Scan & Sense method guide

Intelligence Needs Register

The register turns strategic uncertainty into owned, decision-critical questions for technology and market intelligence.

Beginner-friendly guide · 4 min read

What Intelligence Needs Register does

The register turns strategic uncertainty into owned, decision-critical questions for technology and market intelligence.

An intelligence needs register converts uncertainty into a managed set of questions. It stops market and technology intelligence from becoming a collection of interesting articles with no clear decision user.

Each entry should state the decision, what is not known, when an answer is needed, what evidence already exists and who will act on the result.

Technology-intelligence research separates the questions decision-makers need answered from the scanning and sourcing activities used to answer them. This prevents scouting from becoming undirected browsing.[1][2]

Method schematicFrom blocked decision to usable evidence

A need begins with a decision, becomes a bounded question, attracts evidence and ends in an explicit response.

  1. 1Decision
  2. 2Question
  3. 3Search
  4. 4Evidence
  5. 5Action

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

Understand the method

The parts in plain language

1

Decision-critical question

Frame the need as an answerable question connected to a real choice, not as a broad subject.[1][2]

Illustrative example

Which three machine-data standards are required by our target customers for 2028 deployments?

2

Evidence threshold

Define what would count as a sufficient answer. Some decisions need directional expert evidence, while others need verified technical or commercial proof.[1][2]

Illustrative example

Five customer interviews plus two live integration tests before platform selection.

3

Owner and deadline

Assign both the person gathering evidence and the decision owner who will use it. Add a date linked to the decision window.[1][2]

Illustrative example

Technology scouting lead reports by March, before the architecture gate in April.

When to use it

  • When roadmap or leadership discussions repeatedly encounter missing information.
  • Before launching a technology-scouting programme.

A practical workflow

  1. 1

    State the decision and the specific question blocking it.

  2. 2

    Record urgency, horizon, owner, current evidence and the knowledge gap.

  3. 3

    Choose an appropriate intelligence mode and assign follow-up.

  4. 4

    Review the backlog and close, revise or promote needs as evidence arrives.

Fictional worked example

Example: selecting a battery technology

This example is illustrative rather than a reported case. A roadmap choice depends on future cost, safety and supply conditions.

Question

Observation:The team does not know which chemistry can meet the 2030 duty cycle.

Implication:Specify performance, cost and geography rather than asking broadly about batteries.

Search

Observation:Published data and supplier claims disagree.

Implication:Combine literature, supplier interviews and independent testing.

Close

Observation:Evidence supports two candidates for different conditions.

Implication:Record a conditional choice instead of forcing one universal answer.

From analysis to decision

How to interpret the result

  • 1Prioritise needs by decision value and deadline, not curiosity.
  • 2Close or reframe questions when the decision changes.
  • 3Preserve sources and confidence so later users can understand why the answer was accepted.

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

What a useful output looks like

A prioritised backlog of intelligence questions.
Traceable briefs for scouting, research and monitoring.

Common pitfalls

  • Avoid vague topics such as “AI” that are not framed as answerable questions.
  • Close stale needs so the register remains decision-led.

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

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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