Sanjiv Raman 0:00:07.0: 

Thank you for joining us this afternoon. I just want to introduce myself, Sanjiv with Grant Thornton. 

 

Adam Nichols 0:00:15.5: 

Hopefully, you guys can hear me all right as well. I’m Adam Nichols, I’m VP of Planning at Fairlife. Our office is actually right down the street in the West Loop, so this is an easy commute in. Excited to be here. 

 

Sanjiv Raman 0:00:24.9:

Perfect. So again today, we want to talk about the journey that fairlife has gone through over the last 12, 14 months around improving and optimizing your supply chain planning processes. Before we get started there, Adam, maybe for those that don’t know of your products, can you share a little bit of the story about fairlife? 

 

Adam Nichols 0:00:42.2: 

Yes. So fairlife’s a Chicago-based nutrition dairy company, again headquartered in the West Loop. Really founded in 2012, but the work behind it had been going on for over 20 years with Mike McCloskey and Tim Doleman, our CEO. There’s a bunch of people trying to figure out a way to unlock the nutrition and power of dairy. The dairy industry had been stagnant for a while, especially in the ‘90s, things were declining. They thought there was a real opportunity there. So in 2012, they got an investment from Coke to launch the brand and fund the first line. In 2020, Coke actually fully bought out fairlife, so we’re a fully owned subsidiary now. We work very closely with them, although operate independently. We continue to grow for those that are unaware. When I started at fairlife in 2020, we were maybe $600 million in retail sales. We hit $1 billion in ‘21, and we’re on track to hit $3 billion this year. So that presents a lot of challenges. I’ve never seen anything like it, just the scale and flexibility. It gets pretty intense. We leverage our ultrafiltration technology and our patented processes to drive products that have higher protein content, less sugar. We did that in line with, as people got into low carbs, keto, the timing worked out really perfectly. We’ve done a lot of consolidation, just like everyone else since COVID. We’re down to three core brands now: fairlife, which is our big bottle of milk, and we have a small bottle of it as well, Core Power, which is really for maximizing recovery, and then Nutrition Plan, launched in our club stores. 

 

Adam Nichols 0:02:22.8: 

So right now our first site was in Coopersville, Michigan. we started up Goodyear, Arizona in ‘21. I think, if you haven’t seen, Coca-Cola announced last summer, we’ve got a third site opening in Webster, hopefully, by the end of next year. It’s the largest investment Coke’s ever made in North America so pretty excited about that. 

 

Sanjiv Raman 0:02:42.3: 

Awesome. What’s so impressive about fairlife’s story is an industry that hasn’t been disrupted for thousands of years, if you will, to see the degree of growth that you guys have has been pretty spectacular. Thanks for that introduction about fairlife. Tell us a little bit about your background and how you came to fairlife and your role at fairlife?

 

Adam Nichols 0:03:03.0: 

Sure, yes. I’m actually from the Chicago area. My background is actually in chemical engineering at UIC, if anyone knows what UIC is. Yes. So I worked in the chemical industry for about six years. I moved back to Chicago. I worked at Kearney and accidentally got put on a supply chain project, and I’ve been on supply chain ever since. my background is bouncing back and forth between consulting and industry. I worked at a company called Chanalytics for about four and a half years. Sanjiv and I met there actually doing network design and planning. I did planning software implementations, never with Anaplan, but I’d heard a lot about it in the mid-2010s. I joined fairlife in 2020 as director of planning. I’ve been in planning ever since. The role’s grown pretty substantially. we started with just production planning, material planning, and now we’ve also got distribution planning. Customer service demand planning is a new function and supply chain for fairlife. Analytics, the team that’s helping drive in Anaplan implementation, commercialization S&OP, so it’s been pretty exciting. I started with a team of three, and we’ve got a team of probably close to twenty now, and that’ll keep growing as we keep expanding.  

 

Sanjiv Raman 0:04:14.9: 

It’s awesome. so as you started to think about technologies, obviously with organizations that are scaling as fast as you are, eventually Excel hits its limits, and you’re going to go out to the market to look at platforms and technologies that can help improve your decision intelligence and so forth. How did you find Anaplan? 

