Job Shop Cost Estimation: Strategies for Scalable and Agile Quotation

Introduction

Job shop manufacturing involves producing custom, low-volume parts based on specific customer orders instead of high-volume production runs. Accurate cost estimation is critical for job shops to profitably fulfill unique, specialized orders without wasting time and materials. This article provides strategies to help job shops develop accurate quotes and improve profitability when taking on new custom orders.

Key factors include fully understanding all costs involved, estimating expenses as precisely as possible, and implementing processes to continuously enhance quoting accuracy. With diligent cost analysis and estimation, job shops can thrive on custom work without losing money on orders that end up costing more than anticipated.

Understand All Costs

Accurately estimating costs is critical for job shop profitability. When quoting a job, it’s important to understand all the costs involved:

Direct Material Costs

• Cost of raw materials or components needed to manufacture the product
• Can be a significant portion of total costs  
• Important to accurately estimate required quantities and current pricing

Direct Labor Costs

• Wages paid to employees directly involved in production
• Depends on labor rates and estimated production time
• Factor in any overtime or shift differentials that may apply

Overhead Costs

• Indirect costs like rent, utilities, equipment maintenance, etc.
• Allocated to each job based on an overhead rate
• Overhead rate should be periodically updated based on actual overhead costs

Estimate Accurately

Accurate job shop cost estimation is critical for competitiveness and profitability. Here are some strategies to improve accuracy:

Utilize historical data

Review records of similar past jobs to estimate costs. Track materials, labor hours, equipment usage, and other expenses. Analyze trends over time. Maintain a database of past jobs with detailed cost breakdowns that can be referenced for future quotes.

Factor in waste, scrap, defects

Account for expected waste materials, defective parts, and production errors. Add a percentage buffer based on past experience. Track scrap and rework rates over time and adjust estimates accordingly. Implement quality control measures to minimize defects.

Include all steps

Break down the job into every step and component. Estimate costs for raw materials, processing, finishing, assembly, inspection, packing, and overhead. Create detailed routings and bills of materials. Collaborate with production staff to ensure all steps are captured.

Standardize methods

Create templates, checklists, and procedures to ensure estimators capture all costs. Update standard rates regularly. Develop a standardized quoting process that is followed for every job. Provide training to estimators on standardized methods.

Add contingencies

Build in extra percentage buffers for unknowns and risks. Consult production managers to determine appropriate contingency amounts. Consider factors such as part complexity, material lead times, machine downtime, and employee absences. Adjust contingencies based on risk level.

Validate estimates

Have multiple estimators independently quote complex jobs. Compare results and adjust. Review estimates before bidding. Conduct internal peer reviews or get input from production staff. Implement checks and balances and an approval process before submitting quotes.

Track actuals

Record actual costs incurred after job completion. Compare to the original estimate to improve future quoting. Analyze variances to understand root causes. Continuously update estimates based on actual data. Implement a formal “quote vs actual” review process.

Practices for scalable and agile quotation

Automate quoting processes

• Implement quoting software that integrates with CAD/CAM systems and ERP platforms
• Set up product configurators and rules-based algorithms to automatically generate quotes
• Use automated workflows to route quotes through review and approval steps
• Link quoting system with real-time production capacity and material availability data

Modularize quote components

• Break down quotes into standardized modules like materials, processing, finishing, etc.
• Create a library of common quote modules with pre-populated costs and cycle times
• Mix and match modules to quickly build custom quotes
• Continuously refine and expand the module library based on actual job data

Implement agile quoting methods

• Develop a backlog of quote requests and prioritize based on customer needs
• Assign cross-functional quoting teams to work on high-priority quotes
• Use daily stand-up meetings to review quote progress and roadblocks
• Deliver quotes to customers in small batches and incorporate their feedback
• Continuously improve the quoting process based on lessons learned

Leverage data analytics

• Capture and analyze data on quote win rates, profit margins, cost variances, etc.
• Use data analytics tools to identify trends and correlations (e.g. most profitable jobs)
• Develop predictive models to forecast quoting outcomes and costs
• Use data-driven insights to refine quoting strategies and target profitable opportunities

Foster collaboration and knowledge sharing

• Break down silos between sales, engineering and production teams
• Involve production staff early in the quoting process to validate estimates
• Share best practices and lessons learned across the organization
• Implement a knowledge management system to capture and reuse quoting expertise
• Provide regular training and coaching to improve estimating skills

Continuously improve

• Track quote performance metrics (e.g. win rate, margin, cycle time)
• Conduct regular “quote-to-cash” process reviews to identify improvement areas
• Set improvement goals and implement action plans
• Celebrate successes and recognize high-performing employees
• Benchmark quoting performance against industry peers

By implementing these strategies and practices, job shops can develop a scalable and agile quotation process that enables them to quickly respond to customer needs while maintaining accuracy and profitability. A standardized yet flexible quoting approach, combined with data-driven insights and continuous improvement, will help job shops thrive in today’s competitive manufacturing landscape.

Streamline Job Shop Quotation with CADDi Drawer

CADDi Drawer is a powerful tool that can significantly enhance job shops’ quotation processes by enabling quick searching and referencing of past similar drawings and associated data. As shown in the use case map, CADDi Drawer seamlessly integrates into the quotation phase, reducing time and effort required for accurate quotes.

Key features include:

• Auto-extraction of data from PDF drawings, making even handwritten drawings searchable
• Connecting quotation and supply-chain data to drawings via CSV files
• Robust keyword and patented similarity search capabilities

By implementing CADDi Drawer, job shops can:

• Save up to 80% of time spent on creating quotations by identifying optimal pricing based on historical data and past similar drawings
• Allocate more time to customer engagement, increasing revenue opportunities
• Consolidate siloed data and information to enhance knowledge transfer among individuals

In conclusion, CADDi Drawer streamlines quotation processes, reduces costs, and increases revenue for job shops. Its auto-scanning capabilities, data integration, and powerful search functions enable efficient and accurate quoting, positioning job shops for success in a competitive manufacturing landscape.

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