Cost Estimation in Product Development

Are you aware of the hidden costs in your product's raw material? : : Accurately calculating raw material costs is a cornerstone of should-cost modeling. By effectively identifying the materials required, determining the cost per unit, and accounting for potential waste and additional costs like handling and transportation, you can develop a comprehensive and reliable cost model. Key Parameters for Should Cost Process in Material Calculation: # Raw Material Identification: ·  Material type and grade ·  Material source/origin # Material Quantity: · Required quantity (per unit or batch) · Packaging units # Material Cost per Unit: · Supplier quotes · Market prices · Historical data · Discounts and bulk pricing # Material Waste or Loss: · Scrap/waste factor ·  Defects and rejections # Handling and Storage Costs: ·  Material handling · Storage costs (rent, insurance, utilities) · Inventory management # Freight and Transportation: ·  Shipping costs · Delivery method (air, sea, road) ·  Customs and tariffs # Lead Time and Order Frequency: · Lead time variations · Order volume # Supplier Terms and Conditions: · Payment terms · Return and warranty policies · Exchange Rates (For Imported Materials) # Material Substitution and Alternatives: · Substitute materials ·  Material optimization # Environmental and Regulatory Factors: · Recycling or sustainability initiatives · Regulatory compliance # Operational Overheads Related to Materials: · Processing costs · Energy costs ------------------------------------------------------------------------------------- # Ask Yourself: -> Did you consider the net weight and gross weight calculation properly? -> Did you consider scrap weight and scrap cost in your estimation? -> Do you have access to the global raw material index and recent material price database? -> Have you asked your supplier about the raw material cost per kg as well as the scrap cost per kg? -> Do you consider Manufacturing overhead (MOH) and inventory cost (raw materials)? -> What about the scrap cost percentage based on different commodities? -> Did you optimize material through strip layout, nesting, cavity, and other techniques? -> What’s your strategy when the supplier asks for material cost increases due to market fluctuations? -> Did you consider the volume/batch/MOQ impact, as well as regional cost impact, in your calculations? -> Did you consider any coating and primary requirements in the raw material stage? -> Commodity-Specific Considerations, etc.

CAPEX estimation for low maturity technology projects is challenging, particularly when we talk about new equipment. Yet, we still need to be able to get fairly accurate figures to justify the viability of the technology and secure funding for its development. How to do it? Here is what we usually do for hydrogen and carbon capture projects. 1. Define the Project Scope Start by clearly outlining all project boundary, objectives and deliverables. Identify every cost elements required for full scale implementation, from engineering and design to construction and commissioning, while distinguishing between one-off investments and those that can be standardised. 2. Develop the first-of-a-kind CAPEX Estimate • Detailed Bottom-Up Analysis: Break down the project into its individual components, accounting for bespoke engineering, pilot testing, specialized installations, and comprehensive project management. • Risk and Contingency: Due to the innovative nature and inherent uncertainties of FOAK projects, incorporate generous contingencies to cover design modifications, unforeseen challenges, and regulatory uncertainties. • Documentation: Maintain thorough records of assumptions and decisions made during this phase, as these will inform future projects. 3. Estimate to the nth-of-a-kind estimate with learning curves Leverage the insights from the FOAK phase to isolate repeatable cost elements. With each subsequent build, learning curves drive efficiencies: • Standardize Processes: As you replicate the project, streamline designs and processes. • Realize Efficiency Gains: Experience leads to better vendor relationships and operational refinements, translating into significant cost reductions for repeatable components. • Adjust Estimates: Update your cost models to reflect these improvements, using your own or reported learning curves, ensuring more accurate and lower capital expenditure projections for future projects. 4. Implement Continuous Improvement Regularly revisit and refine both FOAK and NOAK estimates. As more operational data becomes available, adjust your assumptions and conduct sensitivity analyses to maintain a robust, realistic capex projection. How do you estimate CAPEX for your technology? #Innovation #research #hydrogen #carboncapture #science #scientist #chemicalengineering

