When something affects us, it has an effect on our decisions. A poor experience reinforces what we value based on the gap between what we expected and what happened. We carry the emotion associated with an issue forward into our next decision.
The link between emotion and outcomes is one of the pillars of behavioral economics and one of the reasons why how people experience a product, service, or situation is key to understanding consequences to an organization. With detailed data and proper analysis, we can go from a review or comment to uncovering an issue worth fixing.
Reviews signal an impact on buying behavior, but we must be careful not to draw hasty conclusions. Because when information is public the number of factors at play multiply. Biases, assumptions, and social signaling are all mixed in and need teasing out based on facts rather than opinion.
The process of turning data into knowledge requires experience and skill, not just talent and a good nose. How much similar data have we seen? What is the context? How do we go about parsing why someone says what they say? And how to we find the connection between what they say and what they will do?
We rely too little on cognitive processes and thinking and put too much faith on incomplete machines for answers. Psychology has had many of the answers of what really affects behavior for a number of years. Recently, we've added volumes of data on the influence of social currency and biases.
Contrary to common belief, machines are not as smart as human brains, they're just much faster at processing data and at correcting wrong inferences. So fast, that we think they have the answer when it is us putting the system together to seek for them. If we put the bias in, speed won't help.
Tapping into emotion
Behavior shows what we value. Emotion is important to uncovering why we do what we do, because much of our behavior comes from our subconscious mind. Emotion is thus a source of untapped insight in business.
When we're energized and enthusiastic about something, engagement is easy. But we don't get there with enthusiasm initiatives, or with incentives. Because when organizations implement them in the absence of cause-effect knowledge they end up rewarding the wrong behaviors.
Change management and culture initiatives are also problematic. Because what we really want is to make decisions that are better for the organization as a whole (and hopefully this means for customer experience.) An organization is a system with interdependence.
Execution needs to take into consideration all units and dependencies to fix and not merely patch problems. Organizations that want to promote a certain culture, or fix their existing culture, need to learn what behaviors help and what detract in reaching that goal. Only then, it's useful to reward those behaviors we want, and do it thoughtfully.
We should use similar thinking with customers in lieu of loyalty schemes that end up becoming mass-personalized (a misnomer) bribery programs because they don't reflect the individual preferences and needs of anyone. The average customer doesn't exist.
People feel heard when someone is listening. Monitoring is not the same as listening. We can only listen once, when we pay attention. Which means learning to listen better by also observing behavior.
If behaviors are key to shedding light on outcomes, and emotion drives behaviors more than we suspected, then understanding the context of decisions can provide the clues we seek to predict outcomes. To do that we need enough specific information about a situation or case to infer a value judgement.
Machines are so far falling short in doing this reliably or well. Which is why people are still involved in reading online comments and reviews, and responding in social media networks. Some say artificial intelligence (AI) and machine learning will eliminate that need.
Instead, when we remember what machines do really well, good cognitive computing will elevate the role of experience and skill not substitute for it. Speed and precision, based on factual data we cannot prove wrong, will support expertise.
Emotion ties to outcomes
The ability to think strategically, to make choices as new data becomes available, or to strategize, continues to be a valuable skill worth pursuing. Social network LinkedIn recently released data on the most promising jobs and in demand skills#.
The findings point to three trends:
- Most in demand skills are skills that have a strong expected value (the long-run average of a random variable) — leadership, communication, collaboration, and time management
- Customer focus is vital to thriving in business — reaching potential customers and ensuring current customers are successful with product are both critical for business success
- Technology is here to stay — many of the jobs of the future will require a degree of technical knowledge.
Engagement lead tops the list of most promising jobs with a Career Advancement Score of 10 out of 10. Top skills are management, leadership, project management, strategy, and communication, which depend on the ability to think critically, make decisions, understand process, align resources, and ability to persuade others.
How we reward people who can deal with dry systems — i.e. engineers and programmers — with much higher compensation vs. people who can deal with wet systems — i.e. human relationships — seems to indicate an understanding of complexity that puts bits on a higher scale than people in abilities to get results. As an avid student of both, I would contend the opposite to be true.
Skills like management and leadership have been harder to measure, so far. The difficulty in measurement is likely the reason for lower compensation of Engagement Leads compared to purely technical leads, despite the complexity involved with human behavior.
Rachel Happe, Principal and co-founder of The Community Roundtable says:
“I do think we will start to see a shift here as technology becomes increasingly cheap and commoditized, the relative value of great people/soft skills goes way up because it will be the scarce resource and the weakest link in the system. The organization that has the strongest 'weak' link will have a competitive advantage.”
For example, in leadership we can measure the behaviors of the people in the scope of a person's influence, and not just the outcomes.
The point is expertise is valuable, and skill in behavioral sciences should be as if not more valuable than technical skill, because it can lead to significant outcomes, like moving people to action. Understanding the role emotion plays in our lives is useful to connection. Emotional intelligence is critical to achieving more favorable outcomes in negotiations, for example.
When it comes to emotion, many organizations undervalue magnitude or intensity and overvalue frequency — losing precious signal in the noise. Superficial quantitative data is not enough to drive insights, nor it provides the full picture to predict future behaviors.
We carry our existing mental models about how things should work into our language. For example, typically we use affect as a verb to indicate we produce an effect on something. We use effect as a noun mostly. However, changing the way we look at things is useful to change the outcomes.
Psychologists use affect (the noun) to refer to feelings and desires as factors in thought or conduct. We communicate affect through emotion. In this sense, affect creates the conditions for us to effect (used as a verb) — to execute, produce, or accomplish something.
For better outcomes, learning to read emotion in context is key, along with developing an understanding of where we are on a range of possible outcomes.