Comparing Design-to-Cost and Design-to-Value

What is design to cost vs design to value? Find out in this compelling case study that’s designed to help you understand design to cost vs design to value, and how to explore design iterations to get the most from your product designs. Design to cost means designing a product to hit a target cost. Design to value means designing products that are focused on delivering value to the customer.

So how do you prioritize and combine these initiatives? Is that even possible? In this no-nonsense case study, we’ll show you how to use manufacturing simulation technology to make real time design iterations to achieve both design to cost and design to value initiatives.



Design to Cost Case Study

Matthew Hinshaw: Hello and welcome to design-to-cost versus design-to-value, a case study. My name is Matthew Hinshaw and I am a senior technical consultant here at aPriori. I work on the implementation team and I’ve worked with dozens of customers across a slew of use cases and industries during my time at aPriori. This presentation, as I mentioned, will focus on the concepts of design-to-cost and design-to-value. We’ll start with an introduction of these terms and some common examples of application. Then I will introduce our case study and walk through a number of design iterations that explore the relationship between design-to-cost and design-to-value.

Before we get started, why is this important? Why do these concepts matter? Well, roughly 80% of a product’s cost is determined during the early stages of the product design cycle. So applying these concepts early new product development is critical in impacting the eventual cost of a product and approaching these ideas once the product is already through those initial design stages could have a limited impact.

Let’s start with the concept of design-to-cost. The core concept behind design-to-cost is designing a product with a focus on hitting a specific target cost. There are many ways to reduce cost and increase profitability. This may include removing functionality or discarding expensive features. There are lots of examples of products that are designed with the intention of hitting a specific cost. Let’s say we’re designing a pop-up toaster. I can go on the Internet right now and purchase any number of pop-up toasters for, say, $30 or less. So if we’re designing a product that is going to be cost competitive in this crowded market of basic pop-up toasters, naturally, we have to aim for the lowest cost price point. This doesn’t mean we completely strip the product of any and all to the end user, but we may need to make trade-offs to remove or limit functionality in order to hit our target cost, such as you likely won’t be able to start this toaster from your phone. For that matter, phones and computer monitors can fall into this category as well. Well, there’s a huge breadth of phone and monitors in terms of price points and capabilities.

If we are designing these products for the low-cost end of the market, we will likely have to be very judicious about what features are included in order to stay cost competitive. Design-to-value, on the other hand, places the emphasis on features that add to customer value. Additionally, of course, we also want to remove features that are not adding customer value. Depending on the application, this could mean a decreased focus on lower cost. Let’s take the International Space Station, for example. Not to say that there is no focus on target cost, but for critical components that are keeping the astronauts on the ISS alive, I imagine there’s a much stronger priority put on product performance, reliability, and survivability of these key components in space. Performance motorsports is another good example. Now, I know there have been some changes recently with respect to budget caps and things like that, but similar to the ISS, the focus for these vehicles is on performance and the value each component adds towards winning races. So now that we’ve defined these two terms, let me introduce the case study for today through which we’ll explore these concepts.

In-House Manufacturing

Let’s talk for a second about in-house manufacturing. I’m sure for many people watching this video, many if not all of your companies have some sort of in-house capabilities. So while I don’t have access to a machine shop or weld booth or something like that, I do proudly have a bit of in-house manufacturing in my apartment in the form of this 3D printer. And as with anyone who has the pleasure of owning a 3D printer, I am constantly looking for new projects and applications for my printer. As a consultant at aPriori, I’m on the phone a lot with customers and naturally have a headset. As work from home became the norm during the pandemic, I realized I needed a place to hang my headset so that I wasn’t just throwing it on the desk when I wasn’t using it. To that end, I put my in-house manufacturing to good use and made the headset hanger you see here in the images. For our case study today, I would like to explore with you how we could bring this prototype headset hanger to market through the lenses of design-to-cost and design-to-value.

Before we get started with evaluating designs, first let’s define our design specifications. The overall product goal is to create an ultra low-cost headset hanger that easily attaches to most desks. With a lot of people working from home or working in a hybrid situation, we have a broad potential market and our product can help anyone struggling with limited desk space or wanting to organize their work. From a design parameter perspective, through some research of typical desks and headsets, we want to support any desk up to one inch in thickness, support headphones that are up to one kilogram in weight and one inch wide, and while many headset hangers on the market use an adhesive to attach to the desk, a critical design criteria for us is not using any adhesive to make it very easy for our end users to position, reposition, and move the hanger to another desk or table as needed. Finally, based on how crowded the headset hanger market is with competitor products, our price target for this product is $5.

