Episode 41
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How Ardent Mills Simplifies Price Optimization

Ardent Mills is North America’s largest flour milling company, feeding approximately 100 million people every day by way of its 40 processing plants and 2,400 essential workers.

Ryan Almos, strategic pricing leader at Ardent Mills, joined us on this episode to discuss the dynamics of the food production industry, his team’s role in enabling sales, and how the company has simplified its pricing approach.

Ryan Almos

Ryan Almos

To me Zilliant is a people company. It's not a pricing algorithm company. What I mean by that is we really unlocked the pricing power when Zilliant got to know our business and know exactly what our sales team members are facing.  When Zilliant understands that, coupled with the analytics that they can provide, that's when this became really powerful. And so to me, Zilliant is a people company first and a pricing algorithm company second. And when they do that, the sky is the limit for where this thing could go.  
- Ryan Almos, Ardent Mills

Episode Transcript

Ryan Almos: How do you create mutually beneficial value for both our customers and Ardent Mills? We've had some tough conversations as it relates to pricing as everyone does, but it was at the end of the conversations, even though it wasn't exactly what both parties wanted, both parties had to give - we actually strengthened our relationships.

That's really critical. How do you have those tough conversations, but make the overall arrangement or agreement between the two parties more binding and more helpful to both parties? When you can do that that's extremely powerful. And the tools that Zilliant has has absolutely helped us get stronger with our customer base.

Lindsay Duran: Hello everyone. And welcome to B2B Reimagined. My name is Lindsay Duran, and I'll be your host for this episode. I'm joined today by Ryan Almos, strategic pricing leader at Ardent Mills. Ryan, welcome to the podcast.

Ryan Almos: Hi, thank you Lindsay. I'm very excited to be here. Thanks for your time today.

Lindsay Duran: Thank you. Before we get started, why don't you give our listeners a little bit of background on Ardent Mills as well as your role?

Ryan Almos: Yeah, Ardent Mills is North America's largest flour milling company. So Ardent Mills has about 40 [00:02:00] assets, again, scattered across North America with the majority of them being in the U.S., and then three in Canada and one in Puerto Rico. We have a specialty bakery, a mixed facility, and a quinoa processing plant that make up our asset base. We recently acquired a few chickpea facilities. So Ardent Mills, currently we feed approximately a hundred million people every day in North America. And we have 2,400 essential workers. And my job at Ardent Mills, I'm the pricing leader. I work with our sales team to make sure that we're achieving the price points that are good for our customers and good for Ardent Mills.

That's really what my day to day entails.

Lindsay Duran: Well, we're thrilled to have you on today. And as a side note, I've had the pleasure of visiting your office in Denver and seeing your, I'll call it your flour lab. I know that's not the technical term for it, but where you test out all of the samples of flour that you're milling.

And I found that to be such a fascinating experience.

Ryan Almos: Thank you. Yeah, we call that the Ardent Mills Innovation Center. We love giving tours. We love [00:03:00] to show it off. You're welcome any time.

Lindsay Duran: I figured you had a much more official name for that than what I could come up with here, but it's a very neat facility.

So thank you for that. So we're here to have you talk about your experience working with Zilliant to overcome various pricing challenges in your business. How long has Ardent Mills been a Zilliant customer now?

Ryan Almos: We've been a Zilliant customer for about five and a half years now.

Lindsay Duran: Excellent. Well, thank you for your business here at Zilliant.

We certainly value the relationship. Let's talk a little bit about what life was like prior to partnering with Zilliant. What were some of the primary pricing challenges that Ardent Mills faced?

Ryan Almos: Ardent Mills has lot of transactions per day. So between 200 and 300 flour transactions per day, and some of the issues we were facing was there wasn't kind of one single source of truth.

A lot of what we were pricing on and selling based on was the industry knowledge that, that our people had. But there really wasn't readily [00:04:00] available margin guidance that was available to our sales reps that are in the field, living and breathing these markets every day. And that's really what Zilliant has helped us deal with.

They've really helped us, you all really have helped us, wrangling all this data and get it into a consumable form that our sales reps can use in the field on a daily basis.

Lindsay Duran: Excellent. Taking a little bit of a step back food production is obviously a critical industry and like every sector, it’s seen some major changes and challenges in the last few years.

What are some of the biggest trends and challenges that you're seeing broadly in the industry?

Ryan Almos: Yeah. I think if we look at the last two years, obviously the COVID impact, it's hitting our mills and the flour milling industry, just like every other industry. And what's really changed more than the last couple of years than in the past has been just the change in the consumer.

