Talk from Anticipation 2017 on stakeholder selection in collaborative foresight contexts

1. Peter Jones, Strategic Foresight & Innovation,
Assembling Requisite
Stakeholder Variety
in Foresight Practice

2. Peter Jones, Ph.D.
Associate Professor, OCAD University Toronto
MDes Strategic Foresight & Innovation
& Design for Health
• Strategic Innovation Lab – 2008 continual foresight design studies
• Co-founder of SDRN and Relating Systems Thinking and Design (RSD)
• Cognitive psychology, human factors, organizational studies
• Practice research & collaborative foresight advising firms, policy shops,
municipalities, government labs

3. Risk of Foresight Biases
• In foresight practice we often mix design methods in attempt to
enhance quality of scenarios & reduce reliance on one method.
• Triangulation (in research) compensates for systematic bias.
• (What are critical anticipatory biases?)
• We can decolonize foresight methods &/or, we can enhance variety.
• Cybernetics (& good sampling practice) aim for “requisite variety”
• Biases in variety of temporal cognition may impact our aims
Impair visioning & optionality in collaborative foresight.

4. Client participants can’t learn to be
long-term thinkers in the course of a workshop.
• We know that in futures workshops not “every voice is equal.”
• People have vastly different capacities for futures thinking and
“critical imagination.”
• Literacy can be trained, but not within a single workshop session.
• We always have a mix of cognitive biases at play in foresight.
• How can we leverage the variance in temporal cognition?

5. People & cognition are sources of all methods.
Jones, P.H. (2017). The futures of Canadian
governance: Foresight competencies for
public administration in the digital era.
Canadian Public Administration. (in press).
Figure modified from Popper, R. (2008). How are foresight
methods selected?” Foresight 10 (6): 62–89.
As we increasingly engage collaborative foresight …
Assemble groups of insight leaders …
Do our methods amplify
variety sufficient to insight
into/for complex future systems?
Robust methods vs.
anti-fragile samples (that
benefit from randomness)

6. Four points of systemic foresight failure …
When we neglect to foresee systematic temporality biases.
1. Cognitive biases in framing
2. Temporal cognitive bias in selection & sources of content
3. Horizon bias in the selection of stakeholders in group methods
4. Insufficient variety in representation
How would be know whether a project was vulnerable to these biases?
We might not.

7. Cognitive & systems theory may be useful.
1. Cognitive biases in problem framing
Who owns framing? Domain expertise critical & if missing we DKDK
2. Temporal cognitive bias in selection & sources of content
The evidence base. Convenience sources & broad signal scanning.
3. Horizon bias among stakeholders selected in group methods
Well-known issue in systems/cybernetics.
Self-selection bias, Recruiting bias, & cognitive biases in groups.
“Who represents the whole system of a future context?”
4. Insufficient variety in representation
How are foresight models & artifacts used in practice?
Tendency for temporal models to be used as extrapolations.

8. Make Methodology Fit the Human.
Underexamined contributions to foresight fragility…
• Sampling of stakeholders associated with a foresight question
• Positivist technological futures bias & ahistoricity
• Groupthink. Black swan insight from other-than-usual suspects
• Requisite Stakeholder Variety provides a reference model
• Mapping category sets to projected stakeholder influence
• Exposes risks & blind spots for oversampling biases
• Reveal variety by expanding & triangulating categories
Method of Evolutionary Sampling.

9. Multi-dimensional sampling by multi-category

10. Evolutionary sampling
• Initial mapping of sampling
categories to Question of interest.
• Dialectic between TQ <> Sample
• Requisite Variety both internal to
Q & exogenous to future system
• STEEP/CI ++
• Social Sectors
• Geographies
• Diversity ranges
• Systematic sampling to minimize
influence of systematic bias

11. Multi-dimensional sampling in action.
Requisite variety to the shared problem.
“Only variety can absorb variety.”

12. Temporality self-selection within groups.
“In what timeframe do you personally prefer to
imagine and plan for significant change?”
STRATEGIC PERFORMANCE
Fit or harmony with future environment.
Horizon 1 “Near” Horizon 2 “Mid” Horizon 3 “Far”
TIME
Anthony Hodgson, Decision Integrity Limited, www.decisionintegrity.com

13. Temporal self-selection within groups.
Typical proportion of horizon bias exhibited within my groups:
• High tech & Engineering
• Startup entrepreneurs
• Social innovation
• Civil service
Horizon 1 “Near” Horizon 2 “Mid” Horizon 3
“Far”

14. Groups self-select to produce trends & temporal scenarios
Mapped in Three Horizons

15. Thanks.
References
• Ashby, W. R. (1958). Requisite variety and its implications for the control of complex systems.
Cybernetica, 1, 83-99.
• Taleb, N. N. (2012). Antifragile: Things that gain from disorder (Vol. 3). NY: Random House.
• Jones, P.H. (2017). The futures of Canadian governance: Foresight competencies for public
administration in the digital era. Canadian Public Administration. (in press).
• Popper, R. (2008). How are foresight methods selected? Foresight 10 (6): 62–89.
• Curry, A., & Hodgson, A. (2008). Seeing in multiple horizons: connecting futures to strategy.
Journal of Futures Studies, 13 (1), 1-20.
• Weigand, K., Flanagan, T., Dye, K., & Jones, P. (2014). Collaborative foresight: Complementing long-
horizon strategic planning. Technological Forecasting and Social Change, 85 134-152.
Peter Jones, Ph.D.
Strategic Innovation Lab slab.ocadu.ca
pjones@ocadu.ca
@redesign