Let’s start with our initial prototype design so we can get a sense of where we stand cost-wise right now. We’ll stay with 3D printing as our manufacturing process to model the initial manufacturing method. Based on our market research, we expect to make 10,000 of these per year, so when analyzing this product, we will assume 10,000 annual volume. For this SLS, or selective laser sintering version, we’re using Nylon 12 as our material as we determine through further analysis that this nylon satisfies our design weight capacity requirements. Let’s take a look at our initial iteration within aP Design. So here I have the CAD file loaded into aP Design, and I’ve costed the part so we can take a look at the results. So as you can see on the left-hand side, I’ve put in the inputs I was just discussing, additive manufacturing, polyamide 12 or Nylon 12, and an annual volume of 10,000. And by running this part in aP Design, we can get cost and manufacturability feedback. So we can see here that we don’t have any design guidance, aP Design isn’t picking up any Design for manufacturing or DFM risks or warnings we need to dig into for this manufacturing method. We can see things like the cycle time for the overall process, but really what we’re looking for down here is the breakdown of cost to get a baseline for where we are at the moment.

The DTC vs DTV Approach in Product Design

Let’s look at this from a Design to Cost or DTC perspective. If I go into the cost results, I can not only see overall cost, see we’re at almost $13 at the moment, I can see the breakdown too. And within our breakdown, we can see that material cost really dominates the cost of this part at the moment, which given we’re running an additive process, is typically relatively efficient around material, this makes sense to have a high material cost with respect to the rest of our costs overall. That being said, though, $12.72 is still very high compared to our ideal target cost of $5. So we’re starting from a point way above that target cost and indicates we need to do some more work to get to a design iteration that works and fits all of our criteria. Within design-to-cost or DTC which is also called the cost approach, and design-to-value or the DTV approach, we can further consider two methodologies while making our design decisions. We can make changes specifically to features on the design, or we can take a look from a manufacturing method perspective and likely design changes that are required as a result of changing our manufacturing method. With both of these throughout the process, we’ll use aPriori design to generate fact-based manufacturing costs. By seeing the cost and manufacturing implications of each action, we can know how to to make data driven decisions from the earliest moments in the design process.

Let’s start with the lens of design-to-cost or DTC. So again, here we are considering design changes with a focus specifically on hitting that $5 target cost. For our first design phase, let’s focus on changing the features of the design, and we’ll try to tackle some low hanging fruit. An easy change here is to reduce the thickness of the hanger, as well as the length of the legs that slide over and under the desk. Less material, of course, leads to lower material cost, as well as faster cycle times, as with selective laser sintering, you just have less motion of the head as you’re laying down material. All this leads to a lower total cost. We can keep all other parameters of the simulation the same, and again, run the part through aPriori design. Through this analysis, we could see a meaningful improvement in cost based on this design iteration from over $12 on the previous baseline, down to between $7 and $8 for this particular design. Again, though, this is not quite at our $5 price point that we’re trying to hit. Additionally, I can tell you some consumer insights from my initial prototyping: shortening the legs does reduce stability of the hanger sitting on the desk because of course there is no adhesive. So from a value approach, shortening the legs would get ruled out in the design-to-value or DTV process.

So I think we need to explore some additional possibilities through this design-to-cost or DTC lens. Let’s dig into a change in manufacturing method next. So here we are maintaining the original design with the longer legs and thicker hanger, but switching from additive manufacturing to injection molding to see if we can gain some cost optimization in this product development process. Now, there is an annual volume consideration here in terms of where the cutover is to move from something like additive manufacturing to a hard tooled process where you have that capital investment. This would come up naturally in your value analysis is you had a value engineering step in your process, but with aPriori we don’t need to wait for a review from value engineering. To figure out whether plastic molding would be more cost effective we just turn to aP Design again and see what this part looks like if we run it within plastic molding. That’s all that it takes to get new baseline metrics.

Material in Design to Cost

Now, I want to talk about material for a second. So previously we were running with Nylon 12, which was satisfying our material requirements. But if I take a look at nylon within this list of materials available, we get a sense of a relatively high unit cost in terms of the cost per mass. Whereas if I look at something like ABS, I get a much more competitive price that would potentially lead to a reduction in cost for my part. So for this simulation, I’m going to choose to run with ABS instead of Nylon 12 and see if we can get some cost savings through this change in material. Now, given we would need to run further analysis to make sure ABS as a material could support the weight requirement for our headset hanger. But let’s take a look at the cost results and we’ll see if the results here warrant digging in further. So now that I’ve run this as plastic molding, I get a number of important pieces of information from aP Design. In the design guidance section, I’m now getting design guidance on what I would need to change on my design in order to enable injection molding. So we can go in here to the details and start to look at what aP Design is giving us. So as we can imagine, the initial part was designed as an additive manufacturing part.