 

Adam Nichols 0:04:34.2: 

Yes. Well, first I’ll say that one of the best things about fairlife is it’s one of the most intelligent groups of leaders I’ve ever seen. They’re all very Excel savvy. So that made our journey to try to get away from Excel a little bit harder because everyone could just go home and build a model. So I’d heard a lot about Anaplan when I was in consulting. Coca-Cola is a big user of it. So we’ve been around that. We leverage their demand planning forecast, at least until now. We’re still going to leverage it, even with demand planning coming on board. They use it for everything. They use it for transportation planning, allocation management. Where we got pulled in a lot over the last couple of years is our demand has just leapfrogged past our capacity. So I was along on that part of the journey. Additionally, like I said, I knew Sanjiv, Rachel Hare, a couple of people at Grant Thornton that were really standing up this competency at GT. We had some honest conversations about it. What I was excited about but nervous about with Anaplan is how flexible and customizable it is. I’d been through experiences where you implement software and then you customize the hell out of it, and then you’re stuck with it. So I just wanted to make sure it made sense. 

 

Adam Nichols 0:05:47.3:

I’d done a lot of optimization work in the past, too, and I was really hoping to leverage that. We were not ready to go from one site to two sites from a network standpoint. The plants just ran and made as many cases as they could, and then we got them, and we had to figure out where to put them and where to send them. So further conversations around that, just to make sure that the customization was actually what we need because we’re in a unique spot. There’s a lot of softwares around dairy manufacturers, but we do things in a way no one else does. There’s obviously a ton of ready-to-drink beverage space. So there’s a lot of softwares around there, but our upstream of that is different as well. So Anaplan was a good blend of systematizing and being able to drive value from it. So, we took the leap. 

 

Sanjiv Raman 0:06:33.7: 

Well, that’s really helpful. I think, as you alluded to, going from one to two plants is a scale shift. Going from two to now, three plants is going to be another fundamental skill shift in supply chain complexity as well, and just navigating through that’s going to be really interesting. 

 

Adam Nichols 0:06:49.5: 

Absolutely. 

 

Sanjiv Raman 0:06:50.3: 

So as you’ve started this journey, talk about some of the first use cases that you chose to deploy. We’ll jump to the slide. That would be helpful.

 

Adam Nichols 0:06:57.0: 

I did it. So we started small and in an unusual space, which is why I had so many conversations about it. Most of the use cases I found started around demand planning or FP&A-type stuff. We weren’t going to get to get funding to do that because Coke already did demand planning in Anaplan. We don’t need to do that. Our FP&A is built off of crazy spreadsheets. So one of the first things we found with Armand, who’s sitting up here - he works for me - when I got my role realigned last year, we picked up S&OP and S&OE, and we had this gap. We had a finite schedule, and then we had a long-range rough-cut capacity plan. They didn’t really communicate very well. We didn’t get good granularity on things that had longer raw material lead times. When we ran into out-of-stock issues, we didn’t have a good way to communicate recovery dates or even see things coming. So we started simple on the supply planning side just to generate what we call the mid-range plan, which is traditional supply planning everywhere else I’ve been. We wanted a weekly production forecast by SKU by line. We wanted to explode it to material requirements, so we could give it to our material planning teams and our procurement teams to be ready for it. Yes, so that’s where we started because we knew we had this gap. We were trying to set up this S&OE process to look out two to three months, and we wanted to leverage it to really give us better visibility to that. 

 

Sanjiv Raman 0:08:18.1:

Perfect. So you started with a mid-range plan…

 

Adam Nichols 0:08:21.1:

Right.

 

Sanjiv Raman 0:08:21.7:

…which was essentially at a weekly level by SKU by production line? You’ll be able to figure out how best to optimize production across those lines and understand where your capacity limits were, and how you essentially could meet your expected demand as well?

 

Adam Nichols 0:08:36.4:

Correct. 

