Have you ever thought what you want on your tombstone? Or wondered what gives you the drive to hustle? Are you the benevolent type, but still have enough ego that you want to be remembered for all the good you did in the world? There are many forces that help drive us to pursue, and the desire to leave a legacy is one of the strongest.
This inherent drive to leave a legacy can manifest in a range of ways: from a desire to have children to wanting to lead a visionary movement that transforms a society. Although the manifestation of the process might differ between individuals, most of us seem to have a desire to create a legacy — to leave something behind when we go. Our desire for legacy can be biological, material, and/or it can be expressed as our values and hard-won knowledge that we pass on to family and friends (Hunter & Rowles, 2005).
What is the Meaning of Legacy?
The word legacy comes from a Latin word legatus, translated as ‘embassador, envoy, deputy.’ In the late 14th century, an old French word legacie was used to describe a body of persons sent on a mission. We can therefore look at legacy metaphorically that when we create a legacy, what we are really doing is appointing our spokesperson for the future. Most of us — either explicit or unknowingly — have a desire for either symbolic or literal immortality (i.e. literal immortality is some belief that there is an afterlife). This seems especially strong in those of us that understand death is inevitable (Sligte, Nijstad, & De Dreu, 2013). Our legacy, if adequately left, transcends the realms of our physical life and brings symbolic immortality.
As our awareness of mortality grows, it brings into focus internal concerns and questions about why we exist. For many, this quest for purpose begins once we realize that the opportunity to leave our mark is finite. For others, this realization can lead fear — a threat to one’s sense of self that we will likely soon be forgotten. Thus, people try to negotiate what us scientists call ‘mortality salience’ in different ways (Sligte, Nijstad, & De Dreu, 2013). When reminded of our impending death, we often look for ways to transcend that feeling and employ different psychological mechanisms to reach symbolic immortality. For instance, we are compelled to connect with influential social groups, because a group’s existence generally transcends the existence of a single individual. Furthermore, groups also bolster our self-esteem and nurture our belief that the world meets the standards and values within our worldview — a rationalization that everything will end well. This has been explored in depth by Terror Management Theory or TMT, which was proposed by Jeff Greenberg, Tom Pyszczynski and Sheldon Solomon (1986).
To create legacy some of us — I fall into the category —turn to our creative side. By introducing new ideas, designs, novel products and original solutions into our current reality we possess the potential to influence societies (and dare I say the world) in a way that will outlive ourselves. Studies have shown that creativity is often used as a force of legacy, especially when the expression of creativity is socially valued — after all, we love our friends… our peers… our ‘tribes’ and most of us either explicitly or secretly want their recognition (Sligte, Nijstad, & De Dreu, 2013).
Why Do You Want to Leave a Legacy?
The crux of legacy is that we look for ways to be existentially reassured our life mattered. We bargain with death as we go through the psychological cycle of grieving our inevitable non-existence (Ross, 1969). We want to leave a legacy because before we can psychologically accept the reality of our own physical annihilation, we put up one hell of a fight. Science suggests a desire to leave something behind when we pass naturally increases as we age (Newton, Herr, Pollack, & McAdams, 2013). Those of us that have had long and productive careers seem to be challenged the most by the process of aging (Wexler & Long, 2009). Intuitively this makes sense; if you worked hard all your life — inevitably making personal sacrifices along the way — you want to believe your life amounted to something in the eyes’ of others because you will not be around to tell your story. You want some recognition for living a dedicated life. Again, various studies suggest the closer to death we get, the more we crave this immortality. A study of women that were faced with a life-threatening illness showed that all subjects consciously started the process of legacy transmission (Hunt, 2007), which could be interpreted that legacy closely links with our relationship to death and mortality.
