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A technical glitch has left our fifth briefing arriving in your inbox twenty four hours later than intended—sorry about that!

This week's featured article attempts to size the intention-action gap—the infamous deviation between someone’s intentions and their actual behaviour—only to discover that the gap on average is really, really big.

The findings:

Someone’s conscious attitude and commitment toward a goal or behaviour, also known as their intention, predicts only 28% of their actual behaviour. The remaining 72% of behaviour is heavily swayed by intangible and often difficult to capture variables like cognitive resource availability, emotional reactivity and resonance, social influence, and personal salience.

Why it matters for you:

• Intentions are often used as a proxy for behaviours that are critical to how we calibrate strategy, design products and estimate market fit, calculate financial or reputational risks, forecast ROI expectations, and plan transformational programs. In the case where estimations hinge on behaviour change, missed targets are inherently bound to the gap.

• Defining and qualifying intentions that underlie your big bets—whether that is the adoption curve within your transformation strategy or the demand curve and market potential for a new product—will allow you to better calibrate for and design to close the gap. Your outcomes will materially improve as a result.

What you can do about it: 

• Double down on data-driven evidence (e.g. deviation analytics, predictive and machine learning, agent-based simulation modelling, natural language processing of unstructured data, behavioural segmentation) to calculate business case assumptions and define product requirements.

• Weave intention-behaviour metrics into the balanced scorecard and/or OKRs to drive adaptive planning, guide feature and functionality prioritization, and feed into feature engineering for behavioural segmentation models.

• Launch pilot programs to test strategic initiatives on a small scale before full implementation, allowing for adjustments to the program or product based on observed behaviours and outcomes.

Explore the intention-action gap deeper by pasting these prompts into your favourite generative AI platform:

• What are some common models to explain the intention-action gap, and how can these models inform the way I build my product strategy / conduct strategic planning / estimate transformation costs / calculate ROI

• What factors contribute to the intention-action gap in the case of achieving strategic goals, and what are some tools we can use or activities that we can do to identify those factors?

• What types of interventions have been effective in bridging the intention-action gap, and how can we implement them into strategic frameworks / product design / feature prioritization?

Oh, one more thing!

Some of you reached out to let me know that the fourth briefing article on future-self continuity led you meandering down a journey of particle filters (oops!) For those who are looking for the actual article, this link should do it!

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