Director, Global Strategic Solutions
Supply Chain Business Intelligence: Data Rich vs. Information Poor with Envista’s Michael Falls
“Shippers tend to be data rich but information poor. Shippers have access today to more data than at any point in history. Because of the fact that their data sources tend to be disparate, meaning I’ve got data coming out of a purchase order management system, out of a warehouse management system, out of a transportation management system and then probably downstream in a freight audit payment solution.
What that means is that shippers tend to not have a way to pull out actionable insights and turn that data into information. So those disparate data sources mean there’s no single source of truth.” –Michael Falls, Director of Global Strategic Solutions, Envista
Welcome to the Down to Freight podcast, where we sit down with transportation, logistics, supply chain, subject matter experts to discuss digital transformation projects. I’m the host of the show, Francis Adanza. And it’s a pleasure to welcome Michael Falls, Director of Global Strategic Solutions with enVista. Mike, it’s great to have you here today.
Francis, thanks so much for having me on the podcast. I appreciate the opportunity to be part of the conversation here.
Absolutely. With that said, do you mind taking a moment to share a little bit more about yourself, your experience and your company?
Yes, absolutely. Yes, like you said, Director of Global Strategic Solutions within enVista. For any of the audience who’s unfamiliar with our company, enVista is a leading consulting and software solutions firm. And we’re really organized into 4 cross-functional solutions areas, so consulting, technology, operations and automation.
We were founded in 2002. We’ve grown organically over the past couple of decades, 8 years of which we’ve actually been on 85,000 staff and growing. And a lot of our high growth is really fueled by just the rapid pace of technological and solutions needs in the supply chain and enterprise commerce spaces. We’ve really adapted and grown our solutions to meet those needs.
Today, we’re supporting end-to-end enterprise commerce solutions and tech for omnichannel retailers and distributors and manufacturers. We’ve got over 1,000 customers across our company, supporting everything from network strategy to systems selection, WMS, OMS PMS, systems like that, facility design build, IT consulting. We’ve got proprietary technology, a unified commerce platform that has order management, point-of-sale, product inventory management.
Now the area that I didn’t mention and core to what I do is our transportation solutions. We are a global freight audit and payment provider, which includes our myShipINFO product. It’s a leading global transportation spend and management solution, and that includes carrier sourcing, PMS selection and implementation also within our transportation solutions and then also our business intelligence product, which is what I’m here to talk about mostly. And I’ve spent really the last 7 years just helping to develop that business intelligence product and be focused really on transportation analytics for large shippers.
Awesome. Thanks again for coming. And BI is an exciting topic. Can you explain more about what that means from the lens of your customer? What kind of intelligence are you providing? And what kind of decisions do you help them make?
Yes. Every time I talk about BI, I always borrow from something I heard an executive leader say a few years ago that rings true, which is that shippers tend to be data-rich but information-poor. Shippers have access today to more data than at any point in history. And because of the fact that their data sources tend to be disparate, meaning I’ve got data coming out of a purchase order management system, out of a warehouse management system, out of the transportation management system, and then probably downstream in a freight audit and payment solution, like enVista has with myShipINFO.
We’ve got access to all of this data, but it’s not necessarily integrated and tied together. And what that means is that shippers tend to not have a way to pull out actionable insights and turn that data into information. So those disparate data sources mean there’s no single source of truth. The upstream reporting and intelligent sources typically don’t give the full picture. If I’ve got a shipment execution software or a TMS that’s got great visibility solutions, it’s not going to have post-manifest adjustments, either additional charges or potentially credits or disputes of carriers downstream. So it’s not going to give me a full cost picture typically, even if it’s got projections.
There also tends to be lack of landed cost visibility, product level visibility, profitability. So there are all of these challenges that shippers face. And historically, there hasn’t been a product or a technology that’s really addressed all of those challenges. And that’s really just in the operations side of things. There’s the whole finance component as well, where shippers face the burden of doing general ledger cost allocation on all of their shipment activity, creating journal entries for all of their shipping activity, paying their carriers, which, if you’re just paying UPS and FedEx, so that’s one thing. But if you’ve got a global shipping network with dozens or hundreds of carriers you’re managing across multiple currencies, that’s a huge manual operation. So there’s that component as well.
