In short
CPG distributor deductions and trade spend management, arguing that AI can’t replace proactive, human-led processes for reviewing, matching, disputing, and acting on deductions.
Guest backgrounds
Yuval Selleck, co-founder and CEO of ProgramMash, built deduction management with AI/ML for ~6 years; previously launched/managed his own brand and entered the space after seeing deduction pitfalls firsthand.
Key claims
Most brands treat deductions reactively (“janitorial work”) and sign contracts without understanding them; deductions are often predictable if planned for. Tools/AI only support—humans must own ~80% of decisions. AI can mis-match similar promotions and can’t handle messy, contract- and relationship-specific environments. Trusting “AI-only” vendors risks data/GL/accrual errors and widespread incorrect audits/disputes.
Notable examples
Late delivery issues that should be detected; UNFI disputes if deductions are disputed without review; AI hallucinations in legal-document tests; brands relying on salespeople to match deductions (ProgramMash says deduction experts should do it).
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOUnderstanding CPG Deductions
0:45 to 1:16
Discussion on the challenges of managing distributor deductions in CPG.
“So I've invited Yuval Selleck, who's the co-founder and CEO of ProgramMash, to talk about how AI is changing the way CBG brands are managing deductions and trade spend.”
Introducing AI in Deduction Management
1:16 to 1:50
Introduction of Yuval Selleck and the impact of AI on deduction processes.
“So if you're still new, go back and listen to episode 98, where Yuval and I break down the basics.”
Proactive vs. Reactive Management
1:50 to 3:55
Exploration of proactive management strategies for deductions.
“And so what I seen and the reason I got into the business, of course, because I had my own brand, I understood exactly how where the pitfalls are.”
Identifying Valid Deductions
3:55 to 5:00
Discussion on the importance of distinguishing valid deductions from invalid ones.
“And that's the foundation of deduction management where AI can come into play.”
The Role of Technology in Deduction Management
5:00 to 6:47
Examination of tools and technology in managing deductions and trade.
“And then I'd love to kind of go into from there, does AI make that easier?”
Human Oversight in AI Tools
6:47 to 11:10
Yuval emphasizes the necessity of human oversight in AI-driven tools.
“I mean, these are the problems that we're facing every single day.”
Future Implications of AI in CPG
11:10 to 14:00
Discussion on the potential future impacts of AI on the CPG industry.
“initially, but there was a lot of pain to get there.”
The Role of AI in Deduction Management
14:00 to 15:40
Explore how AI can impact deduction management and the need for human involvement.
“But then you need to take action to fix those to really diagnose what the issue is.”
Limitations of AI and Importance of Expertise
15:40 to 18:09
Discuss the limitations of AI in handling deductions and the necessity of human expertise.
“They need to be selling, shaking hands, kissing babies, you know, promoting, asking for more money.”
Best Practices for Managing Deductions
18:09 to 19:48
Learn about the best practices for handling deductions and the importance of role specialization.
“I'm just saying AI plus human in the loop is the way to go.”
Transcript
Automatic transcript. May contain errors.0:01Yuval Selik:Welcome to Startup to Scale, a podcast by FoodBevy. I'm your host, Jordan Buckner. Join me as I talk to aspiring entrepreneurs, seasoned industry experts, and everyone in between as we unlock the keys to growing from startup to scale.
0:18Yuval Selik:Distributor deductions are one of the places where CPG brands can quietly lose margin, cash flow, and visibility into what's actually happening in their business. We've talked about this extensively before, but the real challenge isn't actually just knowing what the deductions are. It's creating a plan for them, how to review them consistently, how to decide what to dispute, and how to build a process that doesn't fall apart as retail distribution grows. So I want to kind of dive into this topic, especially as AI is coming into this space and is changing how people build processes around deductions, trade spend, management.
0:53Yuval Selik:So I've invited Yuval Selleck, who's the co-founder and CEO of ProgramMash, to talk about how AI is changing the way CBG brands are managing deductions and trade spend. And I also want to discuss where experienced people are still needed to make judgment calls, manage relationships, and execute the right steps. This conversation is going to be a little bit more intermediate, advanced level on deductions and trade spend. So if you're still new, go back and listen to episode 98, where Yuval and I break down the basics. All right, Yuval, so I'm curious to learn how AI has influenced you and your approach to deduction management.
