The expert is the former Head of M&A and Data Science at XPO Logistics, where he oversaw 400 deals, focused on customer-centric technologies and data strategies. Prior to XPO, the expert served as the Chief Supply Chain Officer and President at Inditex, where he was responsible for the merchandising strategy, inventory management, and distribution. He oversaw the construction of a 5 million square foot distribution facility in Spain. He also developed predictive modeling algorithms for inventory and demand management.
Disclaimer: This interview is for informational purposes only and should not be relied upon as a basis for investment decisions. In Practise is an independent publisher and all opinions expressed by guests are solely their own opinions and do not reflect the opinion of In Practise.
I was with XPO for about five years and prior to that, I was with a company called Inditex. I held various roles there, including running their global supply chain for about five years. I also served as the president of Zara for a year and was interim CFO for about a year, although I didn't enjoy that role as much. But my primary role was in supply chain.
Yes, Zara USA had a strong link with XPO. We had multiple warehouses with XPO in the US. When I moved to XPO, those warehouses also came under my control. Brad, our CEO, wanted it that way. We had warehouses in South Florida, Pennsylvania, and the west coast, although the west coast warehouse was managed by another company, the name of which I can't recall. In total, we had about $100 million worth of business with the company.
That division started in 2019, towards the end of my tenure.
I was involved in transportation as well. In fact, I wrote all the software for the LTL division back in the 2017-2018 period.
XPO was divided into several companies, all of which were part of XPO at one point. These included the supply chain division, the brokerage division, the LTL division, and the international division. The supply chain division was primarily focused on warehousing. All these divisions reported to the corporate level, each having its own division president. There was a corporate team that managed these presidents and their teams, and I was part of that corporate team. My primary role was to handle mergers and acquisitions. This role later expanded to include running the corporate data science team. I was involved with every division on any project at any given time. I worked directly with all the presidents on multiple projects worldwide. Any global initiative involved my team reporting to Brad and supporting all the division presidents in their roles.
Yes, it was an intriguing dynamic that Brad set up. Most of the corporate team that reported to Brad were located in either Greenwich, Connecticut, or Charlotte, as Troy Cooper, our COO at the time, was based there. However, Troy was not my supervisor. All the presidents reported to Troy, while Brad had his own separate team that reported to him. We had SVPs and EVPs, and we essentially had decision-making authority over the division presidents, but we were also there to support them.
Our growth was partly organic, with approximately 70% of it over the five years I was there being through acquisition, and about 30% being organic growth. It's important to understand Brad Jacobs' background, who initiated the roll-up. He was a private equity professional and had previously rolled up United Rentals. Many of the team members at XPO had also worked with him at United Rentals.
The primary goal was for my team to acquire as many companies as possible, given the fragmented market. This was particularly true for the warehousing and brokerage sectors, not so much for the LTL side.
Brad's acquisition strategy was aggressive, to the point of considering the purchase of Old Dominion, which would have doubled the size of the company. However, the family had no interest in pursuing this.
We did have some organic growth. The challenge with XPO's LTL division is that it's incredibly expensive, more so than many other companies that offer LTL. Our strategy was to assure clients that their freight would likely arrive on time, which is crucial for larger companies. Also, the security of the freight was superior to many common carriers, who have damage rates in 3% to 5%. We boasted a damage rate of less than 1%.
XPO LTL also grew by acquisition, which meant we had to spend a lot of time integrating software systems. We quickly realized we were not as efficient as we needed to be, driving our prices up to maintain our margins. LTL was Brad's main focus. He saw the growth potential in the e-commerce market and the bulk transfers with LTL, which he believed would drive the company's growth.
He also noticed that LTL had become a fragmented business, with only regional players and no national player controlling multiple markets. He wanted to get everything under one umbrella. Brad's ultimate goal was to leverage each division to secure large contracts that included warehousing, brokerage, NVOCC, and LTL. However, we struggled with this for five years due to conflicts between division presidents who were reluctant to cross-sell.
There were constant conflicts between divisions. For example, one division would take a contract that negatively impacted their P&L to support the LTL side of the business. This led to ineffective operation of warehouses as they didn't want to invest in a business with no margin. The strategy needed to be adjusted in every area, but Brad was more focused on boosting the LTL division. While it may not have been the best strategy, and we did have disagreements, ultimately, Brad's decision prevailed.
It was quite interesting because as we expanded through acquisitions, we found ourselves with divisions that had remnants of LTL, remnants of brokerage, and remnants of managed transportation. It took us about three years to bring everything under one umbrella and assign them to the appropriate divisions.
Typically, we would acquire a company and they would operate under an earn-out agreement with whichever CEO we had bought out. They would usually want to continue operating their business as usual, so we were constantly trying to shift them away from that.
