Chanan Greenberg is a seasoned executive with 25 years of experience in front line leadership roles. He helped build companies from pre-revenue to successful IPO, lead acquisitions, held 2 CEO entrepreneur positions in companies selling to Government IT-Outsourcing Contractors, Service Providers, Aerospace & Defense, Telecommunication, High-Tech, and Multimedia Distributors. He led the first evangelical sales into Fortune 500 companies overcoming resistance to change and fear of working with early-stage companies. Nurtured C-level personal relationships with customers, partners, and investors.
In this episode, Chanan discusses revenue management and what Model N does that differentiates it from other pricing companies.
Why you have to check out today’s podcast:
- Find out about Model N’s pricing software, how it works and how it differs from other pricing vendors
- Understanding the different channels High Tech industries go through and how this affects pricing and value setting
- How does price execution play a big part in the price optimization
“If you believe in the value of your product and your differentiation and the reason that you exist, don’t be subservient to the rest of the value chain.”
– Chanan Greenberg
Get Accelerate Your Subscription Business: Your Blueprint to Packaging & Pricing for Growth Course at https://www.championsofvalue.com
03:07 – How did he end up in Pricing
04:27 – What industries does High Tech cover
05:37 – The many problem scenarios High Tech help solve
11:49 – How big are the companies that Model N serves
14:51 – Understanding your end customer and why you need to legitimately ask to determine your pricing
17:34 – Difference between Model N’s pricing software and other Pricing companies
23:18 – The importance of having clean data
24:38 – One important pricing advice he has
“Stop thinking about pricing in silos. Pricing has a waterfall that continues well beyond that. It continues into how are you going to do discounting into the channel, whether it’s the ship and debit process or whether you’re paying out a rebate, whether you’re paying out price protection on the inventory that is out there. All these things at the end of the day, bring down that waterfall to its final net results and pricing doesn’t end with optimization. It doesn’t end with analytics and it doesn’t end with the based on the execution of a price and the close of a contract. It continues operating, and unless you can really bring these things into a single continuum, you are invariably going to leave money on the table without any doubt.” – Chanan Greenberg
“If you’re working through channels and you want to understand who is the end customer, what are they willing to pay to determine how much you’re willing to discount, that’s a legitimate ask.” – Chanan Greenberg
“Never assume that you can make up on bad business by scaling the volume. Because bad business is bad business, whether it’s big work or small.” – Chanan Greenberg
“If you have good price execution in place, whether it’s a Model N or a different solution, then bringing in a solution that can help you do the micro-segmentation, try and change the curves of your product lines to adapt to specific market dynamics that you may have in different end markets or different territories, I think definitely has a creative value.” – Chanan Greenberg
“You really need to stick to good price execution because what I’ve found in many companies is they think it’s like a magic formula. You implement it, you did it, and now it just supposed to continue spewing out great pricing for you when in fact you have to keep on feeding that beast every quarter.” – Chanan Greenberg
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Full Interview Transcript
(Note: This transcript was created using Temi, an AI transcription service. Please forgive any transcription or grammatical errors. We probably sounded better in real life.)
Chanan Greenberg: Stop thinking about pricing in silos. Pricing has a waterfall that continues well beyond that. It continues into how are you going to do discounting into the channel, whether it’s the ship and debit process or whether you’re paying out a rebate, whether you’re paying out price protection on the inventory that is out there. All these things at the end of the day, bring down that waterfall to its final net results and pricing doesn’t end with optimization. It doesn’t end with analytics and it doesn’t end with the based on the execution of a price and the close of a contract. It continues operating, and unless you can really bring these things into a single continuum, you are invariably going to leave money on the table without any doubt.
Mark Stiving: Welcome to Impact Pricing, the podcast where we discuss pricing, value, and the data-driven relationship between them. I’m Mark Stiving. Today, our guest is Chanan Greenberg. Here are three things you want to know about Chanan before we start. He is the Senior VP and General Manager of High Tech at Model N, which we’re gonna talk quite a bit about. He and I first met when I was a pricing director at Maxim and I was advocating for Model N as a solution there. He is an amateur astronomer. I didn’t know that about him. I find that fascinating and okay, I’ll give you the fourth one. He has the best voice of anyone I will ever have on this podcast. Welcome, Chanan.