1:29Yuval Selik:And welcome back to the podcast as always. Well, thank you. Of course, I'm looking forward to it. I will say a few controversial statements here. So you should wait till the end or at least listen throughout carefully with intent to set a frame because we kind of have to look at deductions prior to AI and understanding why they happen and how to manage them effectively. And then we can get into AI. Right. And so what I seen and the reason I got into the business, of course, because I had my own brand, I understood exactly how where the pitfalls are. And there's such a thing in life where we make decisions reactively and proactively.
2:05And I think that it flows through all aspects of life, including business and including deductions. Right. So to start off, I think just setting the base about what proactive and reactive management is before getting into AI, because AI flows into, you know, takes over from that.
2:20Yuval Selik:Yeah, let's do it. So from my standpoint, many brands treat deductions like janitorial work. It's always a cleanup. They always have a mop. They're always exercising, you know, some sort of look back. And they're always panicking because what's happening is the money, you know, hits the account short. Three months later, somebody's digging through some emails. They're trying to figure out why. It's always reactive and they're always cleaning up after the fact. And by then, half the paper trail is gone. So proactive deduction management is the opposite. That's where brands should know what a valid deduction looks like for every retailer that they sell into.
2:56They've got the promo plans, the agreements, the contracts, the expected costs. They capture everything up front, right? So when a deduction lands, they're not investigating some sort of mystery. They're matching it against something that they've already planned for. The mindset shift is this, though. I think deductions aren't surprises for the most part. That's a little controversial, right? Because most people will say, I was always surprised. I was always surprised. Yes, some are. But we're playing the CPG game. So you got to accept that piece of it, right? We're not going to go into why. But you get the pointless in the previous episodes.
3:30But for the most part, they're the cost of doing business, right? And they're correct. And they're predictable if you do it right. And I see this happen all the time, Jordan. The brands that win aren't the ones who chase deductions faster. They're the ones who set themselves up so there's little to chase. And that's when you catch the invalid ones early. They, you know, the brands, they led the valid ones through clean. And that's really playing the offense instead of defense. And that's the foundation of deduction management where AI can come into play.
4:01Yuval Selik:Yeah, I mean, I think that what you were talking about in terms of having a plan and a process in place early so that you are building that into your business and planning for it appropriately is key. I think the biggest thing, right, a lot of people are worried about either one, not knowing how deduction chargebacks actually align with their trade spend plans that they agree on, especially for early brands. And then two is being able to tell the difference between a approved or agreed upon deduction of chargeback or an invalid one, because those can happen too. I think the third thing is problems that happen in the system that you should be aware of, right?
4:42Yuval Selik:Like if you're having late delivery times, it's still your fault, but it's not something that should be happening. But if you don't have a process to actually see that, to know it's an issue, it's hard to fix. And so I guess I'd love to, one, you can do a quick overview of just like how, like what are those kind of key processes that you need to stay on top of? And then the ways that you've kind of built the processes to manage those. And then I'd love to kind of go into from there, does AI make that easier? Does it make it harder? Does it complicate things? And where's kind of the role of people in there too?
5:11So what you're really talking about is how do we try to avoid some of the deductions in the first place? And that comes with planning. And I think brands get that backwards. They plan the promotion and the deductions are always an afterthought, right? They have a contract and they don't think about it. They sign stuff. And if you ask them, what did you just sign? They have no idea what they just signed. And that's, wouldn't you agree, like that's 95 % of the brands out there, right? Right.
5:35Yuval Selik:Completely. And now the other thing that I realized, right, is like there might be 10 different charges that can happen, but brands don't realize how those can happen at the same time on the same invoice versus one at a time. And then so it just confuses them. Yeah, I mean, that happens because distributors and retailers know very well that if they give you plain deductions when they happen, right when they happen, it's easy to look for and validate, right? But if they wait three, four months and then they send you six months worth of deductions in one place, good luck. That ain't going to happen.
6:07And so you need support. But, you know, again, I think from a brand's perspective, before they run anything, they should know what's going on, right? What the cost is on the back end. So practically, you know, when they're planning a promo or a launch or even a distribution program, they got to keep track of what's expected to spend. Now, it could be a spreadsheet if they want, or it could be a fancy system, but a tool is just a tool. And so that's one controversial thing that I will say is the tools don't fix things. They help. They support you. But if you can't get it done in Excel, you ain't going to get it done in a six-figure TPM solution.
