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Another meeting invite: to decline, or not to decline? Get into the habit of saying no.

Ludek Stehlik

People & Data Scientist

December 2, 2020

16

min read

Gregory (Scotland Yard detective): "Is there any other point to which you would wish to draw my attention?"

Sherlock Holmes: "To the curious incident of the dog in the night-time.

Gregory: "The dog did nothing in the night-time.

Sherlock Holmes: "That was the curious incident."

By referencing the above exchange between the famous sleuth and a Scotland Yard detective, I wanted to bring to your mind the proverbial "the dog that did not bark" case. It appropriately opens this blog post’s topic: the surprising importance of meetings that are missed (or should be missed) in our calendars because we have declined (or should decline) them for our own good.

Diagnosis: Suffering meetingitis during remote work

The current workplace is full of various distractions, and we often fight a futile battle in defending our time for things that matter to us. For white-collar workers, it's too easy today to get overwhelmed and exhausted by a continuous and never-ending stream of emails, instant messages, off-line and virtual meetings, notifications or phone calls. Meetings are an all-too-common distraction culprit. A sad fact is that the typical (U.S.) employee spends approximately six hours per week in meetings, i.e. 15% of her working time. If you are a manager, this increases to a disturbing 60% of your working time.

An unfortunate takeaway is that it seems - based on the data of some of our clients - that meetings took more rather than less of employees’ working time after COVID-19 pandemic forced many to switch to remote work. Many companies moved to work-from-home (WFH) mode in February 2020. The trendline of typical (median) time spent in both online and non-online meetings per employee, displayed in Graph 1, is higher after this date. 

Graph 1: Median number of hours spent in online and non-online meetings per employee during the last 12 months. There are three facts worth mentioning: a) There is a clear, increasing trend of the proportion of meetings that were conducted online after February 2020 when companies were forced by anti-COVID-19 measures to switch into WFH mode. b) This trend mirrors the development of COVID-19 pandemic over time in the region (back to “normal” in May and June, holidays in July and September, and a new attack of pandemic in September and October). c) The overall number of hours spent in meetings (counting online and non-online meetings together) per employee has increased in comparison with time before January 2020.

We can easily speculate about the causes of this trend. Among plausible hypotheses, there is the case for increased uncertainty, which calls for better alignment. Broken informal channels of communication are also a factor, e.g. quick exchanges at the desk, small talk around the coffee machine - most communication outside official meetings. There is also a greater eagerness for online meetings, given how easy they are to organize and conduct, in comparison with in-person meetings.

The first two hypotheses are supported by the fact that time spent in in-department meetings grew relatively more than time spent in cross-department meetings (or external meetings) after January 2020. Actually, the median proportion of time spent in in-department meetings grew at the expense of two other types of meetings (see Graph 2). The first two hypotheses can also be responsible for the increased proportion of time that employees spent in larger (9+) meetings after February 2020 (see Graph 3).

Graph 2: Median number of hours spent in meetings with different types of relationship between their attendees during the last 12 months.

Graph 3: Median number of hours spent in meetings that differ by their respective size (i.e. by number of attendees) during the last 12 months.

The third hypothesis is then supported by the fact that online meetings tend to be larger than non-online meetings (see Graph 4). This, unfortunately, counteracts their otherwise advantageous property of being typically shorter than non-online meetings (see Graph 5).

Graph 4: Average size of online and non-online meetings during the last 12 months.

Graph 5: Average length of online and non-online meetings during the last 12 months.

To decline, or not to decline?

Unfortunately, when it comes to meetings, quantity does not always go hand in hand with quality. People usually complain that they waste a lot of their time in pointless meetings that have no value to them. According to a survey conducted by Igloo software, 47% of employees consider meetings to be generally unproductive. It is thus more than appropriate to paraphrase Shakespeare's Hamlet: 

“To decline, or not to decline: that is the question:
Whether ‘tis nobler in the mind to suffer
The slings and arrows of overpopulated meetings,
Or to take arms against the sea of discussions,
And by declining, shorten them?”

