Scan & Sense method guide

Trend Explorer

Trend Explorer compares weak signals and trends by domain, impact, maturity and time horizon.

Beginner-friendly guide · 4 min read

What Trend Explorer does

Trend Explorer compares weak signals and trends by domain, impact, maturity and time horizon.

A trend radar helps a team organise evidence about change without pretending that every observation is a forecast. It separates early signals from better-established trends and makes timing, impact and uncertainty visible.

The useful unit is a clearly described change supported by dated evidence. Several signals may support one trend. The team then decides whether to monitor it, investigate it, test a response or act now.

Roadmapping and technology-intelligence research both distinguish signal capture from strategic interpretation. A trend becomes useful when its evidence, likely timing, uncertainty and decision relevance are visible.[1][2][3]

Method schematicEvidence moves towards strategic attention

Signals sit at the edge. Better-evidenced and more decision-relevant trends move closer to action.

InnovationFlow explanatory schematic, synthesised from the method sources[1][2][3].

Understand the method

The parts in plain language

1

Signals

Signals are individual observations that may indicate change, such as a patent cluster, new customer behaviour, a policy proposal or an unusual investment. One signal is rarely enough to establish a trend.[1][2][3]

Illustrative example

Three customers independently ask whether equipment can report product-level energy use.

2

Trends

A trend is a pattern supported by several observations over time. Describe its direction, scope, evidence and possible mechanism rather than using a broad label.[1][2][3]

Illustrative example

Industrial buyers increasingly request auditable product-carbon data in supplier selection.

3

Horizon and response

Position trends by when they may matter and what response is proportionate. Near does not always mean important, and distant does not always mean ignorable.[1][2][3]

Illustrative example

Monitor an immature standard, investigate an emerging customer requirement, and act on a requirement already entering tenders.

When to use it

  • After external scanning has produced many signals.
  • When leaders need a shared view of emerging change without pretending to forecast one future.

A practical workflow

  1. 1

    Combine related observations into a clearly named trend.

  2. 2

    Record evidence, direction, maturity, time horizon and potential impact.

  3. 3

    Compare trends across domains and challenge the most consequential assumptions.

  4. 4

    Route trends into scenarios, intelligence needs, experiments or roadmap initiatives.

Fictional worked example

Example: product-carbon transparency

This example is illustrative rather than a reported case. A manufacturer is reviewing signals about customer expectations for product-level emissions data.

Signal

Observation:Several tenders ask for auditable carbon information.

Implication:Collect examples and identify affected segments.

Pattern

Observation:Requests appear across customers, markets and industry groups.

Implication:Treat this as more than one buyer preference.

Response

Observation:Current data cannot be produced consistently.

Implication:Open an intelligence need and roadmap a data-capability experiment.

From analysis to decision

How to interpret the result

  • 1Separate evidence strength from potential impact.
  • 2Give every important trend an owner and review date.
  • 3Route uncertainties into intelligence or scenarios, and agreed responses into experiments or the roadmap.

The interpretation guidance is an InnovationFlow synthesis of[1][2][3].

What a useful output looks like

A prioritised portfolio of trends and weak signals.
Explicit monitoring, research and action choices.

Common pitfalls

  • Do not confuse a fashionable topic with a well-evidenced trend.
  • Keep source dates visible because the strength and timing of signals change.

References and method basis

  1. [1]Kerr, C., Mortara, L., Phaal, R. and Probert, D. (2006). A conceptual model for technology intelligence. International Journal of Technology Intelligence and Planning, 2(1), 73-93. Source ↗Peer-reviewed research
  2. [2]Mortara, L., Kerr, C., Phaal, R. and Probert, D. (2009). A toolbox of elements to build Technology Intelligence systems. International Journal of Technology Management, 47(4), 322-345. Source ↗Peer-reviewed research
  3. [3]Phaal, R., Farrukh, C.J.P. and Probert, D.R. (2001). T-Plan: The fast start to Technology Roadmapping - planning your route to success. Institute for Manufacturing, University of Cambridge. Source ↗Original method source

This guide synthesises the named sources into practical questions for strategy and innovation work. It does not claim that using a tool by itself produces a successful decision.

Practitioner support

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