So when COVID hit, our retail flour sales skyrocketed and our food service sales fell off. The baking at home had been a trend for the last say couple of decades where there's been less baking at home every year. And so then all of [00:05:00] a sudden that flipped on a dime and and there was a lot more flour demand at their retail level.

And we couldn't meet the demands. That's why you saw the shelves being emptied and everything. It was very short-lived. It didn't seem like it at the time, but it ended up being a matter of weeks. And now I'd say the consumer continues to change and especially going in the alternative grain space we're really seeing consumption per capita of flour continues to go down.

It is flat-lining a little bit. And with the population growth total flour demand has felt pretty stagnant, but the alternative grain space is where we've really seen the growth. And again, I think we don't know exactly what grains they're going to be, but I think it's really important that as the consumer has the money to afford these alternative grains we really see that as an area of growth and where we're going to be going the next couple of years.

Lindsay Duran: Can you talk a little bit about what you consider to be pricing best practices in such a commodity driven industry. Although as what you just described as tastes are changing and more alternative flours at the [00:06:00] market, perhaps it's becoming less commodity driven overall, but what are some of the pricing best practices that you tend to observe?

Ryan Almos: Yeah. In our core flour business, our pricing is extremely visible. What I mean by that is the wheat futures market on any given day represent about 80% of the total flour cost. It's going to ebb and flow depending on the markets, but those wheat futures are a hundred percent visible and anybody can log in to a public website and look at those. So. I think that's the tricky part is just the visibility in a commoditized business like we're in, the other part is the education piece of how different pricing is depending on geographic location, that type of flour or grain being transacted and the transportation markets? Does the customer receive multiple modes of transportation or one?

Those three factors really changed the overall pricing mechanisms that are used in our industry.

Lindsay Duran: Indeed. I think it's often a misconception that just because you're in a commodity driven industry that you [00:07:00] can't necessarily benefit from, more data-driven approaches or optimization driven approaches to setting pricing.

And I think you just named a number of factors that come into play in terms of the ultimate price that a customer will pay.

Ryan Almos: Yeah, absolutely.

Lindsay Duran: So, Ryan, what were some of the key factors that you had in mind in selecting Zilliant to be your pricing partner?

Ryan Almos: Yeah, I would say that the biggest thing was Zilliant really took the time and had some previous experience in flour milling.

Really understood our business really well. And that was the biggest differentiator for Zilliant. They invested their time and their resources in us to understand exactly the inner workings of our business and then design tailored solutions to achieve the pricing goals that we had. We didn't see that from everyone.

Lindsay Duran: Well, that's certainly great to hear. Let's talk a little bit about the implementation process for the project itself. What was the overarching goal or success [00:08:00] criteria that, that you had in place?

Ryan Almos: Yeah, I think those kind of three main objectives. The first was just being more consistent in pricing.

We had a wide range of pricing of a similar product to a similar end customer that kind of goes back to that data wrangling that we were talking about earlier, where it's just, how do we get all of that data consolidated into a form that can be consumed both by, internally and externally, internally by our sales teams and the various teams that are impacted, but then externally by our customers.

And then once we get that data wrangled and the team understands exactly what they need to be selling, why is it that, right? What are their other team members in the like products, the like customers selling? And why is that price-point achievable, right? That was really kind of our goal. And then obviously the third goal that, that every business has is how do you create mutually beneficial value for both our customers and Ardent Mills.

We've had some tough conversations as it relates to pricing as everyone does. At the end of the conversations, even though it wasn't exactly what both parties wanted, right. Both parties had to give, we actually strengthened our relationship. [00:09:00] And I think that's really critical, is how do you have those tough conversations, but make the overall arrangement or agreement between the two parties, more binding and more, more helpful to both parties? When you can do that, that's extremely powerful. And the tools that Zilliant has has absolutely helped us get stronger with our customer base.

Lindsay Duran: I think that's often a very overlooked or underappreciated benefit of taking a more data-driven or pricing science driven approach to pricing in that essentially making sure that your prices are fair and consistent across the customer base, especially when you are working in a potentially highly negotiated environment.

It can actually be a big benefit in terms of overall customer satisfaction.

Ryan Almos: And I think it, what it does is it really builds the confidence, right? That, you're going to the marketplace with a good price, with a good product, with the services that are warranted from that customer base.

And I think it's that confidence piece is huge. It gives your customer, the belief in your [00:10:00] company as well. It's completely understated. And confidence is a huge thing. And it's been, definitely been amplified here at Ardent Mills because of the work Zilliant’s done.

