Time Is Money: How Mental Accounting May Influence What We Spend Our Time On

We’ve all heard that time is money. Though like money, time is a scarce resource that can be consumed, saved, and invested.1 A question then arises: Are we susceptible to the same cognitive biases we encounter in the financial world when making decisions about time? 

Mental accounting, a theory introduced by Richard Thaler who is a founding father of behavioral economics, is an example of a common bias in finance2 that describes the tendency for people to categorize their money into separate non-fungible accounts — or accounts that distinct from each other. Common accounts include savings accounts, chequing accounts, and retirement accounts, which have funds allocated to them based on their source or intended use and often result in irrational decision-making. 

Mental accounting: how it hurts, how it helps

We have all, at least at one point in our lives, surrendered to mental accounting bias. For example, people often spend money earned unexpectedly — such as lottery winnings or gift money — faster than steadier streams of income, and on items of less importance. People also have a tendency to delay purchases for important items because their mental account for them is depleted all while they continue to spend money on less important things. Undoubtedly, these decisions violate economic rationality, which posits that money is a fungible resource whose value remains constant irrespective of its source or intended use. 

Nevertheless, mental accounting bias can also be helpful in some instances; it’s often what allows people to save money in their emergency, retirement, or children’s education funds. By refusing to use money from these highly important accounts regardless of the circumstances, people are able to protect their futures at a small temporary cost. 

Mental accounting and time

Given the aforementioned similarities between money and time, can mental accounting also influence our decision-making when allocating time? Research suggests that the answer is yes.

It is theorized that after people consume the time necessary to satisfy their physiological needs (i.e. eating, hygiene, sleeping), they allocate time towards either consumption (leisure) or production (work) with the ultimate goal of maximizing their total well-being.3 

One series of scenario-based experiments aimed to better understand how our perceptions of time vary based on if the context is a work-related activity or a leisure activity.4 As it turns out, we treat time gained from the postponement of a work-related activity differently than time gained from the postponement of a non work-related activity. We also have an innate threshold for how much time we spend on work-related tasks; we tend to allocate a majority of the time gained to non-work related activities regardless of the source. Such examples include cancellations of plans and completing a task earlier than expected.

From this research, it is clear that the economically rational assumption that money is fungible is often violated. Additionally, it shows that we have separate built-in mental accounts for work and leisure and that we attempt to balance our activities according to these preset expectations.

So what? How can this knowledge help us?

Practical applications

By recognizing how mental accounting may affect the way we allocate time in our daily lives, we can improve our habits to better achieve our goals. 

A classic example of mental accounting in the real world is the problem of finding taxis on a rainy day. Taxi drivers often have a mental account of a daily income target that they aim to achieve. When it’s wet outside, the demand for taxis is often higher, allowing taxi drivers to hit their daily targets faster and ultimately go home earlier. However, this is not economically rational. After all, if drivers are making money at a faster rate on rainy days, they should work longer on these days, which would then allow them to work less on slower days. 

The lesson from the taxi example can be valuable for those of us who are trying to maximize our productivity. Oftentimes, our mental accounts for work and non-work activities may set limits on how much we work on a certain day. If we are feeling very productive on a certain day, celebrating this productivity may only hinder how much work we can get done. 

Similarly, on days that we are feeling unproductive, struggling to be productive may end up being a waste of time, as this time may be better spent rejuvenating ourselves. Being aware of our mental accounts and realizing that we can transfer time to different accounts can ultimately boost our productivity. If you ever realize that there are times where you are wasting high-value productive time, take a step back and think about how you could better allocate your mental time account. Try to override your mental accounts, adjust your mental budgets to your daily mood, and maximize productivity.

