In my lucky 13th episode of the Big Data MBA educational curriculum, I cover the Prioritization Matrix, a key component of my "Thinking Like a Data Scientist" envisioning methodology.
The Prioritization Matrix is my most powerful and collaborative management tool for driving organizational alignment in the use case identification and prioritization process is the Prioritization Matrix. The Prioritization Matrix facilitates the discussion and collaboration between the Business Stakeholders and Data Science stakeholders in identifying the “right” use cases to pursue – those use cases with both meaningful business value (from business stakeholders’ perspectives) and reasonable feasibility of successful implementation (from data science team’s perspective).
One key challenge to a successful data and analytics strategy is gaining consensus and alignment between the business and data science (data & analytic) stakeholders in identifying and prioritizing the use cases that 1) deliver sufficient value to the business, while 2) possess a high probability of success.
The summary of Prioritization Matrix:
- The Prioritization Matrix process provides a framework for driving organizational alignment around the relative value and implementation feasibility of each of the organization’s use cases.
- The Prioritization Matrix process weighs the “value” (financial, customer, operational, environmental) of each use case against the implementation feasibility (data, architecture, technology, skills, timeframe, management support) of those same use cases over the next 12 to 18 months.
- The Prioritization Matrix process, with a properly trained facilitator, gives everyone an active voice in the identification, discussion, and debate on use case value and implementation feasibility.
- The discussions, explanations, and justifications between the different stakeholders about the relative placement of each of the use cases may be the single most important outcome from the prioritization process.
To read more, check out my eBook "The Art of Thinking Like a Data Scientist" at
www.DeanofBigData.com
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#Big_Data #Data_Science #Data_Monetization #Digital_Transformation