If we were moving over to plastic molding, we would, of course, need to put in draft angles so that the design can easily release from the mold during manufacturing. So this is expected, but we would, of course, need to make these changes. aP Design is also calling out radius issues. So here, if you’ve got a sharp edge, that means that you need a matching sharp edge in the mold. And that might be something we want to avoid in terms of stress concentration. So we might want to take a look at these as well from a redesign perspective if we’re going to go ahead with injection molding. And lastly, we have an entry here around material issue. So the thickness of the part, which wasn’t as big of an issue when we were running this through additive, is greater than recommended for ABS, through plastic molding. So if we want to take this path forward within running this part and manufacturing this part as a plastic molded part, we really may want to dig in further into a redesign to reduce the thickness, maybe add some stiffeners and approach this part from a different perspective, given some of this feedback. But let’s take a look at the cost implications, too see if it would even make sense to pursue that design decision.

If we go back over here to our cost results, we get some great insight into overall cost. So whereas previously our iteration, our first one was almost $13, the next one was closer to $8 per hanger, here we are well under our target cost. Another interesting piece to note is that the distribution of costs has changed. So whereas for the additive part, 60 percent of the material of the overall cost was locked into that material cost. Here, the driving factors are really labor and overhead, not necessarily material, because it’s a relatively small part and the material is less expensive than say for additive. So by running this simulation, we get an understanding of design guidance, we get an understanding of cost results. And from a lowest cost perspective, this looks like this could be a good path forward for this part. If we can keep that initial design, we likely need to make some changes to enable the injection molding manufacturing process, but we’re here under our target cost.

Addressing Design Issues in DTC Iterations

That being said, if we think a little bit further about the design, there are still some clear issues overall that we haven’t addressed through these DTC iterations. The largest issue I see is really in desk compatibility. Yes, this design technically fits a desk up to one inch, but the stability as your desk gets thinner is most definitely compromised. It would be worthwhile now to consider this design from the perspective of what features or value add to the end user and see what results you generate. So let’s dig in now to some design-to-value focused design iterations. So here we have a new design iteration that includes an additional hook. Many of our target consumers likely have multiple devices, even if they do not have multiple headsets. So a second hook may be value add for the customer stakeholders. It could also be used to hang the cord for their headset if they have a corded headset. For this simulation, we’re keeping the learnings from our last design-to-cost simulation and running the part as injection molding with a material of ABS, as that seems to be the most cost effective from our DTC and value engineering perspective. Let’s take a look at this part in aP Design. Once again, I’ve loaded in the new CAD file, set my inputs as I’ve done before, and we can take a look at the design guidance and the cost results.

So if we start in design guidance, we’re really getting a lot of the same information that were we to take this further, we still will need draft angles, consideration for radii. And of course, the material thickness issue is still a challenge and might even be slightly thicker here with the way this iteration went through. So certainly worth further consideration there. On the cost side, however, we get to some interesting results. Our previous iteration was right around 250 and this iteration is as well. As I talked about a second ago, for these injection molded parts, they’re relatively small, the material is not a major factor, and it’s really the processing time that leads to the final cost that we see that’s the major cost driver. So because the thickness of the part is roughly the same as it was before, the material cost is only increased slightly with the additional hook. The overall fully burdened cost has not changed significantly, certainly gone up a little bit, but not changed significantly because the overall processing, the time the part spends in the molding machine, etc, hasn’t changed significantly.

Adding Value to the User Through DTC

This is great insight. This is really good information we could take moving forward because in this iteration, we’ve added value to the user. There’s another feature on this part that brings more value than just the singular hanger that we had before, but we have not significantly increased cost. We’ve been able to increase value without that increase in cost, which is the goal of any number of value engineering initiatives. This is good insight we can hold on to and we can bring this with us as we think about some future iterations and how we can use this information to our advantage. Now, as we did with design-to-cost or DTC, we’ll take a look at a little bit more of a value approach to manufacturing for adding customer value into this design while trying to maintain the low cost. So in this instance, we are keeping the initial design, but changing the nature of the product and even potentially our target consumer. I propose here that we could create custom made hangers based on the customer’s specific headset and desk parameters. This might radically change our supply chain strategy, and is in line of what many manufacturing startups are doing today. In this customer value approach, we could go to the consumer, they could put in how thick that their desk is, how large their headset is and what they want to hang here. And then we could laser center parts out of aluminum and tumble deeper for a really nice finish. There are tradeoffs in this direct-to-consumer procurement strategy of course, especially as you get into product lifecycle management and limited re-use. But the bottom line is you can see how this technology enables us to quickly create hangers through optimization for each of our customers needs.