Let me give you an example. We made a large acquisition that included Menlo Logistics, Jacobson, and New Breed Logistics. All three of these companies had transportation brokerages, which they were reluctant to give up as it was deeply integrated into their culture. We had to firmly guide them toward the future state we envisioned.
We had many acquisitions that had tapped into different parts of the supply chain. We knew when we bought them that we were going to integrate them into a different division. However, it was going to take some time to accomplish this. Some of them lacked advanced technology, some had weak leadership, others had union issues, and some had a variety of other problems. It was quite a diverse mix.
The LTL industry has evolved over time, starting in the 1980s in the US and progressively getting more challenging. The industry is extremely capital-intensive. If you're trying to start a company, you need to have the financial capacity for trucking and cross-docking space.
You're likely to face union issues, as the Teamsters have a significant presence in this industry. Small companies that managed to finance six trucks would venture into less-than-truckload operations. However, they would often stall as they were merely poaching customers from other businesses, and no new markets were being developed.
At any given time, there were around 4500 LTL companies in the US. From a private equity perspective, this signaled a need for consolidation, as many of these companies were likely looking to cash out.
During my tenure, the cost of capital was low, and borrowing rates were incredibly low. This made it feasible to acquire new companies, even at a premium. We were aware that the return on investment would materialize in the long run.
We were in the right place at the right time to start the consolidation of the LTL market. However, we noticed that many companies were reluctant to sell to XPO. We often had to increase our offers by 30% to 40% above market value to persuade them to sell. Brad was willing to do this, despite the potential reduction in ROI over a five to seven-year period.
He believed that these acquisitions would eventually contribute to the top line. We did manage to acquire some companies below market value, as they were ready to cash out or were facing financial difficulties.
In LTL operations, it's crucial to have an entire network of trucking working in harmony. If they operate independently, it can lead to a lack of accountability and create operational issues due to the formation of independent silos. Our initial goal was to unify everyone under one division.
As we acquired companies, we understood that many of them had their own divisions and preferred to operate independently, especially during their earn-out process. We used a strategy called the Influencer Model to manage this, but it took longer than expected.
By 2019, it became clear that creating a one-stop shop was unlikely. A holistic Third-Party Logistics (3PL) that does everything is challenging to operate because not all companies offer everything. However, all the companies wanted advanced technology and many desired consumer data warehousing.
Independent companies can create operational issues. For instance, Landstar operates independent silos, but this model has its drawbacks. It can lead to integration issues with technology, problems with driver pools, and questions about who bears the cost when trucks break down or when there are labor issues.
If you operate independently, you're on your own. But if you operate as a unified company, other networks can support you during hard times. Terminals often face such issues.
The cost models also vary as certain markets are more expensive than others. If you can provide holistic rates, you might take a hit in one market but profit in another. When you perform network optimization for a customer, which our software does, it can be a challenge to maintain independence. Landstar has tried and failed at this for years.
Ultimately, everything pointed us towards operating under one entity. Landstar makes decent money as they're a low-cost provider. However, the demand for fast freight delivery can lead to issues in an independently operated network. If a terminal is in financial trouble and hasn't been paying the bills, it can cause further problems. We concluded that operation under one entity was necessary.
There were many independent silos making decisions that were not necessarily aligned with the company's overall strategy.
Identifying potential acquisitions isn't difficult. There are countless brokers out there scouting companies open for bids. However, convincing a company to sell is the challenging part, especially if they've been successful. In a fragmented market, you encounter many family-owned companies. Some were public companies, some were larger companies owned by private equity. Securing the right financial backing was usually the biggest hurdle. But scouting a company was relatively straightforward. I had a team of 40 people looking at deals in any given market in LTL and any part of the supply chain. We would reach out to their executives or go through an acquisition process with a broker. We had many brokers who would inform us of companies that might be interested in selling. We would then make initial contact via email, phone call, or social media to find the right players. Finding the right players isn't difficult.
The most challenging part is the due diligence process, trying to get them to the table to sell the company. In a booming market, many are ready to exit the stressful transportation industry. If someone offers you $40 million to retire and live off dividends for the next 25 years, you're probably going to accept. But getting them to the table with the right offer is the most challenging part. The integration process, if you have a good playbook, isn't as challenging. We had our fair share of problems, usually related to aligning everyone on the same page. The beginning phase is the most critical. During due diligence, you're negotiating over their financials from the past seven to ten years. We used multiple models, including discounted cash flow models, EV to EBITDA models, and sales multiples, to try to get them to the table with a deal that made sense for our financial modeling of what we thought we could make of the company.
