How changes spread between project interfaces

Step 0 Selected: —
Local iterations 4 Spillover 0.15 / 0.05 Friction cap A>70 → improvement ×0.5

Five fictional interfaces share parties, so a change can ripple through a small network. Try clarifying scope, inspect the changes, then alter an assumption.

Model assumptions and limits

Scores, equal weighting, coefficients and thresholds are invented teaching assumptions, not surveyed evidence or a calibrated organisational forecast. A step is one action, not a day. The index averages four attributes and 100 minus Ambiguity.

Nudges ripple through a fixed number of coupling waves. An absolute set holds the selected attribute at the requested value for the step. Only realised, clamped local changes spill to neighbours. Friction damps beneficial spillover when the receiver's ambiguity exceeds its threshold. On each nonzero action or scenario, the threshold penalty applies once across all interfaces; a zero action does nothing.

The four scenarios directly change their stated attributes and apply the threshold penalty; they do not run the local coupling or spillover engine. Reset restores both baseline values and assumptions. Applying the five coupling controls replaces the coupling-edge list with those five relationships. Nothing is saved automatically: export simulation state to keep a session.

Adapted from the older Interface Maturity Simulator (source revision 9d9c253, reviewed 2 October 2026). The SharpCloud mapping remains a conceptual export, not an integration or official API format.

Controls

Tip: Click a cell
Model knobs (editable)
Local coupling edges (editable):
Ambiguity → Trust, Ambiguity → Escalation, Trust → Adaptability, Trust → Incentives, Incentives → Ambiguity

Last action log

Undo is stateful
Ready.
The matrix is a SharpCloud-like representation: rows = “stories” (interfaces), columns = attributes (Trust, Adaptability, …). Click a cell → pick a Δ → watch local coupling + network spillover.
Click any cell to select it. Values are 0–100. Ambiguity is inverted (high = bad) for color.

Network legend

Nodes = interfaces (stories). Color = “maturity index”.
Edges: shared party uses spillover 0.15. Weak ties use 0.05.
Maturity index (0–100) = average of: Trust, Adaptability, Escalation readiness, Shared incentives, and (100 − Ambiguity).
Hover nodes for details. Tip: after a nudge, weak ties can still move (slowly), but weights dampen large interfaces.

Maturity index by interface

Average maturity trend

Notes you can say out loud in a demo

Chart values and recent index history

      

    


    

      

        
How this maps to SharpCloud (conceptual)

        

          
    
            
  1. Stories: each interface row becomes a Story (e.g., “PM↔Design”).
    2. 
            
  2. Attributes: Trust, Adaptability, Ambiguity, EscalationReadiness, SharedIncentives (numeric 0–100).
    3. 
            
  3. Tags: Owner, Workstream Tag, Parties (e.g., Party:PM).
    4. 
            
  4. Relationships: connect Stories if they share a Party (strong tie), else weak tie (optional).
    5. 
            
  5. Panels:
              
      
                
    • Attribute Matrix: heatmap (this page’s Matrix view)
      • 
                
    • Network view: relationships graph (this page’s Network view)
      • 
                
    • Dashboard: KPIs and trends (this page’s Dashboard view)
      • 
              
    
            
    6. 
          

          This page exports a standalone JSON “pack” + CSV you could adapt to whatever import/API process you use—without depending on any SharpCloud instance.
        

      


      


      

        

          
Export pack (JSON)

          

            
            
          

          
        


        

          
Attribute table (CSV)

          

            
            
          

          
        

      


      


      

        
Import / Export state (for this simulator)

        
Paste a previously exported simulator state JSON here and click “Load state”.