There are some cost tradeoffs of course associated with some design changes before we send these parts out. But unlike the previous designs, this customer value approach is really focused on customizability and visual appearance as means to give value to our end user. Of course, this all comes at a significantly higher cost compared to some of the plastic molding examples, a factor of 10x. We would likely need to perform further market research to understand if there’s a market for this kind of bracket at this price point and if it makes sense to take this further, because this really does change the nature of the kind of product we’re putting forward. Maybe it’s a good alternative for a custom-design startup, but it does not help with our overall goal of this low cost headset hanger. So where does this put us? We’ve looked at design-to-cost examples. We’ve looked at some design-to-value focused iterations. Are these two really mutually exclusive? There are some contrasting goals potentially, but let’s take a step back and look at what we’ve learned from these different iterations.

We saw from the design-to-cost focused iterations that we can, of course, reduce costs through shrinking the part footprint to reduce material used. But the largest reduction in cost came from the material change and switching to injection molding, which, as we saw, would likely require some design updates to make the design compatible with injection molding. From the design-to-value iterations, we saw how multiple hooks could add value, as could customizability of the hanger. However, the customizability of the hanger really speaks to a larger consistent problem with nearly all of these designs, which is the current design just doesn’t support multiple thicknesses of desks very well. With our target consumer likely encountering a variety of desk thicknesses, this feature would really add meaningful value to the product, but we need to be able to still hit our target cost.

aP Design Targets Product Cost from the Design Phase

Let’s see how we can bring all this feedback together in the design phase to hit our product cost target while still considering customer value. Enter iteration six. Here we are taking a meaningful jump forward in terms of functionality, where we add a thumbscrew and a cap feature to specifically support using this hanger on multiple desk thicknesses. In doing so, we also do away with the stability issues that kept the legs on the hanger itself so long, and we can shorten those up to remove unnecessary material and costs like we did in one of the design-to-cost or DTC iterations. Running this assembly in aP Design and ABS, including the thumbscrew component, which is likely an off-the-shelf purchase, we get to a cost just above our target cost. So here we have major improvement in value, but we have made the product more expensive as a result of bringing this additional value to the end user. Again, we kind of see this contrasting behavior between this design-to-cost focus/dtc and design-to-value focus, but let’s try to take this a step further and try to leverage some insight we can get from aP Design. Because we can run quick design iterations in aP Design, let’s try some alternate materials.

We know from our previous iterations and analysis that Nylon 12 is a suitable material for the weight requirement for the design, but we shied away from that because it looked like the material cost itself was significantly more expensive than ABS. But let’s run some iterations and let’s take a look at using Nylon 12 in our latest design iteration. When we run this, it turns out even though Nylon 12 material cost-wise is more expensive than ABS, the processing parameters are such that the cooling time is meaningfully shorter. So by switching to a more expensive material on a cost per mass perspective, overall, we are actually achieving cost reduction on the part. For small parts like this in injection molding, the cost is primarily driven by the processing time, not the material cost. We learned that from one of the design-to-value iterations. So the end result is a final product, design iteration seven, which has a cost significantly lower than our target cost, but still maintains the flexible desk thickness feature, which is adding value to the end user without compromising on cost.

So if we take a step back and look at the trajectory of this design, this is where we end up. We started with our initial prototype way above our target cost and worked through a number of design-to-cost/DTC focused and design-to-value focused iterations to understand how these decisions impacted the cost. We finally landed on a design that brings meaningful customer value above and beyond the initial design while still coming in well below the product target cost. We did that by considering the outputs of our previous iterations that had a narrower focus and brought these takeaways together to influence and impact the final design. This really brings us to the fundamental nature of design-to-cost and design-to-value. These activities are not mutually exclusive. They really fall on a spectrum.

aP Design lets you get cost and manufacturability feedback on new product designs as you work through the design process. So no matter where you fall on the spectrum, you can make data-informed decisions quickly as you reduce costs and add value. I hope this session was valuable and insightful and thank you for joining.


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