DEMO: Automated And Scalable Quoting For Suppliers

Hello everyone, and welcome to my session, Quoting for Suppliers. My name is Matt Roy, and I am the manager of the North American Expert Services Team at aPriori. I lead a team of consultants that work closely with their clients to ensure success in value generation with the aPriori tool through various business and technical activities.This product demonstration will consist of a brief presentation and a demo lasting 10-15 minutes long.

Manufacturing Quoting Software for Suppliers

Why should you use aPriori to quote in the first place? We’re going to go through what a typical quoting workflow with aPriori may look like. We’ll then flip over to aPriori and our aP Analytics tool for a brief demonstration. And then after that, we’ll wrap it up with how this use case can be further improved. So that first question, why use aPriori to quote? Quoting is a paramount function within a supplier’s sales process. You need to ensure products are quoted intelligently to ensure profitability. Now, traditionally, this has been either done by hand by experts in that area of manufacturing or via home grown tools, most often Excel-based, from my experience. There’s no element of consistency or accuracy to the quoting of components. We somewhat forgo fidelity across these quotes. With aPriori, we can greatly streamline the workflow of folks in a quoting capacity leveraging cost estimating software.

Throughout this demonstration, you’ll be able to have a better idea of how aPriori can be a crucial tool to your manufacturing business’s success by standardizing the quoting process. Since aPriori runs off a code-based and removes potential subjectivity, the results are repeatable. The same component costed on different days by different people result in the same answer. This is, of course, if assumptions are persistent and maintained, such as material costs, production costs, raw materials, supply chain details, etc.. The way that aPriori does this is it leverages the component’s geometry to determine what is required in order to manufacture the component and interprets the implications as such, including times and costs. There are multiple flavors of reporting available through aPriori inherently. You can run Excel-based reports straight from the UI or use our web-based business intelligence tool, aP Analytics.

The ultimate goal for using this reporting tool is to understand the whole scope of what you’re quoting. Oftentimes, you’re not quoting single components, but large RFQs or bid packages. With this enhanced efficiency, you can expect to see increases in throughput, consistency in quality, and as a result, reduction in cost incurred as well, not only for the goods that we’re manufacturing for our OEMs, but also in the time that we save in the process of quoting itself.

Manufacturing Cost Estimating

This slide goes through some of the more discrete challenges and potential benefits that aPriori can provide in the quoting use case. So in addition to what I had previously spoken to on the last slide, these are a bit more formal. Some of what we see with challenges are; accurate estimates and accurate quotes requires a lot of manufacturing expertise, including shop floor experience, which is hard to come by. We also see challenges around access to data that seems to be a roadblock for a lot of people, and lack of consideration of manufacturability and equipment type.

Where aPriori can help bridge some of these challenges is that our solution allows for more personnel access. We level the playing field by including that manufacturing expertise in aPriori’s manufacturing estimating software . It allows you to become a strategic partner because we can provide this manufacturability feedback and cost very quickly, sometimes in as quick as 30 seconds per costing event, and we can enable suppliers to get involved earlier and mitigate potential delays in production. We can use tools available to us from the aPriori suite, such as aP Pro, we can use a tool called aP Generate, which allows us to automatically generate cost for our components that are of interest based on certain criteria, check into PLM, into a particular file directory, etc. And then finally, we can use aP Analytics to digest all of that information in real-time and report out in a meaningful manner that allows us to make more informed business decisions and ultimately, increase profit margins.

Customer Quotes Workflow Case Study

What does a typical quoting workflow look like within aPriori? First, of course, we need all of our parts in a central location or file directory. From there, we can load our parts into aPriori through whatever means is most applicable for your use case. This could either be loading the parts in one by one using our bulk costing tool, or aP Generate. The main idea here is just to get the parts into aPriori and cost them appropriately with the most relevant inputs and assumptions. From there, we can export this data from our costing events into aP Analytics. And finally, we can either use the numerous out-of-the-box reports we have in aP Analytics or we can create ad hoc reports, which allows the end user flexibility to determine which fields and data from aPriori, which we want to share.

With that said, I’m going to jump into a brief demonstration of this workflow. I’m going to launch aPriori. So I have aPriori up right now. And what we’re going to do here… And I have already gone ahead and costed this part previously to save some time. But the main idea here is that this is a stock machine component. It’s a relatively simple stock machining component, a flat plate. We need to set some inputs as a result of us wanting to have a cost for this component. We need to set the process group, so you can see that I’ve set this to stock machining. We need to set a VPE or digital factory, which is a representation of where the part is manufactured within the scope of the world. For example, if you would like to assume this part to be manufactured in China, India or Mexico, you could change that assumption here in the virtual production environment to replicate the region within the world that you are interested in assuming the manufacturing of this component. From there, we need to set our material. In this case, I’m going with aluminum 6061, but you would wanna set the material that is of interest for you on this particular component.

