Thought Leaders In Cloud Computing: Steven Smith, President And CEO, Gcommerce Inc.
By Sramana Mitra and guest author Shaloo Shalini
In the following interview, Sramana and Steven discuss how supply chain services for Internet-based electronic data interchange (EDI) in the automotive and traditional whole goods markets are adopting cloud computing to their advantage.
Steven Smith is the president and CEO of GCommerce, Inc. He started his career at Ruan Cos.’ Iowa Export-Import after graduating from Grinnell College. He founded GCommerce in 2000 in New York. A few years later, in 2003, he moved the company to Iowa, weary of New York’s high costs. Smith picked Des Moines over sites in Illinois, Nevada, and New Jersey. Smith pledged that the 20-employee company would grow to 150 workers in about four years, but things did not work out well until Smith decided to rethink his software strategy and rebuild the company. He put his focus on helping auto parts retailers, distributors, and suppliers connect. Smith knew this business best. His father had worked for Gates Corp., a parts maker, while he helped Prestone antifreeze become a leading supplier to Wal-Mart. After GCommerce made the auto parts supply chain more efficient, customers wanted them to make it easier to fulfill special orders, such as requests for the parts that are not stocked. It was a problem Smith had wanted to solve for years, but the solution was expensive and technologically complex until GCommerce hit upon cloud computing. Lost sales, employee time, and other problems with special orders represent 80 percent of the costs in the supply chain, GCommerce estimates. Smith said that a conservative estimate of the cost is $20 billion a year. GCommerce promises to change that, in some cases cutting from 15 minutes to 15 seconds the time needed to find and order a part through its virtual inventory cloud (VIC) offering.
GCommerce, Inc. employs 40 people and has become the cornerstone of the supply chain for the auto aftermarket industry. Today, GCommerce is a leading provider of Software-as-a-Service (SaaS) based technology solutions designed to streamline the distribution and supply chain operations. Its connectivity solutions facilitate real time, effective information sharing between incompatible business systems and technologies, enabling firms to improve revenue, operational efficiencies, and profitability.
SM: Let us begin our conversation about cloud computing adoption and cloud computing strategies within the context of GCommerce and your 300 billion automotive aftermarket industry.
SS: GCommerce is the market leaders for a business-to-business exchange services in the $300 billion automotive after market in the United States. Globally, it is a trillion-dollar market. We provide and automate the entire procurement cycle in this market. The core problem that we are addressing, using this transformational solution called the virtual inventory cloud built on Microsoft Azure SQL Azure Platforms, is the lack of visibility on inventory, products, and the supply chain. Today, there are 10 million part numbers that are in distribution in the marketplace. These parts are spread across the 47,000 retailers and 216,000 repair shops in the ecosystem. An average distributions center stocks only about 200,000 parts. An average store stocks 13,000 parts. You have a massive inventory disconnect between being able to stock the products that either the consumer or the repair shop needs and the ability to deliver quick, quality service.
GCommerce rendered a solution we call the VIC to virtualize the availability of capacity to inventory in the supply chain by bringing together and harnessing all of our participants in the marketplace. We have over 1,000 suppliers and over 200 major commercial wholesalers and retailers in the ecosystem, including significant retail distribution and suppliers in Mexico and Canada. We have a large ecosystem that is participating in the VIC. The idea is, with Microsoft we are taking about a $20 billion problem called drop ship special order. It is core to what Amazon does – providing the ability to take an order and drop ship special orders to any location. In the context of this $20 billion problem in a $300 billion marketplace, with our solution, we can take a 15-minute process and convert it to a 15-second one. What is typically done today by using the phone, e-mail, extranets, and sort of random ad hoc processes that take about 15 minutes, takes only 15 seconds with our VIC.
SM: Let me drill down a bit more into some of the things you said. What is the total number of parts that you mentioned are in the automobile aftermarket industry?
SS: Three million are highly active ones out of 10 million parts.
SM: I was talking to the CIO of Mahindra Satyam just a couple of days ago about these series as well. We discussed the Supply Chain Operations Reference (SCOR) as a method or model for supply chain standardization.
SS: I know these people, and I know Mahindra as well. I used to export products to that organization.
SM: What you are doing is kind of supply chain standardization for the automotive industry across those 10 million stock-keeping units (SKUs), is that correct?