Declining a meeting invitation is one of the basic tools we have for protecting our limited time resources. Despite the ease and straightforwardness with which it can be used within our daily routines, it is highly underutilized. As you can see in Graph 6, the recent typical decline rate for our sample of companies lies between 4% and 7%, which is, given common complaints on meetings’ uselessness, a very low number. It is understandable that after switching to WFH the decline rate went down - people in uncertain times needed tighter connections with their colleagues and managers. Even before the WFH switch, however, the numbers were very low.

Graph 6: Meeting decline rate during the last 12 months.

So why do people struggle with declining meeting invitations? Taking inspiration from Christian Rudder’s Dataclysm, we can use Google search to peek into the human psyche and get a glimpse of what thoughts and worries people have in their minds when they consider declining the meeting. Based on this data, it seems that people’s concerns are mainly about (not) being perceived by others as rude, uncooperative and/or idle.

Fig. 1: The first few results from Google searching the term “how to decline meeting”.

Harnessing the power of social norms

Many employees feel uncomfortable about declining meeting invitations, even when they don't see the benefit of said meetings. So what can help? An effective and scalable solution might be to make such a behavior a (new) norm. We can be inspired here by the principles of behavioral change popularized by The Behavioural Insights Team (BIT). This team was originally a UK government agency, and is now a global social purpose company that applies behavioral science insights to inform policy and improve public services. To make those principles more accessible to others, the BIT came up with the MINDSPACE acronym, referring to nine factors that robustly affect people's behavior, based on the conducted studies (see Fig. 2 for depiction of those factors). 

Fig. 2: BIT’s MINDSPACE framework to aid the application of behavioral economics insights to informing policy and improving public services. The framework consists of the nine factors (Messenger, Incentives, Norms, Defaults, Salience, Priming, Affect, Commitment, Environment) that are proven to be robust shapers of human behavior. (The picture was taken from the BIT’s original document about MINDSPACE framework.) 

In the context of our topic, the most relevant is the factor of Norms that states that people tend to do what others around them are already doing. The psychology of this certainly applies when given the choice of whether or not to recycle towels in hotels - most of us conform when informed that most hotel guests opt to recycle their towels at least once during their stay. 

In the case of declining meetings, we can apply this principle simply by explicitly stating that under some conditions it is absolutely normal, appropriate and desirable for an employee to decline an invitation to a meeting. It should be the expectation when said employee needs to protect her valuable time for high-quality work and well-being. Ideally, we should combine it with the Messenger principle (that refers to the fact that we are heavily influenced by who communicates information) and let employees with both formal and informal authority be a role model of this new, desirable behavior. 

Boosting goal intention with implementation intention

To further enhance the chance that employees will comply with this new norm and expectation, it is a good idea to give them explicit guidelines on how to proceed when deciding whether or not to decline meeting invitations. 

Here we draw from behavioral science insight that we can increase the probability of our success in dealing with difficulties on the way to our goals if we specify in advance our response to specific conditions. This self-regulatory strategy is known as implementation intention, which has a form of simple "if-then” rules that predetermine specific and desired behaviors in response to particular future events or cues. It has been successfully implemented for better goal attainment and habit and behavior modification in various areas, from voting behavior and medication compliance to emotion regulation or weight reduction. By specifying the when, where and how part of our behavior we can thus aspire to boost our rather weak goal intentions. A simple statement is not enough to fortify a result - just remind yourself of how successful you usually are with your New Year's resolutions. 

Fortunately, using common sense in combination with some Google search, you can quickly find some reasonable rules that will help you with deciding whether to attend the meeting or not. Below are a few examples of such rules, specifying conditions under which one should not attend the meeting:

Feel free to add other rules that are relevant based on your own experience.

The importance of what is missing

Our analytics platform helps companies to analyze and optimize the way their employees work on various collaboration platforms. The data paints a strong picture of what employees have done but offers less when it comes to what they have not done. However, as demonstrated by Sherlock Holmes’ story in the opening of this blog post, what is missing can sometimes be more informative than what is present.