Lindsay Duran: That's great to hear. How long did it take to roll out the Zilliant guidance?

Ryan Almos: We had a minimally viable product, I would say within six to nine months. And I would say the constant iterations are still going. So we're five and a half years in and we're constantly iterating our algorithms both on the Ardent side and on the Zilliant side. To really answer your question, it took us six to nine months just to get to something to where our sales reps could use.

Lindsay Duran: Excellent. And I know that price means a lot of different things in a lot of different businesses. Can you talk a little bit about what types of prices that we are delivering price guidance for at Ardent?

Ryan Almos: We have kind of like our product list that comes through Zilliant. So it's going to give a start, target and floor price mechanism.

And then we add what we call customer-specific pricing, where the algorithm is going to look more around the last price paid by the customer. Then it's going to take other pieces [00:11:00] of information such as what is that region sold for? What is that like kind of customer sold for and created a pricing mechanism for the three of those.

And then we also have time values built in, right. Is that a spot account? Is it long-term, those sorts of things, just like you would pay data value on an option? No different in flour pricing, how do we put a time value of money into the pricing mechanism that we use today?

Lindsay Duran: And I know that simplicity was a core tenant of the model and how you wanted to approach this. I think people often have the misconception that price optimization has to be extremely complex in terms of the factors that it takes into account or the model itself in order to work correctly and capture the business. When you think about simplicity, tell me more about what you mean by that and how that's been vital to achieving results.

Ryan Almos: Couple of the first models that we ran Ardent Mills really struggled with. We had all the data from the model and we just sent it directly to our sales [00:12:00] team. And we said, okay. Yep. Here's all the data you can slice and dice it any way you want. But I think we just needed to simplify it.

We needed to make it more of an output to our sales team, as opposed to a group of data that they sliced and diced. And I think that was huge as we really think about how did we simplify it? It was along the lines of. Just listening first. What did our sales team really need? Did they need all that data or did they really need the output? In a lot of ways that, most of them needed the output, right?

Because we want them to be spending time with our customer base, being in front of our customers and helping our customers win all day. Not looking through internal data. And I think that was really crucial for us is just simplifying the model so that the reps could use it, and then they can explain it to the customers too.

That was the other thing is we had a bunch of really pretty charts and really pretty graphs and everything else, but it was just overkill for what we really needed to get our products to the market in the most efficient manner that we could. And I think the last thing that, that simplicity did too, is it, it really reminded our [00:13:00] sales reps that, a lot of you have been selling these products for decades.

Don't forget to think. Is what the model is saying, does it make sense or not? If the answer is, “No, hey, this doesn't feel right,” don't just ignore that gut feeling. Rely on that. Don't forget that. When we've had reps that have really taken what they know about the industry and about the markets, and then apply the analytics that we get, that's really made them better and a more valuable asset for Ardent Mills, which ultimately creates value for them intrinsically as well. And so it's football season, right? To use a football analogy. If it's fourth and one at the 50-yard line and the analytics tell you, you have a 70% chance that you're going to get a first down by going for it, that's great. But it's what defense is the other team playing? What's the score of the game? Do you have a great play call? I mean, all of those things that you inherently know about your football team, you have to use alongside the analytics to make a good decision. Well, business is no different.

The analytics really drive decision-making. You can't forget how to truly operate your [00:14:00] business.

Lindsay Duran: Absolutely. You've touched on so many key things there. And one of the things that strikes me is we often talk about how artificial intelligence or machine learning or data science, whatever term you want to use there is really powerful, but really the power comes in when you then add in some additional human intelligence, a model can't know everything.

It can know a lot of things and help guide the decision. But there is something to be said for having additional context and that experience to make the best use of the output of a model. And I think your football analogy does a great job explaining that. I think you also touched on the importance of early collaboration and input from the sales team.

You can build a great model, but if the sales team doesn't understand the output or doesn't understand how to apply the guidance that they're being given in a selling situation, then it's really all for [00:15:00] naught. And so that adoption with the sales team and that early collaboration is certainly really key.

Ryan Almos: Yeah. I think absolutely. And listening first, right? When your team members believe that you really care about them, you see their day to day operations, and you're now designing tools to help them through their processes. That's when you get adoption, that's when the team believes in you. And that's when these analytics become extremely powerful,

Lindsay Duran: Indeed.

And I know that you personally spend a good amount of time with the customer success team over at Zilliant. Can you talk a little bit about how our customer success organization has helped along the way?

