What is a comparison perimeter?

Before your users view their first results, learn what a comparison perimeter is and discover how it helps contextualize and position your teams’ performance within your account.

Table of contents

Understand comparison perimeters

Use comparison perimeters

Configure comparison perimeters

Best practices

Understand comparison perimeters

Overview of comparison perimeters

Comparison perimeters determine the benchmarking of broader metadata against which users can position themselves relative to their specific analysis perimeter. From a functional perspective, they act as cross-reference data, displayed by default across all KPIs accessible on the platform. They should not be confused with analysis perimeters (learn more), nor with period comparison (which does not require Administration access).

In the SatisFactory platform, a comparison perimeter can be assigned to each user or user group to allow them to compare their data only with broader data relevant to their context (role, department, brand, region, etc.). An analysis perimeter should therefore normally be a subset of the comparison perimeter to provide meaningful perspective where the observed entity is positioned within its overall context.

Thus, for each new user created on the platform, it is possible (but not mandatory) to assign the comparison perimeter that best matches their role within the organization and their environment (area, brand, region, etc.). For user groups covering all available data (head office, administrators), configuring a comparison perimeter is not necessary.

Detailed overview of comparison perimeters

While natively integrating analysis and comparison perimeter display restrictions into the interface, the platform also provides flexibility for customized configuration.

You therefore have the option, either independently or with SatisFactory support, to create specific comparison perimeters to perfectly align users’ broader data visibility with their respective operational environment.

Use comparison perimeters

By providing correlation and positioning within data analysis, comparison perimeters are essential drivers to:

Manage comparisons without compromising data governance

• Define a comparison perimeter complementary to the analysis perimeter in order to precisely control which entities serve as reference benchmarks for each group, without expanding access to analyzed data
• Strictly regulate accessible comparison groups (example: a store compares only with stores in the same region or format), while keeping its own analysis perimeter unchanged

Preserve confidentiality and competitive data separation

• Secure rankings and benchmarks by applying comparison filters upstream, independently of raw data access rights

Guide artificial intelligence recommendations

• Personalize decision-support features (insights, flash reports, etc.) based on the gap between analysis perimeter and comparison perimeter

Ensure benchmark reliability and relevance

• Compare each entity against a truly representative reference set built on consistent and controlled criteria
• Avoid interpretation bias by comparing only comparable entities (customer typology, geographic area, source, etc.)
• Ensure consistency in comparative analyses of scores, averages, or calculations while preserving each user’s analysis scope aligned with their responsibilities

Contextualize performance and observed gaps

• Give meaning to results by evaluating relative performance within a relevant operational, local, or organizational context
• Adjust objectives, thresholds, and gaps according to a coherent reference group rather than a global average that may be disconnected from field reality
• Facilitate identification of improvement levers by highlighting actionable and comparable gaps

Accelerate result interpretation and adoption

• Provide immediate visibility of the user’s relative position within their comparison group
• Remove the need to manually rebuild benchmark samples or filters for each analysis
• Improve user autonomy by providing ready-to-use, reliable comparative dashboards

Align comparison reference frameworks with the organization

• Standardize comparison logic across the organization by defining common perimeters
• Ensure consistent performance interpretation between head office teams, intermediate managers, and field teams

Configure comparison perimeters

Access comparison perimeter management

From the platform's administration center, you can create, modify, and delete the comparison perimeters of your account.

⚠️ The administration center is only accessible to users whose profile holds administrator privileges ("Manage").

To do this, from the platform's left sidebar, access the administration center by clicking on the "Administration" tab.

Then, in the administration center's left sidebar, expand the "Users and roles" section, then click on the "Users" sub-section.

Then create a new user or edit an existing user.

Manage comparison perimeters

Master the creation, modification, and deletion of comparison perimeters on your account by consulting our dedicated article: Manage comparison perimeters.

Best practices

Define a comparison perimeter broader than the analysis perimeter

The comparison perimeter must always include the user’s analysis perimeter. It serves as a reference framework and enables local performance to be positioned within a broader context. A comparison perimeter identical to or narrower than the analysis perimeter provides no analytical value and may lead to misinterpretation of indicators.

Adapt the comparison perimeter to the level of responsibility

The comparison perimeter must align with the user’s actual role within the organization. The higher the hierarchical level, the broader the comparison perimeter can be. Conversely, a perimeter that is too broad for operational users may generate irrelevant or difficult-to-interpret comparisons because the user has no action leverage over all visible data.

Use comparison as a steering and contextualization tool

The comparison perimeter should help understand performance gaps, identify trends, and position a local perimeter within a reference set. It should not be designed as an individual monitoring tool. Favor aggregated comparisons to promote more constructive interpretation and better user adoption.

Remain vigilant regarding data confidentiality and governance

Defining a comparison perimeter implies broader data visibility. It is therefore essential to ensure accessible information complies with internal confidentiality, compliance, and governance rules. Even if users cannot act on data within their comparison perimeter, simply viewing it may create organizational or regulatory concerns.

Do not enable a comparison perimeter without a clear need

A comparison perimeter is not mandatory and must serve a defined objective. Some organizations intentionally avoid operational comparisons to prevent competitive dynamics or misinterpretation of results. In such cases, the absence of a comparison perimeter is a deliberate structural choice, not a functional limitation.

Clearly explain comparison logic to users

A poorly understood comparison perimeter is often poorly used. It is recommended to clearly explain to users what their analysis perimeter includes, what their comparison perimeter covers, and the intended purpose of this comparison. This facilitates interpretation and strengthens user autonomy.

Anticipate internal benchmarking use cases during setup

The comparison perimeter forms the foundation of local internal benchmarking logic. It is therefore important to anticipate future uses during initial configuration: performance monitoring, gap detection, best practice sharing, or managerial animation. A perimeter designed solely for analytical purposes may prove unsuitable when used for operational steering or internal communication.

Test comparison perimeters before large-scale deployment

Data confidentiality is critical. Use the "Login As" feature to verify exactly what an end user sees within both analysis and comparison perimeters. Ensure they can access their own data, that default filters prevent unauthorized access to sensitive information, and that comparisons remain relevant.

Periodically reassess comparison perimeter relevance

Even though they should remain stable, comparison perimeters must be reviewed regularly. Organizational changes, customer journeys, channels, or collection systems may render certain comparisons obsolete. Periodic reassessment ensures perimeters remain aligned with operational reality and customer experience objectives.

Define relevant comparison rules

Beyond user-specific data, consider which benchmark data should be included within perimeters. Provide sufficient visibility to allow fair evaluation (national or regional averages) without overwhelming users or exposing detailed scores of other entities if not appropriate.

For further assistance or to report a specific issue, please contact our Support team.