Every time we acquire a company, we gain an incremental advantage. One aspect of this is our willingness to pay above market value for the company. This approach has contributed to the success of our roll-up strategy. We're willing to pay 10% to 20% over market value because the company has likely spoken to four or five other potential buyers. They want to know what their company is valued at, what we're willing to offer for it, and the terms of the deal. If we have this information beforehand, perhaps from dealing with the same broker they used previously, we can leverage it for a competitive advantage.
We're acquiring the customer base. In any part of the 3PL logistics supply chain, you're essentially acquiring the customers.
We also take into account any unfavorable contracts the company may have. We're prepared from the outset that we may lose 10% to 15% of their contracts either because we decide to end the relationship with the customer or attempt to renegotiate the terms. The first step is always to try and renegotiate. If the deal isn't profitable for us, we'll assess the cost accounting and determine our break-even point. If it doesn't make sense for us to continue doing business with a particular customer, we'll end the relationship. I've had to let go of many customers because they weren't willing to renegotiate. Often, they'd go to another company and end up with a worse deal. I would always warn them of this possibility. Sometimes, they'd come back to us a couple of years later asking for the old deal, but we couldn't offer it because it wasn't profitable for us.
Profitability and saturation are key factors to consider. By saturation, I mean the concentration of your customer base. It's not ideal for a small company to have one to three customers making up a large portion of their business. For example, we encountered a trucking company in South Florida where 64% of their business came from a single customer. Despite making $75 million a year in revenue, the loss of that contract could dramatically decrease the company's value overnight.
Another factor we consider is market presence. Are you in a growing industry? Are you specializing in air freight, which we have little interest in? Are your contracts solid for the next five to seven years? What is the likelihood of retaining a contract if it comes up for bid again? There's usually a 50-50 chance of keeping a contract during a rebid, as customers often switch if a lower price is offered.
We also look at the region a company operates in. Is there an economic impact over time? Is the population increasing? The supply chain is heavily influenced by population density. For instance, the Southeast part of the United States is densely populated with many small towns, whereas the Northeast has large towns with high population density. The Mountain West, on the other hand, is sparsely populated, meaning longer delivery distances.
Our goal was to control the entire US, and essentially all of North America, with the LTL side of the business. We also ventured into Europe, which is a different beast altogether. It's not necessarily more challenging, but there are more regulations to deal with.
Other considerations include growth potential, brand recognition, and population density in the market. These factors can affect your valuation. LTL companies typically grow regionally rather than nationally due to high travel costs. This is similar to the old franchising model where franchises would only grow in one region. National growth for transportation companies is often slow and costly, as they have to use partner networks to move freight for their customers, which isn't profitable.
Suppose you sign a contract with a national company like Lowe's or Home Depot. You're only going to get business with them. Let's say they want to use your services across the entire East Coast, but you only have one terminal in New Jersey, and 80% of their customer base is in the Northeast. How would you support that contract? It would be impossible without expanding your company. However, the capital required for such expansion could significantly impact your bottom line for up to five years. This is due to the costs associated with renting trucks, hiring personnel, securing terminal space, and other capital costs involved in your expansion.
Would their revenue offset these costs? Probably not. Moreover, if you're primarily based in the Southeast and they're not leveraging much of that, Lowe's probably wouldn't consider doing business with you because they would be aware of your network limitations.
This scenario illustrates how rapid expansion can potentially harm an LTL company. It requires substantial capital to grow and expand, and this process usually happens very slowly.
We typically utilize various formulas based on consumer data to determine the industries in a particular area. For instance, in the Southeast and Northwest, lumber is a significant industry. Hence, we know that many industries in these regions will revolve around that. In the Southeast or Southwest, there are numerous food companies, indicating a probable high volume of outbound freight from these companies.
When considering final mile distribution, the most expensive part of any traditional supply chain, LTL plays a significant role. LTL handles a lot of pickups and consolidations, and it also carries out most of the final mile transportation in the US, excluding small packages. However, we never ventured into that area. Our focus was more on business-to-business models. We did cater to business-to-consumer in some areas, but most consumers who order home deliveries do not order in LTL quantities, only businesses do.
LTL is costly primarily because it doesn't optimize the entire network of the truck. A full truckload is more optimized for a company, and it's more profitable because costs can be reduced more easily. The number of touch points also plays a role. Each touch point increases costs because it involves human labor, which drives up labor, transportation, and fuel costs.
Most companies are in the omnichannel space, which is a massive market globally, regardless of ecommerce, which only accounts for 10% of final mile. So, when trying to optimize space across a network, adding more touch points involving humans can lead to damages. Even with advanced electronics, if the goods are not put in the right truck at the cross-dock, it can lead to problems, which happens quite often.