And then there’s just the cost validation, right? Again, there are shippers that we work with who maybe manage $5 million to $10 million in costs. And then there are shippers we work with who manage $500 million in shipping costs. And so just validating all of those expenses, having the intelligence to do that as well. So those are all of the problems that shippers face. And historically, there hasn’t been one unified solution to resolve.
Now what is that solution? It’s business intelligence. It’s having a comprehensive platform that provides you with visibility into your all modes global shipping costs and helps you optimize. And I guess I would just say, this is a less mature discipline in supply chain than in some other areas. So when I say data-rich, information-poor, that’s not necessarily a problem that sales or marketing decision-makers face in the same way, not to say they don’t face it at all.
But typically, if you’re data-rich in sales and marketing, you’re probably information-rich as well. You’ve figured out how to use that in actionable ways. But because of the presence of disparate data sources and all of the problems that I just outlined, supply chain and transportation leaders in specific typically don’t have that same luxury, which is really what, again, my focus over the better part of the last decade has been in terms of producing high-quality transportation analytics and BI to solve those problems.
Got it. No, that’s a great overview. I can’t say that I’ve ever worked for a company or spoke with a company that didn’t have all those problems that you listed. So for those in the audience that are thinking about doing a BI project and they know they have all of these problems, like what are some things that they should think about getting started before they even begin looking at technology?
Yes, it’s a good question. In large part, it depends on the size of the shipper. So I work with shippers today who manage $5 million in costs, like I said, or less, all the way up through $50 million, $250 million to $1 billion with a B in spend. And it depends too on the type of shipping costs that you have. There are so many businesses out there today that have started and are shipping small parcels and they have a shipment execution system that integrates them to a UPS and a postal service or a FedEx. And then there are these other multinational companies who are doing ocean and air inbound and intermodal and LTL and truckload.
What you’re considering really depends on your shipping profile, number one. That’s the point I’m making there is your shipping profile. And then also what data do you have at your disposal today.
So like Francis, you said you’ve never known a company who hasn’t faced the challenges that I just mentioned. So if everyone is facing this problem of disparate data sources, then really the question becomes, what are those disparate data sources? And how do we tie those together? What’s the solution? Because everyone at the end of the day is looking for the same things out of data. You’re looking to reduce your costs. You’re looking to improve your performance to serve your customers. You’re looking to make your associates’ jobs easier with the data that you have.
There’s a number of ways that companies are getting BI today, and we can get into that. But really it’s understanding your profile and then understanding what are the data sources that we have today because, ultimately, that’s going to create your starting point in terms of what your BI journey will look like downstream.
Got it. Okay. So I can’t imagine it’s as easy as, hey, I found the solution that I want to work with. Everything is integrated. And like all my reporting is nice, fancy charts and graphs. There’s probably a lot of like data standardization and normalization before you can get to the key insights to make these decisions. And you mentioned like the size and scope. Let’s just say, for the enterprise clients that you work with, like on average, like what is a typical time frame or total cost of ownership before they begin going down this journey, go through some of that minutia, and then here you are in a much better place with all the fancy dashboards?
Right. It depends on which route you take in terms of solving the problem of being information-poor to continue to use that analogy. There are 2 typical paths I see shippers go down. At this point, most enterprise-level companies have a corporate business intelligence solution. Most of your audience, the company you work for, probably has a Tableau or a Power BI. At the corporate level, there’s been an investment in a technology that’s going to be the corporate BI solution.
And if I was running a company today, I would implement the exact same type of solution. It makes a lot of sense, set up an enterprise data warehouse, have a data lake and try and get all of your data sources across your company and within your umbrella into that enterprise data warehouse or EDW and then downstream into the BI. But also, it’s problematic to go that route because, especially from a logistics perspective, the resources who are probably implementing a corporate BI solution, they understand data but they don’t necessarily understand supply chain data or transportation data. And they don’t understand how to pile all those disparate sources together.
