If you had 30 minutes with a CEO, decision factories, decision managers, KISS 2.0, and being nice

2023-05-09 · Source: Mike Talks AI · Field: Business & Management — Corporate Strategy & Leadership, Project & Product Management, Operations & Process Management · Depth: Intermediate, quick

Summary

A recent discussion with John Brandon Elam, Decision Systems Leader at Toyota, highlights the concept of creating "Decision Factories" within organizations, moving beyond mere models and dashboards to focus on actionable decisions. This approach, detailed in Elam's new book, emphasizes improving decision-making speed and quality through data and analytical models. Key insights from the conversation include the necessity of assigning a single individual, potentially a group product manager, responsibility for the entire analytic decision process, from data to IT. The discussion also introduces "KISS 2.0" (Keep it Simple, to Start) for decision factories, advocating for starting with simpler systems before scaling complexity. Other points cover the importance of interpersonal skills, user feedback in tool development, appropriate model selection based on complexity, and aligning incentives between transformation and operations teams.

Key takeaway

For VPs of Engineering or Data grappling with organizational efficiency, shifting focus from merely building models to establishing "Decision Factories" is crucial. Your teams should prioritize end-to-end ownership of analytic decisions and adopt a "Keep it Simple, to Start" approach for new systems. This strategy will accelerate decision-making and ensure that analytical efforts directly translate into tangible business outcomes, rather than just producing data outputs.

Key insights

Organizations should evolve into "Decision Factories" by prioritizing actionable decisions over just models and dashboards.

Principles

• Assign single ownership for analytic decision processes.
• Start simple, then scale complexity (KISS 2.0).
• Align incentives between transformation and operations.

Method

To build effective tools, listen to user complaints, solicit honest feedback on early versions, and incorporate that feedback into future iterations to facilitate change management.

In practice

• Use the simplest model that works for forecasting.
• Cultivate technical intuition for better management.
• Prioritize being "nice" to enhance collaboration.

Topics

• Decision Factories
• Decision Management
• Model Selection
• Organizational Transformation
• Change Management

Best for: VP of Engineering/Data, Executive, Product Manager, CTO, Director of AI/ML, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by Mike Talks AI.