By Sramana Mitra and guest author Shaloo Shalini
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.