OUR APPROACH
Different problems require different starting points.
Some clients come with a clearly defined analytical problem. Others know something is not working but are not yet sure what should be built.
Lemma structures engagements around the level of clarity, complexity, and ongoing support the problem requires.
01: “We know there’s a problem, but we’re not sure what the solution is.”
DIAGNOSTIC
You may have unreliable forecasting, manual reporting, spreadsheet-heavy workflows, unclear resource decisions, or an interest in AI without a clear use case.
In this scenario, we’d start by defining the problem, reviewing the relevant data and workflow, identifying constraints, and determining what kind of intervention is actually warranted.
Typical outcome
A focused assessment with findings, key analytical outputs, identified limitations, recommended next steps, and an implementation roadmap. The diagnostic should be useful even if no larger project follows.
02: “We know what we need. We need it built.”
PROJECT
When the desired outcome is clear enough to define scope and completion criteria, we work on a fixed-fee project.
In this scenario, that might mean a forecasting system, statistical model, operational dashboard, reporting automation, data pipeline, decision-support tool, or AI-assisted workflow.
Typical structure
Assess → Build → Validate → Handoff
You’d purchase the completed outcome, not a collection of billable technical tasks.
03: “We need this capability on an ongoing basis.”
FRACTIONAL ANALYTICS
For organizations with recurring analytical needs but no reason to build a full internal data team, Lemma can stay involved as an ongoing technical partner.
The work can include analysis, modeling, forecasting, automation, decision support, recurring reporting, and continued improvement of systems already in production.
Typical structure
A set of active priorities, a regular working cadence, and ongoing support as needs evolve.