SS: That is correct. The automotive aftermarket is actually an amalgamation of many subsegments of the heavy-duty industry, which is itself about a $50 billion segment. This market encompasses organizations like Komatzu and Mahindra. I understand people like that who actually fit into this ecosystem. Since this automotive aftermarket is so large, it crosses not just traditional products like replacement parts but performance and appearance accessories, tools and equipment, and heavy-duty products which ultimately find their way into excavation equipment, buses, or any type of industrial product that is automotive. It ties into a vast ecosystem globally.
SM: Before GCommerce came up with this kind of standardized taxonomy, what was the norm in automotive aftermarket industry? What was there before and after GCommerce? One of the reasons I am pursuing the question of taxonomy is because this is obviously coming out through the Thought Leaders in Cloud Computing (TLCC) conversations in our series in general. The point is that for any serious level of standardization to happen around cloud computing in various different industries and various different functional areas, the taxonomy standardization is a critical piece. This is what allows large data sets to talk to each other without huge amounts of customization and integration. What are your thoughts on that?
SS: I will let our CTO, Jason Popillion, jump into this discussion briefly to share his insights on taxonomy. I would like to mention that we created a canonized data model using the “Super Spec.” It is neat, and we will send you some supporting documentation, but I will let Jason tell you more about that.
SM: Okay, go ahead, Jason.
JP: You are kind of hitting right at the core here. You are exactly right about what we recognized early in our business. Our virtual inventory cloud (VIC) is actually built upon a foundational network that we have created. We, in a sense, perfected that taxonomy as it pertains to the automotive aftermarket in the procurement process within the automotive aftermarket industry. What we recognized was that looking at the buyer and seller relationship, the buyer is going to buy supplies from multiple suppliers all over the world. A buyer’s and a seller’s ability to communicate electronically in a streamlined, efficient manner depends on all participants having some kind of common dialogue. The problem is that they do not necessarily have this electronically because this conversation could be happening between a large enterprise buyer buying air fresheners and a small mom-and-pop outfit. Well, that small shop is not going to be to able to meet the electronic needs of that large enterprise buyer. There are multiple levels of variations between a buyer and his or her suppliers and they have to be accommodated.
At GCommerce, we tackled this disparity from two perspectives. We started by building a specification model. We looked at what the existing electronic data standards followed. We adapted all of those electronic data standards. We also looked at what the customers we were on boarding into our network were sending us. We looked at the commonalities between these two. We factored in how the customers order products and what are the unique attributes of what they do. Next, we overlaid that to create the specifications that we call “super specification.” These “super specs” were shared with the market through an organization called the Automotive Aftermarket Industry Association (AAIA). This organization represents buyers and sellers in the automotive aftermarket. We went back to them and said, Look, here is how we looked at the ecosystem of this market. Here is what we found, and by implementing a super spec standardization, [we created a] taxonomy of how to communicate between a buyer and a seller, or the most common attributes. With this, you can run a more efficient shop and onboard connections to people in a much faster, more streamlined manner. We actually got statistics from a few of our customers for whom this made a great difference.
SS: I am sending those statistics to Sramana right now. These are actually information that the industry gathered from people using the super specifications, which are based on a canonized approach to a global taxonomy for procurement. They establish a global data standard for this industry.
SM: Very interesting! When you put this specification together for AAIA and member use, in what format do you distribute it or make this data available? Also, what your business model for it?
JP: The format is that of a defined specification say an electronic data specification for a purchase order. What we have done is, we looked at those versions of a purchase order across multiple versions of electronic data interchange (EDI) standards; we also looked at it across other file formats like XML, flat file, comma delimited, and standards like those that we receive from what customers have been sending us in this industry to do that communication. We overlaid those attributes, and that is how we came up with the super spec model. What we deliver to the industry is that written detailed specification of all the common attributes – the ones that are required, the ones that are optional, and so forth.
SM: What you delivered to the Automotive Aftermarket Industry Association was a metadata structure of sorts?
JP: Yes, exactly.
