Finding types and common foresight terminology

FIBRES uses Finding types to organize different kinds and levels of foresight information and data. This article explains the default types like Signals, Technologies, Trends and Megatrends, and how they relate to common foresight terminology, and how the taxonomy can be adapted to different research contexts and organizational needs. Different organizations and fields may use these terms somewhat differently, so the most important thing is to define your taxonomy clearly and use it consistently.

1. FIBRES taxonomy

FIBRES has two main content structures:

• Findings describe individual topics, developments, or observations.
• Portfolios bring several Findings together for analysis, discussion, or reporting.

Findings

A Finding is the main object used to save information in FIBRES.

The four default Finding types are:

• Signal
• Technology
• Trend
• Megatrend

Every Finding has a Finding type, shown as a colored label above its title.

The four default Finding types

These Finding types are not maturity stages. A Signal does not automatically become a Trend, and a Trend does not automatically become a Megatrend. Instead, they represent different types and levels of foresight information.

Megatrends in different foresight contexts

In foresight, a megatrend usually refers to a broad, long-term and systemic development with the potential to transform societies, economies, industries and everyday life. Common examples include:

• Climate change
• Demographic change
• Urbanization
• Digitalization

Megatrends typically develop over decades and influence several industries, markets and areas of society. They often consist of several interconnected trends rather than a single development.

Megatrends can also be defined within the specific scope of a radar. A context-specific Megatrend is a broad, long-term change reshaping an industry or operating environment.

For example, a mobility radar might treat Electrification of Mobility as a Megatrend because it affects vehicles, energy systems, infrastructure, supply chains, regulation and consumer behavior.

What qualifies as a Megatrend depends on the radar’s purpose and scope. It should be broad, long-lasting and transformative—not simply important.

How Findings connect

Finding types are not a rigid hierarchy, but they can support one another:

• Signals provide observations and evidence.
• Trends describe broader patterns of change.
• Technologies enable, accelerate, or respond to change.
• Megatrends provide the wider context.

For example:

A city permits fully driverless taxis

Signal

Mobility services become increasingly autonomous

Trend

Autonomous driving systems and sensor technologies

Technology

Digitalization and automation reshape society

Megatrend

These relationships can be created with linkages and explored in the FIBRES Network view.

Megatrends, Trends, and Technologies appear as bubbles in the full Network. Halos around these Findings show the number of linked Signals: the wider the halo, the more Signals are linked to the Finding. Signals can be mad evisible by double-clicking the finding bubble.

2. Foresight terminology

The following concepts are commonly used in foresight and futures studies. They help explain how change is identified and interpreted, but they are not all default FIBRES Finding types.

Signals and weak signals

FIBRES uses Signal as the default Finding type for individual observations and pieces of news.

In foresight, weak signal is often used more specifically for an early, surprising, or uncertain observation that could indicate a larger change. Its meaning may not yet be clear, and it may challenge current assumptions.

Examples of weak signals could include:

• A new behavior appearing among a small group of users
• An unusual research breakthrough
• A startup testing an unexpected business model
• An early regulatory proposal
• A product being used in an unintended way
• A fringe idea beginning to attract attention

Not every Signal is necessarily weak. Some Signals provide new evidence for a well-established Trend, while others may point toward genuinely new change.

In FIBRES, both can be saved using the Signal Finding type. If distinguishing weak signals is useful, use:

• A tag
• A Classification such as Phenomenon maturity
• A custom Finding type
• Linkages to emerging Trends or Technologies

Several related Signals may support the identification of a Trend. However, Signals do not automatically become Trends: human interpretation is needed to determine whether they form a meaningful pattern.

Drivers of change

Underlying forces behind multiple weak signals, trends, and phenomena. They represent the broader directional shifts happening in the operating environment. Multiple distinct trends can share a single driver.​

Examples include:

• Demographic change
• Changing customer expectations
• New regulation
• Economic pressure

Wild cards

A wild card is a surprising event or development with a low probability but potentially significant consequences.

Wild cards are useful for challenging assumptions and exploring disruption in scenario planning, risk intelligence, and strategy work.

3. Customer-specific Finding and Portfolio types

The default taxonomy provides a useful starting point, but organizations may need terminology that better matches their foresight purpose and existing processes.

Depending on your FIBRES plan and account configuration, FIBRES supports custom Finding types and custom Portfolio types.

Custom Finding types

An organization could use custom Finding types such as:

• Innovation Area
• Strategic Opportunity
• Emerging Risk
• Customer Need
• Business Model Opportunity
• Startup
• Competitor Move
• Regulatory Development
• Capability

Custom templates can also define which information should be included in each Finding type.

Use a custom Finding type when the content represents a distinct kind of individual topic that your organization wants to create, assess, link, filter, and potentially position on a radar.

Before adding one, ask:

• Does this represent a genuinely different type of content?
• Will users understand when to use it?
• Does it require a different description template?
• Should it appear on a radar or in the Network?
• Could the same need be handled with a tag or Classification?

Keep the taxonomy fit for purpose

You do not need to use every available type.

Start with a simple taxonomy that supports the purpose of your foresight work. Add custom Finding or Portfolio types when they make the content easier to understand, manage, filter, and apply.

The most important thing is that users understand the terminology and apply it consistently.

Key takeaways

• Signals are source-based observations that provide evidence for broader Findings.
• Technologies describe technological developments, capabilities or enabling solutions.
• Trends bring related Signals together into a broader description of what is changing.
• Megatrends describe broad, long-term transformations and may provide context for many related Trends and Technologies. Megatrends can be broadly recognized or defined within a specific industry or operating environment.
• Finding types describe different kinds of information—not different levels of maturity.
• Organizations can adapt the taxonomy through custom Finding types.