Another factor to consider is the rising cost of wages in the LTL market. Due to trucker shortages, companies are now having to pay 50% to 75% more than they did 10 years ago to hire a truck driver. This increase in wages drives up rates, the cost of goods, and overall costs, creating what we call a bullwhip effect in the supply chain.
The network density of a target company is incredibly important. However, it's like playing a chess game. If you've just acquired a company with a dense market in three or four U.S. states, and you need to have a dense market in the adjacent states, then the acquisition makes total sense. You're adding more capacity to those markets and can leverage them back and forth. This is why silos don't work. You need the networks to be interconnected. Density is crucial because it reduces cost and drives down the price of the freight.
In LTL, the higher your price, the less business you're likely to get.
There are several KPIs that can be used. These include route mileage, fuel cost in the market, labor cost, and miles traveled between touches. There are software tools available to assist with this, but they are not always 100% accurate. At XPO, we developed some that performed predictive modeling. We utilized Facebook's predictive model and other algorithms for predictive modeling to anticipate where freight would be at any given time. This allowed us to adjust our pricing accordingly.
Density within an LTL network is crucial. Without it, long-term competitiveness is unlikely. This is why regional players remain as compact as possible until expansion is absolutely necessary.
The greatest expense is the travel from one point to the next. If you can consolidate your freight through specific cross-docks and reduce the frequency of this, it is beneficial. More full truckloads to a terminal for final mile delivery is preferable. Smaller deliveries do not always justify a dense network. However, when dealing with customers with large amounts of freight, extra density in a certain market is necessary for final mile delivery. Otherwise, you risk pricing yourself out of many deliveries. The key is consolidation techniques in the supply chain, whether it's at a port, an LTL cross-dock, or through a truck brokerage.
The more freight you can load onto one truck and the less distance it has to travel, the better.
It may sound counterintuitive, but the math always favors better density through your network. This also allows for growth. Many LTL contracts are lost due to a lack of capability to reach a certain market. If you're dealing with smaller customers, a less dense network might make sense, and a brokerage could be used. However, we dealt with customers like Home Depot, Lowe's, Verizon Communications, and Comcast, multi-billion dollar companies that move a lot of inventory. If you're looking to create a model with less density, I would recommend a brokerage network for optimization. However, your rolled throughput yield to the final mile, which means your freight is actually going to show up undamaged, is going to be incredibly high compared to what you want. So you have to build that into your model too as well.
Yes, that is indeed the ultimate goal in any transportation network. There's another point I omitted that needs to be discussed. We are now in an Amazonian economy where everything must be readily available.
The model you're referring to, with fewer terminals and longer transportation, is known as the Dell model. It was effectively leveraged in the 1990s. Longer transportation meant lower inventory. It worked well for Dell computers, and many companies adopted it, closing warehouses and terminals to optimize for this model.
However, those days are over.
Amazon has changed the game. Companies are now required to carry higher amounts of inventory due to the multitude of options available. Understanding consumer behavior is key to this. Inventories are now much higher than they were in the 1990s for any omnichannel retailer.
If you can't deliver the same day or the next day, you're going to lose sales. Customers can easily order from Home Depot or Lowe's using their phones. Omnichannel retail and Amazon have revolutionized the industry.
People often ask me why Amazon is building so many warehouses in the US and globally. They are adopting the LTL model, ensuring they have the capacity and the ability to deliver as quickly as possible. They also need to do it as cheaply as possible.
If the final mile transportation costs are too high for a customer who doesn't have Amazon Prime, they will order from another provider offering free shipping. This happens 75% of the time on every ecommerce channel. Shopify has also generated multiple data lines on this.
So, the need is to have it fast, carry more inventory than before, and realize that the old lean tactics no longer work with the consumer. This shift started about twelve years ago. I warned the executives at Inditex that it was coming, and they were hit hard by the pandemic because of it.
They still wanted to maintain low inventory, which was a significant problem I continually highlighted. We lacked a functioning omnichannel strategy. The entire strategy was to drive consumers to the store and neglect the e-commerce side. Unfortunately, Amazon and other European companies figured it out before they did.
When the pandemic hit, they lost all their store traffic. They went from 7,000 stores to 3,500 within a two-year period. As a result, they were closing stores rapidly. That's how supply chains must operate now. It's all about speed to market.
As I mentioned earlier, it's crucial to be strategic about the regions where you want to acquire network capabilities. The importance of technology capabilities cannot be overstated. If everyone isn't aligned technologically, running a network of terminals or warehouses becomes extremely challenging. This is a lesson we learned quickly at XPO.
At one point, we had to overhaul all of our warehouse management systems to be on the same platform because we had 17 different WMS and 45 different transportation management systems in the LTL network. My task was to consolidate these into one system for better coordination.
