48 lines
2.3 KiB
Markdown
48 lines
2.3 KiB
Markdown
# Chapter 8: Keeping the Wolves at Bay
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## Core Focus
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The tension between simplification and usefulness in strategic mapping. Introduces worth-based development, pricing granularity, and flow.
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## The Simplicity Trap
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Ashby's Law of Requisite Variety: "the controlling mechanism of a system must be capable of representing what is being controlled." Organizations oversimplify through 2x2 matrices, trading deeper understanding for apparent manageability.
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## Worth-Based Development
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Using a Large Format Printer (LFP) project example: shifting from contract-based to outcome-based compensation aligns incentives. Charging per lead generated rather than upfront:
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- Focuses both parties on actual user value
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- Incentivizes cost-effectiveness
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- But exposes friction with rigid budgeting systems ("corporate corpus")
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Result: more leads in 3 months than the client typically produced annually.
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## Pricing Granularity
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Zimki (2006) charged per function call. This granular cost visibility enabled:
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- Identifying inefficient code
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- Informed investment decisions about optimization
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- Predated AWS Lambda by 8 years
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## Flow and Capital Movement
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Maps contain multiple flows: financial, physical, informational, risk, time, social. Understanding flows enables financial modeling and reveals where to invest for maximum impact.
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## Efficiency vs. Effectiveness
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Critical distinction demonstrated via manufacturing example:
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- Company proposed millions in robotics to automate server modification
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- Mapping revealed root cause: custom server racks forcing expensive modifications
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- Effective solution: eliminate the value chain by adopting utility computing
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- Not "make the ineffective process more efficient"
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"Be very careful of process improvements focused solely on efficiency without questioning why the process exists."
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## Key Takeaways
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1. Simplification carries costs - trading complexity for manageability hides critical insights
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2. Align incentives with value through outcome-based models
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3. The corporate corpus resists change - good intentions embedded in systems impede innovation
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4. Maps reveal hidden assumptions normalized through repetition
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5. Granularity enables optimization - detailed cost visibility drives better decisions
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6. Question the premises - before improving efficiency, verify the activity merits existence
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