Chanan Greenberg: Thank you, Mark. I will try to get my radiophonic voice working for you today.
Mark Stiving: You don’t even have to work at it. Your voice is so amazing. I want to ask a really quick question about astronomy. If I could. My wife and I bought a spotting scope for birds and then we took off. We bought a little mount that goes over the eyepiece so I can put my iPhone on there and take pictures and it’s horrible. I’m guessing that there are telescopes or spotting scopes that have digital lenses already built into it and I can just connect it to my computer. Is that true or not?
Chanan Greenberg: It is true. There are some telescopes that have built-in CCD chips, and CMO chips that can actually capture images for you just like a camera would. And they’re actually designed specifically for astronomy application. So, they have some nifty cooling functionality that reduces noise from the image. So, there are some scopes that have those built-in. Although most serious amateur astronomers will use a separate camera that is specifically designed for deep space imaging and is, you know, has special adapters to attach to the telescope. But they’re pretty cool toys.
Mark Stiving: Well, you can never have enough toys. That’s my philosophy.
Chanan Greenberg: Absolutely.
Mark Stiving: And let’s start this off with how did you get into pricing? Did you actually get into pricing or did you find yourself at Model N?
Chanan Greenberg: So, when I joined Model N, a short 15 years ago, Model N was already positioning itself as a revenue management company where pricing was a part of the continuum and essentially it covered everything from pricing to deal negotiation to commercial incentives in the forms of chargebacks and rebates as well as some regulatory processes including government pricing. So, Model N had all those constructs when I already joined back in 2005 and they were specifically geared towards the life sciences space and when I joined the goal was to expand Model N’s reach into other verticals. And as we started narrowing our focus down on High Tech and High Tech manufacturing, that drew our attention more and more to pricing as a key lever to help these companies drive more value. So, while we do rebates and discounting the performance rebates, discount rebates, inventory management and other things for our High Tech customers, really that vision of an end to end pricing continuum that factors in all the components was the key driver and remains the key driver for our business in High Tech.
Mark Stiving: Yeah. Just so I can get my arms around this. When you say the words High Tech, what industries are we talking about? Can you give us a few examples?
Chanan Greenberg: Sure. The sub-industries that we cover in High Tech include the following. You have semiconductor and component manufacturers as one segment. Another segment would be networking and wireless. Another one would be bay storage solutions for the next one after that would be consumer electronics and one after that would be software. We actually exclude medical devices out of our definition of High Tech, although many, many analysts would include medical devices as part of High Tech. We actually view that as part of our life sciences business because of some unique attributes of many companies there that are more aligned with the rest of the life sciences business.
Mark Stiving: You and I met out of the semiconductor industry and semiconductors, I find, just amazingly complicated and unique in that they have the ship and debit and registrations and all these weird things that go on in selling through a channel. So, having a product like Model N to help manage all that just makes tons of sense. Do those other industries have similar problems or quirks about them that make it really useful for a company like Model N to jump into that space?
Chanan Greenberg: Yeah, I think that if you were to take it in the simplest form, the commonality across all the segments that we operate in is the combination of a very high volume of transactions, a large product catalog. In other words, you have more than one or two products, but hundreds or thousands of skews in your catalog and a mixture of thousands and sometimes tens of thousands or more of customers. When you overlay that with a fulfillment that is going through a channel, you’ve created the perfect condition to get things wrong. And what I mean by that is whether it’s negotiating pricing with a channel, while an end customer has really agreed to pay a certain price, but you find yourself renegotiating a new price with a channel that’s doing the fulfillment, not really creating the demand. Unless you can create a linkage between these processes, you’re going to be leaving money on the table.
