Which changes could alter strategic assumptions?

Trend work fails when it becomes a catalogue of fashionable topics. Strategic foresight is a disciplined way to notice change, challenge assumptions, construct multiple plausible futures and make present choices more robust. It does not predict one future.

A signal becomes strategically relevant when it has a credible mechanism, potential consequence and connection to a decision.

1. Signal taxonomy

Classify observations as:

  • event: bounded occurrence;
  • signal: evidence pointing toward possible change;
  • trend: sustained directional change supported across time;
  • driver: force shaping multiple trends;
  • uncertainty: high-impact variable with materially different outcomes;
  • discontinuity: change that can invalidate the current system;
  • scenario: coherent plausible future, not forecast.

Tag source, date, geography, affected assumption, direction, maturity, confidence and time horizon.

2. Scanning discipline

The UK Futures Toolkit defines horizon scanning as systematic collection of emerging trends and weak signals and advises looking beyond usual timescales, sources and culture.1 Build a diverse source network and schedule scanning; otherwise urgent operational news dominates.

For each signal ask: what is observed, what mechanism could matter, what would confirm or weaken it, which decision is exposed, and by when?

3. From signals to scenarios

  1. Define the focal decision and horizon.
  2. map drivers and causal relationships;
  3. identify predetermined elements and critical uncertainties;
  4. construct distinct, internally coherent scenarios;
  5. explore customer, competitor, value-pool and capability consequences;
  6. stress-test options across scenarios;
  7. define no-regret moves, options, hedges and signposts.

OECD’s foresight toolkit uses a five-step process to challenge assumptions, create scenarios, stress-test strategies and develop action plans; it explicitly treats disruptions as plausible possibilities, not predictions.2

4. Avoid trend errors

  • extrapolating a short series;
  • confusing attention with adoption;
  • ignoring counter-trends and constraints;
  • treating global change as locally uniform;
  • assigning spurious probability to imaginative scenarios;
  • producing foresight without owners, triggers or options.

5. AI-native application

AI expands scanning breadth, multilingual coverage and relationship mapping. It also amplifies duplicated reporting, fabricated sources and popularity bias. Use whitelisted or scored sources, preserve original records, identify common origins, test retrieval completeness and require human scenario judgment.

6. APAC and Hong Kong application

Use global drivers with locally specific transmission mechanisms. For Hong Kong, consider trade and capital flows, tourism, demographics, regulation, Mainland linkages, professional services and infrastructure. Local official data supplies baselines; regional sources explain cross-border mechanisms.

7. Outputs and governance

Maintain a signal library, driver map, scenario set, assumption exposure matrix, strategic-option portfolio and signpost dashboard. Quarterly reviews should examine changed evidence, not rewrite scenarios for novelty.

9. Decision playbook

Maintain a small assumption exposure portfolio. For each strategic assumption record relevant drivers, confirming and disconfirming indicators, exposure if wrong, response lead time and accountable owner. Prioritise assumptions with high consequence and long response time.

Scenario quality depends on distinct causal logics, not imaginative prose. Each scenario should explain how it emerged, who gains or loses, which early indicators appear and how strategic options perform. The most useful output is often a changed present decision, not the scenario document.

OECD work on anticipatory capacity emphasises institutionalisation: skills, governance and integration into normal decision processes.3 This matters commercially because an occasional workshop does not create a sensing capability.

10. Failure modes

Avoid linear “more/less” scenarios, one preferred future plus token alternatives, probabilities unsupported by evidence and global megatrends detached from customer mechanisms. Do not assume a strong signal is an inevitable trend; actively scan counter-signals and constraints.

Review quarterly for evidence movement and annually for architecture, with event-driven review after discontinuities. Preserve prior versions so leaders can see whether the world changed or the organisation’s interpretation changed.

Sources

1UK Government Office for Science, *The Futures Toolkit* (updated 2024). https://www.gov.uk/government/publications/futures-toolkit-for-policy-makers-and-analysts/the-futures-toolkit-html

2OECD, *Strategic Foresight Toolkit for Resilient Public Policy* (2025). https://doi.org/10.1787/bcdd9304-en

3OECD, *Building Anticipatory Capacity with Strategic Foresight in Government* (2025). https://www.oecd.org/en/publications/building-anticipatory-capacity-with-strategic-foresight-in-government_d7eb0bb6-en.html

Apply this research

Turn the framework into a decision, evidence plan and practical next move for your organisation.

Discuss the decision