 

Sanjiv Raman 0:08:36.5:

Yes, and you’ve used the optimizer to be able to get that as well?

 

Adam Nichols 0:08:41.4:

Yes, perfect.

 

Sanjiv Raman 0:08:43:

So talk about some of the stakeholders that you had to network with as you started to get this off the ground. Who did you need to get buy-in from, and how did you start to socialize it outside of your immediate group? 

 

Adam Nichols 0:08:53.9:

Yes, that’s a great question. We intentionally started smaller because of the stakeholder management. Historically, fairlife has not been one to invest in external services like consulting, not really a lot of IT investment either. We have a lot of smart people that can build really impressive - we had an ERP system that was built in Excel just with macros on steroids that ran the plant in Michigan for eight years. So we started small. We really focused just on my boss, who’s our chief supply chain officer, getting some buy-in from IT, and then also support from our co-counterparts. [?Sara Parke 0:09:30.2] especially has been a big proponent of this. So we started there and then we incorporated the results we had into how we displayed information, how we talked about challenges or allocation attainment, demand release levers, line start-ups. I think as people started to see the granularity, more and more people started paying attention and more and more people started asking questions like, ‘Oh, can we also do this with it? Could we do that with it?’ So again, we started narrow and then broadened out from there. We needed to prove that we could drive value out of this quickly with the hope that as we do that, more things would come down the line, and that’s how it’s worked out for us. 

 

Sanjiv Raman 0:10:12.5:

Perfect. This is great. So, tell us about, you said you started with weekly production planning, which was in the mid-range. Obviously, we see a bunch of stuff on the right there as well. So tell us a little bit of the story of how you got from deploying the weekly production planning to being able to think about the roadmap of what else you wanted to do with Anaplan and where you’re at today. 

 

Adam Nichols 0:10:35.7: 

Yes, the logical next step for us was our capacity file, which was this just behemoth of a spreadsheet. We struggled with it. We have scenarios all the time. We’d have months where we had 20 versions of the sheet, and you had to figure out which one was which. So our next step was how do we leverage what we’ve done for the 13-week plan and then start building it out into our long-range plan? So that was the next step, trying to get rid of Excel sheets. Our long-range sheet was one sheet that generated an output that we then copied and pasted into another spreadsheet that did stuff for transportation and did stuff for warehouse. So, as we started talking about it, we actually ended up doing long-range planning, but not just for the production plan. We did it for milk planning, which is pretty critical for us. Our SKU mix is really important. We can’t make a ton of Core Power Elite, for example, at one time because of how much protein is in it. So you got to find the right balance there. When you only look at the packaging science, sometimes you miss that. So we looked at milk planning, we looked at transportation forecasting, which had been a gap for us, warehousing forecasting, which we never really historically until a guy named Sean Delaney started a couple of years ago. We usually didn’t find more warehouse space until we were out of warehouse space. 

 

Adam Nichols 0:11:48.5:

So we were trying to get in front of it. Then more stuff with bomb explosions so that we had longer time horizons for forecasts we could give our vendors. That had always been a gap for us. So, that’s really where we started. I would say the other thing that’s been really, really cool for us, our IT ecosystem is messy. Probably a nice way to say it. We have multiple ERP systems. We interact with Coke’s SAP system. There’s master data we’re leveraging in our BI platforms that just existed in CSV files that were uploaded to Microsoft Azure. So, we’ve also just leveraged Anaplan as a place to store and standardize and control data. So things like allocations we didn’t have a home for. We put it there so we can drive reporting off of it. Customer master data, so we could link customer [?ship-tos 0:12:38.3] across all three ERP systems, we moved to there. So, that was really it: expanding the time horizons, getting more functionality on it, leveraging the master data capabilities. Then also we ended up in this weird spot where we had mid-range, which had some functionality. Long-range would have different functionality. So we’ve actually spent a lot of time this year harmonizing it, so we can look at milk capacity, transportation forecasting, warehouse capacity in both versions of it, which has been a huge help. 