Cost Accuracy of FS vs FEED vs DED The accuracy of cost estimates varies depending on the phase of the project, from the initial feasibility study to the detailed engineering design (DED). Each phase involves different levels of detail and certainty, which impacts the precision of the cost estimates. Here's an overview of the expected accuracy for each phase: 1. **Feasibility Study** - **Purpose**: To assess the viability of a project before significant resources are committed. - **Detail Level**: Low. Rough estimates based on preliminary data and assumptions. - **Accuracy Range**: Typically -30% to +50%. - **Methods**: Conceptual estimating techniques, analogous estimates, parametric models, or expert judgment. - **Considerations**: High level of uncertainty due to limited information. Includes rough order-of-magnitude (ROM) estimates. 2. **Front-End Engineering Design (FEED)** - **Purpose**: To refine project scope, define major components, and develop a more precise budget. - **Detail Level**: Moderate to high. More detailed than feasibility, but not as comprehensive as DED. - **Accuracy Range**: Typically -15% to +30%. - **Methods**: Detailed quantity take-offs, preliminary design specifications, vendor quotes, and more accurate cost databases. - **Considerations**: Includes preliminary engineering and design work, risk assessments, and early procurement planning. 3. **Detailed Engineering Design (DED)** - **Purpose**: To finalize all project designs, specifications, and procurement plans. - **Detail Level**: High. Comprehensive and detailed engineering and design. - **Accuracy Range**: Typically -5% to +15%. - **Methods**: Detailed engineering drawings, complete material take-offs, finalized vendor and subcontractor quotes, and detailed cost databases. - **Considerations**: Most precise phase with minimized uncertainties, incorporating all finalized details of the project. Best Practices to Enhance Accuracy: 1. **Data Quality and Detail**: Use high-quality data and detailed designs at each phase to improve accuracy. 2. **Experience and Expertise**: Leverage the experience of project managers, engineers, and cost estimators. 3. **Historical Data**: Utilize historical project data to inform estimates and validate assumptions. 4. **Contingency Planning**: Include appropriate contingency allowances to manage unforeseen changes. 5. **Regular Reviews**: Continuously update and refine estimates as more information becomes available. 6. **Software Tools**: Employ specialized cost estimation software to enhance precision and manage complex data. By following these practices, you can ensure that your cost estimates are as accurate and reliable as possible, providing a solid foundation for successful project management and execution. #ProjectManagement #CostEstimation #Project

As a former Solution Architect, I believe FinOps can be much more proactive - the rise of #ShiftingLeft proves there is a need for cost management early on in the software lifecycle. We just published our Cost-Aware Product Decisions Insights article (https://lnkd.in/e5NbwSpd) on having cost considerations in the initial product design and early deployment, rather than reactively looking at waste. 🖍 Product design phase: introduce cost/benefit analysis to understand the cost drivers, but also look at the value that product might bring. Think about what success looks like and how to measure it, which helps in setting unit metrics early on. 🏗 Build: once you have the product requirements, treat cost as a non-functional requirement. Architecting with cost in mind and make well-documented trade-offs. Involving the FinOps team in this stage helps in creating an accurate cost estimation, but also in bringing best practices and efficiency techniques. ⚙ Operate: designing and architecting will always include some assumptions. - by setting governance & policies, reporting and analysis before even deploying, you have the guardrails and data points needed to adapt your environment early on, avoiding a shock bill in the end. Really keen to get your opinion, ideas, experience on this topic! Great teamwork with the amazing Vasilio M., Rob Martin and Amber Gregorio!