Interestingly, the receiving process, driver scheduling, and route optimization were different in all 45 locations. This caused significant delays in transportation through the network because not everyone was able to perform tasks in the same way.
Yes, there were differences in labeling, receiving processes, outbound scheduling processes, and labor management systems. None of these systems coordinated with each other.
For instance, if I'm working with Home Depot and I'm bringing in 75 trucks into one terminal for a brake bulk, and I have to go through two different terminals to get all the freight there, but they don't all communicate with each other. This is a common tactic in supply chain, known as vendor consolidation, and XPO used it extensively.
The issue arises when I receive a Purchase Order (PO) electronically through EDI or an API feed, and the data doesn't match what was sent because my system doesn't understand it. My system doesn't know how to bifurcate that. So, there's a delay of about seven days because we have to use our manual system. But Home Depot can't afford this delay because those POs have to be in their stores by the end of the week.
Brad and I were extremely frustrated with the LTL industry because it was all based on these same strategies. We felt like we had bought a monster that wasn't communicating with itself. This underlines the importance of having an interconnected network.
There are many factors to consider. Financial metrics suggest that the sales multiple should be at a certain level. LTL, being capital-intensive, doesn't usually have a high sales multiple. In a high market, you might see one to two times sales. I've seen a few go higher, which was surprising. The LTL industry typically lacks up-to-date technology. Many still use outdated AS/400 systems, which are Cobalt-based and challenging to work with.
We also consider the type of technology they have, their current customers, and their growth potential. We assess if they fit into our current model and if we are willing to pay a 20% premium for a competitive advantage in a certain region. It's mostly financial modeling, but about 30% is optics, looking at the growth trajectory in that area.
We also look at the condition of their fleet. We assess the extent of damage, the amount spent on repair and maintenance over the past five years, and if they are investing in anything beyond combustible engine technology. We consider if they have the capability to invest in driverless or autonomous vehicles, which we were continuously exploring.
When I first joined, our ability to provide front-end services for our customers was our most significant competitive advantage. By the time I left, we had improved significantly and were probably the best in the industry. It's not about having flashy tech, but about being able to operate in a more fluid, lean way that eliminates hidden costs in their network.
Yes, our base ROI model projected between 35% and 45% over a five-year period. However, we had multiple models and it varied. We might aim for a 35% return on one company over the next five years, and for another, it might be closer to 60%.
We would consider these models, but often Brad would rely on his intuition, recognizing a growing industry. We would present Brad with various financial models, including EV, EBITDA, and discounted cash flow models. We would then consolidate these to predict a likely yield, such as 35%. Brad would then set a maximum cash outlay to achieve this return.
We would also build in buffers based on our experiences with other acquisitions. As a math person, I developed many predictive models for the company's finances.
Once we have completed the acquisition, we would announce internally and externally that we have acquired a particular company. About four weeks into this process, my responsibility was to present Brad and Troy with a three-year minimum operating plan for the newly acquired company.
This plan, based on our due diligence analysis, would detail which customers we would retain and which we would let go. It would also outline potential changes in the staff structure, such as bringing in a new sales team, letting go of the terminal or regional manager, or adding more responsibilities to existing managers.
Most of these managers had an earn-out or stock option program. We would assess who would stay beyond the earn-out period and who would want to leave. We would individually discuss with all the executives of the company their future plans post-earnout.
The majority of the CEOs chose not to stay, but a few did. Those who stayed would take on different roles within the company, either on the integration side or the operations side, depending on where we felt they fit best.
After making a company-wide announcement, we would start transitioning people in and out of roles. If there was a terminal or a regional there, we would begin the process of bringing the company under our umbrella. At this point, we would also start dissolving the entity as it existed and create a structure where they report through a specific chain within the company.
If a contract wasn't profitable, it wasn't necessarily a deal-breaker. We would try to negotiate with the customer, perhaps suggesting a rate increase to achieve profitability. Alternatively, we might decide that the contract wasn't suitable for us. We would then review the contract and consult our legal team for an assessment of our exposure.
Some terminals had as many as 500 contracts, others had 55, and each one was typically written differently. At XPO, we had a standard contract that we would aim to transition them into. This often involved re-selling the contract to the customer, explaining that they were now under XPO's terms.
There were instances where we wouldn't alter their existing contract because we either liked it or were unsure of how we wanted to proceed. In such cases, we'd let it sit. However, around 80% of the contracts would transition over to XPO's legal team and we would sign a new contract with the customer.
More often than not, we'd offer them new terms, trying to get them to agree to terms that were favorable to us, whether it was cash terms, current rates, or accessorials. However, this wasn't always the case. If we felt the terms were already favorable, we'd simply present the new contract and propose an extension for another two years. This was the case about 70% of the time.
