Technology/Product Function/Market Matrices can be tightly integrated into companies’ quality function deployment or QFD or Six Sigma methodologies. A typical phased approach to QFD based planning is shown in the “Four Phases of QFD Analysis” figure.
Phase 1 of this 4-phase approach is product planning. Customer requirements are typically matrixed against the technical requirements. In other words “what we need” against “how will do it”. We saw above that it’s often important to match not only customer requirements, but be thinking about the Customer Benefit or Product Feature/Function. Adding a column for Customer Benefit or Product Feature/Function to the Customer Requirements column on the left side of the Product Planning matric enables linkage to Sales and Marketing materials and efforts. An even more sophisticated and insightful approach is to use three columns: (1) customer requirements, (2) customer features, and (3) the Desirability Function Curve shape. An example of these three columns is shown in the “Relating Customer Requirements to Benefits via Desirability Functions” figure.
The column showing the desirability function is extremely important especially when we think back to a technology maturity curve. Customer requirements are often put as minimum or target. In fact what the customer is going to buy is based on their perceived value as being plateaued, linear, increasing, or exponential. Knowing which of these five curve shapes applies to the customer’s perceived value helps tremendously in determining which technology is going to best meet the product or service requirement. If only a little change is needed in the customer requirement and the customer’s Desirability Function Curve shape is only slightly higher or flat, then an incremental technology approach is most appropriate. On the other hand if there is significant customer benefit to increasing the customer requirement, or the Desirability Function Curve is bent, then next generation or breakthrough technology are the appropriate ones to invest in (especially when one applies principles of strategic intent versus strategic planning).
In order to give the elements of QFD a strategic perspective Experience Curves are often utilized. Experience Curves for cost are fairly robust across many industries. Three examples are shown in the “Experience Curves” figure. Technical strategies to achieve a roughly 80% slope in price reduction are a good planning tool. These curves can be applied to personnel as well as products as shown in the “Planning for Personnel Cost Reduction” figure. Developing technical strategies to improve the productivity of personnel, especially in service industries, is an important strategic planning element.
However, as practiced at Alcoa, also taking into account the theoretical limits of materials and processes is very valuable in the context of technology planning. The theoretical limit sets realistic or at least likely upper bounds on the advancement of any specific product feature, or lower bounds on the cost reductions available.
The recent work in cyber physical systems / machine learning tools must also be considered when using Experience Curves to predict the future for strategic planning. The curves can be disrupted by deep neural network tools that offer significant advantage in the process space over modeling methods requiring less extensive and less specialized computation.