We were told by people who'd actually done this: "$800K–$1M, minimum." We launched for $250K. The cost to build has collapsed. Here's what changed. When my co-founders and I walked into a potential 3PL partner's office, the first question was: "Who's the IT guy?" We looked at each other. It's all of us. That moment kind of summarizes how we built Milieu. We're not talking about a simple product: Physical goods. Lab workflows. Personalization. Consumer software. Complex internal tooling. Regulatory compliance. We have been told on 5 distinct occasions by experienced CPG founders and VCs - "There's no way you're doing this for less than $800K–$1M, minimum." They were not wrong about the complexity, just the price tag - because in 2026 there's so much sh*t you used to have to outsource that you just don't anymore. Here's how the math actually ended up working out: Engineering / Software Old playbook: - Hire a full stack team - Contract out API work - Pay for DevOps Budget: $300–400K What we did: -Coded it ourselves with AI copilots -Two technical co-founders -Some contract help, a lot of late nights Actual cost: ~$40K Ops (fulfillment, logistics, physical product) Old playbook: -Pay for enterprise SaaS/tools -Work with multiple contract manufacturers -Contract a product designer Budget: $150–200K What we did: -Built internal tooling with AI (single platform perfect for our needs) -Partnered strategically — outsourced testing to trusted lab -Invested in minimal product filling/prototyping tools -Lab and HQ in Ann Arbor, MI (cheap state to distribute and manufacture out of) Actual cost: ~$30K Brand / Content / Growth Old playbook: -Retain an agency -Hire a brand lead -Pay for photo shoots, copywriters, designers Budget: $120–150K What we did: -Strategized in-house -Designed our own products and packaging -Wrote our own copy -Used AI to speed up iteration Actual cost: ~$20K Everything else (product tooling, legal, compliance) -Automated what we could -Good templates, methodical setup -Contractor help where judgment mattered Actual cost: ~$80K All in: ~$237,195.12 to launch. in 2026, "build" is way more accessible than people think this is a crazy time to be alive

Cost Evaluation Techniques 🧮 1. Zero-Based Costing (ZBC) A method where each cost element is justified from scratch (“zero base”) rather than using historical prices or vendor quotes. Purpose: To identify what a product should cost based on its fundamental materials, labor, overheads, and profit. Use Case: Negotiating with suppliers; cost transparency analysis; design-to-cost projects. 💡 2. Should-Be Cost (SBC) / Should-Cost Analysis Estimates what a product should cost if produced efficiently, considering realistic input costs, manufacturing processes, and logistics. Purpose: Helps buyers understand supplier pricing structures and negotiate better deals. Use Case: Strategic sourcing, supplier benchmarking, and value engineering. 💰 3. Total Cost of Ownership (TCO) Evaluates the total cost incurred over the product’s entire lifecycle—not just the purchase price. Components Include: Purchase cost Transportation & logistics Installation & commissioning Maintenance & operation Downtime & disposal costs Use Case: Evaluating long-term value, particularly for capital goods and complex systems. 🚢 4. Landed Cost Approach Calculates the total cost of a product once it arrives at the buyer’s location. Includes: Purchase price + transportation + insurance + customs duties + taxes + handling charges. Use Case: Import/export decision-making; supplier comparisons across regions. ⚙️ 5. Activity-Based Costing (ABC) Assigns costs to products/services based on the activities required to produce them. Purpose: Identifies high-cost activities and inefficiencies in the procurement process. Use Case: Indirect cost analysis; process optimization. 📈 6. Life Cycle Costing (LCC) Similar to TCO, but includes environmental and end-of-life costs. Use Case: Sustainability-oriented procurement and long-term investment analysis. 📊 7. Parametric Cost Estimation Uses mathematical models or historical data to estimate costs based on key parameters (e.g., weight, size, power). Use Case: Early-stage cost estimation for new designs or unproven suppliers. 🧩 8. Value Analysis / Value Engineering (VA/VE) Examines functions of a product or service to improve value by reducing cost without compromising quality. Use Case: Collaborative supplier development and continuous improvement initiatives. 🧾 9. Target Costing Begins with a desired market price and profit margin to determine the maximum allowable cost for production. Use Case: Cost planning during product design and supplier collaboration. 🌍 10. Cost Benchmarking Compares supplier or internal costs with industry standards, peers, or market averages. Use Case: Price validation, supplier performance evaluation. 📦 11. Clean Sheet Costing A detailed breakdown of costs built from the ground up—material, labor, overhead, logistics, and profit Use Case: Advanced negotiations and supplier transparency discussions.

