Increase Revenue with Faster Make vs Buy Analysis

Key Takeaways:

• It’s not always feasible to make a product or component in-house. Conversely, it is not necessarily cost-effective to purchase it from a supplier
• Conducting a make vs buy analysis quickly using AI & automated 3D-CAD analysis can facilitate faster and better decision-making on making and buying parts leading to winning new business

Challenges

Today’s quoting and estimating teams must do more with fewer resources in an effort to win more business. At the same time, they must meet ongoing customer expectations to respond to quote requests faster and meet challenging program launch deadlines. However, time and resource constraints still persist.

On average, metal fabricators and injection molders can take more than three days to respond to an RFQ, which can significantly diminish their ability to win. Being able to quickly analyze and assess the RFQ package is critical. Part of that analysis often includes evaluating whether to make or buy the parts or components that make up the bill of material (BOM).

Many companies still rely on homegrown manual tools like Excel spreadsheets. They can be useful, but they tend to slow down the process, diminish collaboration and standardization, and are most helpful when costing well-known and familiar parts. Once the parts become more complex, unfamiliar, or push capability boundaries, it becomes important to weigh whether to make, buy, or, in some cases, not quote the job.

Leaders must ensure their teams conduct make vs. buy analysis quickly and methodically. A delay of just one day can result in a competitor winning the business. Some studies indicate that quoting within three days is the sweet spot for winning the bid. Of course, this depends on many factors, including the part complexity, the urgency of the request, and the industry requesting it.

How can quoting professionals respond quickly while also having confidence that margins are protected? 

Make vs Buy Solutions To Consider

Not all make vs buy analysis solutions are the same. It is best to look for a comprehensive one that can be integrated easily, is user-friendly, and provides a level of expert support. Here are a few more considerations:

• Automate make vs buy analysis, leveraging AI-powered insights that estimate parts directly from geometry within 3D-CAD
• Evaluate make vs buy faster, and simulate “what if” scenarios to more clearly understand the financial implications and lead times involved in making a product in-house vs outsourcing it to external suppliers
• Use advanced cost models in conjunction with AI-powered insights to generate precise cost estimates
• Streamline the cost estimation process with 3D CAD Geometry Analysis, Bulk Costing Analysis, and PLM Integration-Based Analysis
• Analyze direct and indirect costs, tooling costs, impact of tight tolerancing on cycle time, supplier capabilities, and geographical considerations
• Leverage should cost estimates in supplier negotiations to get the best pricing and terms
• Weigh cost, carbon, and design for manufacturability (DFM) simultaneously

It’s sometimes helpful to go back and evaluate the standard RFQ and make vs. buy review process to evaluate technical and business decisions. These can include:

• Strategic Alignment: Does it fit within our product and company vision? Does producing this part fit with our long-term goals? Does it give us a strategic competitive advantage? Balancing short-term gains with long-term strategy is crucial. Companies need to ensure that their decisions align with their overall strategic goals and core competencies.
• Capabilities: Do we actually have the knowledge and skills to make this part? Do we have the ability to make this part? Is this customer or part important to the company’s future growth? Do we have suppliers that can reliably support this part or product with our quality and cost expectations? For instance, a Tier One supplier might receive an RFQ containing 10 individual machine parts. However, they realize that they can only make eight of those parts and have to outsource two to a Tier Two supplier. They need to respond quickly, or they might lose out on the bid. In order to accelerate their quoting time, the Tier One supplier needs to pinpoint Tier Two suppliers that can make those two parts as well as provide pricing for them in order to generate their quote. aPriori provides Regional Data Libraries for 89 global regions to quickly identify preferred suppliers based on a number of factors, including region and pricing. It also fosters stronger, more strategic supplier partnerships that, in some cases, can fast-track quotes or even lead to Zero RFQs, which also accelerate the quoting process, increase bid wins, and grow revenue.
• Capacity: Do we have the machine time capacity and/or labor resources to produce it? Do we have the machine time capacity to take on this job/program? Do we need to add additional shifts, operators, or machines to execute? If we go with external suppliers, can we get pricing from them quickly so that we don’t lose out on a bid due to quoting delays? Manufacturers must be able to quickly access external suppliers’ capabilities and pricing. Waiting on external suppliers (who also maybe waiting on their own external suppliers for pricing before quoting you) can lead to significant RFQ delays and loss of potential revenue. In-house production can reduce dependency on external suppliers and streamline production, but it might also require significant lead time to set up.
• Business Case Justification: What is the compelling reason for making it in-house vs outsourcing it? Profit margins? Competition? Intellectual property concerns? Is there a strategic goal that supports make vs. buy? For example, procuring the part from a supplier might be more expensive upfront. However, if it is for a strategic customer that can provide a higher volume of business down the road, it might make sense to outsource now to retain that customer for future revenue growth.

Benefits 

1. Quote faster and win more business since AI-driven insights give you a “first to quote” advantage                                                                             
   Read how Soucy reduced quoting time from 8 hours to 1 hour with aPriori
2. Achieve higher profit margins with more accurate and favorable pricing by leveraging AI-powered sourcing insights and automated quoting
   See how Thompson Aero saved 40% on the top 50 most expensive machined parts with aPriori
3. Streamline make vs buy decision-making via a faster, more informed appraisal of cost, manufacturability, and supplier capabilities               
   Discover how Eaton used AI and aPriori to cut design time by 87%
4. Accelerate time to market with shorter quoting processes, faster supplier response times, and more competitive pricing                                   
   Hear how Flex automated quoting and significantly reduced lead times
5. Improve overall efficiencies and workflows, especially if quoting software is collaborative across product development to fast-track quoting
   Watch Sylwia Lambert of TE Connectivity explain how aPriori helped them cut a supplier’s energy cost increase by half and foster greater collaboration

Realizing Faster Quoting Times = Increasing Revenue 

With a make vs. buy analysis, you can realize faster quoting times, streamline operations, secure more wins, and increase revenue growth. Want to learn more about how you can achieve “first to quote” and drive more revenue? Contact us to schedule a meeting and demo.