Gamification entered the enterprise world in the mid-2000s. At the time, a number of startup companies (e.g., Bunchball, Gigya, Badgeville, Foursquare and SCVNGR, to name a few) entered the market with the promise of increased employee engagement through point, badge and similar compensation and incentivization schemes. These are collectively referred to as gamification. The underlying assumption was that people would complete tasks and goals more quickly and more accurately because the incentives were present.
These solutions targeted customer loyalty, sales enablement and some marketing initiatives, but the most successful applications were in sales. Despite raising significant capital, the majority of these companies folded because client’s internal adoption was low, and in many cases, these offering were no more effective than simply posting current sales results or sales metrics on the wall.
Although gamification is currently seen more as a product feature than as a technology market of its own, gamification is still present. In this article, I address why gamification did not realize its initially promised potential, and offer specific recommendations for improving its effectiveness.
To address these issues, I take a psychological science approach. I outline a theory proposed by myself and others (e.g., Higgins, 2000; Maddox, Markman, & Baldwin, 2007; Maddox & Markman, 2010) which argues that the speed and accuracy of task completion depends upon two aspects of motivation: the global motivational state and the local motivational state.
To ground these concepts in an example, suppose you are an employee who has been called into a meeting with your supervisor. You have been informed that your supervisor will be outlining a new task for you to complete, but you have no details regarding the task. When you enter the supervisor’s office, you enter with some global motivational state that is completely independent of the task to be requested. Your motivational state could involve excitement for the new (currently unknown) challenge, or it could involve stress or pressure. Once the task is explained to you, you will engage in completing the task under some local motivational state. For example, you might be told that you will earn 10 points if you complete the task within a week. In this case, your local motivation is such that you will engage in the task in order to earn the 10 points.
Critically, current gamification offerings affect the local motivational state of the individual. They affect how the individual engages with the specific task at hand. Earning 10 points for completing some task or goal affects the local motivational state because it is tied directly to the (local) task at hand. The theory I outline below suggests that the local motivational state is only half the story. The speed and accuracy of task completion is determined by the interaction between the local and global motivational states.
The Psychological Science of Motivation: Global and Local Motivation
The psychological science literature suggests that the working memory and attention, collectively referred to as effort, that an individual allocates to completing a task, is determined from the local and global motivational state.
Commercial incentive gamification strategies focus just on the local motivational state, and focus only on what is referred to in the motivation literature as a local approach motivational state. Local and global motivational states come in two forms: approach and avoidance (see the Table below).
With respect to local motivation, when you earn points for completing some task you are in a local approach motivated state. For example, suppose you earn 5 points if you close a new deal each day, or obtain a $5 coupon if you purchase more than $50 in merchandise in the next week. When you avoid losing points for completing some task you are in a local avoidance motivated state. For example, suppose you are allocated 5 points each day, but if you do not close a deal you lose those 5 points. Analogously, suppose you obtain a $5 coupon from your favorite online store, but if you do not purchase at least $50 in merchandise, that coupon is not valid. Notice that the outcome for local approach and avoidance states are identical. If you close the deal you get 5 points, and if you purchase $50 in merchandise you get the $5 coupon. The critical distinction is in the “framing” of the local incentive. In one case you work to earn an incentive (approach), and in the other case you work to avoid losing an incentive (avoidance).
Global motivation is not directly tied to the task at hand, but is critical in determining the amount of effort allocated to the task. Global motivation also comes in two forms: approach and avoidance. Some people have an approach motivated personality, referred to as a promotion-focused personality (Higgins, 2000). These individuals are likely to produce a lot, but they may make more mistakes along the way. Other people have an avoidance motivated personality, referred to as a prevention-focused personality (Higgins, 2000). These individuals are more likely to be cautious, but they rarely make mistakes. Importantly, it is not the case that approach motivated personalities are better or worse than avoidance personalities. They are simply different. In fact, one can easily envision employment situations in which one personality may be more ideal than the other.
When one’s current affective state is more positive than negative, that individual is in a global approach motivated state. On the other hand, when one’s current affective state is more negative than positive, that individual is in a global avoidance motivated state (Maddox, Gorlick, Worthy, & Beevers, 2012; Maddox & Markman, 2010). Finally, the social setting can lead to an approach or avoidance motivated state. Suppose you are in a situation in which success will reap you and your co-workers a benefit, but failure will not change the status quo, then you are in a global approach motivated state. On the other hand, suppose the success or failure of the team rides squarely on your success or failure because the rest of the team have succeeded, then you are in a global avoidance motivated state (Maddox, Koslov, Yi, & Chandrasekaran, 2015).