Estimating costing in projects is a key part of project cost management. It involves forecasting how much money will be required to complete project activities. Here’s a breakdown of how it’s done, including the types, tools, and techniques used: 🔹 1. Cost Estimating – Definition Cost estimating is the process of developing an approximation of the monetary resources needed to complete project activities. It includes direct and indirect costs, such as: Labor Materials Equipment Services Facilities Overheads Contingency reserves 🔹 2. Types of Cost Estimates Estimate Type Description Accuracy Range Used When Rough Order of Magnitude (ROM) Broad estimate for feasibility phase -25% to +75% Early project phases Budget Estimate More refined, used for funding requests -10% to +25% Planning phase Definitive Estimate Most accurate, used for baselines and control -5% to +10% Execution/Pre-construction 🔹 3. Common Cost Estimating Techniques A. Analogous Estimating (Top-Down) Based on historical data from similar projects. Fast but less accurate. ✅ Example: Last bridge project cost $1.2M, so estimate similar cost. B. Parametric Estimating Uses mathematical models based on historical data and variables. ✅ Example: $50 per meter of cable × 1,000 meters = $50,000. C. Bottom-Up Estimating Estimates each activity or work package and sums them up. Most accurate but time-consuming. ✅ Example: Labor (300 hrs × $40/hr) + Materials ($5,000) + Equipment ($2,000). D. Three-Point Estimating Considers uncertainty with three estimates: Optimistic (O), Most likely (M), Pessimistic (P) Expected Cost (PERT) = (O + 4M + P) / 6 ✅ Example: ($10K + 4×$12K + $15K) / 6 = $12.17K E. Expert Judgment Use the knowledge of experienced professionals or SMEs. ✅ Often used in combination with other methods. F. Reserve Analysis Adds contingency for identified risks and management reserve for unknowns. ✅ Example: Add 10% of total cost for contingency. 🔹 4. Outputs of Cost Estimating Process Cost estimates Basis of estimates (assumptions, methodology) Project documents updates (e.g. risk register, schedule) 🔹 5. Tools & Software Microsoft Project, Primavera P6 Spreadsheets (Excel) Cost estimating software like CostX, RSMeans, or specialized ERP tools Would you like an example of a cost estimate worksheet or a template for your type of projects (e.g. construction, electrical, hydraulic)? #costing #estimating

Cost Estimating 🔹 What is Cost Estimating? Predicting project cost from scope + drawings + specs + market data. Used for: Tendering | Budgeting | Cost Control. Golden rule: realistic, defendable, measurable + market-based. 🔹 Levels of Accuracy: Conceptual (-25%/+40%) – Feasibility Preliminary (-15%/+20%) – Budget approval Detailed (-5%/+10%) – Tender/BOQ Control (based on actual BOQ/contracts) – Payments 🔹 Components of an Estimate: 1. Direct costs (labour, materials, plant) 2. Indirect costs (site + head office overheads) 3. Profit & Risk (margin + contingencies) 🔹 Step-by-Step Process: 1. Understand the scope 2. Quantity Take-Off (QTO) 3. Build unit rates  Unit Rate = Materials + Labour + Plant + OH + Profit 4. Add preliminaries 5. Include risk/contingencies (5–10%) 6. Review & benchmark 🔹 Quick Example: Blockwork 200 m² → 109 SAR/m² → Total = 21,800 SAR 🔹 Common Junior Mistakes: ❌ Ignoring wastage ❌ Overlooking site conditions ❌ Using “market rates” with no breakdown ❌ Forgetting preliminaries ❌ Copy-pasting old rates 🔹 Pro Tips: ✅ Keep a rate build-up sheet ✅ Build your own rate database ✅ Cross-check against cost/m² benchmarks ✅ Never submit without risk allowance ✅ Accuracy matters more than being the cheapest #QuantitySurveying #CostEstimating #BOQ