6:38That's for sure. It's actually going to be worse because at least you know how to use Excel. You won't know how to use a TPM solution. And the wrong people are on it anyway. So you got salespeople managing trade, you have founders and CFOs managing deductions. I mean, these are the problems that we're facing every single day. And so everybody's chasing the next shiny new object and they're seeing all these new pop-ups of companies come out, come about. We'll talk about that promising AI is going to solve, you know, their woes and problems, but that's a huge misconception because I don't care if you have the God of AI, Fable 55, you know, I don't care what model you have and I don't care what platform you have.
7:12If you don't have the people running the show, it ain't going to work. It's just that we're not in an industry that is clean. This is not a clean industry. This industry has more holes than any Swiss cheese that you can find in Switzerland. Right. That's where Swiss cheese come from. So that's the deal. The holiest Swiss cheese, it's worse in CPG. So you're expecting AI or a tool to fix that? No, you can't. Impossible.
7:37Yuval Selik:So talk about that. Let's kind of talk into the tools, right? So like right now, you kind of mentioned a couple. There's Excel. There's some TPM software like Promomash and some others. And then there's on the AI side of things, right, there's people integrating some of the chat analysis tools into software. And then there's founders who are just going directly into the chat GPT or cloud and dropping in their reports from distributors to kind of help analyze those. And so I'd love your perspective because you're in this every day on what that role of like the software is and is AI helping? Are you integrating that into PromoMash in ways?
8:13Yuval Selik:Are you not? And what reasons and kind of your perspective on that part? So talk about ProMash and AI in a second, but there's a hill that I'm going to die on. And that hill is 80 % of the ownership must be done by a human. Okay. 20 % is the tool. And I put tool as AI, as software, as algorithms, as ML. I mean, all of it is kind of working in tandem. ProMatch started using AI six years ago when we were coding with AI. We weren't using scanners. We were using machine learning and coding. We started that trend. This was kind of pioneered it six years ago. And we've enhanced it ever since. But never does a deduction invoice pass through an AI without a human looking at it, ever, because I know what's going to happen.
8:55And we could talk about that later. But right now, the disservice that I see in this industry, and this happens every revolution, every technological revolution, you have a bunch of entrants coming in, taking advantage of the product, right? It happened in 2006 and 2007 with mortgages. It happened in 2000 with 1999 or whatever with the internet. It happened in the industrial revolution. It happened when horses were replaced by cars. I mean, it doesn't really matter the type of revolution or technology. companies will come and say that this technology will completely transform and transform the world.
9:32And for the most part, the funny thing is everybody's wrong. And I'll tell you why everybody's wrong. The biggest optimists are wrong because it's going to be way more than they ever imagined. And the biggest pessimists are wrong because it's never going to be that bad. So everybody's going to be wrong and everybody is wrong right now. And my problem, I mean, we could talk about this shit for like hours, but the problem is when you have trillions of dollars funding companies that just put AI in their name or in their, you know,.ai or whatever it is, you are setting yourself up for a very interesting next few years.
10:03Because even today with the best models, AI isn't capable of managing this type of environment. It's too complex. It's too messy. It's too Swiss cheesy. It's too, you have to understand the contextual aspect of so much in so many different departments and so many different relationships and a type of relationship and the type of brokers you're working with. Every broker is different. Every contract is different. And you're going to ask AI, a model and a chatbot to do it for you. Good luck. And I'll tell you where the disservice lies. Every day, a new company comes up on the radar and you know them because they're probably calling you up, right?
10:38We do deductions. It's AI forward. And we found the formula. And it's like five of them or six of them like in the last few months. And there's a couple of, you know, ones that were about a year, a year and a half. The technology and the companies, the brands, so I'm not going to name names, but all these new TPM and deduction management solutions that have launched in the last three years, let's say, they're still new. Everyone looks good on paper. I can put a website up, put a nice story together, market the shit out of it, and look like I know my stuff. But the problem, and we've learned this hard problem, Ash, the first few years is where we got burned because the backend had to catch up with our ambition.
