whatever shortcomings agentic AI comes with, it will improve over time; the trajectory will be sharply upward as it accumulates more data and experience.  

The Bottom Line … 

… will be the bottom line. As long as agents simplify our lives, make us more productive, lower our stress levels and make us more money, we’re going to use them. The advantages will be enormous, and you need to learn about agentic AI now to accrue those benefits sooner than your competitors.  

Thinkers360 just published their Top 50 Global Thought Leaders and Influencers on Agentic AI 2025. At the top of the list, with a score of 100 (2nd place was a 66) sits Noelle Russell from the AI Leadership Institute. Noelle is joining us at this year’s Applied AI for Distributors in Chicago on June 24–26. She’s delivering a keynote presentation and will join us for the reception afterwards so you can ask her questions and learn from her. Noelle has vast expertise on AI in general and Agentic AI in particular and we’re honored and delighted to welcome her to the conference.  

We’d like to welcome you, too! If you want to keep up, catch up or stay ahead in AI, you or someone from your company should attend this conference. Many companies send multiple attendees so they can attend simultaneous sessions on different tracks. This is the only major AI conference for distributors in the U.S. – don’t miss it.  

Learn more about Applied AI for Distributors. 

The post Agentic AI: The Next Big Thing after ChatGPT appeared first on Distribution Strategy Group.

One of the advantages of aging is the joy of sharing what you’ve learned with people who are earlier in their careers. One of the challenges, of course, is that sometimes those people don’t listen to their elders any more closely than I did at their age!  

However, if your goal is to drive more profits, here are a few tips I have learned along the way. If this isn’t your goal, then don’t tell your boss because you’re doing it wrong!  

Lesson 1: Profitability is Complicated 

When I was a young branch manager – at a tender 24 years of age – Grainger didn’t show us cost or profitability. We just had pricing tiers and rules about how to apply them. That reinforced the belief that driving profits was about NOT DISCOUNTING. If my branch team and I resisted the urge to mark down prices, then we’d be profitable enough not to earn an angry visit from my District Manager.  

When I began working for other distributors, I began to see that better purchasing practices could make a big difference in our profitability. Rogue buying in branches drove up costs while putting Strategic Buying Agreements in place resulted in higher margins for us, as well as better rebates and marketing co-op.  

Later, I attended a workshop led by Randy MacLean, who is speaking at our upcoming conference in November, and had one of those lightning-strike moments in my brain when I realized that some accounts were extremely expensive to service while others cost us relatively little. Reducing cost-to-serve could transform a company with ordinary profits into one with extraordinary profits without touching pricing at all – or even changing our sales. This had even more impact on account profitability than gross margins! 

When I worked at White Cap, the construction supplies distributor, I saw the incredible impact on profitability when we put in place extensive training and education programs for our employees to help them understand exactly where profits came from and their role in growing them. Part of this involved helping the team understand the mechanics of profitability but an equally important breakthrough was changing their mindset so they understood that we deserved the margin we earned.  

And there’s more: From proper category management to managing delivery costs, driving efficiency in returns processing to lowering operating costs, distributors have opportunities to optimize profitability across the enterprise. Controlling discounting is important – and just one small step towards driving profits for a distributor.  

Lesson 2: You Need a Profitability Leader 

Why do most companies have a vice president of sales and almost none have a vice president of profits? The distance between the sales line and the income line on your P&L is filled with all of your company’s COGS and expenses and the drop is probably 70% to 95%. Why is the top line important enough to justify a dedicated executive but the bottom line is not?  

And don’t tell me it’s your CFO. With responsibilities including treasury, financial accounting, audit, managing debt, bank covenants, insurance, working capital, assets, board duties and more, CFOs don’t have time to take the lead in maximizing profits, too. 

It’s also not your Director of Pricing. This is an important role since pricing drives a significant part of your profits, but what about the areas I identified in Lesson 1? Who’s managing cost to serve, driving purchasing optimization, checking in on rebates and co-op opportunities and leading the never-ending efforts to educate the entire company on how to drive up profitability? 

