Effective quoting is about more than just pricing.
While price is a key factor, it’s only one part of a larger, strategic process that impacts profit margins, customer trust and long-term profitability.
Precise and timely quotes boost client confidence in a company’s ability to deliver on-time and on-budget. Slow or inaccurate quotes, meanwhile, can lead to lost business, strained relationships and reduced business revenue.
Three components are critical for high-quality quotes: Accuracy, speed and profitability. In this piece, we’ll break down the quoting process, offer best practices to improve quote processes and explore the growing roles of maintenance and technology in comprehensive quotes.
Understanding the manufacturing quoting process
A manufacturing quote is a document provided by manufacturers to clients that includes total manufacturing costs, projected timelines and itemized pricing.
Manufacturing quotes typically include:
- Material costs
- Labor costs
- Overhead costs
- Expected lead time
- Risk and contingency costs
Quoting is often complex because it depends on multiple factors, including client needs, manufacturing type and the current economic climate. For example, a quote for repeat production from a high-volume manufacturer will look different than one for a custom part produced by a specialized job shop.
It’s worth noting that manufacturing quotes are different than estimates. Think of estimates as educated guesses. Prospective clients reach out to manufacturers looking for a sense of what projects will cost from end-to-end. Based on a general intake form or informal meeting, the manufacturer produces an estimate.
If the client decides to move forward, the manufacturer creates a quote that contains in-depth pricing, labor and timeline data.
Estimates are not legal agreements. Once quotes are accepted and signed, they typically become legally binding.
Key inputs required for an accurate manufacturing quote
To build an accurate quote, teams need data. Higher-quality data yields better quotes—outdated, redundant or incorrect data can lead to pricing over- or under-estimations.
Key inputs required for an accurate manufacturing quote include:
- Engineering drawings and specifications
- Bill of materials (BOM) details
- Defined routing and manufacturing process steps
- Machine cycle time data
- Labor rates and skill requirements
- Setup and changeover times
- Scrap and yield assumptions
- Lead time constraints and scheduling limits
- Quality and compliance requirements
Missing inputs are the most common source of errors. For example, if quotes don’t account for lead time constraints, clients may be frustrated by a lack of progress, while manufacturers may face reduced profit margins.
How to calculate a manufacturing quote
The complexity of manufacturing quotes makes them well-suited to standardized calculation processes.
Four components are common in quote calculations:
Step 1: Material cost calculations
- Raw materials
- Expected waste and scrap volumes
Step 2: Labor cost calculations
- Direct labor
- Setup labor
- Indirect labor
Step 3: Machine and equipment cost calculations
- Run time
- Depreciation
- Energy consumption
Step 4: Overhead cost allocations
- Facility costs
- Maintenance
- Utilities
In addition to these steps, companies must also consider factors such as margins, markups, risk buffers and contingencies.
Consider a high-volume manufacturer producing a quote for a new client. The client needs 1,000 automotive parts produced on a tight timeline. If the quote only includes the cost to produce each part, companies risk breaking even, or operating at a loss. Markups ensure a profit, while additional quote costs should be built in as risk buffers or contingencies in the event of material shortages or sudden equipment failures.
The quote for this client would include the price of materials, labor and assembly for each part, plus any contingency and risk buffer fees. In addition, the quote should include a predicted timeline for manufacture and delivery.
Common challenges in the manufacturing quoting process
Several challenges are common in the manufacturing quoting process, such as:
- Incomplete or unclear customer requirements
- Inaccurate cost assumptions
- Underestimating labor or setup time
- Ignoring maintenance or downtime risks
- Manual spreadsheets and disconnected systems
- Long quote turnaround times
- Inconsistent pricing across sales teams
- Poor visibility into historical job data
How to improve quote accuracy
Accuracy is the core component of manufacturing quotes. If quote data is not accurate, both speed and profitability suffer. Correcting quotes takes additional time, and if errors slip through the cracks, companies may inadvertently undercharge for products or services.