The other problem with implementing a corporate BI solution is the supply chain typically is pretty far down on the food chain in terms of where that implementation lands. So if I’m running an enterprise-level corporation and I’ve got a corporate BI initiative, I’d probably implement, again, I’ll go back to sales and marketing. I’m probably going to implement those data sources first and then supply chain is somewhere further down the list. Now this is changing as companies recognize what a cost driver supply chain becomes, both either as a secret weapon or as a disadvantage, depending on how you use it. But in most places, it’s lower on the food chain in terms of corporate BI.
So what you’ve got to do really when you go down this BI journey, I think this is what you’re getting at, is shippers need to decide what’s the solution that’s going to allow them to aggregate all of their data, connect all the supply chain data sources and ideally do it at the endpoint. So the way that we do it is because we’re a global freight audit and payment solution, we have access to all of the carrier billing data that exists across the shippers network. And because we’re the endpoint, I mean, when you think about the furthest upstream of the journey, right, purchase order for some inbound freight move occurs.
And then there’s an ocean or air import potentially from overseas to the United States will go through the traditional retail model here. And then there’s some sort of dray move and there’s a move to a distribution center and then there’s freight out to a store or there’s parcel direct to consumer. There’s all of these different components in the supply chain process. And so the endpoint of that is going to be the final mile carrier actually delivering a bill saying, here are the costs for your final freight load.
And if you can tie back all of that data along the way, you can make great business decisions. You can’t make the best business decisions with only part of the data across those different systems. You have to make it with all the data. So to answer your question in terms of timeline, probably both of those solutions that I described are going to be part of the mix. There’s going to be a corporate BI integration to an EDW at some point in the journey, and there’s going to be a recognition that transportation stakeholders are typically going to leverage a system outside of that corporate BI solution. So it’s really important to pick the right one.
If you’re working with a freight audit and payment provider like enVista, again, I can kind of only speak from our experience. The runway is it typically takes a few weeks to implement small parcel, U.S. domestic carrier solutions into our platform. It typically takes a couple of months after that to match that data, what we would call an order match. So to match that to the UPS, the FedEx, the postal service, the OnTracs of the world, match that data back to order data or back to other disparate supply chain data sources that we’ve got the full picture.
And so we’re talking a couple of months really to full visibility. Now you start adding on like a total global freight network, then you’re talking 3 months or 6 months or sometimes longer, depending on the resources that a company can provide. But that’s a typical timeline for shippers that we’re integrating into our platform.
Got it. That’s super helpful. So how would a client or an organization measure the impact that BI has on their business?
The measurement, I think, is going to depend on what the intended outcome is. At the end of the day, it all comes down to optimization. You can call it different things. But when you’re leveraging BI, you’re trying to optimize your cost. You’re trying to optimize your performance to serve your customers, and you’re trying to optimize your workforce, right? So it’s cost optimization, service optimization and what I would call role optimization.
I don’t coin a lot of terms, but role optimization is one that I’ve coined. So I’ll start there. Role optimization would be the idea that you can use business intelligence to automate reporting to eliminate non value-added activity in your associate work days. People aren’t rolling up and manipulating data. You’ve got a product or a platform, where you can just use data as intelligence. So there’s no manipulation involved. So that’s business efficiency role optimization.
The most commonly sold reason for business intelligence would be the second, cost optimization, where maybe you’re doing things like adjusting your service level or modal usage. You figure out ways that you can ship maybe a standard or ground service level instead of an express service level. It will cut your cost in half, but you can actually reach the customer in the same amount of time. So that would be an example of cost optimization or reducing non value-added expenses, like post-manifest charges, accessorials, changing your box sizes.