The fact that every end customer can effectively become their own price points for a specific skew. Managing that process effectively again has a great upside opportunity to actually increase pricing and capture more pocket a price from that end customer. But it also creates the opportunity of actually bleeding margin into the channel. So, these commonalities exist across virtually every segment that I just mentioned. It doesn’t really matter if it’s a semiconductor or if it’s a data storage. If you think of a disc as a product, you can take the same disc and you know, sell it as an embedded solution in a laptop. You can sell it as a stand-alone external storage solution through a B2B value chain. Or you could be selling it through a consumer value chain, like, I don’t know, best buy or fries.
But you can also have other end customers like you know, card providers. You know, Google and AWS are big consumers of storage solutions. So, multifaceted segmentation of the different end markets have the exact same products will go to, but it will have different pricing points for each one of these markets. And then you overlay that with geo differences and you overlay that with any customers negotiating their own specific price for channels. And you have the exact same problems that that semiconductor companies have, which is just getting control over that price, the baseline price execution correctly. And then factoring in the fact that once you’ve negotiated whatever discounts you have, you might still be paying out a discount rebate, which is the equivalent of the ship and debit and semiconductor for the rest of high tech to the channel. You might be paying performance rebates, you might be paying price protection on the inventory if you’re changing the values of inventory over time. All these same problems apply to virtually every aspect of high tech with perhaps one exception in the software space where they don’t really have inventory or not, you know, not traditional inventory that to deal with. So, elements like price protection with full hours, but all the other elements of controlling the discounts, inconsistent execution of the pricing, the payments of rebates and discount rebates, they all still apply.
Mark Stiving: Okay. I got to say that as you went through that list of different scenarios, I was getting antsy because every one of them felt so painful. Now, in case our listeners didn’t really understand all that, I want to give you a really clear example. Back when I was working in the semiconductor space, what would happen is we would have negotiated a contract with a really big customer for the sake of argument, let’s call it HP, so we would negotiate a contract with HP and so when HP wanted to buy from us, we sold them apart for a dollar and then we would get a request from one of our distributors that said, Hey, we’ve got this customer out there that wants to buy 100,000 pieces. They want to pay 80 cents. Would you do that deal? We have to somehow find a way to figure out that that deal was actually HP. We already had a contract with HP for a dollar and if we had bid 80 cents, we would have just lost or given away 20 cents on 100,000 units.
Chanan Greenberg: Exactly. And some of the problems are even simpler than that. If you just think of the sheer volume that these companies need to deal with where these companies are handling tens of thousands of quotes on a monthly basis and as much as 50 to 60% of these quotes require some special price review. There’s a customer saying that they want a better price as simple as that. Or it could be that a competitor is offering a better price and there’s that sort of pressure for whatever reason, about 50 to 60% of all transactions in high tech or a special price request. So, in essence, what we’re saying is we’re taking your carefully planned price book and the wonderful segmentation and price curves that you’ve created and thrown them out the window. And we’re going to deal with this deal as a one-off.
And that’s what you’re doing 50 or 60% of the time. And with that kind of volume, you just cannot continuously throw more people at it at some points with just so many people who could be, you know, product line managers or a deal desk or a sales operations function that can just review every single one of these deals. And because they can’t do it, they don’t do it. And the result is they focus on the higher value deals because obviously, they have the biggest impact. And then the rest of the deals, probably 30 to 40% of those deals simply automatically default to the lowest approved price because they know that they can approve that price, they don’t have time to review the deal in any more detail. So they just approve it. That is not the way to optimize pricing and optimize the revenue you’re going to make on the deal. And that’s where it becomes really important to support these processes with pricing automation. And that’s one of the key things and model and focuses on.
Mark Stiving: Yeah, that just sounds incredible. But one of the questions that I wanted to talk to you about is does Model N fits well with smaller companies? And it sounds like the answer to that is no. It sounds like you have to have a really big transaction volume, customer base, SKU count.
