Electronic Thesis/Dissertation
 

A Generalized Approach to Measure and Predict Innovation Maturity Progression Aligned to Business Objectives

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The ability to manage transformative change is paramount to the success of an organization trying to accommodate the unique characteristics of continuous market disruptions. The rate of change the business environment must accommodate requires an approach that provides decision-makers with the ability to identify, forecast, and pick potential innovation alternatives that produce the greatest measured impact. The use of existing innovation maturity models provides limited insight, and industry practitioners lack a generalized means to validate the contextual correlation between innovation maturity progression and business outcomes. Knowing the overall maturity level of the process or capability alone will not provide the granularity needed to identify, assess, or suggest which innovations produce the greatest impact. The purpose of this quantitative study is to evaluate the critical attributes that drive innovation maturity progression.This research establishes an extended Innovation Maturity Model (IMMe) as a generalized framework to measure and predict an organization’s transformation by aligning and measuring innovation processes, capabilities, and activities in context to business outcomes. Additionally, statistically significant regressions explained which IMMe attributes and components were accountable for maturity progression. The ability to isolate the potential changes that have the greatest overall impact on the business enables decision makers with a tool to identify, account for, and adapt to evolving criterion.The IMMe consist of five components: innovation process, innovation portfolio, business and functional criterion, and a semantic model. The components of the IMMe provide a generalized mechanism to predict and measure innovation progression aligned specifically to business objectives and outcomes. Three industry environments were tested with the IMMe, and insights from these case studies show the model to be viable and useful in support of innovation management processes. The additional components of the IMMe provide the needed bridge to establish a definitive relationship and correlation between innovation maturity progression and business outcomes. The IMMe will help leaders and decision makers identify relationships between planned, predicted, and evolving criterion to hit an elusive moving target – continuous transformation.

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