It’s VERY COMPLEX to optimize profits and it takes a long-term implementation of best practices, training, measurements, reporting and accountability. Sure, everyone is involved in improving profits, but everyone is involved in growing sales, too, right? Why provide specialized leadership for one and not the other?  

Lesson 3: Margin Equals Value 

This one took me the longest to internalize. The reason you can sell products for more than you paid for them is that you add value to them. The challenge is that there are hundreds of things you can do to add value but every customer values different things. Consider: 

• For a large manufacturing customer, you assemble kits of products for certain subassemblies and for their MRO needs you refill their tool crib bins and also place industrial vending machines on the shop floor. Additionally, they use eprocurement to buy from you, so you’ve built a custom catalog for them and, for a specified set of 200 products, you guarantee availability and delivery within four hours because they’re essential to the operation of the plant. You also offer 24×7 emergency service – gratis. 

• For a small manufacturing customer, you simply sell plant maintenance supplies and miscellaneous products, and they send a driver on a milk run every day to pick up will calls from you and other distributors.  

• For a contractor customer, you offer counter service for their technicians who need electric motors, controls, ventilation products and other components and parts necessary to restore systems at commercial establishments so they can reopen after a mechanical failure. It’s extremely difficult to forecast the products they need or when they’ll need them. 

If you and I sat in front of a whiteboard, we could probably put together 25 more customer needs profiles in an hour. For every customer, the distributor’s role in the supply chain is essential – you need a mix of products from many manufacturers, as well as the ability to forecast and stock inventory and deliver it quickly to meet demand. But how do you price thousands of products for thousands of customers in countless scenarios? No wonder distributors’ pricing systems are so much more complex than retailers’! 

I’ve seen situations in which executives – out of a failure to appreciate this complexity or from sheer frustration – try to force simple pricing structures onto an organization: “We’re going to simplify our pricing system! I want three-tiered pricing with business rules about how to apply them and the sales force is going to have to slot their customers into this matrix based on annual volume!” 

This works for about as long as it takes you to read this sentence. First, you see creeping concessions for especially large customers … then the discount tiers change by product category … next thing you know the new “simple” system has so many exceptions that it’s harder to understand than the old system.  

A much smarter approach (listen up – I learned the hard way), is to understand how you add value for certain kinds of customers and then price based on the value you add. Even that isn’t simple though because you have to discount in exchange for large purchase volumes and in the context of what competitors are charging. But starting with the premise that you will segment customers by need, add up how you add value to each segment, and then price accordingly to at least make sense of how you earn the markup you place on products.  

Optimizing Profitability is Difficult, Essential and Hard Work 

In your organization, who understands these issues so well they can sit with your executive team and facilitate an in-depth discussion about how to take advantage of all these opportunities, understanding the nuances and trade-offs?  

Do you have a profit optimization plan that considers best practices, sources of data and emerging technologies that can grow your bottom line over the next several years, or do you just make assumptions about how you’ll improve with some vague platitudes about what you’ll do to get there? 

If you can answer those questions authoritatively – congratulations; you are the unicorn of distributor profitability! For everyone else, be sure to send someone to our upcoming conference, The Profit and Productivity Summit for Distributors on Nov. 11-13 in Chicago.  

I’ll be moderating a panel of experts on the same topic as this article, “What I Wish I Knew About Driving Profits 20 Years Ago,” and we’ll deep dive on these issues and others. Plus, you’ll meet with the world’s leading technology providers of profit-driving technologies for distributors and network with other executives grappling with the same problems you’re trying to solve.  

Given the incredible opportunities you have to improve your profitability and the complexity of the challenge, how can you skip the industry’s only dedicated conference on distributor profitability?  

Join us for the upcoming Profit and Productivity Summit for Distributors Nov. 11-13 in Chicago.  

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