Many authors also think that the wish to create a legacy is connected both with generativity and narcissism (Newton, Herr, Pollack, & McAdams, 2013). Generativity is a psychological concept, usually regarded as a positive one — generativity often emerges in midlife and can be connected with parenthood or other social roles, such as mentoring. Erikson (1974) defined it as “…the establishment, the guidance, and the enrichment of the living generation and the world it inherits.” Erikson viewed it as a concept that is often focused on the next generation and an inherent individual care for its well-being. Narcissism, on the other hand, is usually viewed as a more negative concept (though there is a distinction between normal and pathological narcissism). Generativity is focused on others, while the concept of narcissism focuses on one self. We could therefore conclude that wanting to leave a legacy on some level is associated with narcissism since you do not need to be remembered to help society. It appears that legacy is likely a combination of both selflessness and narcissism (Rubinstein, 1996).
Many people indeed associate a need for legacy with ego; an act of ego beyond death. In contrast, the desire to selflessly change the world is viewed as more altruistic in nature — those that do things anonymously and do not wish to be recognized for it. Nonetheless, some point out that legacy has the potential to go beyond the ego and be weighted in altruism. It can surpass cultural constraints and become a broader aspect of human development that is a psychological driver of greater good (Hunt, 2007).
One thing about legacy that science seems to agree on is that this desire is somewhat universally seeded in us. Since it is often connected with having children and passing either goods, values, knowledge and/or wisdom onto them, being childless can (in some people) create a feeling of despair and/or sadness as they feel they are no outlets to leave a legacy (Rubinstein, 1996). It was observed that some childless women looked for other ways to meaningfully influence and support others (e.g. family members, community), or alternatively they wanted to create a legacy that related to the whole human species. This desire can sometimes drive very old people to participate in, for example, antinuclear protests even if building more nuclear power plants probably isn’t going to influence them anymore. Some studies show that older people, it can be more important to pass on values and beliefs than material possessions (Hunter, 2007). It is clear that legacy means different things to different people, but that for most of us it is the pursuit of symbolic immortality that drives us.
Erikson, E. H. (1974). Dimensions of a new identity. New York, NY: W. W. Norton & Company, Inc
Greenberg, J., Pyszczynski, T., & Solomon, S. (1986). The causes and consequences of a need for self-esteem: A terror management theory. In R. F. Baumeister (Ed.), Public self and private self (pp. 189-212). New York, NY: Springer-Verlag.
Hunter, E. G. (2007). Beyond death: inheriting the past and giving to the future, transmitting the legacy of one’s self. Omega, 56(4), 313-329.
Hunter, E. G., & Rowles, G. D. (2005). Leaving a legacy: Toward a typology. Journal of Aging Studies, 19, 327–347.
Kübler Ross (1969). On Death and Dying. New York: Scribner Classics.
Newton, N., Herr, J., Pollack, J., & McAdams, D. (2013). Selfless or Selfish? Generativity and Narcissism as Components of Legacy. Journal Of Adult Development, 21(1), 59-68.
Rubinstein, R. (1996). Childlessness, legacy, and generativity. Generations, 20(3), 58.
Sligte, D., Nijstad, B., & De Dreu, C. (2013). Leaving a Legacy Neutralizes Negative Effects of Death Anxiety on Creativity. Personality And Social Psychology Bulletin, 39(9), 1152-1163.
Wexler, G., & Long, L. (2009). Lifetimes and Legacies: Mortality, Immortality, and the Needs of Aging and Dying Donors. The American Archivist, (2). 478.