 

Adam Nichols 0:13:06.5:

I’ll just call out just because they’re on there. The big thing we’re working on now is demand planning. Demand planning at fairlife’s historically been a commercial function. This year, I got approval for a headcount. So we’re doing a demand planning lite. We rely on Coke’s forecast for part of our business, we rely on our internal forecasts for a different part of our business, but it doesn’t have the granularity we need. So we’re standing up demand planning now as a way to bring all of these different forecasts together, a brand forecast to have, for lack of saying what everyone else always has, one single source of truth. We do think it’ll help to have that be the starting point of our supply planning models, one single source of truth. So when you get into the supply planning side, you don’t have to worry about it. That’s been a little bit more complex for us. 

 

Sanjiv Raman 0:13:52.7:

This is great. This is the story we hear from a lot of our Anaplan customers as well is that what else can we do with Anaplan? What else can we put there? Sometimes it’s a conversation about maybe not the right place for it, right?

 

Adam Nichols 0:14:04.8:

Yes. 

 

Sanjiv Raman 0:14:04.6:

This should really be a function of the ERP, where do we want to house master data and so on and so forth. Having moved away from Excel and these different technologies, what were some of the more interesting or harder problems that you were able to solve with Anaplan that you were not able to before?

 

Adam Nichols 0:14:23.0:

Yes, it’s a great question. So we have some of what we call big bottle SKUs and smaller bottle SKUs, multi-serve, single serve. We’ve had multiple lines of the network historically that could run both, but it’s a very detrimental changeover. That sounds dramatic, right, but the longer changeover it takes longer, it’s expensive. It takes longer to dial in the lines. So we’ve done a lot to streamline that, and we’ve seen efficiency gains at the plants because of it. We have one line at one of our sites that still flexes between both of them, and we had the classic supply chain struggle between manufacturing that just wanted to run one thing for a very long time to gain efficiencies, and then the reality of our network and our warehouse constraints. It was conflict all the time. Every time we got close to a changeover, there were a lot of things that we had to look at and try to convince people we were doing things the right way. So we leveraged Anaplan in the scenario building to say, all right, this is what it would look like if we actually ran for two months straight on one size, right? We would need three times as much warehouse space. We’d have [unclear word 0:15:27.1] issues. 

Adam Nichols 0:15:27.8:

Then on the flip side, because we also got pressure from our warehouse team, ‘You can’t just change over all the time,’ the lost cases you would have by flexing that much. So we came to a good spot where I think we’ve been in a harmonious place where we’ve got our built-in cycles. Once we fill up our warehouse space, we switch to the other size. As more lines are coming up this year and next year, that evaluation needs to continue to happen because the math is going to change. Hopefully, we’ll have to make less of one and more of the other. So our goal is to leverage Anaplan to continually evaluate that so that we get ahead of these cycles. We let our warehouse teams know. It’s worked out really well for us. It’s got a lot of the emotion out of it. We’ve got this plan, this data, and we adjust it when we need to. 

 

Sanjiv Raman 0:16:12.9:

As you said, adding the third plant and adding more lines to those plants will add the complexity of trying to solve the same problem and figuring out how to assign production rules across the network in a quantitative and rigorous way, where you can take some of that emotion out as well. 

 

Adam Nichols 0:16:29.8: 

Yes, absolutely. 

 

Sanjiv Raman 0:16:31.3: 

Tell us a little bit about some of the learnings over the last 12 to 14 months as you’ve gone through this transformation.

 

Adam Nichols 0:16:40.5:

Yes. I’ll start with data. We’ve done a lot of work to build up this enterprise data model to standardize between our multiple ERP systems and other reports that we have. So, I thought we were further ahead on that. I’ll say, no matter how good you think your data is, it’s probably not. As we’ve added more modules now as we’re getting into demand planning, we realized we don’t have a way of easily filtering between promotional donation type orders versus real sales orders, which hasn’t really mattered for supply chain because I just care about what the forecast is, but now that we’re using historicals to drive a demand plan, it matters, right? So I’d say it’s little things like that, things that popped up and you just have to be ready for it. To realize you might not have the granularity you thought, that was a big one. I would say the one that I was surprised I fell into - I’ve done implementations. I’ve seen scope creep. That happens on everything, and things pop up as you get through a project that you didn’t realize before. So I went into this saying, ‘I want to start simple. We got to get this done fast and just prove the concept out, and then we can add complexity.’ Within a week, I already blew that up. We did scope expansion. I’m like, man, it would be really good if we could add all of these things so that we can flex lanes and stuff like that, and I don’t think we’ve used it once, and it probably added a month and a half to our timeline. 

