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How social cognitive theory explains the mechanics of motivation

25.11.2025

⏳ 5 mins read

Motivation drives human behaviour because we always, consciously or not, organise our actions to meet specific ends. In a professional context, motivation is a driver for success in education and career. It’s surprising how little we learn about motivation in school. While motivations are expressed and gauged in job applications and interviews, I have never, in my 12+ years of experience, discussed motivation holistically during my employment or even in exit interviews.

In my opinion, most of us who accomplish individual and collective goals, consciously or not, modulate elements of motivation. To do so, we define goals (OKRs, SMART goals), utilise our skillset, let ourselves be guided by our values, regulate ourselves based on feedback (1:1s, retro sessions, performance reviews), and get rewarded for performance (promotions, value awards). But we were never taught the mechanics of this process.

In this blog, I’ve explained how the mechanics of motivation according to social cognitive theory can help drive individual and collective (team) performance. The variables of motivation have been briefly introduced with supporting ideas based on my experience and insights.

Although the target audience is roles in leadership, cross-functional collaboration, and Human Resources, I’ve simplified the concepts and supporting ideas to benefit every reader.

Concepts

Motivation

Although there are several definitions, at the crux, motivation is goal-oriented behaviour. There are six high-level variables that encompass the mechanics of motivation: Goals, Self-evaluations of progress, Values, Outcome expectations, Self-efficacy and Social Comparison.

Goals

Goals are what we consciously try to achieve. Commitment to goals is necessary to affect our behaviour.

The effects of goals on motivation depend on three properties:

Specificity – Goals with benchmarks trigger self-evaluations of progress and improve motivation. Specific goals such as “walk 5 km under 60 mins” make it easy to track progress through average split pace, which improves motivation until the goal is attained.

The nature of data mining, machine learning and AI projects makes them inherently specific because they are always about benchmarks in the end. Lucky for them, they don’t have to put in extra effort to define such goals. But for other projects, performance standards are necessary beyond OKRs and sprint goals, i.e., in tasks or user stories, to activate and improve motivation.

Proximity – Short-term goals enhance motivation more than long-term goals because it is easier to evaluate progress. Sprint goals or even task goals are in closer proximity than quarterly OKRs.

Consistently attaining goals can raise self-efficacy (explained below), which keeps us motivated even when met with difficulties in pursuit of other goals. Designing short-term goals (e.g. sprint goals or tasks) for success is necessary to raise self-efficacy.

Difficulty – The right level of difficulty makes us work harder and thereby increases motivation. However, overly difficult goals can demotivate, and very easy goals can lead to procrastination.

Principal or staff engineers are typically motivated by advanced topics in their area of expertise. For example, goals related to optimisation of GPUs for AI workloads may provide the right level of challenge for a senior engineer compared to setting up basic ML pipelines.

Self-Evaluation of Progress

Positive self-evaluations of progress sustain motivation. Self-evaluations of performance goals lead to higher motivation and achievement. A progress of having walked 3/5 km in 35 minutes will keep us motivated to walk the remaining 2 km in the remaining 25 minutes. Monitoring average split pace (a simple metric) can help us self-regulate to achieve the goal.

Lack of specificity in goals makes it hard to evaluate progress, which may not sustain motivation.

Outcome Expectations

We engage in tasks because of our beliefs in the expected outcomes of our actions. When we believe that our actions will lead to positive outcomes, we stay motivated even when the progress is slow—for example, in R&D projects.

Outcome expectations vary between individuals and projects. A developer working on a complex project may stay motivated because its success improves her visibility within the organisation. However, the outcome expectations of the project itself may be things like improved operational efficiency or enhanced customer engagement.

Roles in delivery (e.g., product owner, project manager) should ensure alignment on collective goals and outcome expectations of every contributor to keep the team motivated.

Values

Values are a significant contributor to motivation. However, I feel that somehow only Human Resources is considered responsible for them. Values can help people exert the force and effort required to reach goals. Attaching a value to outcomes helps us take (or avoid) actions necessary to attain goals. Thinking only in terms of company values can limit their role in our motivation.

For example, I greatly value knowledge and therefore am always highly motivated to work on tasks that involve gathering information, research, or investigation. Roles in leadership, project and product management should foster an environment where team members can identify and associate relevant values that help in attaining goals.

Self-Efficacy

Self-efficacy is our belief in our abilities to accomplish a task. It is what keeps us going despite difficulties in pursuit of our goal. A series of successes raises self-efficacy, whereas failures lower it. Lower self-efficacy can reduce enthusiasm when encountering difficulties and make people give up.

For example, creating performance improvement plans with goals that have excessively high performance standards can lower self-efficacy and defeat the purpose. Achievable goals with positive feedback on performance help raise self-efficacy.

Social Comparison

We tend to socially compare our capabilities and performance. Comparisons can result in higher motivation, especially when we learn from self-evaluations that we are competent or improving.

However, negative self-evaluations can reduce motivation.

In my opinion, social comparisons for performance at work do not make sense unless we work on identical tasks. However, they are useful when acquiring new skills, especially in the age of AI.

Conclusion

Motivation is not only about a value or something that deeply resonates with us. Motivation is a process with six variables. By examining each variable and depending on the situation, roles in leadership and cross-functional collaboration can take actions that activate, improve and sustain motivation. In my opinion, balancing objectivity (e.g. goal specificity, proximity) with subjectivity (e.g. values) is the most effective way to attain goals with high levels of motivation. 

I chose social cognitive theory because of familiarity, but I recommend exploring other theories (e.g. cybernetic control processes and self-determination theory) as described in The Oxford Handbook of Human Motivation to gain different perspectives.

My Rabbit Hole Path: What is Motivation? → Verywell Mind → Psychology Today → Wikipedia → Oxford Handbook on Human Motivation