Should-cost methodology is emerging as one of the most reliable solutions to help #upstream players address their current challenges, providing the granular cost transparency needed to deal with the changing landscape. So how does it work? After breaking down the total cost of a project, product, or service into granular components and assessing the #cost drivers for each, companies can determine the reasonable should-cost of a service or product based on its constituent elements. Compared to traditional solutions (which limit the benchmark to a finite number of past projects), should-cost can estimate the costs associated with any combination of design, geographic footprint, and commercial agreement. Initially developed, fine-tuned, and deployed at scale in the automotive sector, the #shouldcost methodology uses bottom-up modeling of all supply chain costs through a four-step approach: ➡️Step 1: Analyzing the design choices and 2D or 3D drawings of the project to derive a bill of quantities for raw and bulk materials. ➡️Step 2: Mapping the end-to-end value chain to identify all the manufacturing steps required to produce each component. ➡️Step 3: Costing the required quantities and value chains to calculate direct costs, leveraging proprietary databases and productivity models tailored to each country, technology, and sector. ➡️Step 4: Completing the bottom-up should-cost calculations to define should-cost components, including all elements of suppliers’ cost structures. Through its flexible, unbiased, and fact-based methodology, a should-cost analysis can, therefore, provide up-to-date, end-to-end transparency on the entire supply chain cost structure for an upstream project’s tenancy in common (TIC) investment. To illustrate, we performed a deep dive should-cost analysis for #LNG tanks, providing full transparency on key cost drivers for further negotiation with the supplier. This analysis enabled a fact-based negotiation with the supplier and led to an 8% cost reduction on the final negotiated price compared to the initial bid. #capitalexcellence #mckinsey #lngtanks #oilandgas #procurement #projectmanagement #labor #materials

Hardware isn’t easy, but innovation never is. The road to hardware is undeniably tough, and in the end, it’s up to you to decide if the impact is worth the journey. Newcomers often dive in with the same questions: 🔘 How long will it take? 🔘 How much will it cost? 🔘 What challenges should I expect? There’s no simple, one-size-fits-all answer. The truth is far from linear—it’s complex, winding, and full of unexpected hurdles. Here’s the reality:  🔩 Development Time: 1–2 years to hit the shelves. Building hardware isn’t a sprint; it’s a marathon. From concept to production, every phase demands meticulous planning and execution.  - ⚒️ Prototyping: Iterating on designs, testing functionality, and validating concepts can take 6–12 months alone.   - ⚙️ Manufacturing readiness: Moving from a prototype to a production-ready model requires tooling, testing, and refining processes—another several months.   - 🧰 Supply chain coordination: Securing components, materials, and factory capacity can introduce further delays, especially with global disruptions.     ❇️ Bottom line: If you’re rushing to market, you’re likely to cut corners, and with hardware, mistakes are costly.  🗜️ Engineering Costs: $50K to $1M+ upfront.   Think of hardware development as a massive upfront investment—it’s not something you can bootstrap lightly.  - 📐✏️ Design and prototyping: Industrial design, mechanical engineering, and electronics development can burn through budgets fast.   - 🪛 Tooling: Injection molds and other production tools can cost hundreds of thousands on their own.   - 🧪 Testing and iterations: Each round of prototyping adds costs, and failure isn’t optional—it’s inevitable.   - 🫂 Team expertise: Specialists in design, engineering, and manufacturing aren’t cheap, but they’re essential.  ❇️ The truth: Your budget isn’t just for the device—it’s for the process of getting it right.  Hardware requires grit, time, and resources. But for those who persist, the rewards are more than worth it.  #HardTech #HardwareInnovation #hardware