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Innovation & Improvement - Coggle Diagram

- - - - conformance quality (low defects)
      - time to market/ time to volume
      - manufacturing/ service cost
    - - design for manufacturing (DFM; product design rules)
      - design for six sigma (DFSS; reducing defects in manufacturing)
      - manufacturing's involvement in prototyping
      - simultaneous (or concurrent engineering)
- - - - e.g., productivity, defect levels, etc.
  - - - characterised by a linear relationship in log-log scale graph
      - indicating that the amount of direct labour hours needed for 1 unit of production reduces by a similar % every time the cumulative volume doubles
  - - - means that we can extrapolate into the future with reasonable accuracy
    - - we learn more each time we process a unit & learning cumulates
        
        log (cost) vs. log (cumulative volume) graph appears as a straight line
        
        each doubling of cumulative volume decreases cost by L%
    - - models stipulate annual productivity growths, annual reductions in defect levels, etc.
    - - planning & budgeting of resources
      - to check whether implementation of new processes "is on track" or not
- - - - Any improvement must be made in accordance with the scientific method: generate hypotheses, test, then implement
      - Process variability is reduced to eliminate problems - all work is highly specified as to content, sequence, timing and outcome
      - All employees are empowered to make improvements; managers are coaches
      - All activities, connections and flow paths have built-in tests to signal problems automatically (= control)
    - - Unvalidated theories
        
        use highly scientific solutions but don’t verify that the new designs deliver results
        
        operational learning (know-how): low
        
        conceptual learning (know-why): high
      - Fire fighting
        
        operational learning (know-how): low
        
        tries to solve the problem at hand, brainstorming possible causes without scientific insights
        
        conceptual learning (know-why): low
      - Operationally validated theories
        
        operational learning (know-how): high
        
        Draw on scientific insights to implement solutions that produce replicable results
        
        conceptual learning (know-why): high
      - Artisan skills
        
        operational learning (know-how): high
        
        solve the problem at hand, but the “why” is poorly understood and the solutions don’t transfer easily
        
        conceptual learning (know-why): low
  - - - Make sure the system can be copied and is worth copying
      - Work from a single, active template (process you want to copy)
      - Copy as closely and completely as you can (plant & equipment, skill sets and procedures)
      - Don’t reformulate, adapt, or improve upon until you have reached acceptable results
    - - Neither people nor documents can fully explain how a complex system works
      - We are often overconfident about our understanding of why
        something works
  - - - Identify the knowledge gaps and learn proactively
      - Use a stage-gate process to start small and reduce risk quickly before committing large amounts of resources
        
        feasibility studies
        
        product prototype
        
        pilot plant
        
        full-scale plant
      - Use simulation to test new products/processes and avoid errors (learning before doing)
      - Use partners/contractors to manage risk
- - - - use of conceptual knowledge
        
        Design strategies: Process is developed “on paper” or “in silico” (through computer simulation); interactions are well understood and can be taken into account
        
        "lab"
    - - operational learning
        
        Learning curve
        kaizen & standardized work
        
        Manage the interplay between these two learning modes or loci
        
        large-scale operations
    - - Later if fidelity (how close is it to reality) of “lab experiments” is high (ability of “lab” to simulate manufacturing scale behavior)
      - Later if cost of “lab experiments” is low compared to those in large-scale
- - - - (innovation & improvement program matrix - the multi-dimensional diagram with capabilities, performance overkill/ superior/ acceptable/ dismissal)
    - - (efficient frontier - one capability : low to high v. unit cost : high to low)
- - - - process of ops strategy includes both of these
- - - - Communicate with top management and other functions in complex or hostile environments
      - Pay attention to functional deliberation (to strengthen operations) when the environment becomes less certain (use simple rules to coordinate efficiently)