Ryan Almos: So far, we've been very fortunate to have great customer success managers. And why they're so big, I mean, I tell Zilliant this all the time to me Zilliant is a people company. It's not a pricing algorithm company. What I mean by that is we really unlocked the pricing power when Zilliant got to know our business and know exactly what our sales team members are facing and the different markets that are out there.

When Zilliant [00:16:00] understands that, and then we couple that with the analytics that they can provide, that's when this became really powerful. And so to me, Zilliant is a people company first and a pricing algorithm company second. And when they do that, the sky is the limit for where this thing could go.

Lindsay Duran: Along that same line, Ryan, when it came to COVID-19 and how Ardent Mills was impacted, what role has Zilliant played in helping navigate some of that market upheaval that the pandemic caused?

Ryan Almos: Yeah, I think the Zilliant algorithms, I mean, what they helped us do was as our customer base was shifting faster than we've ever seen, the model was ready for it. The model knew that as that happened and the different price points we're achieving for the different customer segments and so forth, the model could recognize all that in real time, it could adjust.

And give us the right price points that we should be targeting in a very fast manner, much quicker than we could have gathered all that data and just calculated by hand. That's really what Zilliant helped us do through the COVID process.

Lindsay Duran: [00:17:00] Indeed, that speed and agility is so important. And I think we've seen with a number of other customers over the course of the past year, in particular as inflation and inventory and supply chain challenges, and really just being able to respond quickly and understand the market dynamic quickly is so key to that. Companies risk losing a lot in terms of not only sales, but also in terms of margin overall.

And Ryan with the caveat that nothing it seems is very easy to predict these days. What does the future hold for your team? What's next on the pricing journey?

Ryan Almos: Well, I think you just hit on part of it, Lindsay, just like any business we're in a time of inflation here. And we certainly feel some – slash - most of it will not be transitory.

And so how do we have these inflation adjusted metrics if you will, to feed our algorithm. And so we're in a business where our biggest costs other than wheat is labor. And right now it's just hard to know what that labor is going to cost. And what is our [00:18:00] true cost of goods sold going to be?

And the same thing with the supply chains and the freight markets that are out there. So really like what's next on our pricing journey is just being ready for that entering in deals that maybe have some inflation clauses or building various inflation models in, into our pricing algorithms today. That's really where we see the next, at least 12 months.

But unfortunately, it's probably going to be longer.

Lindsay Duran: I think that answer is probably common across the vast majority of companies out there. So you're certainly not alone in this. Is there anything else that you'd like to share with our listeners, perhaps a closing thought on how to successfully execute a pricing strategy or running a successful pricing project?

Ryan Almos: Yeah, I got a couple of things. The first of them is, you really need one ownership as it relates to pricing, right? Obviously it's a team of people that implement it and kind of manage it and make sure that the teams are following the rules and that sort of thing. If there's not one owner of [00:19:00] pricing, it's very easy for things to fall through the cracks.

That's something that I think Ardent Mills did a little bit is we tried to throw some of the pricing on top of other people's desks. And until we really had a true owner held accountable for making sure that the pricing made sense and there was rationale behind every sale, we had some struggles, right?

And I think that's one thing that hopefully can help some other businesses out that have an owner. Have somebody who is responsible every day for the price points that are being achieved. When they're not, is truly held accountable and can make a change. And I think the second thing that we've really learned…

Don't be afraid to fail. And I know that's a lot easier said than done, but mistakes are going to happen. There's going to be times where you're going to take three steps forward and one step back. But when that step back happens, just make sure it's tuition. Make sure that you've paid tuition and you educated the sales rep.

You educated yourself, you educated Zilliant. And as long as it's tuition and you continue to optimize the models and make them better, you'll take that three steps ahead. And one step back to five steps ahead, and then seven steps ahead and 12 steps. [00:20:00] And when that happens, the real power of Zilliant and pricing algorithms is unleashed.

Lindsay Duran: I think that's fantastic advice and certainly great perspective from someone who's been in the pricing trenches, if you will. Ryan, I really want to thank you again for taking the time to speak with us today. I think our listeners will certainly find your experience to be extremely valid.

Ryan Almos: Well, no, thank you for the time, Lindsay and I really enjoyed it. I hope others find it of value as you say.

Lindsay Duran: Indeed. I also want to thank each of our podcast listeners for joining us for this episode. At Zilliant we're committed to your success. And should you need any assistance or would like to speak with us, please don't hesitate to reach out at any time. Please also take a moment to rate and review the show if you are enjoying the content as it helps us to continue to put out great free content. Until next time, have a great day. And we will see you on the next episode of B2B Reimagined.

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