The Psychological Science of Motivation and Effort
The psychological science literature suggests that the allocation of working memory and attention (or effort) is determined from the combination of global and local motivational factors. Specifically, when global and local motivation are aligned, effort is increased. This might occur if the individual has an approach motivated personality, is in a good mood, or is in a positive social situation and gains points for completing tasks and goals. In addition, effort is enhanced when individuals are simultaneously in a global and local avoidance motivational state. This might occur if the learner has an avoidance motivated personality, is in a bad mood, or is in a negative social situation and avoids losing points for completing tasks and goals.
This same research suggests that effort is reduced when individuals are simultaneously in a global approach and local avoidance motivational state, or are simultaneously in a global avoidance and local approach motivational state. Notice that the latter situation in which one is in a global avoidance but in a local approach state is quite likely in the corporate sector.
Nearly all gamification schemes in corporate training involve a local approach motivational state in which the employee or customer earns points for completing some task or goal. What this research suggests is that if you have an avoidant personality, are in a bad mood, or are in a social pressure situation and are attempting to earn points for completing tasks, your effort will be reduced not enhanced.
It is worth mentioning that the magnitude of these motivational alignment and misalignment effects are not trivial. In my own research focused on learning, I have found that motivational alignment increases task accuracy and overall task completion rates by anywhere from 10% – 40% (Maddox & Markman, 2010).
An understanding of the motivation-effort framework leads me to a number of comments and recommendations for enterprise applications.
First and foremost, I recommend that developers continue to embrace the notion of gamification in enterprise applications. When properly aligned, the increases in effort can be quite large. In addition, because working memory and attention are relevant to so many aspects of the workplace, gamification can have substantive effects in a broad range of sectors including hiring, onboarding, short-term and long-term compensation, learning, and performance to name just a few.
Second, buyers should educate themselves on the importance of motivation, and should expect gamification offerings to incorporate and address global and local motivational effects on effort. Current offerings typically focus exclusively on local approach motivation by offering points for completing tasks. Local avoidance motivation can be incorporated by providing points up front that will be lost if the task is not completed. Global motivational factors must also be acknowledged and addressed. When an individual is under performance pressure or has an avoidant personality, they will expend significantly more effort in completing a task if they are engaged in the task to avoid losing points.
Third, a major strength of this motivation-effort framework is that many aspects of global motivation can be manipulated or measured in the workplace. We at Amalgam Insights have the necessary expertise to help companies measure and identify relevant personality types, induce positive affect, and identify and induce positive vs. negative social situations. Although expertise is required to achieve these aims, the implementation is relatively inexpensive, and is dwarfed by the increase in ROI from enhanced task effort.
Fourth, managers trying to optimize productivity and employee satisfaction need to understand which of their employees and which situations are more attuned to global approach-based motivation vs. avoidance-based motivation. Since a local approach and a local avoidance state are mathematically equivalent, and simply involve a difference in framing, management can select the local motivational state that is optimal for a given situation or individual.
Finally, I recommend that developers and users begin to explore true personalization in gamification by leveraging this motivation-effort framework rather than a one-size-fits-all approach. The sky is the limit. One can induce global approach or avoidance states through mood induction or by carefully crafting the social setting. One can induce a local approach or local avoidance state easily simply by incorporating a points-earned or points-lost incentive structure. Finally, one can combine the induced motivational alignment with the task at hand to optimize performance.
Higgins, E.T. (2000). Making a good decision: Value from fit. American Psychologist, 55, 1217-1230.
Maddox, W.T., Gorlick, M.A., Worthy, D.A., & Beevers, C.G. (2012). Depressive symptoms enhance loss-minimization, but attenuate gain-maximization in history dependent decision-making. Cognition, 125, 118-124.
Maddox, W.T., Koslov, S., Yi, H-G., & Chandrasekaran, B. (2015). Performance pressure enhances speech learning, Applied Psycholinguistics, 12, 1-28.
Maddox, W.T., & Markman, A.B. (2010). The motivation-cognition interface in learning and decision making, Current Directions in Psychological Science, 19, 106-110.
Maddox, W.T., Markman, A.B., & Baldwin, G.C. (2007). Using classification to understand the motivation-learning interface. The Psychology
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