• Jeff Doolittle

Out-of-the-Box Thinking isn’t Enough for Leaders


Fostering innovation is a critical leadership responsibility. Leading in today's turbulent and digital marketplace requires more than cliché advice about out-of-the-box thinking. Leadership performance expectations are increasingly more complex. Leaders are expected to deliver low cost and high reliability, standardization and personalization, global consistency and local sensitivity, to name a few. Advances in technology are driving this evolution as leaders scramble to provide choices to stakeholders with competing priorities. The challenge leaders face is that our thinking is easily limited by the familiar. A closed mind is a hard thing to open. It is a classic "blind men and an elephant" parable problem where an individual perceives absolute truth based on subjective experiences. The conventional advice for leaders to think outside the box does not go far enough to produce significant positive change. Leaders looking to innovate need data-informed creative thinking.


“There’s one thing worse than change and that’s the status quo.” John le Carre

Debunking an Innovation Myth


Innovation and analytics thrive in a change-based environment. A commonly held myth is that innovation comes from an epiphany versus hard work, personal sacrifice, and taking risks. The story of how Isaac Newton discovered gravity is a commonly used example of the widely held oversimplification of innovation. In reality, Isaac Newton used mathematics to explain how gravity works, rather than an apple falling on his head that lead to the discovery. The epiphany aspect of innovation is like when the last piece of a puzzle fits together. What matters is the ability for leaders to clearly see a problem with the talent to solve it rather than the epiphany moment.



What Leaders Really Need


Technology is collecting a deluge of information that has the potential to make or break any organization. In a 2019 Gartner survey of HR leaders, only 21% believe their organizations effectively use talent analytics to make better decisions. Descriptive, diagnostic, predictive, prescriptive, and cognitive analytics provides leaders with technology-enabled data-driven models and visualizations within the innovation process. Leaders need the ability to leverage analytics in each of the four phases of innovation:

  1. Problem exploration: Answering what are the possible problems?

  2. Problem selection: Answering what problems should be solved first?

  3. Solution exploration: Answering what are the possible solutions for the selected problem?

  4. Solution selection: Answering what are the best solutions to the selected problem?



Artificial Intelligence (AI) is a GameChanger


Artificial Intelligence is reshaping the world. AI promises to enhance leaders' decision-making speed by making sense of the deluge of data available today, better managing creative complexity and asking and answering questions better throughout the innovation process. Today, AI is already positively impacting each of the four phases of innovation. In one recent case study involving the solution selection phase, a team utilized AI modeling to identify highly-rated features important to 1000 stakeholders from more than 60 countries. The AI model proved to be 23% better at predicting highly-rated features than average community ratings. The case study suggested that AI could indeed help innovation leaders automate solution selection. The volatile marketplace rewards speed and speed creates time for leaders that can be used to generate more significant advantages.


We can partner with you to develop a more future smart organization and get the workforce introduction to Artificial Intelligence and data analytics right. Partner with us and build increased organizational creativity and a culture that fits the future of the business you need. Contact us to schedule a conversation.


References:


Bartlett, R. (2013). A practitioner's guide to data analytics: Using data analysis to improve your organization's decision-making and strategy. McGraw-Hill. New York.


BCG Henderson Institute. (2020). In conversation with Yves Morieux about complexity. https://bcghendersoninstitute.com/in-conversation-with-yves-morieux-about-complexity-858c7ccf7b30


Berkun, S. (2010). The myths of innovation (1st ed.). O'Reilly Media, Inc.


Kakatkar, C., Bilgram, V., & Füller, J. (2020). Innovation analytics: Leveraging artificial intelligence in the innovation process. Business Horizons, 63(2), 171-181.


Kanter, R. (2020). Think outside the building: How advanced leaders can change the world one small innovation at a time. Hachette Book Group, Inc.


Ledet, E., McNulty, K., Morales, D., & Shandell, M. (2020). How to be great at people analytics. McKinsey & Company. https://www.mckinsey.com/business-functions/organization/our-insights/how-to-be-great-at-people-analytics



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About Jeff Doolittle

He is the founder of Organizational Talent Consulting in Grand Rapids, MI. Executive leaders who work with Jeff describe him as thoughtful, decisive, intelligent, and collaborative.  Jeff is a business executive with over twenty years of talent development and organizational strategy experience working with C-suite leaders in Fortune 100, Forbes top 25 private, for-profit, non-profit, and global companies in many industries.

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