{"id":7717,"date":"2020-02-21T09:50:06","date_gmt":"2020-02-21T09:50:06","guid":{"rendered":"https:\/\/www.pdsxchange.com\/?p=7717"},"modified":"2020-02-21T09:50:06","modified_gmt":"2020-02-21T09:50:06","slug":"scoring-uncertainty","status":"publish","type":"post","link":"https:\/\/www.frost.com\/events\/innovation\/scoring-uncertainty\/","title":{"rendered":"Scoring Uncertainty"},"content":{"rendered":"

By Ralph Morales III<\/strong>
\nHead of Innovation Practice<\/em>
\nSmartOrg, Inc.<\/p>\n

Scoring uncertainty in an innovation project is the first step to developing a validation plan to determine efficiently whether the innovation is viable and valuable.<\/p>\n

Developing a list of hypotheses<\/strong><\/p>\n

It begins with determining what questions have to be answered for the innovation project to be viable, valuable and ultimately successful.\u00a0 For each of those questions, there are two key factors:<\/p>\n

    \n
  1. How much or little do we know about that question at present?<\/li>\n
  2. How much impact on the project will the answer to that question have?<\/li>\n<\/ol>\n

    The interaction of these factors will determine whether the question is a matter of project viability or one of how much value the project can generate.<\/p>\n

    To help create a plan of action, each question should be reformulated as a hypothesis, a possible answer to the question that needs to be validated and verified.\u00a0 A hypothesis can be a true\/false proposition, a matter of degree (e.g., how big or how much), or a hybrid of the two.<\/p>\n

    The list of hypotheses should be as exhaustive as possible at this stage so that there\u2019s a high degree of confidence that all of the critical issues affecting the project have been identified.\u00a0 In the next phase, the hypotheses will be evaluated for their relative importance and priority.<\/p>\n

    Hypothesis Development<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
    Hypothesis<\/strong><\/td>\nIgnorance<\/strong><\/td>\nImpact<\/strong><\/td>\n<\/tr>\n
    Alpha<\/td>\n5<\/td>\n5<\/td>\n<\/tr>\n
    Bravo<\/td>\n1<\/td>\n2<\/td>\n<\/tr>\n
    Charlie<\/td>\n4<\/td>\n2<\/td>\n<\/tr>\n
    Delta<\/td>\n3<\/td>\n2<\/td>\n<\/tr>\n
    Echo<\/td>\n4<\/td>\n4<\/td>\n<\/tr>\n
    Foxtrot<\/td>\n3<\/td>\n9<\/td>\n<\/tr>\n
    Golf<\/td>\n7<\/td>\n10<\/td>\n<\/tr>\n
    Hotel<\/td>\n1<\/td>\n2<\/td>\n<\/tr>\n
    Indigo<\/td>\n4<\/td>\n3<\/td>\n<\/tr>\n
    Juliet<\/td>\n9<\/td>\n9<\/td>\n<\/tr>\n
    Kilo<\/td>\n3<\/td>\n9<\/td>\n<\/tr>\n
    Lima<\/td>\n6<\/td>\n1<\/td>\n<\/tr>\n
    Mike<\/td>\n6<\/td>\n9<\/td>\n<\/tr>\n
    November<\/td>\n2<\/td>\n7<\/td>\n<\/tr>\n
    Oscar<\/td>\n9<\/td>\n5<\/td>\n<\/tr>\n
    Papa<\/td>\n5<\/td>\n1<\/td>\n<\/tr>\n
    Quebec<\/td>\n10<\/td>\n7<\/td>\n<\/tr>\n
    Romeo<\/td>\n6<\/td>\n8<\/td>\n<\/tr>\n
    Sierra<\/td>\n3<\/td>\n7<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Assess each hypothesis for its impact and maturity<\/p>\n

    Plotting the hypotheses on a 4-box plot gives a visual representation of how they fall into different categories of importance and priority.<\/p>\n

    At the top right quadrant, the hypotheses with the greatest impact and greatest level of ignorance represent areas that might be hiding fatal flaws in the project. These are the Kill Shot hypotheses, and these speak to the viability of the project.<\/p>\n

    At the bottom right quadrant, the hypotheses represent the important deliverables of the project. The impact is great, but the level of ignorance is low. These hypotheses are about well-understood aspects of the project, the core of the project\u2019s value proposition.<\/p>\n

    At the top left quadrant, the hypotheses represent factors that can affect the value the project can yield or the path to reaching a successful result. They have to be explored, but their impact is limited enough that they won\u2019t kill the project.<\/p>\n

    In the lower left quadrant are hypotheses about areas that are low-impact and well-understood, and these need to be managed more than validated or verified. These areas can affect the value the project yields but not the viability of the project.<\/p>\n