SS: In terms of business model, we built ours on the reverse market adoption model. Once we realized that the legacy messed up this process and that making it work is really based on the classic enterprise application integration (EAI) approach, which is a problematic approach, we decided to get the super spec done. Having realized this early on, we went to a data-driven model, and for the data-driven model to work we have to canonize the data. Therefore, Jason’s point was to re-create the super spec. An important approach we took here is that we donated the super spec to the industry, which then created a board of directors from all across the industry including buyers, retailers, sellers, system providers, and ERP providers, and those people sit at the table and are driving the super spec adoption. We maintain the super spec for this board. That has allowed us to drive this approach forward because we have such a large ecosystem. These people are evangelizing around Jason’s super spec and the canonization of that data and the metadata. We already have the market adoption for this data-driven model. We maintain the business rules but the architecture, the super specification, we have donated to the industry.
SM: Who owns the data itself? Are those 10 million parts that are floating through this ecosystem sitting in a database? Where is this data categorized based on the right taxonomy, and where does that data sit?
JP: The individuals involved in the process own that data. The suppliers and the manufacturers own that data because they are the ones that are producing those parts and defining part numbers out of their systems. They are selling and capturing that information. However, there are other entities that own portions of that data. There are catalogue providers, those who create online catalogues and on behalf of these suppliers. There is a new application that we have in the cloud called virtual inventory cloud. That is actually taking their vendor inventory information. When we get that file, we run it through a transformational process and load it a repository of the cloud for access through one of our applications for availability.
Some of these suppliers do not send files. They do manage, hold, and obtain close control over their inventory data information. They are willing to expose that information to us but through secure methods. They use a Web services method that follows a standard called Internet parts ordering (IPO). That is a Web services–based call, which is wrapped in security that goes directly to that supplier’s system asking for a particular part. That supplier’s system would kick back a Web services–based response saying, yes, it is available; here are the rules on how to order it, and so forth. Then you can turn around and kick off an order over the Web to the services supplier that would hit their business system, and they would ship the part and trade invoices and all of that stuff.
This brings us to the cloud story: What is the essence of why the cloud is important? Well, the essence is that we have used the cloud to fulfill a story within automotive aftermarket that suits the cloud paradigm and meets our industry’s needs. What we have created as the virtual inventory cloud is solving a problem of order supply chain, but it give you visibility into these 10 million parts wherever they are, regardless of your technical capabilities. We have created this very low-cost model for you to gain access to something that you had no visibility of before. Because of that, you now have visibility, not just visibility but visibility in a very quick manner. Earlier you might have been able to find out what that part is, then called somebody and went through, say, five or 10 minutes of process trying to get something done in a traditional model. We have streamlined the process using the cloud paradigm and brought it down to 15 seconds. What you end up with as a user is a special order process. If a special order process took 15 minutes traditionally and a company was able to do only 20 of those in a day, now it is able to do 120 or more in a day.
SM: In these two different modes you have described of creating this repository, one through suppliers loading their specifications onto your system and another through a Web services based–call to their system, what is the split of the 10 million parts inventory that is out there? How much of that is on the repository in each of those modes? How much do you still have to cover?
JP: I would say it is going to end up in an 80/20 split in the weeks to come. We have probably about 3 million parts on our systems today, so we still have a lot more to on-board.
SS: Well, you see what happens, Sramana, it is about 10 million and we fully load the 3 million active ones. Having the 3 million on our system is probably going to cover about 85% of the non-special order enquires. In terms of the overall 10 million, 8 million will end up being not in the system and 2 million will access to some type of remote call like the Web services call.
SM: OK.
SS: The 80/20 rule would be the cut off. The Pareto law would rule in this case.
SM: Can you tell to me more about the architecture of your cloud solution?
SS: Ok. This is where it gets cool, Jason. This is the fun stuff and Jason would like to answer it.
JP: In terms of architecture, if you look at the ground part of it, there are two major parts. We have an on-premise network that is our traditional network, and we have been using that for doing business for a while. Then there is this canonical data model, and our super spec has been implemented throughout that. For all of the data files that we get in, they are mapping and translations to whatever format is there in the super spec. We have a cloud or an off-premise setup as well that is based on the cloud model.
These two work together to deliver and transform data in a quick, streamlined, and secure manner between our networks, our traditional electronic data interchange (EDI)–based network and the clouds for this inventory files. This is important because if we are getting masses of inventory files in small increments, we have to have an environment that will process those quickly, efficiently, and securely and then pass them onto a cloud in an architecture that does what is best for the data in the cloud, send to the repository and make it available to the world. That is how we have designed this first part of architecture.