To improve quote accuracy, follow these guidelines:
- Use historical job data and actuals
- Standardize cost assumptions
- Involve engineering and operations early
- Validate routing and cycle times
- Account for maintenance and reliability risks
- Regularly review quote values vs. actual performance
- Build continuous improvement through feedback loops
After every quote, it’s worth taking the time to identify any inaccuracies and implement processes that help improve accuracy for next time.
How to speed up the quoting process
Quote speed also matters. For example, if your company and a competitor offer similar products at a similar price point, closing the deal may come down to which business gets a quote to the customer first.
To speed up your quote process, consider:
- Standard quote templates
- Modular pricing structures
- Predefined routings for common jobs
- Automation and digital quoting tools
- Integrating ERP software, CMMS and job costing systems
- Reducing reworks through clearer request for quotation (RFQ) documents
- Enabling cross-functional collaboration between sales, engineering and operations teams
While it’s never a good idea to sacrifice accuracy for speed, creating standardized quote practices can help bolster both of these components.
The role of maintenance & asset reliability in accurate quoting
Maintenance and reliability data play a key role in the quoting process.
For example, reliability metrics such as mean time between failure (MTBF) and mean time to repair (MTTR) inform machine uptime assumptions, which in turn impacts profitability. If machines fail without warning, the results range from missed delivery commitments to cancelled contracts.
Industrial maintenance costs also fall under the banner of overhead in a quote, since maintenance may be required during production runs. Maintenance strategies, meanwhile, such as the development of predictive maintenance processes, can help reduce quote risk by increasing the likelihood that issues are identified and addressed before they disrupt production. In addition, reliability data can be used to improve lead time accuracy.
For manufacturers, the result is accurate quotes that are better aligned with actual production capacity.
Technology’s role in modern manufacturing quoting
Digital transformation drives the next generation of manufacturing quoting. Equipped with digitized records and the right technologies, manufacturers are better prepared to navigate evolving customer expectations.
Systems that support improved quoting include:
- Integrated enterprise resource planning (ERP) software
- Advanced manufacturing quoting software and configure, price, quote (CPQ) tools
- Connected CMMS solutions for equipment performance insights
- Improved analytics for margin tracking
- Enhanced solutions, such as digital twins and simulations for complex jobs
There’s also a shift underway toward AI-assisted cost estimation. While it’s important to keep humans in the loop to ensure accuracy and feasibility, AI-assisted tools offer the benefits of reduced manual effort and increased quote accuracy.
Measuring and improving quoting performance
So how do you measure and improve the success of quoting practices?
Start with metrics such as your quote-to-win ratio, quote turnaround time, margin accuracy (quoted vs. actual) and requote frequency. For example, if your quote turnaround time has historically averaged one week, but recent quotes have been taking two weeks or longer, it may be time to reassess current practices.
It’s also important to track customer feedback through emails, follow-up calls and surveys. Even if quoting processes went off without a hitch on your end, customers may have a different experience. The more you know about this experience, the better for your bottom line.
To improve quote performance over time, implement comprehensive key performance indicator (KPI) tracking. This helps identify processes that are working as intended and those that require adjustment, setting the stage for continuous improvement.
How ATS helps manufacturers improve quoting outcomes
ATS works with manufacturers to improve reliability by strengthening maintenance strategies, asset data quality and operational visibility.
This starts with strategies for predictive and preventive maintenance to help streamline operations. Common predictive maintenance cost savings include improved uptime estimations and fewer instances of unplanned downtime.
ATS also enables the capture of real-time asset reliability insights to drive data-driven decision making and provides comprehensive maintenance solutions that align operational processes with financial goals.
High-quality quotes are accurate, quick and profitable. ATS helps manufacturers strengthen maintenance strategies and asset reliability, so quotes reflect real production capacity. Let’s talk.
