Approximately 37% of all new product launches fail, making the understanding of why they fail imperative to reducing risk and improving organizational strategy. Products fail for many reasons due to factors like inadequate market analysis, product defects, high costs, and production problems. The seemingly endless amount of data points that must be captured and synthesized to attain the true voice of the customer (VOC) can be overwhelming and must drive every new product development decision to give it a solid platform to launch from.
Enter more contemporary business-process methods, such as Design for Six Sigma (DFSS), that systematically capture VOC data, optimize product design, and launch products to meet customer needs. DFSS consists of a stepwise approach where customer needs are built directly into product solutions based on research and statistics to facilitate continuous improvement for existing processes and to create new ones where none previously existed. This approach induces uncertainty for companies because measurement and improvement are no longer executed after a procedure is in place, and may appear to create additional overhead in the beginning. However, implementing DFSS at the start will increase the Six Sigma methodology’s effectiveness.
Many myths surround product development methodologies, DFSS included, which result in organizations hesitating to leverage the tool. First, DFSS does not replace a company’s current product development process, but instead augments it by instituting a series of statistical tools to quantitatively enhance decision making and results in an area historically considered more art than science. Second, DFSS is not the sole responsibility of design or engineering departments; the most effective new products are the result of cross-functional teams of customer research, design, engineering, supply chain, and manufacturing professionals that effectively balance all customer requirements. Further, DFSS is similar to the traditional DMAIC (Design, Measure, Analyze, Improve, Control) Six Sigma process, but different as DMAIC is reactive, detecting and resolving problems. DFSS is proactive, designing out problems before they occur. Last, there is no single dominant methodology for DFSS, which often complicates industry training and the communication needed to properly implement DFSS.
Why Design for Six Sigma?
DFSS is a systematic methodology for designing or redesigning new products that meet customer requirements while improving product profitability by delivering the right product, at the right time, and the right cost. The methodology centers around the idea that if you design Six Sigma quality into a product, customers will be satisfied and your company will benefit financially, increasing the probability that your new product will perform well in the market. Six Sigma tools are integrated at the outset of product development to achieve Six Sigma performance, a defect rate of 3.4 defects per million opportunities (DPMO), 99.9997% perfect in production. DFSS focuses heavily on customer analysis to design superior products, specifically the transition of customer needs to process requirements while minimizing defects, cost, and time. Typically, the DFSS methodology payoff is substantial and could produce a successful launch for a first product or prolong company survival.
1) Tailor Product Attributes to Customers Needs
Conventional design processes rely on a series of assumptions about product features that will sell. DFSS is different in that it asks the question “What will customers buy?” and summarizes the responses into a VOC. DFSS then identifies key customer needs before starting the product’s design, then prioritizes and translates the top customer needs into design requirements. These key customer design requirements are Critical-to-Quality characteristics (CTQs) – the select few measurable characteristics essential to the specific part of the product that must be within statistical control to guarantee customer satisfaction. When collaborating with cross-functional team members, supply chain professionals can leverage operations expertise and Quality Function Deployment (QFD) analysis to assist in translating the VOC into CTQs.
To further leverage the QFD analysis to develop disruptive products, project teams can follow on with a Kano Model to rank essential and differentiating product attributes, VOC Table (VOCT) to record customer needs and context to better understand both explicit and implicit customer requirements, and House of Quality (HOQ) Tool, to focus the organization on CTQs.
2) Use Statistical Analysis to Improve Design Concept Selection
A DFSS tool called the Pugh Concept Selection Methodology is a scoring matrix to select between alternative designs, which is executed most effectively when team members perform independently and then compare scoring results. The development of the criteria (usually 10 total) is critical to include supply chain team members, outside of design and engineering, to properly incorporate product criteria such as cost, assembly, and ease of transport. Supply chain also plays a vital role in providing an alternative view point in independently scoring and ranking design concept alternatives that consider criteria impacted by procurement, manufacturing, and distribution.
Often after a Pugh Matrix is completed to select a design a Concept, FEMA is typically conducted on the leading concepts. Supply chain, specifically manufacturing and quality professionals, can play a vital role in expediting Concept FEMAs by quickly building process maps and identifying potential failure modes. Typically, the overall highest-ranked design may be inferior on certain criteria, like cost for instance, and procurement team members can frequently improve select cost criteria in leading designs when involved early in product development.
3) Optimize the Product by Designing for “X”
Traditional product development completes a product design and then “throws it over the wall” either to procurement to quote with potential suppliers and manufacturing, or to a contract manufacturer to figure out how to build it. This approach leads to a limited number of suppliers able to quote a specific part or product as designed, increasing cost and manufacturing challenges due to expensive design change requests. Involvement of supply chain in the product development process to assist with Designing for X (DFx), manufacturing, assembly, and service can dramatically improve quality, lower cost, and reduce time to market.
There are many DFSS tools, such as Poka Yokes and Process Capability Studies, that can be utilized to design in quality to the assembly processes on day one. Poka Yokes, when implemented into the design effectively, prevent the improper assembly of products and prevent manufacturing processes, equipment, and tooling from being performed incorrectly. Supply chain teams are often in the best position to request, verify, and share with product development teams, suppliers’ available process capabilities, Cp, Cpk, and Cr, which can quickly be incorporated into product technical specifications.
Considering the overwhelming evidence that incorporating the DFSS methodology into a company’s product development process leads to more successful new products, why do more companies not implement DFSS? As with Six Sigma, even more so with DFSS, it does not produce immediate results and the statistical tools may be intimidating to teams newer to the Six Sigma management techniques. The DFSS methodology provides the supporting data to make decisions that are statistically founded and in a shorter amount of time, ultimately driving out cost while designing quality into products. DFSS offers proven tools, processes, and methodologies to enhance an organization’s existing product development practices. If properly implemented, DFSS can lead to superior product development effectiveness and to outperforming the competition.