 

Adam Nichols 0:18:06.8:

So I would say, we’ve taken those learnings as we’ve continued to go down this path to just try to simplify, start simple and then add complexity as opposed to going the other way around. That really caught us. It’s no surprise I fell for it. Then the third one I would say is probably change management. Our first module it was easy. It was people that reported to me that were excited about it. They wanted the functionality, and it still took us probably two months longer to actually convert than I thought it would. It’s because everyone’s comfortable with Excel. We have a million things going on all the time. We can’t risk messing up by messing with Anaplan. So, we’ve got through that, and I think as we’ve gone forward, we add in more time for dual usage. That’s what we’re doing right now with LRP, just to make sure everyone’s comfortable that we’ve caught everything so that we can do a clean cutover. I think the change management I took for granted because, again, we started simple. It was three people on our team that were with us every step of the way that were excited about it. It still took a long time to really cut the cord and switch over. So, that’s something you’re always going to run into. We’re trying to be better about it now.

 

Sanjiv Raman 0:19:20.7:

We’ve talked about it too. It’s probably better to slow down before moving fast, I think. You’ve gone through this journey over the last six, eight, twelve months. Let’s not add more. Let’s wait for this to be fully adopted. There’ll be learnings from it. There’ll be iterations that we might want to work through before we think about expanding this out to all the other facets applying across the organization as well. 

 

Adam Nichols 0:19:42.3: 

Absolutely.

 

Sanjiv Raman 0:19:42.7:

We’ve talked about adding the third plant and adding more lines and looking at different routes to market. Over the short period, how has Anaplan helped you to be able to scale effectively as the business has scaled as well? 

 

Adam Nichols 0:19:57.1: 

Yes, that’s a great question. As we started doing this last spring, we had another line start up last summer. It was pretty remarkable how much it helped not only plan milk and materials coming into the line, but as we estimated, we could do volume scenarios on what if the line really takes off, what does that mean for the rest of our network, what if it lags a little bit, how do we react. So I think that’s a functionality we haven’t always had. We typically waited until something was turning on to plan around it. So, we’ve leveraged that quite a bit. We’ve got another line starting up in the next couple of months, and we’re building that into Anaplan as well. It’s much easier this time. We’ve learned a lot. We’re setting up the framework for Webster so we can do it. 

 

Sanjiv Raman 0:20:41.7:

Webster’s the new plant?

 

Adam Nichols 0:20:42.6:

Webster’s the new plant, yes, sorry, next year. So it’s helped us do scenario planning. I would say above all else, scenario planning has been huge for us because we do scenario planning all the time. Then historically, it’s taken us just a ton of time to do it. Sometimes to the point where by the time you’re done, you have to do a different scenario anyway. So, the way we’ve set it up to manage different demand scenarios and production scenarios has been just a huge, huge help to help scenario and game plan as we get into these start-ups, as they’re always volatile. You’ve got to be ready for every possibility. 

Sanjiv Raman 0:21:15.9:

This is great. I think this is a really interesting topic, especially as we talk about how Anaplan can be leveraged in scale with scenario planning. Every client that we’ve delivered wants scenario planning. Nobody knows how to do scenario planning well. Just because moving from Excel, running scenarios in Excel is a nightmare. So working that muscle of asking the right questions, iterating and understanding the trade-offs, and quantifying those trade-offs in a cyclical, systematic manner is something that you guys are working through and had a leg up just because of how the organizational culture was around asking the right questions and constantly probing and challenging as well. 