Chanan Greenberg: I think it’s fair. I think it’ll be helpful to perhaps put numbers against what small and what is big. I think that if you’re a $20 million company or a $50 million company, the one thing that’s keeping you up at night is how do I become $100 million company or $150 million company? And it’s less about am I leaving 1% of margin on the table or more? I think that when you start hitting the 200, 250 million range in revenue, that’s when you start seeing enough volume and enough complexity to really start feeling the pains. And more importantly, you can actually quantify them. So, if you’re a company that’s let’s say still relatively small, but you’re growing at 10% 15% and someone can show you that you might be leaving five extra points on the table with different processes that can be optimized, that now starts becoming meaningful to your business. So, normally we would say that I’m the lower end of the range that we work with is around 200 it’s 150 million and yes, as they get bigger, the value increases and obviously the pains and complexity that they’re dealing with are bigger. About 75% of modeling customers are greater than a billion. So, anywhere between one to 50 billion is sort of the range that we typically serve. But about 25 maybe a little more than 25% of our customers are now are between the 250 million to 1 billion range.
Mark Stiving: Yeah. It’s interesting because back when I advocated for Model N, I was at a, let’s call it a one and a half-billion-dollar company and I could pick out or found nine different places where we’re leaking money just through bad quoting processes, bad pricing. And we quantified that to over a hundred million dollars a year.
Chanan Greenberg: That’s, it’s not shocking at all.
Mark Stiving: Yeah. And so that, I mean, if you think about it, 100 million, what is it? That’s 10% of $1 billion. That’s a big number.
Chanan Greenberg: It is a big number. And I think, again, Model N we like to set up our sponsors too and overachieve so they can be the heroes of the day once we’re successful at a deployment. So, we never claim that you can really capture everything. You know, I mean, you’re right that it could be as much as 10% being left on the table, but there are so many, you know, variables that impact how much of it you can really optimize. And so typically we tell people, you know, if you go in with anywhere between a three to 5% improvement rates, that is safe grounds. That is an area where you can pretty much bet your money on that you will be able to deliver that value to the company. And we were very pleased that we have customers that obviously exceeded that.
Mark Stiving: Do you think there are any lessons here for small businesses? So we’re not going to talk about Model N for just a second. And do you think that there are things that small companies could do, that said, Hey, we should focus more on this quote process that we put in place? I
Chanan Greenberg: I think that there are two things I’d say. Number one is if you believe in the value of your product and your differentiation and the reason that you exist, don’t be subservient to the rest of the value chain. There are companies who fear the value chain they operate in and they’re afraid to not even, I’m not necessarily saying demand higher pricing or avoid discounting. I’m saying asking for information. So, if you’re working through channels and you want to understand who is the end customer, what are they willing to pay to determine how much you’re willing to discount, that’s a legitimate ask. Especially if you’re providing these channels with various forms of protection and incentives, whether it’s price protection, whether it’s a deal registration programs, whether it’s a, you know, the ship and debit program or rebates, you’re giving quite a bit into the channel.
It’s legitimate to ask. And yes, and yet I do see companies, especially on the smaller end, still fearing to demand the data that they really should have to run their business effectively. If you do not understand what your end customer is doing and it becomes an opaque situation through a variety of different types of channels, you’re not really in control of your own destiny. And so I think that is one thing that I would advise small companies. And the other one never assumes that you can make up on bad business by scaling the volume. Because bad business is bad business, whether it’s big work or small. So, having discipline on understanding what are our goals from a margin, where do we want to take the company? And it’s still in that even along before you bring in tools long before you know, even if your only tool is an Excel spreadsheet, you can still instill that culture and that process in a company. So, then when you are ready to scale and bring in tools, those tools should be enforcement of an existing policy, not completely new learning of, now margins and revenue optimization are important. They’re always important.
Mark Stiving: Yeah. I think both of those are phenomenal recommendations for small businesses or any business actually. But I want to just pound on that first one. You said if a company doesn’t own the end-user data, if you don’t have a relationship with your end-users, then it’s impossible to truly know what they value to get them the next version of the product to capture the value that we’re delivering. So, everybody should have that, have access to that date and inform it, have a relationship with those end customers. But how is Model N different from other pricing companies, pricing software out there?