The second part of how these two aspects play together is through their single sign-on model for authentication and authorization. When a person logs in, we have a two-base entry point into the cloud; the first one is through a Web portal that we have called virtual inventory cloud. Anyone can go into that Web portal and log in. Once people put in their password credentials, they will go into our on-premise system for authentication, and then the system will establish a tight and secure trust between our on-premise and cloud systems. It will then go to the cloud and get what that user is authorized to do and feed it back. It will build their streams and present their part data, and the vendors can collect from that all the information based on rules. It will show industry rules on how they can see things, what they can see, and how to display it and to whom. Security and all of those parameters are built in to that cloud.
SM: What is the response from the industry? There are a large number of players on the AAIA board; what is their response to architecture such as yours, and what is their interest in getting on board?
SS: That is interesting because in essence the industry is all about performance, and they are all about seeing the results. They want things to work, they want to work quickly, effectively, and accurately, and they want it now. What GCommerce has done is used their existing models of logging in through this single sign-on methodology. This allows them to use their accounts, the ones they have already created, in our system to work seamlessly with the introduction of cloud. They do not have to do anything else; they have the same user ID and same passwords authorizing them to keep doing stuff.
In essence, they don’t see any difference; they don’t know if the repository is in our data center here, which is really in a private cloud, or if it in the Microsoft data center in San Antonio. They cannot tell any difference, so from their standpoint, their visual interaction with that is negligible. Where they started to focus attention is security. Well, when we explain to the security model and that the close trust we have between two environments, the on-premise and our cloud environment, and they see how we manipulate and store data and move it over, security becomes a nonissue.
SM: Can you explain to me why security is such a big issue if you have a parts catalogue of some sort, which is essentially what you are putting together here – a centralized parts catalogue of the world’s auto parts. Don’t you want the buyers and everyone else to know what parts you offer?
SS: Sure. This a good question, indeed. Here is how I can answer it. For one, we do not provide a catalogue where a catalogue is information about the parts that are available in the world regardless of who you are. What we are presenting is parts that are available to buy right now, today, that are not stocked anywhere. These are the parts that you have access to buy, and not every one has access to buy from every vendor out there. They already have pre-existing agreements with buyers and so those vendors will authorize buyer to be able to buy their parts and some of the contracts go down to what part they can buy and how they can buy it.
SM: I see. Therefore, it is the application and permission that they are worried about.
SS: That is right, and some of the same people who are buyers are suppliers in other ways, too. Some vendors do not want their prices to be shown to the world; they do not want people to know what parts they have in stock or what parts they do not have. There’s a lot of information: The metadata that eventually could be mined out of this potentially demonstrates how parts are being sold and are being moved and what and where are the best selling parts, which parts they should start stocking more instead of leaving them on fresh order.
SM: I see. Well, there was an attempt to do something like this 10, maybe 12 years ago, to bring together the automotive supply chain. What happened there, and why is it that it is working now, or working to the extent that we can say it’s working compared to what happened then?
SS: I will explain that; it is the kind of my life’s work. I grew up in this business, and now I am 41 years old. Here is what happened. First of all, the automotive industry actually has two spheres of influence. One is the industry that makes cars, and then there is the aftersales market. Covisint, which still exists today, was established by the Big Three. Compuware owns it, and they are actually one of our partners because we handle theGeneral Motors (GM) relationship in collaboration with Covisint. The bottom line is that they were trying to establish an electronic data interchange (EDI) data exchange standard for the vehicle side of the industry. The aftermarket side of the industry never really went down that path. Covisint was never active in this side of the market. That is the number 1 reason. The number 2 reason is that other companies, including Aribaand CommerceOne, also wanted to do this in the automotive and many other industries. The approach, however, was much more of a “build it and they will come.” There is a problem with that approach. Those who have the economic power are the retailers, the buying groups and the wholesalers. AutoZone, Carquest, NAPA,O’Reillys, and Craig, they are the ones that actually drive the market economically. Therefore, our model is built upon the hub-and-spoke model from the Wal-Mart world. In this model, Wal-Mart drives and all the suppliers follow. So, the reason that 12 years ago similar initiatives by companies such as Ariba, CommerceOne, andVerticalNet did not succeed as much was that they didn’t abide by the rules of the jungle, which are that a person who has economic power drives the adoption. Everyone would argue that no one has done a better job of that than Wal-Mart. I spent five years working with Wal-Mart internationally in supply chains, and we when we started GCommerce, we operated from that same viewpoint. That is, we get the AutoZones and the big buying groups like Alliance. Federated Auto Parts, O’Reillys, NAPA, and Carquest on board. They drive adoption for our solution. If you do not follow that economic model, you end up with anemic adoption.