Finally, our most high level input that we require is volume and batch size. This is going to have a pretty large and substantial impact to components that are done by a hard tool processing. Think of plastic molding, think of progressive die or transfer die in sheet metal, die casting, forging. Any manufacturing process that requires us to invest at some point or another in tooling that would enable the creation of the component itself.

Now, once that’s complete, you can go ahead and click the cost button here. Wait for this to cost. And while it’s doing that, I’ll talk through a little bit about the information that aPriori presents to us. We get various cost information in our cost summary. We can see what the breakdown is for raw material costs, labor, and otherwise, we could go into our part details tab if we’re interested, and we can consume a lot more discrete information about the explicit processes that we’re using, along with their labor rates, direct overhead rates, the discrete cycle times for each line item and so forth. Once we complete our costing, we’ll go ahead and save our component, make sure that we maintain that record. The save is complete. And then what I do is I go ahead and create a rollup. I’ve already gone ahead and done this and included about five parts. When you create a rollup, it’s a container of information that allows us to aggregate all the parts in a quote package or bid package in a meaningful manner. It allows us to group the parts together and enable the export of this data to our cost insight reporting platform to allow us to consume this data that we’ve since provided to ourselves. In order to do so, it’s very straight forward. All you would do is go to File, New Rollup, you’d give it a name, identify the scenario name, click Okay, and go for it. Again, I’ve already done this for ease of demonstration.

Now, once you have this completed, you need to create the export cadence for this report. And I’m not gonna go through that here, but you do that through aP Analytics. Now, what I will go through is what it looks like after we’ve exported the data. So I have a report here that I’ve named “Package Report” and this is an ad hoc report that I created. Now, if you recall, a couple of moments ago, I mentioned that aP Analytics has either out-of-the-box reports that are shipped with the tool, or you have the option to create ad hoc reports, which affords our end users a bit more flexibility. In this case, I have opted to create an ad hoc report to summarize the high-level costing outputs for this analysis. Depending on what you’re looking for, there might be an out-of-the-box report that accommodates your needs, but in this case, I just chose an ad hoc report. You can see in this table that there’s a line item for each one of those discrete components that was in the rollup, there are five total.

We can also see, I’ve reported out here on the scenarios annual volume, the total plan volume based on its production life, what the variable cost might be, direct and labor, for example, direct overhead, that is, the scenario piece part cost, which includes a couple other additional parameters, and then the fully burden cost, which includes any amortized investment as related to hard tooling. So you’ll see for our injection molding exercise part, our scenario, fully burden cost increases because there’s investment associated with it. And then the last call finally is that investment broken out so that we may understand better what that looks like.

How Manufacturing Companies Can Automate Zero RFQ

So at the beginning, I mentioned how can this use case be improved? It seems pretty efficient as it is. You load your part to an aPriori, you cost them, you organize that information into a logical rollup or container, export that to cost insight reporting, run reports, consume the data and potentially share with the OEMs that you’re quoting for. Now, how can we improve this process? Well, we have this concept that has been deployed to various other customers called zero RFQ. Call it what you would like, but the idea here in our zero RFQ approach is that we’re eliminating some of the churn that’s associated with the quoting process. So like I said, quoting with aPriori is great, but there’s more efficient and value-add manner in which we can engage with the OEM through zero RFQ.

What if this process was automated and seamless, OEM and supplier and lock step and agreed-upon approaches in generating costs that’s mutually beneficial? This is zero RFQ. When an OEM and suppliers are at odds, negotiation can be time-consuming, and therefore we incur quite a bit of additional cost of the overall process. Using our RFQ relationship and building that up with your OEMs, this could be mutually beneficial. OEMs get parts at a fair price, the suppliers make a certain percentage of profit, and each side is encouraged to engage in continuous improvement to lower costs and maintain margins.

So the ask here is, if this is of interest, work with your aPriori customer services representative or your customer success manager to be provided with more detailed content on this approach. And through the concept of RFQ, products end up costing less while margin health for both sides are adequately maintained. And further more, collaboration is absolutely paramount to maintaining a successful business on either side of the deal, regardless if you’re an OEM or a supplier.