11:17And so it looked good. Everybody thought we were great. initially, but there was a lot of pain to get there. It took us six years, seven years now to get to where we are right now. And we're still getting better and better and better. And I still would say that we're not a hundred percent. So you take these companies that are like five months old, all of a sudden managing 25 % of somebody's trade in AI with no people and no support and asking salespeople who are busy anyway to check on the platform. They don't know the platform. They don't even have the time to check on the platform. And the whole thing is going to blow up like it did in 2000.
11:52Now in 2000, it was a financial blow up. I think with AI, it's going to be a data blow up. I think what's going to happen is a year, two years down the line, because you work with Chad and Claude, and I love both. I mean, believe me, Claude is my best friend. I'm on it 24 seven, but it tells me a lot of things that I love because it tells me how good I am. It tells me how wonderful I am. It tells me how smart I am. It tells me how pretty I am. It tells me everything. And guess what? It's wrong partially. Not about me, but everything else. He's wrong about it because ultimately what's going to happen with brands, and this is where AI is going to really shine in the next few years, they're going to have an audit or they're going to look at their books and their accruals are going to be completely wrong.
12:34They're coding, they're GL fund mapping, they're promotional matching, they're, you know, the trade reasoning behind what's effective, what is in effect, they're planning. Planning fully without really having a great, you know, team behind you. went play. All of that is a recipe for disaster. I'm not saying it doesn't do good things. It does. But fully trusting these new companies that are coming out and saying, I have no people, I have AI, and you guys just manage it. It's scary because brands don't know how to use these platforms anyway, and they don't know how to check it anyway. So that's the problem.
13:01They don't have the right folks. They don't have the trade experts and the deduction experts to check the system. So they rely on the system. They take it at face value. They manage what they manage, just like you would trust, you know, chat GPT to give you, send you an email response or something like that. And it sounds great, but if it doesn't have all the contacts, what happens when it bombs, you know, UNFI with disputes? It disputes everything, whatever it is. Hey, dispute this. What do you think the relationship with UNFI is going to be like if you're just disputing stuff without looking at it?
13:30Yuval Selik:Yeah, I think the other thing that's so interesting within there too is, right, like you learned this early on in ProMash is that you need those experts. You understand the relationships, how deductions work, what they actually mean, how it relates to the business. And it's not just the tool, as you mentioned, but it's the inputs to the tool, plus how you actually make decisions based on what it's telling you, right? Because as you mentioned, there are a lot of things that are valid deductions, valid chargebacks, but they might represent an underlying issue or challenge in the business. But then you need to take action to fix those to really diagnose what the issue is.
14:06Yuval Selik:And if you don't have someone internally or a really good partner who's surfacing those, then those can get missed and not acted upon, which I think is really detrimental to a brand and can be really challenging. You know, I'm kind of curious, like, I definitely agree with, like, the human approach. You know, where do you think AI can make the biggest immediate impact in deduction management? So now that I got it off, you know, my chest on how I feel about AI, don't get me wrong. I do love AI and I'm doing vibe coding and I'm creating prototypes and it's changing my business as well. But it's just it's heartbreaking.
14:40You know, at 10 o 'clock at night, I'm arguing with AI that it's back and forth. It's really, really annoying. But I think the biggest immediate win is matching deductions to plan spent. That's one thing that it could do fairly well. It's not fully accurate by any means, but it gives you a good head start. It could look at a deduction and suggest, right? It could say, here's the promo that this probably ties back to. But again, it needs a human. You don't want to just accept it because I've seen what happens if there's multiple deduction, multiple trade plans that are very similar or very close and it just chooses one.
15:13And it's like you're dealing with your curls. And that's the problem. It's like if you don't get it right, your curls are off. And so that's where the time goes today, right? It's just trying to match it manually with the salespeople and salespeople should not be matching promotions in the first place. That's one rule that I disagree with. And I think every brand wants to do that. And I think it's the wrong approach. which is hugely wrong. That's why ProMash, we have our team match deductions on behalf of the brand. We don't want the brand's salespeople to match deductions. They need to be selling, shaking hands, kissing babies, you know, promoting, asking for more money.