The above application discusses how recognizing that time is fungible can be helpful. In some situations, however, it may also help us to cater to our automatic tendencies. Understanding how we mentally budget time can also help us minimize procrastination. One of the main explanations for why we procrastinate is present bias, which is our tendency to overvalue short-term benefits and underestimate the long-term consequences of a decision, resulting in a search for instant gratification and cognitive dissonance with our goals.5

We may be able to use mental budgeting to our advantage by effectively minimizing the influence of present bias. The results of the study described above show, once we decide our mental time budgets, we often try our best to balance and abide by these budgets. Therefore, employing mental budgets to plan our days may be more beneficial in helping us achieve our goals than traditional day schedules.

For example, let’s say a college student named Jack is planning out his Saturday. Jack, like many, may plan out his day like this:

11:00am – 1:00pm: Homework

1:00pm – 1:30pm: Lunch

1:30pm – 4:00pm: Homework

4:00pm – 6:00pm: Social Time

6:00pm – 8:00pm: Work for club

8:00pm – 8:30pm: Dinner

8:30pm – 10:00pm: Homework

However, if Jack finds himself procrastinating often, he might actually benefit from thinking of his responsibilities in terms of time accounts — 6 hours for homework, 2 hours for club work, and 2 hours for social time, for example. By doing so, Jack’s focus for the day is to stick to these time accounts rather than the schedule.

Finally, another application for this research in our daily lives is managing our work-life balance. If you are someone who often struggles with this, try using mental accounting to ensure you are dedicated to both aspects of your life. For example, if you have a tendency to get absorbed with work or other responsibilities on the weekend, it may help to label a certain time period of Saturday (i.e. Saturday evening) as “family time.” By doing so, your decision on Saturday evening is not whether you should do work or spend time with the family. Instead, the decision will be between going to the aquarium or going on a hike. 

Ultimate takeaways

Mental accounting can be both detrimental or advantageous to our decision-making when allocating both money and time. We must also keep in mind that our preferences for how we want to allocate our time are heavily dependent on various individual and situational factors. Additionally, as Kahneman and Tversky described, it may not even be worthwhile to try to adjust our mental accounting biases because fixing one aspect of the problem may just create other problems.6 Perhaps, the question we need to answer for ourselves is if the benefits from adjusting our time allocation decisions outweigh the cognitive costs associated with making these adjustments.

Fitting The Behavioral Science Piece In The Organizational Puzzle

I often joke that if a contest for the most mysterious job title in my company existed, I would be the clear frontrunner. It seems as if every time I’m introduced to someone, I’m asked the same question: “So, exactly what do you do?”

This week marked my two year anniversary of working as a behavioral scientist in a product-driven tech company, and I still don’t have an exact answer to that question. But, having worked my way through the company, I’m now in a comfortable position to think about the question more clearly at least. 

My biggest realization about this role is a double-edged sword: Behavioral science actually overlaps with many roles in product-led tech companies. That’s good because that means behavioral science is becoming increasingly relevant to everyone, irrespective of what role one is in. That’s also bad because the onus of proving the importance of a stand-alone behavioral science role is entirely on us.

Based on my experience, I’ve put together some thoughts on where product organization and behavioral science overlap, and what differentiation a behavioral scientist can bring to an organization as a whole. 

Is behavioral science the same as user research?

In a generic sense, yes. User research is, rather obviously, about understanding users. Behavioral scientists do the same; yet, the nuance is in the process.

User research teams conduct qualitative research through in-depth interviews, discussions, and usability tests. They also conduct quantitative research through surveys. This research is then condensed into a form that product and design teams can consume and use for the product development.

Behavioral science research is more focused on uncovering the reasons behind why people do what they do. While interviews and surveys are useful techniques, it is more important for behavioral scientists to understand the context under which decisions are being made. Doing so helps them use that context to map and diagnose the behavior of the user. In other words, putting into words what the user cannot say. This comes not just from interviews, but from experiments and observations and conducting literature reviews of existing theories.

Can user research benefit from behavioral science?

Absolutely. If you are a user researcher and you have a behavioral scientist in your organization, integrate them into your research to help you uncover biases and blindspots that are not necessarily visible in plain sight.