    Hypothesis Assessment<\/strong><\/p>\n

    \"\"<\/p>\n

    Summarize the assessments<\/p>\n

    You can now assign the categories to your list of hypotheses.<\/p>\n

    Hypothesis Summary<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
    Hypothesis<\/td>\nIgnorance<\/td>\nImpact<\/td>\nType<\/td>\n<\/tr>\n
    Alpha<\/td>\n5<\/td>\n5<\/td>\nKillShot<\/td>\n<\/tr>\n
    Bravo<\/td>\n1<\/td>\n2<\/td>\nManageIt<\/td>\n<\/tr>\n
    Charlie<\/td>\n4<\/td>\n2<\/td>\nManageIt<\/td>\n<\/tr>\n
    Delta<\/td>\n3<\/td>\n2<\/td>\nManageIt<\/td>\n<\/tr>\n
    Echo<\/td>\n4<\/td>\n4<\/td>\nManageIt<\/td>\n<\/tr>\n
    Foxtrot<\/td>\n3<\/td>\n9<\/td>\nLearnMore<\/td>\n<\/tr>\n
    Golf<\/td>\n7<\/td>\n10<\/td>\nKillShot<\/td>\n<\/tr>\n
    Hotel<\/td>\n1<\/td>\n2<\/td>\nManageIt<\/td>\n<\/tr>\n
    Indigo<\/td>\n4<\/td>\n3<\/td>\nManageIt<\/td>\n<\/tr>\n
    Juliet<\/td>\n9<\/td>\n9<\/td>\nKillShot<\/td>\n<\/tr>\n
    Kilo<\/td>\n3<\/td>\n9<\/td>\nLearnMore<\/td>\n<\/tr>\n
    Lima<\/td>\n6<\/td>\n1<\/td>\nImportantDeliverable<\/td>\n<\/tr>\n
    Mike<\/td>\n6<\/td>\n9<\/td>\nKillShot<\/td>\n<\/tr>\n
    November<\/td>\n2<\/td>\n7<\/td>\nLearnMore<\/td>\n<\/tr>\n
    Oscar<\/td>\n9<\/td>\n5<\/td>\nKillShot<\/td>\n<\/tr>\n
    Papa<\/td>\n5<\/td>\n1<\/td>\nImportantDeliverable<\/td>\n<\/tr>\n
    Quebec<\/td>\n10<\/td>\n7<\/td>\nKillShot<\/td>\n<\/tr>\n
    Romeo<\/td>\n6<\/td>\n8<\/td>\nKillShot<\/td>\n<\/tr>\n
    Sierra<\/td>\n3<\/td>\n7<\/td>\nLearnMore<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Assess the distance to an Investment Grade Proposal<\/p>\n

    Sorting the hypotheses by category creates a stack like the one shown in Figure 4. The Kill Shots are at the top of the stack because these represent the category of ignorance that can terminate the project.\u00a0 This ignorance has to be resolved before the project is ready for an investment grade proposal.<\/p>\n

    The investment grade proposal will ask for a substantial investment to move ahead with implementation of the innovation. The cumulative ignorance at this point reflects that there are still areas that need to be resolved, but these areas will affect how much value the innovation can yield rather than whether the innovation itself is viable.\u00a0<\/strong><\/p>\n

    Distance to Investment Grade Proposal<\/strong><\/p>\n

    \"\"<\/p>\n

    Design and prioritize experiments to test the hypotheses and buy down ignorance<\/strong><\/p>\n

    Now you can put together the validation plan. The plan will consist of a series of experiments to test the most significant hypotheses, in an efficient sequence.<\/p>\n

    The first set of experiments will test the Kill Shot hypotheses, because if any of these fail validation, the project as conceived is not viable. By including the cost of the experiments in the prioritization, they can be ranked by cost efficiency (the ratio of ignorance bought down to the cost of the experiment).<\/p>\n

    The priority of the experiments gives a sequence in which to perform the experiments. If the most cost-efficient experiments pan out, the cumulative ignorance score of the project drops, and it makes sense to proceed to the less cost-efficient (but still necessary) experiments.<\/p>\n

    Experiment Prioritization<\/strong><\/p>\n

    \"\"<\/p>\n

    If all of the experiments in the Kill Shot category validate the corresponding hypotheses, the project is ready for an investment grade proposal. The innovation project shifts to implementation, delivery and management aimed at maximizing the value generated.<\/p>\n

    Tags: #innovationportfolio #business #strategy #decisionmaking<\/p>\n","protected":false},"excerpt":{"rendered":"

    By Ralph Morales III Head of Innovation Practice SmartOrg, Inc. Scoring uncertainty in an innovation project is the first step to developing a validation plan to determine efficiently whether the innovation is viable and valuable. 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