Quote conversion became visible without extra admin overhead

Using their existing WorkflowMax export process, we built a practical reporting model so leadership could see volume, conversion and value trends in one place.

17,000+

quotes analysed

dashboard views

91%

of quotes found uncategorised

Context

The team had substantial quote history in WorkflowMax but limited visibility of conversion patterns over time. Native reporting did not provide the level of practical analysis required for month-to-month decisions.

What Needed Attention

Very large quote dataset with limited structured analysis.
Leadership needed monthly conversion and value trends without manual rework each cycle.
Data quality weaknesses were hidden by existing reporting views.

How We Worked

Mapped the existing export process so the solution would fit current work practice.
Built a lightweight dashboard model with three linked analysis views: volume, conversion and value.
Set up a simple refresh workflow so internal teams could update reporting independently.
Used the model to surface category and quality gaps that affected decision confidence.

Outcomes

Leadership gained a reliable view of quote volume, conversion and value patterns.
Reporting shifted from ad hoc extraction to a repeatable monthly rhythm.
A major data quality issue (91% uncategorised records) was identified and made visible for remediation.

Engagement Profile

Medium-length engagement with design, build, handover and practical support sessions.

Evidence Base

De-identified dashboard framework and output examples.
Source export structure and transformation logic.
Refresh process documentation used by internal staff.

Client details are anonymised; metrics are drawn from project records and de-identified artefacts.

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