 

Adam Nichols 0:21:53.1:

Yes, absolutely. 

 

Sanjiv Raman 0:21:54.8:

So, obviously we’ve gone through this over the last six, eight, twelve months. Tell us a little bit about where else you think Anaplan potentially could be helpful for fairlife? 

 

Adam Nichols 0:22:06.0:

Yes, it’s a great question. I think right now we’ve done a lot in a short amount of time. We need to stabilize and refine. There’s still little quirks where we design something in mid-range and then we realize we want to do it differently when we did long-range, and now we got to still go back and offset them. I think we still have a ton of opportunities in material planning, especially because we have multiple ERP systems. We have a really old version of NetSuite that has no supply chain functionality at all. So material planning is a big one for us. I think there’s more and more interest now in FP&A. The guy I hired for demand planning was in FP&A before. He ran the massive - I think our CEO calls it the Cadillac of spreadsheets - every month to do our cash flow analysis. He’s like, ‘Man, this would be so much easier in Anaplan.’ So I think we’re starting to get some buy-in there as well. Strategic modeling will be a big one for us. We don’t have enough capacity. Even with all the new lines we’re adding, we’re still chasing. So, the ability to quickly spin up strategic models to evaluate co-manufacturing options or where to add another line or add another site will be huge for us as well.

 

Sanjiv Raman 0:23:15.7:

Good problems to have for sure. 

 

Adam Nichols 0:23:17.6:

Good problems to have, yes.

 

Sanjiv Raman 0:23:18.7:

Perfect. I’ll wrap up with a curve ball since AI is in the zeitgeist. What are you guys thinking about in terms of incorporating AI or Anaplan intelligence, if you will, into your planning processes? 

 

Adam Nichols 0:23:33.9: 

Sanjiv told he was going to ask this yesterday, so I was trying to do research so I could sound smart. I’ll be honest, I really don’t know. It’s a great question. I’m like, AI it just feels like it’s in hype right now, but there’s these little nuggets of value you’re seeing out there. There’s a guy on my team that uses ChatGPT to make SQL scripts. When he first showed me it, I’m like, ‘What?’ It takes him 20 minutes to write the right thing for ChatGPT to get the SQL script and then put it in there and then tweak it. I’m like, ‘You could have just written your script at that point.’ Then as I thought about it, if I haven’t done it in a while, I just google it anyway. Then I click through a million things and figure out where to start. It’s almost a skill. He’s got better and better at it. My boss has just made an AI photo headshot because he didn’t want to get a new headshot, so he loaded six pictures into this thing, and it looks incredible. So, I know there’s a lot out there, I think we have a lot of opportunities to leverage it. What I’m worried about right now is our data is still not great. It feels like diving into an AI platform right now would be going from a manual scooter to a Ferrari. 

 

Adam Nichols 0:24:44.2:

So, I think we need to step up there, but as AI gets better, and you’re already seeing it, as it gets better at identifying issues and errors in data, these irregularities, man, I think the sky’s the limit. I do think it’s going to be disruptive. I think we could use it in demand planning for sure. I know Coke’s trying to leverage that right now, but even on production material planning, it could be huge. We’re also, outside of just Anaplan, we have a ton of data from our sites, and we’ve got a team right now trying to leverage data science and predictive analytics and machine learning to figure out - we’ve got 30 data points for every major piece of equipment in our plans. How can we use that to figure out when a part’s about to wear out so we can get in front of it? So there’s still a lot of work to do there, but I’ll be honest, the sky’s the limit. I don’t know where we’ll start. I want to be open-minded about it. As opportunities come to leverage it, I think we can get a lot out of it, but yes, I think we have to prepare ourselves for it internally too. 

 

Sanjiv Raman 0:25:43.6:

Okay. Thanks, Adam. Those were all the questions I had for you. So I’ll pause now and maybe turn it out to the audience if you have any questions for us. 

 

Unknown Speaker 0:25:53.0: 

All right, let’s dive right in. 