There was a 10% who would dispute with us, and probably 20% we would either ask to leave or they would choose to leave because they were uncomfortable being with a larger company. However, losing contracts could open up capacity in our broader network, which could benefit the entire company. For instance, we might now be able to service lanes that a certain customer had that we didn't previously service.
This was part of a concerted effort by the president to optimize the network, aiming to increase lane density and capacity within each terminal.
We would estimate what we believed to be a good EBITDA.
In the LTL industry, if you're achieving over 25% EBITDA, that's considered quite successful.
Some of our operations were exceeding that, while others were actually operating at a loss. We had a robust cost accounting team within my group that would optimize everything. They would identify contracts that weren't profitable and we would either have to increase the rates or potentially consider parting ways with the customer in that area.
However, there were some national or regional contracts where we were losing money in one terminal but not in others. In such cases, we wouldn't make changes as overall, the contract was still profitable. We might be making 25%, 30% on it. We might try to optimize the lanes in that area through operational techniques, but we wouldn't typically terminate the contract.
Most of our decisions were based on standard cost accounting, comparing what we were making versus what we were charging. We also considered whether we were providing the best service to the customer by optimizing their network. We would keep them informed about any challenges we were facing and the steps we were taking to address those challenges. For instance, if we couldn't service a particular area, we might consider acquiring a company that could. We spent a lot of time communicating with individual customers, keeping them informed about our company's activities.
Sometimes that was due to our own shortcomings as a company. We may not have done a good job informing the customer about how their freight should flow through our network. Sometimes we weren't paying enough attention, or the companies hadn't conducted a thorough analysis. My role was to ensure that this analysis was done correctly.
For instance, if I have a contract with a company like Comcast, where I'm making 45% EBITDA in the Southeast, but only 15% in the Northeast, I probably wouldn't make any changes. However, during the rebid, I would bring up the fact that we're not making as much in the Northeast, where most of their freight is moving. We might need to lower the rates in the Southeast and increase them in the Northeast, which could potentially even out the costs. But our costs would be less, so in reality, we would make a better profit.
This isn't a one-scenario situation. There could be multiple factors causing a contract to be unprofitable or not as profitable as we'd like. The last thing we want to do with supply chain is go back to a customer and say we need to raise their rates by 20% because our labor costs are too high. They might just decide to take their business elsewhere. So we had to be very careful about how we approached such situations.
There could be labor issues affecting pickup density, or perhaps the right capacity for the customer isn't available. There might not be enough trucks for that particular lane. You might find yourself needing to purchase capacity to service the account, and the capacity you're buying could involve using rental trucks or a partner company because you don't have the ability to handle everything they have, and you're not willing to invest in that ability.
I was the one tasked with analyzing all these potential issues. There might be a technology-related issue that frequently comes up, like not having ICC 128 labels, lacking an integration for that, or not having an API feed for us to display. Perhaps your TMS system isn't routing the freight at the right level.
There could be issues happening at the customer's location. They might be a warehouse or a factory from which we're picking up that's having problems with capacity. In your analysis, you would identify that and say, "If you can fix your capacity, your cost goes down, and we all win." But you really had to understand the entire value stream of what they were doing so you could present ideas to them.
A cost-saving idea is never a bad thing in supply chain as long as it brings in new business. I was very good at identifying potential areas for improvement. For instance, maybe your warehousing throughput is really bad, but I have a solution for you that will reduce that warehouse capacity by 40%. On the back end, you're going to save another 22% in total. So we all win in this scenario.
That was part of what my team did. My side job was managing the data science team. We did some data mining and data laking for our customers' data on the front end. It would take a while if they wanted us to go deep. But typically, we would take our internal data and then have conversations with our customers. We would request access to their data to present them with a more functional plan. They never denied us access.
We would ask for access to their TMS, as most of them had their own internal TMS. We would also request access to their YMS, their yard management system, their ERP, and their MRP if they were a factory. All this data would tell us if they were experiencing flow issues inside their factory, or if we weren't doing our job correctly. Maybe we weren't picking up on the right schedule, or perhaps we needed more frequent pickups at their location to get stuff off their dock, which could be causing their factory or warehouse to clog up.
We would occasionally run into that issue. In such cases, we would propose a plan where we would charge more on the transportation side, but guarantee that they would save three times that on the warehousing side because their labor cost is currently so high due to us. To sell this, you have to understand the supply chain.
I would approach a customer and tell them that I've managed two of the top ten supply chains in the world, and I achieved this through data. I would explain my experiences at Starbucks, where I ran their supply chain for several years, and at Inditex. Mentioning Inditex to any supply chain professional is akin to saying you've worked for Google in tech. They would then ask for help in understanding where they're losing money.