I have generally been an advocate of behavior change science. Designing healthy habits and routines can be an effective way to elicit change in the appropriate environment. However, similar to some of the legitimacy issues executive consulting faced when “life” coaches hit the scene, a wave of unqualified behavioral “designers” have been able to find an audience due to the increased ease at which garbage can be disseminated thanks to the power of the Internet. An important disclosure is I am one of those peddlers, so I am chucking big rocks at my big glass house. That said, it is long overdue to air some dirty laundry — so here we go…
Many popular behavior change interventions are designed for short intervention-behavior lags — i.e. the desired behavior of the user takes place almost at the same time as the intervention is administered. For instance, you see your Fitbit on your arm and get reminded to walk, so you get up from your desk and take a phone meeting outside while walking; or a more common example, a beep in your car nudges you to fasten your seatbelt, you hear the beep and you buckle up. But one of our many dirty little secrets is that these interventions are not particularly useful after the “treatment” has been administered (Rogers & Frey, 2014). For instance, taking the seatbelt example, one study showed that if drivers were reminded to fasten their seatbelt immediately before they drove off, their compliance was significantly better than if they were reminded 5 minutes earlier (Austin, Sigurdsson, & Rubin, 2006). Moreover, and more importantly, a delayed prompt (when there was a 5-minute lag between the prompt and the driver entering the car) the intervention was no more effective than receiving no prompt at all (i.e. the study’s control group). A few minutes seems to be enough for our attention to wander off and for another stimulus to take over — in other words, if an stimuli is not administered in real-time the effectiveness of the behavioral intervention diminishes — if (what people of my sort call) a “trigger” happens after the action that needs changing is taken, the intervention is usually a lot less effective.
Therefore, what behavioral designers and marketers often try to do is alter our thoughts in real time. Real-time stimulus is pretty effective and can acutely change our behavior in the short-term. These tactics are frequently used in conjunction with framing our choice as riskaversion. For example, if you are going to the beach and you get told that by not wearing sunscreen, you will have a higher chance of developing skin cancer, chances are you are more likely to buy sunscreen (for evidence of this see: Detweiler et al., 1999). But, it is questionable at best if you will actually change your habit of generally not buying sunscreen before going out in the sun; in the sunscreen study the perception of risk was only changed in that moment. Changing thoughts in an enduring matter has proven to be much more difficult. Behavior interventions are supposed to be able to bridge time, but if the intervention is not administered just before the target behavior occurs, this is unlikely to happen. For instance, a study that looked at Biggest Loser contestants showed that during the show — when contestants were bombarded with different inputs, interventions and coaches — participants lost considerable weight. Six years later however they gained back, on average, 70% of the lost weight (Fothergill et al., 2016).
The hard reality about behavior change is it is not easy to create persistence — although there are different pathways that have been connected with the process for lasting behavior change. The problem is these complicated pathways are rarely designed well in novel behavior change models. Instead designers look for dramatic results so they can market themselves and their intervention. That is the bullshit part, so what can you do about it?
In their research paper, Todd Rogers and Kerin Frey (researchers from Harvard University) describe some of the features that are likely to bridge time. These include feeling socially accountable (e.g., not wanting to let down family and friends), linking performance with the intervention, pre-committing to a certain behavior and/or deliberately changing perceptions and consequential thoughts (Rogers & Frey, 2014). The importance of this last one (deliberately changing perceptions and consequential thoughts), has been shown to be extremely important for lasting behavioral change. This is why cognitive-behavioral therapy is touted as an evidence-based, efficient technique for changing habits — science continues to support the idea that deliberate practice creates new and lasting cognitive patterns and pathways (Pearson, Lipton, Cleland, & Yee, 2002).
The premise of self-licensing is that when you feel you have invested legitimate effort into something, an internal self-licensing cue can get produced that justifies a negative action, many times in the form of a hedonic action of consumption or self-gratification. Ever remember a time you rewarded your 30 minutes of cardio with a milkshake Jamba Juice. At least one study showed that a self-licensing cue leads to increased snack intake (Witt Huberts, Evers, & De Ridder, 2012). Self-licensing is a distinct behavioral mechanism that has been shown to be associated with unhealthy behaviors — distinct from other self-control failure mechanisms in the sense that the behavioral breakdown is actually masked as a reward.
The rub for you is the phenomenon of self-licensing (sometimes referred to as moral licensing) is widely recognized. Good behavioral designers know when people perform well they will feel liberated to engage in these behaviors (Merritt, Effron, & Monin, 2010). Why do you think most health clubs have a juice bar? Science suggests that even if you simply imagine doing something altruistic, you are more likely to indulge. If you, on the other hand, did not imagine doing a good deed, you are more likely to choose prudent behaviors (Khan & Dhar, 2006). It appears that when we feel virtuous this can often influence our future behavior in a negative way — because, come on, we all like a pat on the back once in a while.