 

Audience 0:25:57.4: 

So at the beginning, you mentioned how your execs are very heavy on Excel or have been in the past. How has that evolved with Anaplan expanding in your business? 

 

Adam Nichols 0:26:07.7:

That’s a great question. Actually we have a technology roadmap that I created a year and a half ago when we were trying to sell this thing, and there was Excel all over it. I think we’ve come a long way. We’ve got a lot of Anaplan now. We’ve actually, on the finite side of things, we’ve built some tools to help us as well. So, we’ve come a long way, I’d say. And supply chain we’re almost done with Excel. Well, as much as you can be, Excel is never going to go away, but there’s still other opportunities out there. So good progress, but still more things to go after. 

Audience 0:26:44.7:

All right. So before I ask my question, I’ll give you a little bit of context because it will get there, but you talked a lot about the data and all your bespoke ERP systems and whatnot. So our parent company, a global manufacturing company, is rolling out Anaplan to us here in the United States. A lot of the feedback and a lot of the resistance or the nervousness that they’re giving us is around our data quality, the amount of data that we have, our hierarchies and whatnot. It sounded like, as you described it, right, that you were able to overcome a lot of those data challenges and/or Anaplan was able to be pretty flexible in terms of being able to take in a lot of data and manage it, which is a bit counterintuitive to what we’ve heard from our parent company, which is it’s rigid, you need to have your data perfect, you need everything to be working end to end. So just if you could go into a little bit more detail in terms of your experience, how much effort you put into cleansing data, getting data right and making it so that you truly can optimize and use Anaplan to the best of its ability. 

 

Adam Nichols 0:27:58.2:

Yes, that’s a good question. I think we came into it with an open mind, knowing that we had opportunities. So, I’ll give a good example. A big chunk of our business leverages the Coca-Cola warehouse network, our chilled product and our club product. So, all the end transactions we actually pay attention to on the supply chain side are in Coke’s SAP system. They’ve set it up very well. There’s customer hierarchies, product hierarchies. When we started, we had no way of joining that together with the customer hierarchies we had. So, I think Anaplan is as flexible as you want it to be, but we have one dedicated resource on my team that’s just focused on data, so leveraging the data hub to come in, creating dashboards to identify things that are wrong, I’d say a lot of our hierarchies and stuff like that, we had to create on our own. So, I’ll say Anaplan didn’t necessarily do it for us, but we had the flexibility to do it in a way that made the most sense. It takes a lot of effort. 

 

Adam Nichols 0:29:00.6:

Once you set it up, as long as you have good master data processes the rest of it flows through, but there’s got to be a commitment to - and we’ve struggled with this too - to keep it up to date because Anaplan has been a much better solution for us to have some of this master data, like SKU lookups across the ERP system, customer lookups across the system, but they’re still manual. Someone’s got to go in and manually adjust it every time you add a SKU or add a customer. If you don’t do that, depending how big your business is, you fall behind really quick. So hopefully that answers your question. I will say our models were flexible in setting them up and then a little bit less flexible once you get rolling with it. As we’ve identified new things where we need to be able to adjust and be agile, we’ve tweaked our models to be able to do it. I’ll say the good news on Anaplan, from what we’ve seen, and as people on my team have learned it is, once you understand how it works, it’s not overly difficult to make those adjustments. You’ve just got to be really careful with change management and control to make sure you don’t have the wrong people doing the wrong things. 

 

Sanjiv Raman 0:30:10.9:

Just a couple of things to add there as well. One, I’d say establish your data strategy and establish guardrails around what you want to do within Anaplan and what you should not do within Anaplan. As an example, don’t create product codes and customer codes in Anaplan. Anaplan can it. Not the right place for it. What you could do in Anaplan is maybe establish some routings if your ERP can’t necessarily manage that. Define guardrails. Second, approach it with a degree of pragmatism because yes, data is not great anywhere, right, but you’re still planning and you’re running a business successfully, so what is the mechanism to be able to continue to progressively get better as you start to use the tool? Sunlight is the best disinfectant. As you start to see data, as you start to use it, your data will obviously get better as well. So approach it with this degree of pragmatism as well, so that you’re not overwhelmed or inundated by data quality issues and so on and so forth. Hopefully, that was helpful. 