Chanan Greenberg: I think that the key difference between Model N and all the other pricing vendors out there is really twofold. Or maybe I’ll put it into three buckets. The first one is where are we coming from? All of the pricing tools out there. If you go to PPS and you see the pricing, the professional pricing society events and you see all the pricing vendors there, they all came from the exact same background, which is pricing analytics and pricing science. And the underlying assumption with many of them was that the underscoring capabilities of price execution are already there. They’re taken care of by CPQ or by ERP or something else and they just work fine. And all you really need to do is to tweak the front end of the process by dialing in on micro-segmentation and finding out where you can optimize a price curve in one product line or in one end market or in a different region.
And that’s just going to be a ton of value upfront and there is credence to that point of view. Because if you look at specific industries that have actually worked really, really well. You can look at the process of manufacturing space and the chemical space. You can look at travel and accommodation even in distribution, a beverage, and alcohol. They’ve been a few industries where that assumption has been proven to be absolutely true and great value has been attained. The Model N comes from a very different angle, which is actually price execution itself is quite broken. And so if you’re not going to fix that no matter how well you fine-tune the upfront price book, your ability to execute that is going to be significantly impacted. And what we have found, because we were a vertical company and that’s the other big difference is we don’t try and be everything for everyone.
If a CPG company you know, reaches out to us at and oil and gas company reaches out and says, we’d like your solution. We are unlikely to engage unless it’s a miraculous fit-out of the box and then maybe, but generally we’re going to stay focused on the industries that we really understand. And why is that important? Because for example, in high tech it is a different market dynamic than oil and gas or process manufacturing or all the other industries. It is very hit-driven. It’s very dependent on macroeconomics and the abilities to go and build predictive modeling on what your pricing should be. Three-quarters hours are not there. You know you can build an algorithm to tell you what should a plane ticket price be between November 15 and December 15 December 25 in this country because you have seasonality, you have things that play in there.
Whereas High Tech is really operating on a different dynamic. Also, the speed at which new products are being introduced is significantly higher. So, when you’re introducing a new product, past performance is not really relevant. So you can’t really draw on that to conclude what you should be doing and therefore we found that the focus on price execution, deal optimization and controlling the end to end process of upfront discounting and posting and incentives to be the most consistent way to deliver value in any market, in any product, family for any high tech company and I think those are the key differences between Model N and another pricing vendors. It’s really our focus on the industry and the angle that we’re coming at it’s compared to the others. If you take a look at public case studies, just do a tally of a public case studies in High Tech for pricing solutions, you will find that Model N has more public case studies than all the other pricing vendors combined because of the challenges I said earlier on.
Mark Stiving: Yeah, it almost sounds to me like it’s an and not an or. I should pick up a pricing optimization software package to price my older products, not the new releases and yet I still need to manage the channel. I still need to manage the revenue execution piece.
Chanan Greenberg: In principle you’re right, in reality, I have rarely seen that work and I’ll explain why at least from my opinion. First of all when I look and I’ve seen at least, 15 different projects of price optimization and pricing analytics solutions in the tech industry. You know at a minimum probably seeing more of them that did not use Model N that they bought into the story of that upfront optimization and they try to implement it and most of them were not successful. What happens then is nobody wants egg on their face. They try and figure out, well how else can I use it? And then they end up using it for price execution. So, a company may have all the pricing analytics solutions initially, but because that didn’t work after a year or a year and a half, they convert it into, okay well we’re going to try and use this for our quotes. And then they get stuck with a solution that actually wasn’t really well designed to do quoting, for example, as their tool of choice. And that means it comes at the expense of a system like Model N that would be more relevant to that use case. And so I can tell you that probably 60 or 70% of the deals the Model N has done in the last five years has been simply replacing pricing analytics tools that have been converted into price execution with Model N’s price execution.
Mark Stiving: Yeah. I think if I were going to try to do both at the same time or I’m sorry if I’m gonna try to do both, I would do price execution first. I remember when we installed Model N probably the single biggest problem we had was getting the data cleaned up, right? Getting a customer master and making sure all the part numbers were incorrectly and not multiple times. And without clean data, you really can’t do price optimization.