False expectations regarding the future also seem to influence our choices. For instance, if we believe we will have to make a certain choice twice, this influences our decision and might make us more self-indulgent. Studies of consumers performed by Khan and Dhar (2007) showed that participants were more likely to choose an unhealthy snack (a chocolate chip cookie) over a healthy snack (low fat yogurt) if they believed they will have to make the same choice the week after. In other words — in our minds — just projecting we might do something healthy has us doing dumb shit in the present moment. The best advice I have got for you here is to be mindful and simply not do dumb shit. If you are reading this, chances are you are smart, so look at what you are trying to accomplish and gut check yourself to see if you are self-licensing. Since this phenomenon is common with those trying to lose weight I’ll use gym goers as an example. One, your treadmill is lying to you (see: Putting Very Little Weight in Calorie Counting Methods) — if you are looking to create a calorie deficit you are probably already overestimating the calories you have burnt exercising. Two, that fruit smoothie you think is a healthy reward for a job well done — it likely comes close to the caloric intake of a banana split. Not that I am suggesting you drink soda as an alternative, but keep in mind that if that was your guilty pleasure after a hard workout, you would likely be taking in 66% less calories than your average juice bar alternative.
The concept of self-licensing is similar to what some call ego depletion. Ego depletion and willpower have been blogged to death by folks like me so I won’t go too deep here. I am already stoked you have made it this far. The short version though is willpower is seen as a muscle that can get exhausted when we use it a lot (Baumeister et al., 2008). When our willpower’s capacity is temporarily used up, ego depletion causes us to make less restrained choices (like snacking on cookies or cake, instead of more healthy options like fruit or salad). Moreover, and what fascinates researchers is, when we use willpower resources in one area of our lives, this can backfire in seemingly unrelated areas of our lives. For instance, experiments have shown that when people tried to resist the temptation to eat sweets, they subsequently gave up faster on difficult mental exercises (Baumeister et al., 1998).
If you have read this far then by now you either agree or disagree with me that behavior change is incredibly complex and influenced by multiple factors and circumstances. However, to make these complex concepts comprehensible we have really smart thought leaders in this space dumbing down ideas at the cost of holistic comprehension. Take the very popular behavioral model proposed by BJ Fogg (BJ Fogg’s Behavoral Model) — this model has been accused by many that study behavior change as somewhat overly simplistic (although my guess is that for BJ simplicity was his intention). BJ’s model focuses on three elements of behavior: motivation, ability and trigger. In the model, motivation and ability need to be at certain thresholds for a target behavior to be ‘triggered’. BJ also defines subcomponents of each element — in his model, his three core motivators are: pleasure/pain, hope/fear, social acceptance/rejection. What I see as missing in BJ’s model is a road to long-term behavior change, as most of these levers are acute and episodic. The notable exception is social pressure; as I alluded before social pressure has been shown to be a useful method in some cases when we want to cement a certain behavior (we will not go too deep down the rabbit hole of social contagion here, but the science is interesting for those interested). One scientific example is a study that examined people who thought their neighbors could see a report of their energy usage. This group was more likely to reduce their energy usage, and more surprisingly the effect stayed measurable even years after the initial intervention was removed (Allcott & Rogers, 2014) — meaning these folks were still energy conscious even after the reports that their neighbors knew what they were up to stopped coming to their mailbox.
To be fair to BJ, he clearly knows the role environment contributes to our behavior, but the environment’s importance is downplayed in his popular model — and this model is constantly referenced by would-be behavioral designers. In the information regarding his Tiny Habits protocol BJ does mention three things that can change behavior in the long-run: an epiphany (very rare, like: holy shit, I just had a heart attack I should work out more), change of context (hey, what do you know? environment) and taking baby steps (aka BJ’s 2nd baby after his B=MAT model: Tiny Habits).
