Accenture Banking Blog

A key part of behavioural science lies in the second word: science. A focus on science, data, and analytics can make behavioural science a valuable tool for enabling change. In this blog post, I want to look at the data-driven aspects of behavioural science: how it enables us to extract insights in the first place, and how we can use data and analytics to scale successes.

A data-driven approach to behavioural science

Our approach to behavioural science is multidisciplinary—incorporating behavioural economics, psychology, neuroscience, and more—as these each provide different perspectives on human behaviour and decision making. This approach enables us to understand human biases and why it’s difficult to change. It also enables us to uncover what inspires people at individual, team, and enterprise levels to change their mindsets to achieve a vision or strategic goal.

As behavioural economist Dan Ariely says, behavioural science involves identifying two factors: what fuels change to inspire people and drive new behaviours, and what creates friction to stand in the way of transformation. (Notably, Ariely is now Chief Behavioural Officer at Lemonade, the insurtech that can pay out one-quarter of its claims within 3 seconds.)

At Accenture, we apply behavioural science to help organisations change their mindsets or behaviours at scale. For example:

  • Structured experiments require firms to track change on running experiments by using randomised control trials or A/B/n This enables you to test and learn with agility. Importantly, it also identifies what works and what doesn’t. You can apply data from experiments to inform future change interventions.
  • Open experiments can help people spark new behaviours through microchallenges. For example, there may be a uniting vision or purpose, but individual leaders and teams are empowered to define their own challenges to achieve them. This encourages grassroots change. We’ve seen that open experiments can encourage people to act out or try on new behaviours—and in the process, form new habits and beliefs that they didn’t think was possible before.
  • Large-scale analytics can look for patterns in behavioural data to understand how people behave. Analytics can provide insight into how people behave today, and how that is changing in different groups.

And we recently welcomed ?WhatIf! to the Accenture family. For over 25 years, ?WhatIf! has helped clients innovate for growth. You can watch my conversation with the firm’s co-founder Matt Kingdon about how remote teams can innovate through uncertainty.

Experiments and analytics can help identify what fuels change to inspire people and drive new behaviours—and what creates friction to stand in the way of change.

Case study: Analytics and data-driven experimentation is good for teams and leaders

One UK tier-one financial services provider used controlled experiments to challenge the status quo and achieve cultural change at scale. It identified a sample population and identified which behaviours worked on small scale before rolling them out more widely.

One experiment featured a leader handing over decision-making responsibilities to her team for a week. At the end of the week, the data showed that 98 per cent of the time, the team made the same—or better—decisions the leader would have made.

What does this tell us? That delegating responsibility has a dual purpose. First, it enhances team performance by empowering people and increasing their commitment to a shared vision. Second, it frees up leadership capacity—by half a day, in this example.

More nudge, less sludge

Finally, we all have a duty to use behavioural science ethically and responsibly. The world doesn’t need any more automatic subscriptions to newsletters you don’t want, or airlines pressuring you to buy things you may not need, such as hotel packages, rental cars, and insurance extras. (Interventions like these, which don’t keep a person’s best interest at heart, are called ‘sludge’ in behavioural science.)

Similarly, to create lasting change, we need to approach change with a growth mindset and encourage people and teams to find their own paths. This applies to coaching programs, as well. For example, positive coaching programs can help people connect their change journey with inner purpose or self-image, rather than fix a problem. Richard Boyatzis, Melvin Smith, and Ellen Van Oosten have interesting perspectives on the difference between ‘coaching for compassion’ by helping people discover how they would like to grow, and ‘coaching for compliance’ to close the gap between current capabilities and some aspirational or organisational standard.

When done right, behavioural science nudges people to do the right thing in a way that’s cool, not creepy—and, obviously, in line with the vision and purpose of the underlying transformation.

Used ethically and responsibly, behavioural science can inspire people to do the right thing, not just tick a box or manipulate them into a new behaviour.

Ultimately, we all win when we put people at the focus of a multidisciplinary, data-driven and ethical approach to applying behavioural science. It allows organisations to transform with people, identify opportunities to fuel change, and mitigate sources of friction that could hinder the transformation journey. It enables behaviours that matter for the future, grounded in interventions that work.

Behavioural science can inspire a sense of belonging and unlock desired mindsets. And that’s not just good for an organisation. It empowers people to take agency for their mindset and actions and provides purpose that aligns with a greater vision. In addition, people that are equipped for change can be more adaptive to future change.

Key takeaway? Behavioural science and people are at the heart of transformation and better performance.

In my next post, I’ll outline the five steps to using behavioural science to enable change.

To find out more about how to use behavioural science to put people at the focus of transformation, please contact me here, or @andyyoungACN on Twitter.

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