 

Adam Nichols 0:31:06.2:

That’s good. 

 

Unknown speaker 0:31:08.8:

Any other questions far side of the room?

 

Audience 0:31:17.4:

I work for a food manufacturing facility as well, and we have a decent ERP, but it still makes sense that we do our production schedule monthly, weekly in Excel. You’ve touched on it a little bit certainly, but can you elaborate any more on what drove the decision to move that into Anaplan versus maybe an ERP system or Excel or just some of the benefits that you have had by moving that into Anaplan? 

 

Adam Nichols 0:31:47.4:

Yes, absolutely. In our first site with NetSuite, we didn’t have anywhere to put a production schedule. So there was a lot of effort and time put into developing this spreadsheet on steroids that made an actual - it was really impressive. You could make this full Gantt view production schedule, and that’s what that site leveraged for a long time. Goodyear started up with Dynamics, Microsoft Dynamics 365. So, we had the ability to do a production schedule in it, but what we found is once we really got into it - our finished goods schedule is critical for us measuring plant efficiencies, schedule attainment, USLs versus OEEs, and we couldn’t get Dynamics to get us to the granularity we wanted to. Once a production run started, if you ran faster or slower, you couldn’t change it, and it was messing up a lot of our processes. So honestly, because we only had the ability to do production schedules and dynamics for one site but not both, we knew we didn’t want to build out Excel. We knew we needed to do something that could do exactly what we wanted it to do. We looked at other scheduling options to see if we could bring it in, but every single one of them we were going to have to customize anyway. 

 

Adam Nichols 0:33:07.2:

So I’ll tell you, on the finite scheduling side, we actually we worked with another firm. We actually developed our own software for it. We’d already been working at it on the manufacturing side for shop floor excellence and behavioral-based safety. So we added a finite scheduling app to that, and we’re leveraging it across both sites now, which took a long time to get across the finish line, but we finally have that in a consistent place. Once we had that, the mid-range and long-range, we picked Anaplan for a variety of reasons. One, we didn’t have a place to do it. We tried building it in Excel. We had a couple of models, but people just kept breaking it. It got out of date very, very fast. It was just more annoying than anything. We had seen how Coca-Cola had leveraged Anaplan in a similar way, and because we had their expertise, their agreement, we decided that that’s exactly where we needed to start. We needed a real supply plan in a more traditional sense. So that’s why we didn’t leverage our ERP systems. We didn’t really have a great way to do it. I think that the goal is for us to get dynamics across all of our sites in the next three years, maybe. We’ll see. 

Adam Nichols 0:34:20.5:

So I think there’s more opportunities for us to leverage some things in ERP than what we’re doing today, but I think the scheduling side of it, we’re probably going to keep out because we know exactly how we need to manage our plans, how we need to schedule our plans to drive everything else. We’ve spent a lot of time perfecting it. So essentially that’s how we ended up where we were. It was a lot easier to leverage something like Anaplan to build something fast versus trying to get a consistent ERP across both sites when the ERP wasn’t working that well for us in general. 

 

Sanjiv Raman 0:34:49.0:

I think it also comes down to a combinatorial problem, right? This is how many problems are we looking to solve at the same time, and the scale of your supply chain network, which will dictate whether you can stay in Excel or Excel gets too large. One plant, two lines, dedicated products or dedicated lines, yes, you can do that in Excel, but when you add more complexity in terms of switching products within lines, switching products across lines, as well as now having multiple locations, that’s when the problem set becomes much larger. You’ll need the rigor of an optimization model and so forth to be able to do that more effectively as well. 

 

Unknown Speaker 0:35:21.5:

Adam, Sanjiv, what a story that you’ve told us today. That brings us to the end of our time, but I know you’re happy to answer more questions for a couple more minutes. Thanks so much, everybody. We’ll be starting our next session at 3:15.