The truth is BJ just repackaged stuff from Kurt Lewin, that Lewin himself probably repackaged from someone else. We in the business all do this. As a gestalt psychologist, Lewin believed that a person’s environment determines their behavior, which he expressed with his formula: B= f (P, E). Behavior —in his view — is a function of a person (P) and their environment (E). In one of his original books, Lewin actually originally proposed that behavior is a function of a person’s entire situation: B=f(S) …later Lewin expanded situation (S) into person and environment (Lewin, 1936). Lewin’s contribution to behavior change was an emphasis on all the different elements that need to be considered to attempt to understand our behavior. Another gestalt psychologist, Kurt Koffka, summarized this in his famous (though often wrongly translated) saying: The whole is other than the sum of the parts. In other words, it is folly to approach behavior change using a purely reductionist approach. Lewin (1936) found we are often affected differently by the same physical environment, so even though I am admittedly bullish on them, even environmental changes fail us sometime.
However, in my opinion environmental interventions are where we are seeing the highest return on investment with regards to behavioral design. If you have not already, go down the rabbit hole of Brian Wansink’s work. Wansink is continuing to show us through his research how environmental design can influence our behavior. For instance, he popularized mindless eating ideas that suggest we often eat things without being aware of its nutritional value or volume (Wansink, 2004).
A study published this year in JAMA, described a randomized control trial that looked at the efficiency of weight-loss interventions. The hypothesis was that technology-enhanced weight-loss interventions will result in greater weight-loss compared to standard interventions. Surprisingly, the hypothesis was rejected. Participants who received a wearable device and an accompanying Web interface to monitor their diet and physical activity lost less weight compared to those who only received the standard intervention (Jakicic et al., 2016). Other researchers, too, concluded that when it comes to changing behavior, wearables might not be as beneficial as we once believed. I do believe wearables have potential, but it appears they cannot drive health behavior change alone (Patel, Asch & Volpp, 2015). There is a big gap between recording information and behavior change — to be honest after studying this now for over half-a-decade I believe the available data suggests that tracking devices probably cannot bridge this gap. Furthermore, it can take decades for a product to recover from a halo effect (Kerger et al., 2016). To be clear, some wearable devices can indeed deliver change (I am especially bullish on condition specific wearables). Also, some consumer products prove to be useful tools, because (1) they are often bought by people who are already motivated to change and (2) successful behavioral interventions can be built around them (Patel, Asch & Volpp, 2015). Look: the key to sustainability of behavior change is to transform external motivation into internal — all of us know it — the problem is that it is a bit tricky.
Reality: we need to believe and be enrolled to some degree in our own behavior change, or we are generally just wasting our time. “Destination addiction” refers to those that are always chasing something, but find no fulfillment in the process of change. Take for instance someone who buys a wearable because they believe that tracking their progress will add enjoyment to something they really do not enjoy doing. A lot of my life is spent evaluating these wearables. Many of these devices actually do the opposite (i.e. they add dissatisfaction) by adding unneeded friction to a process that is difficult to begin with — in extreme cases these devices even risk changing our identity (Lupton, 2015). Furthermore, whether supported by a wearable of not, canned behavioral interventions run the risk of missing the real cause of a problem because many only focusing on symptoms (for instance, personally I am fat because I drink too much, and I drink too much because my baby cries; how is my Fitbit going to fix my crying baby? I am joking of course, but you get the point). Rigged protocols and behavior change technologies that run on static algorithms cannot always perform a deep and comprehensive assessment about your individual situation. It is rare that a single behavior change model applies to a large population. Also, behavioral interventions that use technology and online platforms often reduce the amount of human contact you are exposed to (to be fair to hardware and software designers, investors want to know a product is scalable and human invention is rarely scalable). What does minimizing human interaction mean for the future behavior change through technology? I am not totally in the hater camp — some studies show that online therapy can be just as effective as face-to-face contact, plus it is more scalable and affordable (Mohr et al., 2012) — these are truths. However, the jury is out about the long-term effects these interventions can have, specifically their lasting effect on the human psychology and the process of socialization we have discussed throughout. Online interventions are very different to personal interventions. From what I can tell online modalities are not evaluated with the same amount of rigor as face-to-face practice. Also, individuals involved in the delivery of such models are not necessarily competent practitioners, especially since interactive computer-based communication has yet to provide an apples-to-apples comparison to face-to-face verbal exchange (Childress, 2000).