15:46That's what they're supposed to do. Let professionals do the rest of this stuff. But I think that one of the reasons is, you know, from a matching perspective, it takes hours, you know, just in a single account. So AI can do the first pass in seconds, gets you most of the way there. But even here, and I've tested this internally, there are gaps. So even with our matching platform and what we're doing and we're building right now, there are a lot of the gaps. But in general, the thing is, and I'll go back to AI in general, the biggest impact is only available to brands that have perfect data and zero brands have perfect data.
16:19And I mean that, zero brands have perfect data. So you can think you have perfect data, you don't. I mean, maybe Mars and Hershey's has great data, I'll give you that. But for the brands you and I work with, Zero brands have perfect data. So then that's where the limitation is. So I think it can aggregate, it can find patterns, it could give you insights, it can give you suggestions, it can give you things that are helpful, right? Just like the difference between the first Word doc, you know, like Apple created Word or whatever it was, not Word, what was Pages? Pages, yeah. Versus doing it on a typewriter.
16:56Yeah, there's something to be said about that technological leap. And that's where we are right now. It's an enhancement. It enhances what you currently do and it helps you with it. But it doesn't replace it. That's what I'm trying to say.
17:09Yuval Selik:Yeah, I think that one thing that I've seen as well is that, right, like if you have nothing, AI can either be really helpful or send you in the wrong direction, right? Confidently send you in the wrong direction. And so managing anything, in this case, tradesman deductions, you have to have a baseline understanding of which deductions are valid, what the contract says, how they actually work, how they align with your promotions. And that's like there's some information out there, but it really takes that experience of knowing and working with the distributors with these tools, like how things work, right?
17:41Yuval Selik:Like codes are changing with distributors and there's new programs that they launch. And that affects how your numbers look. And AI is not great at catching on to those updates. And so it can make it seem like you can tell you one story when the reality is different. You know, that said, I would say, like, if you have nothing, you've never done this before, you maybe don't have the resources to hire someone like it could probably get you something that's a little better than nothing. If you have the right mindset that it still might be wrong. I'm not knocking AI at all. I'm just saying AI plus human in the loop is the way to go.
18:14AI is the game changer that this industry and every industry, you know, required. IT did a study recently where they put AI to the test of some, you know, legal documents and some other things. And they found high double digit hallucinations on all of the simple stuff that AI is supposed to do well. So I hear people putting in their freaking contracts, not just CPG. I'm just saying like legal contracts through chat GPT and saying, what do you think? and it gives them, oh, this is great, or here's some changes, and they go with it without an attorney, okay? Bad mistake. It's the same thing. It's not just CPG.
18:48It's every industry. It can help. It can speed things up. It could summarize. God knows how I ever managed my world without AI prior to Fathom, my note taker and every, it transformed my life, but it didn't replace me. And that's the big thing that everybody needs to understand. Until AI becomes that good that it can replace people, you better be the one in the loop you better understand what you're dealing with because you're going to find yourself in deep doo-doo if you don't just my take that's that's the hill that i'm dying on i don't know people will people will argue but you know if you don't have anybody arguing with you you're not making you know any noise so i love it yeah i love that perspective
19:28Yuval Selik:and yeah definitely having someone in the loop and not just a person but an expert who knows how they work and how to build those relationships word of advice don't let salespeople do trade. Don't let anyone but deduction people, experts do deductions. Everyone should do what they do best, their job title, right? That's the trick. You follow that principle, you'll be fine. Love that. Yuval, thanks so much for being on as always and talking through this. If you want to learn more about ProMash and how it can help your brand, check out the details in the show notes. Yuval, thanks again. Appreciate it.
19:59Thanks, Jordan.
From the publisher
Distributor deductions can quietly drain a CPG brand’s margins, especially when there is no clear process for planning, reviewing, and disputing them. In this episode, I sit down with Yuval Selik, co-founder and CEO of Promomash, to explore how AI is changing deduction and trade spend management.
We discuss where AI can save time, why clean data and proactive planning still matter, and why experienced people must remain involved in every decision. Yuval also shares why relying entirely on AI could lead to inaccurate accruals, incorrect promotional matching, unnecessary disputes, and damaged distributor relationships.
Startup to Scale is a podcast by Foodbevy, an online community to connect emerging food, beverage, and CPG founders to great resources and partners to grow their business. Visit us at Foodbevy.com to learn about becoming a member or an industry partner today.