Is behavioral science the same as design?

As someone who loves all things design, I wish that this answer is a yes. A designer in a product organization focuses on putting the product into a visual form, taking into account the users’ and the business’ needs. This is a highly technical process that involves immense stakeholder management and a deep understanding of how various systems interact in the backend, with the goal of producing a front-end that is simple enough for the user.

Behavioral design is a subset of design that is concerned with using design elements to affect behavior change.1 Borrowing heavily from behavioral science, this stream helps designers design for the real user — the one who is busy, inattentive, biased and not perfect, as opposed to the perfect user (who may or may not exist). 

Can design benefit from behavioral science? 

Absolutely. Behavioral science helps designers understand the actual user, rather than the theoretical user. If you’re a designer and you want to involve a behavioral scientist, reach out to them in the initial phases of design. They can help you understand the ‘why’ behind what people really do. It is immensely beneficial to get a behavioral scientist to audit your design from a behavioral perspective so you can uncover fail points early on in the process.

Is behavioral science the same as data science?

No. Data science is a field that analyses structured and unstructured data using machine learning and algorithms to extract useful insights, as well as predictive models.2 Data Scientists typically use mathematics, statistics, analysis, and machine learning to investigate existing patterns in data. The models that they create feed directly into products, making them smarter. For instance, if you have used Spotify and love the recommendations the app gives you, that’s the output of a data science model at work, which takes into account your music preferences and a bunch of other variables to predict what songs you might like.

Behavioral science, on the other hand, puts the predictions of data science models into the real world and helps drive the ‘last-mile’ behavioral change.3

Can data science benefit from behavioral science? 

If examples are anything to go by, then yes. The 2012 Obama presidential campaign was a groundbreaking experiment that employed data scientists to predict voter behavior, which was then used to optimize marketing resources.3 The distinctive part about the campaign was the complementary use of behavioral nudges along with data science models. The data science models could accurately predict which way a voter was likely to vote. But the campaign’s main objective was to sway voters to vote for Obama, and that’s where behavioral science comes in. The campaign team was able to get more votes in their favour by using nudges in communications towards those who were undecided, or not likely to vote for Obama. In other words, behavioral science provided the “last mile” connect that the data science models needed to reach the voter.

If you are a data scientist and you want to see your models being used to drive real behavioral change, reach out to a behavioral scientist — they might just know exactly what to do.

Is behavioral science the same as product marketing?

Not quite. Product marketing is the connection between business and product, and is a critical part of the product life cycle. Before a product is launched, product marketers create the positioning and the go-to-market strategy based on user research. During the launch, they help business teams understand the product and drive its adoption through campaigns.4

Behavioral science plays a critical role in parts of this process, such as providing a deeper understanding of the consumers’ behavior, conducting a diagnosis of the users’ current behavior to identify biases, and identifying interventions in communications that can nudge the adoption of a product.

Can product marketing benefit from behavioral science? 

I’m sure you’re seeing a pattern now, but the answer is yes.  Product marketing relies heavily on understanding users and creating positioning based on that. However, marketing thrives on insights, and behavioral science can help unravel insights that allow a product to be positioned better.

A simple example of this is the difference between explicit and implicit goals.5 If you are marketing a food delivery app, the explicit goal is to make it easier to order food. This is what you would learn from talking to consumers. But, if you were to dig deeper to understand the implicit goal, you might uncover the goal of “excitement” — that is, when customers order food because they want every meal to be a surprise and different from what they’ve had previously. The product positioning then changes from convenience to a more nuanced “variety with convenience”. So, if you are a product marketing manager, talk to a behavioral scientist to uncover insights that might help position the product better.

Be all, end all?