So what should you consider when it comes to evaluating behavioral interventions and their appropriateness? Perhaps some of the more obvious things include transparency regarding the intervention so you can determine fit, level of the interventions intrusiveness and the restrictions the intervention will have on your freedom. Our choices are often limited or eliminated altogether when certain goods or behaviors are banned or restricted — when our intrinsic drive is not truly altered and/or the intervention relies on artificial prohibitions, there is a good chance it can backfire (recidivism).
You see, if we can admit we are gaming ourselves, then at least we can enjoy the game. If we look at the world through the philosophical lenses of James P. Carse who wrote the book Finite and Infinite Games, poor behavior change protocols could be described as finite games. Their purpose is to reach a change, to end the process and win (losing weight, for example). When we rig the system in this fashion however, we get the results I previously highlighted in the Biggest Loser study. The game is over and we level set to the mean (i.e. back to our previous state). After all, most change comes with the potential for relapse. In my experience, behavior change protocols rarely have contingencies for this strong possibility. As an example, 80 to 95 percent of people who give up smoking or alcohol relapse within the first 12 months (Brandon, Vidrine, Litvin, 2007). I am not giving extra weight to the idea of Infinite Games by concluding with this concept, but do understanding that:
True change is not a destination; and,
we (and our users) might as well enjoy the ride.
These two ideas (that I hold as truths) will help us architect behavioral interventions for ourselves and others that have real lasting impact and will not fail us in the long-term.
Man, this post was a lot of words. I would love to stop talking now and learn from you in the comments below. What do you think?
Allcott, H., & Rogers, T. (2014). The short-run and long-run effects of behavioral interventions: experimental evidence from energy conservation. American Economic Review, (10), 3003
Austin, J., Sigurdsson, S. O., & Rubin, Y. S. (2006). An examination of the effects of delayed versus immediate prompts on safety belt use. Environment and Behavior, (1), 140-149.
Baumeister, R. , Bratslavsky, E., Muraven, M., & Tice, D. (1998). Ego depletion: Is the active self a limited resource?. Journal of Personality And Social Psychology, 74(5), 1252-1265.
Baumeister, R. P., Sparks, E. P., Stillman, T. P., & Vohs, K. P. (2008). Free will in consumer behavior: self-control, ego depletion, and choice. Journal of Consumer Psychology: The Official Journal Of The Society For Consumer Psychology, 18(1), 4-13.
Botta, F., Moat, H., & Preis, T. (2015). Quantifying crowd size with mobile phone and Twitter data. Royal Society Open Science, 2(5), 6p.. doi:10.1098/rsos.150162
Brandon, T., Vidrine, J., & Litvin, E. (2007). Relapse and relapse prevention. Annual Review of Clinical Psychology, 3, 257-284.
Burnes, B. (2004). Kurt Lewin and the Planned Approach to Change: A Re-appraisal. Journal of Management Studies, (6), 977-1002.
Carse, J. (2011). Finite and infinite games. Simon and Schuster.
Childress, C. A. (2000). Ethical Issues in Providing Online Psychotherapeutic Interventions. Journal of Medical Internet Research, 2(1), e5. http://doi.org/10.2196/jmir.2.1.e5
Detweiler, J. B., Bedell, B. T., Salovey, P., Rothman, A. J., & Pronin, E. (1999). Message framing and sunscreen use: gain-framed messages motivate beach-goers. Health Psychology, (2), 189-196.