So that is my take on why it did not work earlier. You cannot ignore the channel, especially when the channel and the people in the channel have the economic power. If they are not part of the solution, the solution will never be adopted. In our case, we have had widespread adoption. I mean, we can just take you through the whole underbelly of our business. Our business is expanding exponentially right now because we have laid down the entire infrastructure; now with the cloud we have the ability to grow hyperactively and to be able to port this entire infrastructure and the whole metadata model to other industries. We have just started another vertical market, and we have expanded into Mexico. If you do not approach it from the point of economic power, you are going to fail. I think this was the cause of the big failures in all of those big exchanges. In addition, I think that is the reason why Covisint never made it, and Covisint today really is just an EDI exchange primarily serving companies like General Motors and Ford.
SM: Can you talk to me about the supply chain operations reference (SCOR) models?
SS: The SCOR people have a relationship with the Automotive Aftermarket Industry Association (AAIA), and we are close to AMR, which is now part of Gartner. The AMR people think we can help to create that SCOR model for the supply chain.
SM: For the benefit of our readers, could you send me information about what SCOR is? How has the supply chain industry adopted this model of standardizing taxonomies?
SS: Well, I would say SCOR has just come to the automotive after market in the past 18 months or so. Therefore, that process of getting people to adopt and use the SCOR model is new in this market. I know that in the Consumer Products Group (CPG) and other markets, the supply chain councils have done a much better job of adopting the SCOR model. I am aware of that model from a distance, having worked only with the Supply Chain Council. I am actually presenting at a Supply Chain Council meeting in Houston later in October. In fact, Jason, I think you people are going to be talking about the SCOR model next week when you are at the industry conference, right?
SM: So, what industry does SCOR handle?
SS: Well, this is from what I know by just talking to the Supply Chain Council. I always see them at the EMR, CPG, and hardware conferences. If you look at industries with mass merchants and CPG, for example, the Home Depots, the Wal-Marts, the Targets, the Lowes, the CPG hardware, mass merchant and retail folks, those are the ones adopting SCOR.
SM: Are you saying that Wal-Mart adapted the SCOR model?
SS: No, I do not think Wal-Mart has this. Wal-Mart does not need to. They would rather do their own thing, but I believe that a lot of the manufacturers, suppliers, hardware industry players, they work with the SCOR model. I can refer you to the senior vice president of the Supply Chain Industry Association, and he could probably articulate a more exact definition of what we are doing with SCOR and this industry.
SM: We will follow up with you to get referrals to some of the people who are doing adjacent things in the supply chain. Let’s move in a different direction. What is the Microsoft architecture that you have adopted in deploying your solution? Why has Microsoft recommended you as one of their cloud computing leaders?
JP: Well, we have adopted SQL Azure, the database, for the back end in the cloud and Windows Azure on the front end for Web services and data processing. The other part of data processing is AppFabric, which Microsoft has built on the Azure cloud. AppFabric handles threading, queuing, and localized storage, that type of stuff. It gives the ability to do computing with lot of power under your own design, development, and code sets. There are other pieces that we have in the cloud portion of our system, and there are the pieces used in interactions or design architectures around how we use the cloud or the endpoints into the cloud. Web services is one of our other endpoints that goes to the cloud. As I said earlier, we have two endpoints: the portal application, which is a Microsoft Silverlight application, and a Web services endpoint in which customers from their business systems send us a secured Web service call to the cloud to request inventory, see inventory availability, and get a response. We will also be creating another endpoint, which we call big voice. This will be a unified communications model that will allow us to connect directly to the cloud via a phone call. Imagine a supplier is visiting a store and a customer walks and says to him, I am looking for this part but I am not sure what part number it is. The supplier can call it in on his phone and be able to place the order immediately before the buyer leaves. We are creating these three endpoint models.