I would tell them that I've done everything in this industry. I've handled every aspect of transportation, every warehousing mode you can think of. I've managed massive automation projects that required hundreds of millions of euros in capital. I know how to interconnect the nodes between each other, which is really all you're trying to do.
In each of those touch points, multiple things can happen that cause bottlenecks in the supply chain. A professor from my college, Hal Lee, coined the term "bullwhip effect". He said if you could optimize the bullwhip effect, you can optimize your supply chain and reduce your inventory and transportation costs. I know how to do that.
My selling point was that in this industry, it's all about speed to market, reducing costs, increasing flow, and delivering to the final mile location as quickly as possible without damaging your product. Supply chain management is very simple. It requires a bit of math and a lot of common sense, which, unfortunately, many people lack.
Yes, they care about it because they don't understand it. But the underlying component is that they want to reduce their costs and increase their sales volume. The only way to do that is to examine every node in your supply chain, identify your problems, and optimize what we call your material flow.
You might blame XPO for not moving your freight fast enough, but the problem could actually be with your raw materials. If your raw materials aren't arriving on time, then we're picking up half-empty trucks. If you solve your raw material problem and get it through your factory faster, then those trucks will all be full and your transportation cost will be halved. That's just one of hundreds of examples I could analyze for you.
Supply chain management is starting to require more math than it used to. The person who understands math and supply chain will control the supply chain because that's what controls everything. It's about identifying where your costs are, what's causing bottlenecks, and where the theory of constraints can be applied at multiple different points.
For example, a small package that goes from a warehouse in Chicago to a house in New York City is handled 15 times through FedEx's network on average. That's only the final mile. Imagine all the touches that happen before that. You need to know where to increase those touches for consolidation or decrease them for final mile transportation. Most companies don't know how to do this very well. I was rather shocked at how little the chief supply chain officers I met at XPO knew about optimizing their inventories. And inventory is your biggest cost.
Old Dominion excels in many areas compared to XPO. They have a superior operations strategy. They manage their labor field and route optimization more effectively than XPO, predominantly. Old Dominion has been a regional player for most of their existence, although that's changing now.
On the other hand, we tried to steer XPO towards emulating a lot of what Old Dominion was doing. In fact, we even brought in some of their executives to assist us. However, reaching their level would likely have taken a decade, and I left before that could happen. We were making progress though.
I believe XPO excels in final mile and heavy bulky deliveries in certain markets, as we can leverage the brokerage network and the LTL network. We tried to integrate these to achieve a better cost model.
Old Dominion, however, has a well-established brand with a loyal customer base, some of whom have been with them for many years and are unlikely to switch. They have a structured management team and as a smaller company, they don't have as much bureaucracy as XPO. This has made them a strong regional player with a solid business model. They've always had strong leadership, something XPO has struggled with over time.
XPO is now the big player in the market and has been for a while. Brad Jacobs, who is not as involved as he used to be, has grown the company significantly. In terms of intangible value, Old Dominion would have been the best acquisition XPO could have made, if a deal could have been struck. However, Old Dominion had no interest in merging with XPO.
So, what do you do? You benchmark the best, and I consider Old Dominion to be the best in the LTL industry. The challenge is to figure out what they're doing right. Over time, companies will figure it out, but they must continue to innovate, or they'll become obsolete in the next decade.
They had already integrated technology that I had to build before we came on board, and they've continued to enhance that technology and capability. They've also made significant investments in response to shifting consumer buying behaviors. As I was rebuilding the company, they were already taking it to the next level. They had identified that the ecommerce industry is booming. Currently, ecommerce is growing at about one and a half trillion in market value every year.
They invested a lot of time and energy on how to optimize the ecommerce network. They also take care of their drivers very well. This loyalty is crucial because drivers often switch companies. They have a very forward-looking senior leadership team that is always trying to figure out their company's competitive advantage.
They've invested in other industries, they've tried to expand on their own, and they've made wise decisions with their working capital. I'm not currently analyzing what they're doing, but I can only tell you what I saw when I was analyzing them until about 2019, and they probably have continued on that path. I believe they invest heavily in technology and will continue to do so.
They're allocating their capital expenditure dollars to strategies that are likely to work and observing where the transportation industry is heading. They're not focusing too much on old methodologies and companies. Instead, they're investing in new companies and providing better strategies than other LTL companies have in the past.
Additionally, they have a strong understanding of how supply chains work and have leveraged that knowledge. To secure larger contracts, you need to understand how supply chains work and how they can be optimized. If you don't, you're going to lose out quickly.
