Arbutus evalution / trial approach

Evaluating Arbutus Analytics

Evaluating a data analytics platform such as Arbutus Analyzer is not simply a matter of installing the software and exploring the interface.

Arbutus Analytics is designed to work directly with your organisation’s data, applying structured analytical procedures to achieve specific objectives. As a result, a meaningful evaluation requires more than a technical installation -it requires context, preparation, and guidance.

Evaluations are therefore typically initiated following an initial discussion to align on objectives, scope, and expected outcomes.

Why a guided evaluation matters

Experience shows that unguided evaluations often lead to inconclusive results or an incomplete understanding of the software’s capabilities.

Without a clear approach, it can be difficult to:

• Identify relevant data sources
• Define meaningful analytical objectives
• Translate objectives in analysis steps
• Interpret results correctly
• Understand how the tool fits within existing processes

A guided evaluation ensures that the software is assessed in a way that reflects its actual use in practice.

What a meaningful evaluation looks like

A structured evaluation typically focuses on a specific use case or set of objectives, using your own data where possible.

This allows you to assess:

• How data can be accessed and prepared
• How analytical procedures are applied
• What results are generated and how they are interpreted
• How these results support your audit, compliance, or data analysis objectives

The goal is not to “test features”, but to evaluate how the solution performs in your environment.

How the evaluation is supported

The evaluation is conducted as a guided process. This typically includes:

• An initial discussion to define scope and objectives
• Assistance with installation and accessing to data sources
• Guided sessions (e.g. online meetings) where analytical steps are performed together

During these sessions, we work through the analysis step by step, combining elements of demonstration, training, and workshop. This ensures that the evaluation reflects real use cases and leads to meaningful outcomes.

Preparing for an evaluation

To ensure that an evaluation delivers meaningful results, it is important that certain elements are in place:

• A clear understanding of at least one relevant data source
• Defined objectives or questions you want to address
• An understanding of what successful outcomes would look like
• Initial evaluation criteria
• Alignment on next steps if those criteria are met

This preparation helps ensure that the evaluation is focused, efficient, and relevant.

Scope and approach

A guided evaluation can typically be conducted within a defined and limited scope, focusing on specific use cases and objectives.

In many cases, this initial evaluation can be supported without cost, provided that scope and expectations are clearly defined.

Where organisations wish to explore broader scenarios, multiple use cases, or more extensive implementation aspects, a more structured (and potentially phased) approach may be appropriate. This can include clearly defined stages with decision points based on agreed evaluation criteria.

For larger or more complex environments, evaluations may be structured as part of a broader implementation planning exercise, with defined phases and go/no-go decision points.

From evaluation to implementation

An evaluation is typically the first step in a broader implementation journey.

Where evaluation criteria are met, organisations are in a strong position to proceed with implementation, including training, configuration, and integration into existing processes.

This ensures continuity between evaluation and practical use, rather than treating the evaluation as an isolated exercise.