SS: Jason, one of the things I think Sramana was looking for is why do you think Microsoft positioned us as a thought leader in this space?
JP: Sure, I will address that shortly. The fourth aspect we use is Microsoft BizTalk. BizTalk is not available in the cloud, but what we have done with it is unique. We are one of the industry leaders in using BizTalk. We are the largest BizTalk implementation in terms of the number of artifacts and code pieces that we run on BizTalk, and that is how we got Microsoft’s attention. We offered, as a cloud model, the virtual inventory cloud (VIC). This would be instrumental. We are one of the thought leaders in this because we bring a combination of ingenuity in how to use the cloud, especially between disparate systems. The example is in our on-premise, off-premise model that is a combination of our using BizTalk on the premises and in the cloud to do some transformations. In addition, we have extracted, with Microsoft’s help, some base functionality that remodels what BizTalk currently uses from its core, and we are using some of those features in the cloud. Therefore, it is not fully BizTalk in the cloud but some of its core capacities that we have designed and engineered with Microsoft methodologies to do processing in the cloud. No one else is doing that; we are the only organization doing a transformation process of any type in the cloud.
SM: Okay, got it.
SM: Next in our discussion, I would like to explore entrepreneurial opportunities from your point of view in the supply chain domain. I am talking about the supply chain in general, and it sounds like you are reasonable experts in this domain. Where do you see entrepreneurial opportunities for starting new companies to solve open problems leveraging the cloud architecture?
SS: There is lot of opportunity in reporting and business intelligence, I would say. I know the general manager of the cloud services business, and all he talks about is metadata and canonized approaches to the cloud. People who are going to be successful are those who have metadata and a standardized approach figured out. Once you get into that, suddenly you have a very data-rich environment. I think there are some green spaces around all of that, because now you the capability to have this huge amount of standardized data coming from disparate sources whereby you can start to re-create useful business insights and business intelligence. I think that is one of the big areas for entrepreneurs.
SM: I agree with you. Actually, I think the organizing and streamlining of data opens up huge opportunities for business intelligence and reporting. To help our readers, can you give some use cases of where you think entrepreneurs can build solutions?
SS: Well, Jason, y go ahead if you have a couple on the top of your mind.
JP: Let me give you an example – it is a much-generalized used case – if you think about voting data. Voting data is collected within a county or state, or even regionally or nationally. There are multiple segments of those types of statistical data, which is perfect for applications to capture and store within a cloud to provide back to those agencies. Here is the reason why: if I’m collecting that data and storing it under a common format, every office within the state or area concerned has immediate access to that data in a standardized way at a moment’s notice. It allows you to grow that out regionally; it’s the same standardized data, or you even further; that is, nationally. It is still the same standardized data. Therefore, the ability to go after that data in a moment’s notice is what the key is. When I say moment’s notice, there is a lot that is involved because when you are talking about large data sets, and you have computing power to compound that data, and that’s costly. Using the cloud model, you can lower the cost to be able to provide that type of processing and to go through that size of data set.
SM: Jason, what you are pointing to is that in the context of an industry or is it a situation where the data sets have not yet been standardized. The opportunity there is not so much on analytics reporting yet because the data itself has not been standardized yet.
JP: That industry aspect, yes, that is correct. It is true for any industry; I mean, any industry is of course going to be moving toward standardized data.
SM: Different industries have different capacities for being standardized. If you look at the apparel industry, there is a certain behavior pattern, and trying to standardize the data set of the apparel industry is a different problem from standardizing the data set or taxonomies for the motor industry, right?
JP: That is right!
SS: We agree on that. It is a great point, Sramana, that you bring forth. We call these long-tail industries. If you look at automotive, industrial products, aviation, industrial fluid control, and bearing – they are very much long-tail industries. In fact, in the automotive industry products are still sold today that have been sold regularly for 55 or 60 years. In the case of these long-tail industries, it has been hard to get one’s arms around very large data sets. Now that we have standardized the data, we made a remarkable amount of progress. You can start to run queries and business intelligence about sales out, sales to, sales in, sell-through, and so forth. This is big in terms of bringing the kind of excellence that Wal-Mart shows, bringing that to the entire aftermarket. I think that Wal-Mart has proven in their model. If you look at what they did with retailing, sharing sell-through information with their suppliers and driving an entire category of their business, I think you will see that it is a big win for long-tail industries like this industry.