Besides "the dog that did not bark" case, there is another motivating, and moreover true, story that even more convincingly shows us why it sometimes pays off to focus on missing things: During World War 2, the Allies mapped bullet holes in planes that had been hit by anti-aircraft shooting. They wanted to fortify the aircraft by putting the extra armor in the places that received more bullets. These places are shown as red dots in Fig. 3. At first glance, this seems to be a logical conclusion to focus on these places. After all, these were the most affected parts of the aircraft that returned from their flying missions. But Abraham Wald, the mathematician who applied his statistical skills to various wartime problems, had a different opinion. The red dots represented only damages to aircraft that were still able to return home. The air force thus should strengthen places that were free of bullet holes, because these are places where the aircraft would not survive the impact. 

This phenomenon is referred to as survivorship bias (or selection bias) in behavioral science, and it happens any time one looks at the things that survived, when one should focus (also) on the things that didn't. 

Fig. 3:Graphical illustration of the damaged portions of aircraft (red dots) that were still able to return back from their flying mission. (The picture was made by Cameron Moll).

The meetings that didn’t survive

Can we, similarly as the aircraft analyst above, learn something potentially useful by focusing more on missing/declined meetings? Let's try it out by using Time Is Ltd.'s own calendar data from the last 12 months and compare the meetings that “survived” in our calendars with those that didn't make it. 

I have decided to use for the following comparison meeting characteristics that are both computable - given the available calendar metadata - and potentially relevant for deciding whether to decline the meeting invitation or not - given my own and my colleagues’ experience and understanding of the reasoning and emotions that accompany declining a meeting:

For an estimation of the relationship between meeting characteristics and probability of meeting being declined, I have used a binomial regression model. This model enables us to estimate the size and direction of this relationship for individual meeting characteristics, while controlling for the effect of all other meeting characteristics included in the analysis.

So what are the results? Do they support the hypotheses described above? In Graph 7 you can see the posterior distribution of estimated strength and direction of relationship between the meeting’s characteristics and its chance of being declined. After inspecting the graph (for its more detailed explanation see the description below the graph), it is clear that with exception of after-hours meetings, online meetings and type of relationship between meeting attendees there is some evidence in favor of our hypotheses.

Graph 7: The posterior distribution of estimated strength and direction of relationship between meeting’s characteristics and its chance of being declined. The density plots show credible values of coefficients in the binomial regression model for individual meeting characteristics given the data. The coefficients are expressed on the logit scale, representing how much the natural logarithm of the odds of declining a meeting increases when the predictor is increased by 1 unit (in the case of categorical variables this change is equal to the change from the reference level to the level in question, so for example, in the case of meeting length the reference level with which other levels are compared to is the meeting length below or equal to 30 minutes). There is evidence of a relationship between meeting characteristics and meeting decline when the majority of credible values lies above or below 0 log odds (represented by a dashed line in the graph). The higher is the typical (median) value of the coefficient, the bigger the potential impact of a given meeting characteristic on a person’s decision to decline. When it is above 0, it tends to increase the odds of meeting being declined, when it is below 0, it tends to decrease the odds.

In plain language, these results suggest that at Time Is Ltd. we show the following behavioral tendencies when it comes do declining meetings (listed in the order of hypotheses described above):

What can such findings be useful for, besides satisfying our curiosity? Primarily, we can use it to inform potential interventions in support of, or against, collaboration habits - with the consequences to employee productivity and well-being in mind. 

For example, we have discovered the rather weak relationship between after-hours meetings and a meeting decline rate at Time Is Ltd. This information should be combined with information about how frequent after-hours meetings actually are in our company, and also with related opinions and attitudes of our employees, identified via employee surveys or focus groups. Based on these inputs, the rules and expectations regarding overtime may need to be reconsidered (given well-proven detrimental effects of overtime on employees’ mental and physical health).

