Simulation Studies

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Overview

A simulation study is a multi-session engagement where you and Dexter take a modeling question from raw data to a defended recommendation: scoping the decision, understanding the data, building the model in pieces you can each validate, running the comparison runs that answer the question, and leaving a written record credible enough to take to management. A study runs across as many conversations as the work takes. The factory’s Knowledge Base carries what Dexter learns from one session to the next, and everything the study produces lives in the factory. This page covers the phase arc a study usually follows, what each sign-off certifies, and what the study leaves behind.

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A Study vs. a One-Off Conversation

Most simulation work fits in a plain conversation: a quick model, a chart, a data profile, a schedule tweak. The chat ends, the artifacts remain in the factory, and nothing is lost. A study is different in kind, not just size. It’s long; later answers depend on earlier decisions; the artifacts must be auditable; and someone will act on the recommendation. Losing the record of why a distribution was fitted the way it was — or which ground-truth check the finished model cleared — would sink the effort. A study works in phases that each end with your sign-off, and writes its decisions down in reports and the Knowledge Base so any future session picks the work up with full context. Reach for a study when:

• the decision is consequential — capital, staffing, customer commitments, capacity planning;
• the model has to be defensible, with a validation record behind it;
• the work will clearly span more than one sitting, or more than one person.

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Where Studies Live

A study’s conversations sit in the Dexter sidebar like any others; move them into a folder to keep them together. Everything the study produces — pipelines, models, experiments, reports — lives in the factory alongside your other work.

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Starting a Study

Ask directly — “I want a model of our packaging line to decide whether to add a second labeler.” If the shape of the work warrants a study, Dexter proposes one. The opening moves are the same every time:

1. Scoping. Dexter asks what decision the model needs to drive, in your terms: what’s being weighed, what “correct enough” looks like, which data sources exist, what ground truth the finished model must be validated against, and how deep the model needs to go.
2. The charter. Dexter drafts a short charter — the decision, the sources of truth, the bar the model must clear — and asks you to approve it. Nothing is modeled until you do.
3. The plan. Dexter proposes a phase plan designed for your context and tracks the immediate work in the conversation’s task list.

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The Phases of a Study

A phase is a unit of progress that ends at a sign-off: it produces one or more artifacts you review and either approve or send back. The next phase doesn’t start until the current one closes. The plan is designed for your study — phases split, merge, and reorder to fit the goal, the data, and how well the operation is already understood. There is no fixed phase template; the arc below is one illustrative shape, not a script Dexter marches through. A typical study looks something like: Phases can loop back: if end-to-end validation surfaces a gap the operational representation missed, the plan revises rather than pushing through, and Dexter checks with you before changing it.

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Sign-Offs

At the end of each phase, Dexter shows you what you’re approving — in its reply, in a report, or as the artifact itself in the platform — along with the assumptions and judgment calls it rests on and the evidence: tables, charts, the actual numbers. Then it asks a short approval question. You approve or reject with a comment:

• On approval, the next phase builds on the approved work.
• On rejection, Dexter iterates on your comment and asks again.

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Continuity Across Sessions

A study almost always spans multiple conversations, and several mechanisms make the pickup seamless:

• The Knowledge Base carries the operational context. What the study teaches Dexter about your operation — process flow, capacity, vocabulary, per-source data guides — lands in the factory’s Knowledge Base. Future sessions reload that understanding instead of re-asking.
• Name the study to resume it. In a new conversation, point Dexter at the study’s model, experiments, and reports so far; it reads them before touching the work.
• Tasks stay visible. Multi-step work inside a phase — data cleaning, model construction, an analysis — runs through the task list you can watch in chat.

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What a Study Leaves Behind

Every artifact a study produces is a first-class factory object, usable on its own. A typical study leaves:

• The study documents — charter, data write-ups, operational representation, assumptions register, validation record, recommendation — written up as reports or files in the factory.
• Data pipelines — a record of the transformations that shaped raw uploads into the model’s inputs.
• Custom modules built while characterizing the data, such as dashboards for exploring it.
• One or more simulation models with their entities, schedules, constants, lookup tables, KPI and chart definitions.
• Runs under each model, including the comparison runs from the analysis phase and their replications where variability mattered.
• Reports — the shareable deliverable in PDF, Word, PowerPoint, or Excel.
• Knowledge Base entries encoding what the study taught Dexter about your operation.

The study documents keep the reasoning connected — which artifact answered which question, under which assumptions.

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Limits and Caveats

• Run a study in Max or Ultra mode. Turbo and Fast ask few or no clarifying questions.
• The phase plan is proposed, not imposed. If a phase doesn’t match how you think about the decision, say so at scoping — revisions later are fine, but cheaper early.
• Ask for the sign-offs you want. If you want to approve a step the phase plan doesn’t stop at, say so at scoping.
• Reports are generated on request. The handoff phase scopes the deliverable — audience, format, what to lead with — rather than auto-producing a PDF at close.
• Studies are factory-scoped. A study lives in the factory it started in and can’t move across factories.

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Where to Go Next

• Chat, Tasks & Questions — how Dexter tracks the work and asks for your sign-off
• Simulation Overview — the artifacts a study produces, and how they fit together
• Your First Simulation — the hands-on loop a study automates and extends
• Runs — comparison runs and replications, the analysis of the later phases
• Results and Analytics — reading what the runs produced