VOICES: Jeremy Holt, Strategic Advisor at CADDi - Design World

Originally featured on Design World

Sponsored by CADDi. In this VOICES interview, Design World spoke to Jeremy Holt, strategic advisor at CADDi, to learn how the right software helps companies save costs throughout design, development and production, by modernizing their systems and ensuring the right data is available at the right time.

Design World: Tell us a bit about your background and your role at CADDi.

Jeremy Holt: I’m a former automotive and vehicle industry supplier executive. I ran several different companies focused on engineering, transmission manufacturing and component manufacturing, in every form from startup to private to publicly owned. My entire career has focused on producing highly engineered products, some of which have complex assemblies or go into complex assemblies, such as powertrains in the automotive world.

I have now moved into doing consulting work for clients, and CADDi is a key client for me in the AI software space. I previously ran a technical software business at Ricardo, the engineering consultancy, that did engineering simulation. I bring that manufacturing technology and industry experience into CADDi to help them deploy their software more effectively.

What aspects of CADDi resonate with your experience designing, developing and manufacturing engineered products for the automotive space?

The CADDi software is purpose-designed for highly engineered products. It applies upstream for designing, developing and producing new products or managing legacy products, including the aftermarket. Also compelling is the speed and insight that you can get from data that already exists within the organization which, in my experience, is often very time- and resource-intensive to access and leverage in a manual environment where you’re asking people to go and find data from different systems.

What CADDi can do is connect the dots between those dissimilar systems, and legacy or longtail data, so that you can bring it to the surface, gain insights and make good decisions. Not slowly by adding work to people’s to-do list, but instantly by leveraging the data yourself without bothering engineers or other people to accumulate that information and insight for you.

What opportunities do you see in aftermarket and legacy product line management?

The relevance is greatest where data sits stagnant. It might be in a drawing format, or maybe it was never digitized but is lost somewhere, and to go find that data is very difficult. This means in the aftermarket, you may end up with duplication, or opportunities for consolidation are undiscovered. There might be information, parts and tooling out there that you don’t know already exists and identifying parts the company has already designed, tooled and qualified avoids paying for that work twice. Designing a new part with backward compatibility to earlier service parts is a real opportunity.

For example, transmission manufacturers who have been making transmissions for 30 years have a lot of parts, with a lot of service parts and possibly several design changes along the way. With CADDi, you can dive into that data, and with the right questions can find actionable insights and save time, work, tooling investment and labor investment by leveraging that existing data.

Cost is a constant focus in manufactured products. How can an AI data platform help achieve costing goals?

On costing, you can bring all of that data to the surface and do more accurate costing faster. Connect the design, development and product data with commercial data from dissimilar systems: costing, pricing and actual production data. Together, that might tell you can make 100 parts an hour when you thought you could make 200, and perpetuate erroneous costing. In many companies, the costing system has a formula, a model. That model could be wrong, and you might be providing bad quotes by using that model and not realizing that it doesn’t work when you get to the manufacturing floor. The CADDi system, as it relates to cost, can bring that shop-floor production data into the data set with the costing data and allow you to adjust the models to meet the reality of making similar parts. More informed, more accurate and faster costing is one of the key benefits of the CADDi software.

Some software platforms find certain capabilities hard to implement. How does CADDi approach that challenge, and how does it work with current PLM or CAD systems?

That’s one of the other compelling value propositions for CADDi: it’s very easy to get started. The general approach is to start with a manageable data set that you can put into the CADDi environment, and use that to prove a use case in a manageable deployment. They run a pilot study very quickly, generally at no significant cost, and prove that you can find new insights even in a limited data set. That value can then be expanded by adding more information from different environments and systems.

A larger data set surfaces more of these connections and points to the next problem worth solving. You can then continue expanding the systems that can access information through the CADDi software, so that you can have a progressive deployment with very early wins during the process, and compelling future opportunities.

I think the Subaru case study example is a good one. They started with one department using the software, and after less than one year — only 50 weeks — 50 departments were using the CADDi software with expanded data and amplified value. CADDi assigns an engineer to help deploy the software, which is how companies get early wins.

For engineering and enterprise leaders who know they need to modernize upstream operations but don’t know where to start, what’s the first step? What should they expect early versus later?

The first step is easy, because you don’t have to restructure any data or system to work with CADDi. Simply provide access to your data. CADDi locates that data and maps the relationships between dissimilar systems: ERP, PLM, development spreadsheets, documents, production data and quality reports.

The downstream manufacturing can then have access to all that data without restructuring anything. They can see into your existing system of record and provide opportunities to attain insights from all of that information by allowing the manufacturing operations to see across that data and use it to make better decisions about implementing their production. In fact, many people across the organization can start to leverage information they couldn’t see before.

Early in the deployment, put questions to your own data. Ask what a part cost the last three times you bought it, which suppliers quoted it and what the quality records came back with. Cross-functional associates can explore the data and find things that they didn’t know, or discover insights that are useful for decision making, allowing deeper probing into company pain points or opportunities.

One example might be that if you can look at maintenance records and downtime records, you can tie a specific part to the machine problem it causes, and fix the cause instead of the symptom. Downstream, you can expect to get higher productivity, lower scrap rates and simpler changeovers because you can choose the right parts to change over from. These benefits can be optimized and monetized for improved financial performance from the manufacturing operation, as well as putting pressure on upstream processes to improve design for manufacturing.

For engineering and manufacturing, most of a part’s cost is determined in design, long before a supplier is chosen. The teams that manage cost best are the ones whose engineers can see what the company has already qualified and paid for while the design is still open. That is the window where value analysis and value engineering (VA/VE) can impact the bottom line. Once a part is released, the options narrow and most of the savings are already committed. Read the white paper Value Analysis & Value Engineering for Manufacturing: The Challenges and Solutions of Implementation. Yushiro Kato, co-founder and CEO at CADDi offers a related perspective in a recent Design World interview.

CADDi is a global manufacturing technology company driven by the vision to accelerate physical innovation tenfold. Headquartered in Chicago and Tokyo, the company was founded in 2017 by industry veterans Yushiro Kato and Aki Kobashi, formerly of McKinsey and Apple. CADDi currently serves manufacturing businesses in more than 20 countries, including many of the largest publicly traded companies in Japan and the United States. To learn more, visit caddi.com or follow the conversation on LinkedIn.