About Us

Our vision is to empower process improvement for the most complex software engineering value streams on the planet. To realize this vision, we build domain-tailored solutions that minimize “time to value”, maximize depth of insights, and facilitate concrete business outcomes.

Network of connections showing value-creation network

Built without borders

The Software Delivery Simulator is powered by a global network of individual and organizational contributors. We embrace cross-organizational collaboration, and over-index on transparency, trust, and creativity.

User in front of the computer trying to understand complex problem

Complexity

Systems-of-systems complexity has the potential to undermine process improvement efforts, if not properly addressed. It's impossible to improve a process that you don't understand.

Two users in front of the laptop making decisions

Decision Making

The efficiency, efficacy, and value of a system result from countless small decisions made throughout the lifecycle of the system. Complexity can explode or erode based on the decisions we make every day.

Two coworkers comparing notes or reports

Objectivity

The most important principle for optimal decision making (and thus world-class engineering systems) is objectivity in the face of complexity. Modeling and simulation facilitate the evolution of systems along an objectively optimal path.

Simulator Design

We provide the simulator, but it runs in your browser (only you have access to your data)

Angular

Angular

NodeJS

NodeJS

NPM

NPM

Rust

Rust

WebAssembly

WebAssembly

Roadmap

Our plan for delivering more value and evolving the platform

Function modeling diagram with input and output flows marked

Analyze processes with a function lens

Analyze input-output flows using a “function modeling”, VSM-like lens

Stable
Clock showing value stream process flow over time

Investigate processes with a dynamics lens

Understand and visualize value stream process flows over time, using component models for the software delivery subsystems

Experimental
Multiple directions for more realistic and insightful simulation

Study stochastic simulation dynamics

Use stochastic behaviors to make simulations more realistic and insightful

Experimental
Graph analyzed in detail through the magnifying glass

Explore simulations with graphs and visualizations

Investigate simulation runs and results with powerful visualizations

In Progress
Long and detailed paper report

Export simulation reports

Download a CSV file which contains the comprehensive details of a simulation

To Do
Loading raw data for simulation inputs

Leverage input analysis capabilities

Load raw software delivery tooling data, which is processed and used for simulation inputs

To Do
Information processed and analyze into valuable output

Understand processes through an information lens

Explore and analyze input data (e.g., distribution, parameters, goodness-of-fit) and output data (e.g., summary statistics, autocorrelation, hypothesis testing)

To Do
People in organization connected to analyzed processes

Expand simulation insights with an organizational lens

Connect processes and process improvements to the people involved - across the planning, control, and execution levels

To Do
Toolkit for model creation for library of models

Create custom models within a studio environment

Use a model creation studio to build out a library of custom models

To Do

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