SM: What else is going on in the broader market right now? Is e-commerce is really starting to come alive again? I have seen some statistics; 20,000 e-commerce stores are coming online every week. My point is, whatever category you are a supplier or supplier group in, if that category lends itself to e-commerce – and almost every category, at least in America, lends itself to e-commerce – and if you have to cater to such a fragmented set of electronic stores, the standardization of taxonomy for that industry segment becomes vital, right?
SS: Yes.
SM: Otherwise, how do you cater to all these different stores, electronic stores?
SS: I agree wholeheartedly; this is one of the big things that we have been socializing as we have come out of the inventory club. If you really look at multichannel commerce, there is a lively conversation going on at Microsoft right now among several groups because at the end of the day, many of the people in our ecosystem currently act as facilitating partners for a company like Amazon. They unto themselves also create their own online store and by themselves act as facilitators for e-stores and competitors to Amazon. Every single one of those companies has come to us saying, We love this because you are taking the best of the online world, the access points, the visibility on inventory, all the way back to the original source – the supplier. However, you are driving it not in a way that downplays the channels but in a way that supports them. Now people can go to a store from their house, log on to a smart phone and check some stock, place the order, and have it drop shipped to their house. The formation of the multichannel commerce is a big topic across every industry, including the apparel industry. This is exactly where the virtual inventory cloud (VIC) is centered; it is at the middle of this huge industry dialogue. This pattern that you have mentioned, it is a big deal.
SM: And when you look at usability side of e-commerce or Web stores, vertical search is really a powerful concept. We have seen vertical search evolve from multiple directions, as if we have seen travel search becoming a big category before we knew horizontal search, which was Google. Now we see vertical search in travel, real estate, personals and job search. However, on the e-commerce side, there are already product search engines that are working in a comparison-shopping engine that go across various verticals, and they have created their own taxonomies. It is not there yet from the point of view of streamlining the supply chain to the extent you have streamlined your automotive industry. I think e-commerce will gain a huge leg up if this kind of taxonomy standardization happens across the various different industries. That will make it easier for all e-commerce companies to offer vertical search on their sites according to those taxonomies.
SS: Yes, that is exactly right. This is the other attractive, appealing thing about the VIC – the fact that it is a replicate-able process across industries.
SM: Right! What is your plan with GCommerce – is it to do this kind of taxonomy standardization across different verticals, or are you going to go into the automotive vertical?
SS: We certainly plan to bring the canonical approach, the canonized approach to data, which you just mentioned, but we also plan to bring the procurement model. You see, these patterns replicate themselves across verticals: the construction market, the plumbing and electrical markets, the medical device market, the marine industry, the industrial supply, industrial MRO, and so forth. About 15 standard industrial classification segments have a replicate-able situation; you see this pattern replicating repeatedly. To address this, there is Microsoft, GCommerce, and we have a large stakeholder that is joining this initiative in about 45 days. This is well aligned with Microsoft’s plan to push this body of work to verticals beyond the automotive aftermarket because we have companies like 3M and NGK and others with which we do business in other segments. We have existing relationships that we can leverage that allow us to be welcome when we move into other vertical markets. We are very excited that this thing is highly portable.
Now GCommerce unto itself is only 40 people; although we have an innovative approach, we do not have the muscle. However, Microsoft and the other entity, which is currently under a nondisclosure agreement, have the desire, the muscle and the platform to allow us to migrate across different vertical markets, so that is part of our playbook.
SM: Interesting! I am glad to have listened to you and learned about your industry, so thank you. In addition, we would appreciate if you have other suggestions for people who are knowledgeable in your industry and are leveraging cloud computing in ways that are worth understanding for us for this series, and we would definitely appreciate referrals.
SS: I will send you the link to the senior VP for the supply chain industry association because he may have a good amount of knowledge of SCOR model application references in the supply chain.
SM: Okay, that would be great.
SS: Let me let Jason circle back on the whole cloud thing; I think there are probably a couple of people who can provide you good insights on cloud adoption in the supply chain industry.
JP: Yes, thanks.
SS: Thanks very much for your time. It has been an invigorating discussion.
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