Computer based process for strategy evaluation and optimization based on customer desired outcomes and predictive metrics

A computer implemented method for finding an optimal solution that will satisfy strategic personal and business decisions related to a selected process, comprising the following steps:

• (a) storing data obtained from conducting interviews of a statistically representative sample of individual customers from a plurality of customer sets in connection with specific processes, said data comprising a plurality of desired outcomes from said customer sets, said desired outcomes having predetermined prioritized ratings, each of said desired outcomes defining a benefit of value, said desired outcomes free from any solution or specification, each of said desired outcomes remaining stable over time, each of said desired outcomes having an associated importance factor and an associated satisfaction factor, said satisfaction factor indicating the degree to which a corresponding desired outcome has been achieved, said data including a plurality of predictive metrics, each of said predictive metrics having a corresponding relationship with each of said desired outcomes, said predictive metrics comprising measurable parameters which predict the satisfaction of said desired outcomes, each of said predictive metrics assigned scaled indicator for each of said desired outcomes, said scaled indicators representing the degree to which each predictive metric satisfies a corresponding particular customer desired outcome;
• (b) selecting a specific process to be evaluated for optimization in accordance with said data;
• (c) selecting a plurality of customer sets for evaluation of said selected process;
• (d) weighting the importance of said selected customer sets by assigning each of said selected customer sets a weighting value;
• (e) ranking said desired outcomes associated with said selected process and said selected and weighted customer sets, whereby said desired outcome ranking is dependent upon said customer set weighting values and said importance and satisfaction factors such that desired outcomes identified as important yet unsatisfied are red higher than desired outcomes identified as unimportant or satisfied;
• (f) prioritizing said predictive metrics in terms of the degree to which said predictive metrics predict the satisfaction of said desired outcomes associated with said selected customer sets and said selected process, whereby those predictive metrics which predict satisfaction of said ranked desired outcomes are quantified and prioritized;
• (g) defining a plurality of process specific strategic options, each of said strategic options designed to satisfy said customer desired outcomes;
• (h) quantifying the degree to which each of said strategic options satisfy said customer desired outcomes;
• and
• (i) presenting the quantified strategic to allow the user to determine which of said strategic options best predict satisfaction of each of said desired outcomes.

A computer implemented method for evaluating and optimizing business strategies in connection with a data storage device containing data obtained from conducting interviews of a statistically representative sample of individual customers from a plurality of said discrete customer sets, whereby desired outcomes, identifying benefits that each customer set values, are elicited and stored in said data storage device in discrete files corresponding to said customer sets, each of said desired outcomes having an assigned importance factor and an assigned satisfaction factor, said desired outcomes having predetermined prioritized ratings, said desired outcomes free from any solution or specification, each of said desired outcomes remaining stable over time, said data storage device further including predictive metrics for each of said desired outcomes identified by each of said customer sets, said predictive metrics comprising measurable parameters for satisfying said desired outcomes, each of said predictive metrics assigned scaled indicators for each of said desired outcomes, said scaled indicators representing the degree to which a predictive metric predicts satisfaction of a particular customer desired outcome;

• said method comprising the following steps:
• (a) selecting a plurality of customer sets for analysis;
• (b) assigning weighting values to said selected customer sets thereby positively or negatively weighting the influence of each of said selected customer sets;
• (c) ranking said desired outcomes in terms of importance and satisfaction whereby desired outcomes identified as important yet unsatisfied are ranked high while desired outcomes identified as unimportant or satisfied are ranked low, said rating being dependent upon said customer set weighting;
• (d) prioritizing said predictive metrics, said prioritization dependent upon said cumulative ranking of desired outcomes and dependent upon said predictive metric scaled indicators whereby the predictive metrics which predict satisfaction of high ranked desired outcomes are assigned a high priority while the predictive metrics which predict satisfaction of low ranked dashed outcomes are assigned a low priority;
• (e) displaying a list of said predictive metrics prioritized in terms of normalized importance relative to said ranked desired outcomes;
• (f) defining a plurality of strategic options;
• (g) evaluating each of said defined strategic options in terms of the degree to which each defined strategic options satisfies said desired outcomes;
• and
• (h) presenting the evaluated strategic options to allow the user to determine which od said strategic options best predict satisfaction of each of said desired outcomes.