And then the third one is the service performance optimization, where maybe we’re using the data to change our shipment execution software logic or implement a new transportation management system so that we can reach our customers with better performance time, like an Amazon effect. Everyone’s reaching for faster transit.
So from a measurement perspective, the question really becomes what’s the baseline? And so if the problem we’re trying to solve is reducing costs, then we have to establish what would the costs have been before we made the operational change based on the BI and what are our new costs based on the data that we have coming in. A great example of this is with contract negotiations. The biggest lever that most shippers can pull to really reduce unnecessary costs in their network is based on renegotiating their contracts.
Now business intelligence helps with that and then market intelligence. So it’s got to be the combination of both of them. But that’s really where I think about measurement and baseline is prior to renegotiating my agreements with my carrier network. What would my costs have been based on my previous agreement? What are my new costs going to be based on my new agreements? That’s a very clear before or after. But again, 2 examples to drive it home on the small scale because on the carrier negotiation side, the one I just mentioned, we worked with a $400 million shipper last year, where the negotiations were able to cut out 10% of their unnecessary shipping costs, $40 million. So you can make some really big changes there.
Operational changes are never going to be that wholesale. But that’s where business intelligence can be really valuable. I use that example. If you can find who in your company is shipping next day early AM so that it gets somewhere by 8:30 in the morning, they’re doing it because they think it’s the right thing for the customer. But if you shifted that to standard, you could save x amount of money. That’s a real example. We cut $200,000 out of a $20 million shipper’s network. That’s 1% of their spend.
We use a business intelligence platform to shift packaging types from poly bag to a certain box size because we knew that was going to cut out 0.5 a percentage of their spend. So those things aren’t as wholesale with carrier negotiations in terms of the impact they’ll make. But those things add up. And the point here is that what business intelligence allows you to do, especially when you’re measuring it the right way, like we’re talking about here, is you’re eliminating unnecessary freight expenses. It’s not like you’re cutting headcount through the use of business intelligence.
The point is there’s opportunities to reduce costs in your network while actually improving your performance times, and all you have to do is let the data guide you there. That’s really the beauty of business intelligence.
Awesome. So what advice would you give to others who are thinking about leveraging BI?
I think that the advice I’d give is that there are going to be corporate pressures and operational needs in any BI journey. And so I think you want to pick an approach that allows you to meet both of those. And what I mean there is that the best approach that a decision-maker can make for their transportation operation is one that probably includes multiple BI solutions. The corporate BI strategy, which I touched on earlier, if your company doesn’t have one today, that’s coming. But that should coexist and complement a transportation BI product that your operational stakeholders can use within your transportation operation and your transportation finance users and stakeholders can use.
Most of our enterprise-level customers at this point are shippers who leverage our proprietary product, right, transportation spend and management platform that includes market-leading BI. Really, the transportation ops and transportation finance users are using our product. But at the same time, we’ve got an EDW feed. So it’s just a data export. It’s all of the aggregated data that is cost validated. In a lot of cases, it’s paid data because we’re paying on our customers behalf in a lot of cases. And so that all gets fed into this EDW.
So that way, the corporate BI solution box is checked, and all of the data exists in one umbrella. But there’s a very specific BI tool that really the end users in the transportation space can leverage, that helps drive their day-to-day operations and finance needs. So again, that’s the push. Those products can and should coexist to meet both the needs of your organization but also really put your associates and your stakeholders in the best position to be successful in leveraging business intelligence.
No, that makes a lot of sense. Mike, it was a pleasure speaking with you today. It was very informative. I took away a lot of very helpful and practical BI insights. For those that might want to get in touch with you to learn more, could they connect with you on LinkedIn, visit your website? What’s the best way for them to get in touch?
Yes, definitely. Yes, if you’re interested in learning more about enVista solutions, envistacorp.com would be a great place to go to learn more. But please, yes, do reach out to me. I’d be happy to have a conversation. Linkedin would be a great way to do that, and we look forward to continuing the conversation there.
Great. Thanks again. Appreciate it.
Yes. I appreciate you inviting me, Francis.