Ladder of Inference

“M𝘆 𝗺𝗮𝗻𝗮𝗴𝗲𝗿 𝘄𝗮𝗹𝗸𝗲𝗱 𝗽𝗮𝘀𝘀𝗲𝗱 𝗺𝗲 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘀𝗮𝘆𝗶𝗻𝗴 𝗵𝗲𝗹𝗹𝗼, 𝗜 𝗺𝘂𝘀𝘁 𝗯𝗲 𝗶𝗻 𝘁𝗿𝗼𝘂𝗯𝗹𝗲”

We all know that trust is the foundation of any high-performing team - whether you're managing portfolios, programs, or projects. Without it, success is tough to achieve.

The first step in building or rebuilding trust is understanding what causes mistrust. 

During our Ignite Big-Room Planning Workshops, we dedicate time to helping teams better understand each other’s communication and working styles, leveraging the Insights Discovery diagnostics. Robert Cass often refers to the Ladder of Inference, developed by Harvard professor Chris Argyris.

The ladder of inference is a model that illustrates how people make decisions by going through a series of steps. It's a way to understand how people interpret events and take action based on their beliefs and assumptions. 

Steps of the ladder of inference 

1) Observable Data: What we see or hear.

2) Selecting Data: We filter the data based on personal experiences, beliefs, or values.

3) Adding Meaning: We attach meaning to the data based on our own context.

4) Making Assumptions: We make assumptions based on the meaning we've assigned.

5) Drawing Conclusions: We form conclusions about people, situations, or events.

6) Adopting Beliefs: We adopt beliefs based on our conclusions.

7) Taking Action: Our actions are based on our beliefs.

The ladder of inference can help people avoid jumping to conclusions and make better decisions. We can analyse each step of the process by asking ourselves what we are thinking and why. 

This model helps teams recognise how quickly they can make assumptions and jump to conclusions, often without realizing it. By slowing down and reflecting on how we process information, we can create more open, transparent communication—a critical element of building trust.

Teams need to recognise that everyone operates from a different set of beliefs, assumptions, and experiences. Often, misunderstandings arise because people jump too quickly up the ladder, especially when they don't fully understand the data or make assumptions based on incomplete information.

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AdaptivOrg + Seisma, SEISMA GROUP, Insights

Robert Cass 🟢 🟡 / 🔵 🔴, Sushrut Kamath, Jason Wu, Annie Spiteri, Devon White, Anthony Kandi, Betty Trajkovski, Simone Hambrook, Robert Hogeland