Performance and Perception Expectations

Do not confuse this exercise with cataloguing performance and perception expectations (see Technique 30), which are solution-specific performance characteristics, such as candle bum time (target = 32 hours), or PC battery life (target = 6 hours). Outcome expectations are solution-neutral and reside at a higher level they are JTBD-specific desires, such as maximize duration of illumination (using any solution), or maximize operating time (in whatever way possible). 

Customers have three types of expectations—outcome, performance, and perception. Outcome expectations (see Technique 2), are specific to the/oZ the customer wants to get done. Performance and perception expectations,... 

With many products and services, design occurs at the subsystem level where many target components and processes interact to create the final solution. Thus, when you re defining performance and perception expectations, you need to agree on which part of the solution—target or final—is the focus. 

It s important to identify the customers for your solution by type—each will have different performance and perception expectations. As we mentioned earlier, customers fall into three general categories ... 

Typically, performance and perception expectations fall into five categories ease of use, timeliness, cost, options, and certainty, which refers to a series of quality measures such as reliability, maintainability, and so on. 

For example, Exhibit 30.1 shows end user performance and perception expectations for a Voice Over Internet Protocol (VOIP) service that allows people to make phone calls via the Internet. 

Customer attributes are synonymous with performance and perception expectations, so see Technique 30 to help with forming the front end of your axiomatic design activity. 

Customer attributes (CAs) can be collected in any number of ways. The key to know is that in axiomatic design, performance and perception expectations are equivalent to CAs, and they are what customers expect from a specific product or service. In other words, CAs come into play when you have a specific solution in mind, and you need to design it in the best way. 

Ideal Solution Elements (ISEs) are the features or functions that your innovation must have to meet customer expectations (for more information, see Performance and Perception Expectations, Technique 30). 

The association matrix helps you transform ISEs into new and innovative design concepts that meet the performance and perception expectations for your solution. It does this by pairing each ISE with every other ISE, which may bring to mind associations that were not evident before. 

Translate your innovation s performance and perception expectations into ISEs brief, concise phrases that describe a particular feature or function customers will expect your product or service to have. Note that ISEs should not be descriptions of the solution (e.g., long battery life), but instead should be conceptual (e.g., renewable power) so you have room for creativity. 

Use Paired Comparison Analysis when you need to compare either more upstream innovation ideas or more downstream design concepts. This technique is especially helpful when you don t have objective data regarding how different ideas could meet your customers outcome expectations (see Technique 2), or when you re uncertain about how different design concepts could meet customer performance and perception expectations (see Technique 30). 

If you want a more rigorous method of comparing multiple design concepts against performance and perception expectations, use a Pugh Matrix (Technique 36). 

Each alternative concept is compared to the baseline datum relative to several evaluation criteria, in this case, solution-level performance and perception expectations. Each evaluation criterion becomes a row in the Pugh Matrix. When using the Pugh Matrix to evaluate initial innovation ideas relative to some job to be done, the list of evaluation criteria are synonymous... 

To undertake robust design, you ll definitely need help from an experienced engineer or statistician familiar with this approach to testing and analysis. You ll also need to know how to apply several other techniques in this book including Performance and Perception Expectations (Technique 30), Axiomatic Design (Technique 31), Design FMEA (Technique 40), and Design of Experiments (Technique 50). 

Robust design starts with conceptual system, design, during which you define the ideal performance for your innovation, and make a list of measurable system features that are critical to the customer. You may have already done this using Performance and Perception Expectations (Technique 30). For our skin patch example, the ideal design will consistently dispense a dose of 1.0 mg/hr 0.2, regardless of patient fat content, skin condition, or other environmental factors. 

Even when it s not a life-or-death situation, variation leads to customer dissatisfaction and the inability to reliably meet performance and perception expectations (see Technique 30). As you near the completion of your innovative solution design, you can use MSA to identify and correct measurement system error, resulting in a higher quality, more reliable design. To be successful with MSA, you will need some experience with statistics. 

List the customer-driven outputs across the top of the C E Matrix (Exhibit 54. i). The outputs should be synonymous with the customers performance and perception expectations (see Technique 30 for more information). Underneath each output, rank it on a scale of 1 (less important to the customer) to 10 (more important). If it takes too long to get consensus, use 1, 5, and 9 for the rankings to give the outputs more relative separation. 

For more on customer types, see Performance and Perception Expectations (Technique 30). 

Exhibit 30.1 Performance and Perception Expectations. Exhibit 33.1 Morphological Matrix. 

In reality, business success requires focus on more than just performance and perception expectations, which are related to the features and functionality of specific offerings (solution specific). It s also critical— especially if you want to innovate—to understand outcome expectations, which are less concrete and related to the jobs customers need to get done (solution neutral). For instance, if illuminating the darkness is the job to be done, then doing this with ease and convenience is an outcome expectation. 

Don t confuse solution-specific performance and perception expectations with solution-neutral outcome expectations, or you ll end up in... 

Exhibit I.l shows the difference between performance and perception expectations on the one hand, and outcome expectations on the other. It s necessary to fully address both types of expectations to be successful at innovation. 

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