On average, XPO was about 15% to 18% more expensive than Old Dominion. That was my observation, and it was fairly common in the industry. OD had already invested in their transportation management system and the capabilities to integrate with customer supply chains long before I arrived. They were probably five years ahead of me. I understood their strategy and what I needed to do to surpass them. However, I knew it would take about ten years to reach their level.
This was primarily because many of their contracts were not due for bidding for a long time. They had invested in technology because they understood their customers' needs.
There's a prevalent theory in supply chain management that quickly becomes apparent. The company that invests in its customers will win. It may sound cliché, but if you're willing to offer your customers technology they don't have, they will choose you. They don't want to develop it themselves if they don't have to. If you have capabilities they can access through a software-as-a-service model, they will choose you in a heartbeat. The integration is easier, they don't have to manage it, and it's cheaper in the long run because they can use that software to optimize their network better for what you do.
This was what caught Brad's attention when I joined XPO. I told him, "You've got to do this." Companies don't want to invest in this type of technology because it's only for them. If you invest in it, you're investing in 20,000 potential customers at once. So the cost per click will be significantly lower and you'll just get better at it over time. Most of these companies don't manage supply chains well, anyway. Brad, you've got to be their guide.
I estimated that if I started in 2014 and stayed for ten years, we would have reached our goal by next year. At that point, we had a lot of cleanup to do. So, I set a timeline to surpass ODFL within ten years. However, transitions from one provider to another in the LTL industry are slow, and I was aware of that.
Could we have outperformed them in five years if I had a large team and could do everything I wanted with XPO? Possibly. But they were already far ahead of us. We were essentially in the Stone Age compared to them. We're talking about massive builds, extensive transportation models, lots of algorithms, large data conferences, and integrating new companies, which is not an overnight process. So, I felt that ten years was a reasonable timeline. They’re making progress, but I think they would have advanced faster if I had stayed. However, I might be overconfident. I could have encountered numerous problems that I couldn't foresee.
Let's consider a scenario. If I have you committed to a five-year contract, with a clause that requires you to pay for the remaining three years if you decide to terminate the contract early, you're unlikely to leave. This is a common strategy in the LTL industry. For instance, we're doing $100 million in business, and you're locked into a contract with us for the next five years. If you choose to exit in the third year, you'll have to pay an exit fee of $250,000,000. You're unlikely to leave under these circumstances.
The lock-in techniques in this industry are quite effective. If you wish to challenge this and deal with Brad's attorneys, you're welcome to do so. However, Brad's success rate is around 95%, similar to the U.S. Attorney's office. Initially, people tried to challenge this, but soon realized they couldn't get out of the contract without paying the exit fee.
So, not only would you owe $250,000,000 over the next three years, but you're also incurring $290,000,000 a year in transportation costs. That's why you wouldn't enter into a $100 million a year contract without some form of exit clause. And every contract we had included this clause.
The main reason is that their rates were significantly lower, and they were willing to commit to that time period. The average contract in the LTL industry lasts about three years, but some extend to five years. In the warehouse sector, the average contract duration is a minimum of five years. This was consistent across all sections.
Yes, you've covered all the aspects. We lock in rates for specific lanes, regions, freight classifications, route density. We also consider how frequently you're moving freight, your peak and off-peak seasons, and other factors.
This document may not be reproduced, distributed, or transmitted in any form or by any means including resale of any part, unauthorised distribution to a third party or other electronic methods, without the prior written permission of IP 1 Ltd.
IP 1 Ltd, trading as In Practise (herein referred to as "IP") is a company registered in England and Wales and is not a registered investment advisor or broker-dealer, and is not licensed nor qualified to provide investment advice.
In Practise reserves all copyright, intellectual and other property rights in the Content. The information published in this transcript (“Content”) is for information purposes only and should not be used as the sole basis for making any investment decision. Information provided by IP is to be used as an educational tool and nothing in this Content shall be construed as an offer, recommendation or solicitation regarding any financial product, service or management of investments or securities. The views of the executive expressed in the Content are those of the expert and they are not endorsed by, nor do they represent the opinion of In Practise. In Practise makes no representations and accepts no liability for the Content or for any errors, omissions, or inaccuracies will in no way be held liable for any potential or actual violations of laws, including without limitation any securities laws, based on Information sent to you by In Practise.
© 2024 IP 1 Ltd. All rights reserved.
The expert is the former Head of M&A and Data Science at XPO Logistics, where he oversaw 400 deals, focused on customer-centric technologies and data strategies. Prior to XPO, the expert served as the Chief Supply Chain Officer and President at Inditex, where he was responsible for the merchandising strategy, inventory management, and distribution. He oversaw the construction of a 5 million square foot distribution facility in Spain. He also developed predictive modeling algorithms for inventory and demand management.
Subscribe to access hundreds of interviews and primary research