How to Bridge Differences using a Ladder of Inference

Throughout our daily lives – both in professional and personal contexts – we experience differences of opinion with others. Examples include “that movie was bad vs. that movie was good”; “I deserve a raise vs. you don’t deserve a raise”; “Chris and Pat are well-suited for each other vs. Chris and Pat are a terrible couple”; “the prospect will probably buy our services vs. the prospect isn’t interested in our services”. We often find ourselves either arguing with the other person to convince them of the veracity of our opinion. Or, we find ourselves walking away from the unresolved situation frustrated, “agreeing to disagree”.

The problem is that, especially in a team-driven business environment, unresolved differences of opinion can lead to impasse, missed opportunities, and a corrosive situation.

To bridge these differences, Chris Argyris of the Harvard Business School developed the Ladder of Inference. It is a tool that explains how people draw conclusions and, if discussed explicitly, that can be used to resolve dissension. The tool is a metaphor of a ladder with ascending rungs.

Step 1: Observation

According to Argyris, each person observes a different subset of the real, objective data that they are exposed to. Their past experiences, culture, and other subjective factors determine which data gets included in their particular subset. For example, when you walk into a conference room you might first notice how many chairs there are, if there is a speakerphone available, and whether there are flip charts. You do this because you have been “programmed” to view conference rooms as prospective venues for your meetings. Conversely, when Joe walks into the conference room he might first notice the ceiling tiles. After all, Joe is in the ceiling tile business. The bottom rung of the Ladder of Inference is the objective data; the next rung up is the subjective subset or the “observed data.”

Step 2: Interpretation

Each of us interprets our respective observations – this is done almost instantly, and usually subconsciously. Interpreting data is how we make sense of what we notice, how we attribute meaning to what we see and hear. Again, our interpretations are colored by our past experiences, culture, and other subjective factors. For example, an American might view interrupting someone as being rude, while someone from the Middle East might view it as a sign of being interested and engaged. Thus, the second rung from the bottom is “interpretation”.

Step 3: Conclusion

Finally, we draw conclusions based on our interpretations. Our “conclusions” or opinions make up the final, top rung of the Ladder.

Needless to say, this is a highly efficient process that we rarely even think about. When we see a chair, we don’t have to analyze its shape, parts, materials, etc. Instead, almost instantly we proceed from data observation to conclusion, knowing that it is a piece of furniture on which we can safely sit.

At the same time, quite often there is a lot of subjectivity in this process. Our observed data is limited. Our interpretations are also subjective – given the same data, two people might have different interpretations. And, of course, our conclusions are subjective.

Moreover, when we are exposed to the pool of objective data, we tend to focus on the data that confirms our opinions and biases, and ignore the data that refutes them. For example, if one adopts liberal political views, they are likely to gravitate toward liberal talk shows and newspapers. If they have a negative view of a colleague, they are likely to notice the bad qualities and behaviors. Similarly, if they have a positive view, they are likely to extend the benefit of the doubt or assume a positive interpretation.

Points of Difference

Argyris points out that when people disagree, they tend to discuss things at the top rung, conclusions. His advice is to compare the different rungs of the parties and unpack each party’s thinking – their data, interpretations, and conclusions. When we disagree, we should ask questions that expose the other party’s Ladder and advocate in a way that reveals our own.

Using the Ladder

Let’s referring back to the example of you and your colleague emerging from a client meeting. You might ask your colleague, “What did you see or hear that makes you think that the client is going to use our services (what is your observable data)?”

Your colleague might tell you that she noticed that everyone came on time and that nobody left early. She might add that no objections were raised and that people were nodding their heads (to each other, whenever you faced the presentation screen and had your back to the audience). When asked how she interprets that data, she might say, “Coming on time shows that they took our meeting seriously, remaining in the meeting indicates that they thought we are relevant, a lack of objections implies understanding and agreement, and nodding is indicative of being impressed.” Now that you’ve heard the lower rungs of their Ladder, it’s no surprise that your colleague concludes, “They are going to use our services.”

You now share your observed data: none of the attendees control a budget, some people in the back were fidgeting, and the company is Japanese. You explain to your colleague how you interpret your data – the absence of people that control a budget means that a prospect doesn’t take a meeting seriously, fidgeting is a sign of disinterest, and in Japanese culture nodding and not interrupting doesn’t necessarily imply agreement. And, you explain that, in light of these observations, you had concluded that the client isn’t interested in your company’s services.

Informing a Sound Decision

Using the Ladder of Inference doesn’t point to who is right and who is wrong, per se. Instead, it surfaces important data that either party might have overlooked (e.g., you weren’t aware that people were nodding to each other when your back was turned, your colleague wasn’t familiar with Japanese culture) and allows for new, and perhaps shared interpretations and conclusions. Similarly, using the Ladder of Inference helps one become more aware of one’s own thinking and reasoning, through reflection.

Needless to say, using the Ladder of Inference in conversation can be challenging. For example, when a “fact” seems especially self-evident, be careful – regardless of how obvious it seems, it should be verified by more than one person’s observation or by a technological record (a tape recording or photograph). Otherwise, you are vulnerable to different interpretations and conclusions.

Integrated into team practice, the Ladder of Inference becomes a very healthy tool. In the words of Peter Senge, “There’s something exhilarating about showing other people the links of your reasoning. They may or may not agree with you, but they can see how you got there. And you’re often surprised, yourself, to see how you got there, once you trace out the links.”