Chanan Greenberg: I agree. And I think that if you have good price execution in place, whether it’s a Model N or a different solution, then bringing in a solution that can help you do the micro-segmentation, you know, try and change the curves of your product lines to adapt to specific market dynamics that you may have in different end markets or different territories, I think definitely has a creative value. So I don’t want to sound like I’m knocking it completely, but you need to sequence the right way. And then secondly, you really need to stick to it because what I’ve found in many companies is they think it’s like a magic formula. You implement it, you did it, and now it just supposed to continue spewing out great pricing for you when in fact you have to keep on feeding that beast every quarter.
And not every company has the discipline and the personnel to do that. And so I see companies start off on that trail. And then after a while they just back off and say, Oh, it’s too hard to keep these things maintained. And they just rely on good price execution. So, I do believe the value is there, but not every company has the discipline and the personnel at from a skillset standpoint to do that work well.
Mark Stiving: Nice! Hey, Chanan I have so enjoyed this conversation and before we wrap up, I always ask the following question though. What’s one piece of pricing advice you would give our listeners that you think could have a big impact on their business?
Chanan Greenberg: The one advice on pricing is to stop thinking about pricing in silos. A lot of people tend to think of pricing either as something that they’re doing upfront when they’re setting a price book or when they’re determining how they’re going to execute the pricing and in different pricing rules and tools that they’re going to use for quoting and contract negotiation. And they don’t really think about the fact that pricing has a waterfall that continues well beyond that. It continues into how are you going to do discounting into the channel, whether it’s the shipping debit process or spar debit and the rest of High Tech, whether you’re paying out a rebate, whether you’re paying out price protection on inventory that outed, that is out there. All these things at the end of the day bring down that waterfall to its final net result and pricing doesn’t end with optimization. It doesn’t end with analytics and it doesn’t end with the baseline execution of a price and the close of a contract. It continues operating. And unless you can really bring these things into a single continuum, you are invariably going to leave money on the table without any doubt. That is the big advice. Stop thinking about pricing in silos.
So if your, if I give a practical example, if you’re negotiating a discount with let’s say a channel and that channel is also entitled to a performance rebate on the back end, right? If they sell a million units or something, they’re going to get three points. Okay. But now they’re in the deal asking for a 10 point discounts. If you keep on operating in silos, you’re going to give them the 10% discount and then you can also pay them 3% on the performance rebate at the end of the day. But if you stop thinking in silos and you bring these things together, now you’re going to say to the channel, well Mr. Channel, I’m giving you the 10 points you asked for three points, you’re getting as a rebate at the end of the day. I’ll give you a seven-point discount right now. I’ve given you what you asked for. But for the company, I’ve just saved three points, unnecessary discounting. So if you stop thinking about pricing in silos and think about it as an end to end process, there is significant value to be had.
Mark Stiving: Nice. That is absolutely fantastic. All right, episode 51 all done. My favorite part, let’s see, I think this is the clearest I’ve ever heard on revenue management and the difference between what Model N does and what the pricing optimization companies do. So, an excellent job for that. I’m on. Thank you.
Chanan Greenberg: My pleasure.
Mark Stiving: And thanks for your time today. If anyone wants to contact you, how can they do that?
Chanan Greenberg: The simplest way is email. It’s a C as in Charlie Greenberg as G R E E N as in Nancy, B E R G @modeln.com. I’m happy to respond to any inquiries or on LinkedIn, you can find me there.
Mark Stiving: Excellent. Thanks, Chanan. For our listeners, what was your favorite part of today’s podcast? Let us know in the comments or wherever you downloaded and listened, and while you’re at it, would you please leave us a five-star review? They are very valuable to us. Don’t forget we started a new community on champions of value, a place where you can see all of the things that we publish. You can get there easily at community.championsofvalue.com. If you have any questions or comments about this podcast or about pricing in general, feel free to email me, email@example.com.
Now, go make an impact!
**Note: Mark Stiving has an active LinkedIn community, where he participates in conversations and answers questions. Each week, he creates a blog post for the top question. If you have a question, head over to LinkedIn to communicate directly with Mark.Tags: Accelerate Your Subscription Business, ask a pricing expert, pricing strategy