Some final takeaways

As already mentioned in one of the previous blog posts, when it comes to better time management, we already possess the tools we need to make a change.The issue lies in utilizing them. Fortunately, even for this challenge there are tools that can help us with that. The MINDSPACE framework for behavioral change and implementation intention mentioned in this blog post is an example of such a tool. Don’t hesitate to use it to master “the art of declining meetings” in your own company. 

See you soon in the next blog post. Or maybe not ;)

References

Abraham Wald. (n.d.). Retrieved November 21, 2020, from https://en.wikipedia.org/wiki/Abraham_Wald

Binomial regression. (n.d.). Retrieved November 27, 2020, from https://en.wikipedia.org/wiki/Binomial_regression

Cialdini, R. (2003). Crafting normative messages to protect the environment. Current Directions in Psychological Science, 12, 105–109.

Diffusion of responsibility. (n.d.). Retrieved November 27, 2020, from https://en.wikipedia.org/wiki/Diffusion_of_responsibility

Dolan, P., Hallsworth, M., Halpern, D., King, D., & Vlaev, I. (2010). MINDSPACE. Influencing behaviour through public policy. Retrieved November 21, 2020, from https://www.bi.team/publications/mindspace/

Groupthink. (n.d.). Retrieved November 27, 2020, from https://en.wikipedia.org/wiki/Groupthink

Implementation intention. (n.d.). Retrieved November 21, 2020, from https://en.wikipedia.org/wiki/Implementation_intention

Logit. (n.d.). Retrieved November 27, 2020, from https://en.wikipedia.org/wiki/Logit

Luszczynska, A., Sobczyk, A., & Abraham, C. (2007). Planning to lose weight: Randomized controlled trial of an implementation intention prompt to enhance weight reduction among overweight and obese women. Health Psychology, 26(4), 507-512.

Nickerson, D. W., & Rogers, T. (2010). Do You Have a Voting Plan?: Implementation Intentions, Voter Turnout, and Organic Plan Making. Psychological Science , 21(2), 194-199.

Rogelberg, S. G., Scott, C., & Kello, J. (2007). The Science and Fiction of Meetings. MIT Sloan Management Review, 48(2), 18-21.

Rudder, Ch. (2015). Dataclysm: Love, Sex, Race, and Identity-What Our Online Lives Tell Us about Our Offline Selves. New York: Crown

Schweiger Gallo, I., Keil, A., McCulloch, K. C., Rockstroh, B., & Gollwitzer, P. M. (2009). Strategic automation of emotion regulation. Journal of Personality and Social Psychology, 96, 11-31.

Selection bias. (n.d.). Retrieved November 23, 2020, from https://en.wikipedia.org/wiki/Selection_bias

Survivorship bias. (n.d.). Retrieved November 21, 2020, from https://en.wikipedia.org/wiki/Survivorship_bias

The Adventure of Silver Blaze.(n.d.). Retrieved November 23, 2020, from https://en.wikipedia.org/wiki/The_Adventure_of_Silver_Blaze

Trevisan, D. D., São-João, T., Cornélio, M., Jannuzzi, F., de Sousa, M. R., Rodrigues, R., & Lima, M. H. (2020). Effect of an 'implementation intention' intervention on adherence to oral anti-diabetic medication in Brazilians with type 2 diabetes. Patient Education and Counseling, 103(3), 582-588.

Wainer, H. (1999). The most dangerous profession: A note on nonsampling error. Psychological Methods, 4(3), 250–256.

Wong, K., Chan, A. H. S., & Ngan, S. C. (2019). The Effect of Long Working Hours and Overtime on Occupational Health: A Meta-Analysis of Evidence from 1998 to 2018. International Journal of Environmental Research and Public Health, 16(12), 2102.

wRITTEN BY

Ludek Stehlik

Ph.D. in cognitive psychology, his research focus extends to psychometrics, sociometry, statistics, and HR consulting. Previously worked for Deloitte or Assessment Systems International.