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iRobot’s 4 Best Practices to Optimize Cost Estimation Software and Increase Profits

 | January 4, 2024

Key Takeaways:

  • Get a step-by-step overview of iRobot’s approach to maturing its cost estimation process
  • Discover best practices across the technology, process, and training/education to increase adoption 

The Full Article:

Consumer robotics company iRobot makes life easier in millions of homes daily with products including the autonomous Roomba vacuum cleaner. Growing competition is watering down the market and potentially commoditizing the Roomba. iRobot is responding by refocusing on profitability (lowering costs) and innovation. aPriori’s cost estimation software is a powerful lever that can help achieve better results.

Are Suppliers’ “Black Box” Estimates Accurate?

iRobot initially selected aPriori to provide cost modeling and estimation for new product introductions (NPI). iRobot’s early use of aPriori was “rocky” because its product cost estimates did not match the supplier quotes. It led iRobot cost engineers to ask, “Whose results are inaccurate – ours or the suppliers?” Eventually, they realized that aPriori was an underutilized resource.

iRobot had to identify their exact problems and goals before they could achieve results. As Ajay Verma, iRobot’s Sr. Cost Engineering Advisor aPriori System Owner, put it, “Many people think that when you get aPriori, you will get a calculator, and then say one plus one equals two. Instead, you need to define one and then add one to get two.” Once the iRobot team identified the right assumptions and cost data, they could determine appropriate should cost calculations to compare against supplier quotes.

First, iRobot needed to reassess how it would get accurate should cost data internally and compare that against detailed supplier quotes to conduct an apples-to-apples comparison. Then iRobot had to provide aPriori with the required data to support specific use cases. Additional manufacturing information from their suppliers, such as manufacturing processes, location, and other data, was necessary for the quoting process.

Initially, iRobot wasn’t sure that the time required to add manufacturing and other specifications to aPriori was worth the effort, or in their words, “Is the juice worth the squeeze?” By refocusing their efforts (the squeeze), including more detailed supplier and manufacturing information, the more accurate their results (the juice).

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Utilize cost estimation software for greater accuracy and increased profits

Cost Estimation Software Best Practices

A solution is only as good as the best practices supporting it. iRobot’s commitment to creating and applying best practices, using aPriori’s solution, helped them achieve full value.

#1 Customize aPriori to Your Specific Requirements and Challenges

Do you want to use aPriori for front-end innovation to define design specifications more clearly? Or will you apply aPriori to improve should cost accuracy for supplier negotiations? For should costing, you need to crack the supplier’s “black box” to understand their cost models and other areas where you may be charged more. For example, you might be charged a profit for an individual component and then charged again at the assembly level. As a result, you could be charged a double profit by the supplier, especially if you don’t understand their pricing structure. Then configure aPriori to reflect the manufacturing capabilities of key suppliers (down to the machine level if needed), using specialized digital factories for various suppliers. Then enhance training and software/calculations/database comprehension across the company. Leverage fact-based cost models to better understand suppliers’ quotes by gaining additional costing and operational information.

#2 Take a Bottom-Up Approach to Compare Cost Drivers

Instead of looking at the total cost without context (top-down), use a bottom-up approach (a list of all materials/services and associated costs). Then examine the cost drivers (cost outliers) that aPriori identifies in its analysis. Understand the variances in cost, including the type and age of the machine being used vs. one that is calculated on a new machine. Use this information to start a conversation with suppliers (e.g., “What type of machine are you using for X process?”).

aPriori builds its cost models using this approach and includes detailed factors, including material selection, manufacturing processes, batch size, annual volume, and targeted production costs (direct and indirect overhead) across nearly 90 regions.

Users can add this information into an aPriori digital factory and model different scenarios (e.g., cost changes based on design or material updates). As iRobot gained a better understanding of its suppliers’ capabilities, it was able to use aPriori’s digital factories to increase the accuracy of the should costs. Then they modified their negotiation strategy from total cost comparison to cost driver comparison.

#3 Leverage Your Data to Maximize Supplier Discussion and Negotiations

iRobot noticed a significant gap between their price and aPriori’s cost management model insights. Without specifying his findings but using the aPriori fact-based insights, Mr. Verna sat down with the supplier to discuss noticeable price gaps.

He learned how the supplier calculated machine rates and cycle times, validating that his assumptions were correct. He then presented his cost model to the supplier to determine if costs were correct and if they were within iRobot’s cost estimation.

Based on the discussion, iRobot saved nearly 10% during its first round of negotiations. Mr. Verna noted that each successive cost model entered in the aPriori software furthered cost accuracy. iRobot also optimized product development (challenging perceptions including iRobot’s R&D) and reduced cycle times thanks to cost modeling and subsequent negotiations.

For example, a supplier might take an outdated approach to determine the required clamp force for injection molding, potentially leading to higher costs. These costs are a result of inefficiencies in machine selection. However, aPriori accounts for such clamp force estimation errors. Consequently, more accurate machine selection based on factors like material injection pressure and nominal wall thickness can be made. Similarly, aPriori’s improved cooling time estimation accuracy considers a part’s wall thickness variations. The total cycle time and associated costs are more precisely calculated. A deeper understanding of the molding process spurs more substantive discussions with suppliers, optimizing the production process and achieving cost savings.

#4 Optimize Product Development

iRobot needed to determine how R&D and Product Development could work together to discuss and revisit assumptions and then optimize the Design to Cost (DtC) and Design to Value (DtV) of upcoming products. Getting them right helps reduce costs without compromising quality or value. aPriori’s cost estimating software accelerates the process and provides guidance to ask the right design, procurement, and cost questions. Only then will DtC and DtV project planning be optimized.

Scale Savings with Cost Modeling Insights

Maximizing aPriori not only enabled iRobot to accelerate their cost estimating but helped them gain:

  • Accurate, defensible cost models
  • Identifiable cost outliers to leverage in supplier negotiations
  • A streamlined, standardized, and repeatable cost estimation process
  • Enhanced collaboration and communication with key suppliers

iRobot is a prime example of why you should not expect your cost estimation software tools to be a 100%, out-of-the-box solution. As Mr. Costa aptly stated, “It’s like a plant that you are going to grow. You want to grow with it. It takes time and work but will really benefit your company.”

Is Identifying Design Costs Akin to Looking for a Needle in a Haystack?

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