My advice seems to be that everyone in the organization should talk to behavioral scientists. But, my intent is the opposite of that. I want behavioral scientists to proactively reach out to others in their organizations to offer insights. The simple truth that runs the world is “ask, and you shall get”. A stand-alone behavioral science role comes with the responsibility of proving its value, and this will happen only and only through collaboration. So, if you are a behavioral scientist in a product organization waiting for someone to give you a project, don’t waste your time. Instead, reach out and tell others how you can add value.

COVID-19 May Worsen Biases During The Hiring Process. Here’s How That Can Be Avoided

COVID-19 has disrupted the lives of millions worldwide. It is estimated that unemployment in the US alone will hit 32% — that’s 47 million recent graduates, experienced professionals, minorities, and overseas professionals.1 There is no doubt companies will start to hire skilled and unskilled labour in substantial numbers as we pull through this crisis. But, the ‘new-normal’ presents new challenges for Human Resource (HR) managers. Ethnicity and race-based biases have become more entrenched — all while marginalized communities are suffering disproportionately from the impacts of the virus itself. 

As we rebuild from COVID-19, individual and group identities will emerge based on one’s experience during the crisis. It might then become far too easy for us to judge others based on their past behavior; for example, compliance with quarantine rules, actual infection status, race,2 and perhaps most importantly, job status during the crisis. Such information could create pitfalls that HR managers may find themselves in when evaluating candidates.

By drawing on behavioral science insights, HR managers can develop a new set of tools that can help their evaluations remain unbiased.

Research shows that person-organization fit and person-job fit are established predictors of performance.3 However, these fits don’t always occur because of large informational asymmetries between organizations and job aspirants.4 For example, job applicants may be influenced by a range of factors including perceived job value, perceptions of interview performance, cultural norms, beliefs and interests, and even the wording of the job posting itself. Conversely, the recruiting team may unconsciously attribute certain qualities to specific demographics, and may have an affinity for people with characteristics similar to those who they are familiar with. From this, applicants may be discriminated against on account of their race, gender, or other demographic factors, including where they live or go to school.5,6

In order to reduce the impact of these biases, HR managers can take the following steps: 

Carefully craft job descriptions to remove bias

The wording of job ads matters. When job ads include more masculine than feminine wording, women find these jobs less appealing.7 For example, job postings that state “we will challenge our employees to be proud of their chosen career” or “you will develop leadership skills and learn business principles” are more likely to attract males when compared to “we nurture and support our employees, expecting that they will become committed to their career” or “you will develop interpersonal skills and understanding of business.” Ad wording can also impact how different demographic groups view the organization.8

Anonymize resumes to remove bias against specific groups of people

A racial gap in labour market outcomes exists – we know that African-Americans face differential treatment when searching for jobs such as getting fewer callbacks for each resume they send out.9, 10 There is evidence to show that East Asians may face discrimination in the coming months as well.11 Research shows that bias can be removed by anonymizing resumes in the job screening process. 

Evaluate candidates jointly to help reduce bias against the marginalized

Gender bias in the evaluation of job candidates exists across business, government, and academia. An “evaluation nudge”, in which candidates are evaluated jointly rather than separately, can stop evaluators from relying on cognitive shortcuts, such as group stereotypes. This will focus evaluators’ attention on what they should be doing — evaluating the ability of candidates. Joint evaluation can help address bias against groups other than women, as evaluators have access to more information than they would if they evaluated candidates separately.12 

Use structured interviews and tests to ensure objectivity and fairness

The unstructured interview as a predictive technique is unreliable because of its lack of validity. Research suggests that structured interviews — in which the questions to be asked are predetermined and are directly related to the job — are far more effective in ensuring objectivity and fairness. HR managers must try and articulate attributes they look for in candidates as objectively measurable criteria.13

HR managers will have their hands full as they start evaluating millions of applicants who wish to re-enter the job market when the economy starts to recover. The financial and time-related costs of unbiasedly evaluating candidates are low, and the benefits can be long-lasting and immense. HR managers just need the will to do so.