Fothergill, E., Guo, J., Howard, L., Brychta, R., Chen, K., Skarulis, M. , & … Knuth, N. (2016). Persistent metabolic adaptation 6 years after “The Biggest Loser” competition. Obesity, 24(8), 1612-1619. doi:10.1002/oby.21538
Jakicic, J. M., Davis, K. K., Rogers, R. J., King, W. C., Marcus, M. D., Helsel, D., & … Belle, S. H. (2016). Effect of Wearable Technology Combined With a Lifestyle Intervention on Long-term Weight Loss. JAMA: Journal Of The American Medical Association, 316(11), 1161-1171. doi:10.1001/jama.2016.12858
Kerger, B. D., Bernal, A., Paustenbach, D. J., & Huntley-Fenner, G. (2016). Halo and spillover effect illustrations for selected beneficial medical devices and drugs. BMC Public Health, (1), doi:10.1186/s12889-016-3595-7
Khan, U., & Dhar, R. (2006). Licensing effect in consumer choice. Journal of Marketing Research, 43 (2), 259–266.
Khan, U., & Dhar, R. (2007). Where there is a way, is there a will? The effect of future choices on self-control. Journal of Experimental Psychology: General, 136(2), 277–288.
Lewin, K. (1936). Principles of Topological Psychology. New York: McGraw-Hill.
Lupton, D. (2015). Health promotion in the digital era: a critical commentary. Health Promotion International, 30(1), 174-183.
Merritt, A. C., Effron, D. A., & Monin, B. (2010). Moral Self-Licensing: When Being Good Frees Us to Be Bad. Social & Personality Psychology Compass, 4(5), 344-357. doi:10.1111/j.1751-9004.2010.00263.x
Mohr DC, Ho J, Duffecy J, Reifler D, Sokol L, Burns MN, Jin L, Siddique J. Effect of Telephone-Administered vs Face-to-face Cognitive Behavioral Therapy on Adherence to Therapy and Depression Outcomes Among Primary Care PatientsA Randomized Trial. JAMA. 2012;307(21):2278-2285. doi:10.1001/jama.2012.5588
Patel, M. S., Asch, D. A., & Volpp, K. G. (2015). Wearable devices as facilitators, not drivers, of health behavior change. JAMA: Journal Of The American Medical Association, 313(5), 459-460. doi:10.1001/jama.2014.14781
Pearson, F. S., Lipton, D. S., Cleland, C. M., & Yee, D. S. (2002). The effects of behavioral/cognitive-behavioral programs on recidivism. Crime and Delinquency, (3). 476-496.
Wansink, B. (2004). Environmental factors that increase the food intake and consumption volume of unknowing consumers. Annual Review of Nutrition, 24(1), 455-479. doi:10.1146/annurev.nutr.24.012003.132140
Witt Huberts, J. C., Evers, C., & De Ridder, D. D. (2012). License to sin: Self-licensing as a mechanism underlying hedonic consumption. European Journal of Social Psychology, 42(4), 490-496. doi:10.1002/ejsp.861
This quarter’s Business, Innovation and Entrepreneurship interview is the compilation of getting to discuss “big data” analytics with four exceptional thought leaders at the Motionsoft Technology Summit this year (2016). These four gentlemen in no particular order are: Jafar Adibi, Ph.D., the President, Co-founder, and CTO of re|unify; Jeffrey Cooper, the Senior Manager of Business Development at Samsung; Mark Newman, the President of Heads Up Analytics, and Keith Catanzano, a Partner at 2River Consulting Group. The answers below are summations of their respective answers, as such they are not represented as verbatim but edited for readability and context.
1) When a company is either building a data model (or working with a third party for this type of service), what considerations should an operator have regarding the crossroad of complexity and usability? There are scenarios where too many disparate and incomplete data sets can make it difficult to find the signal from the noise; what are the trade-offs as the amount of available business intelligence information continues to increase? And what considerations should we take into account to maximize any investment in mining data?
[Jafar Adibi]: You need to figure out what problem you are trying to solve. Clients will come to me with data, rich sets of data, and say, “Jafar, now go figure out something to do. Find something interesting.” Generally, this is a waste of time. People believe finding correlations (any correlations) are going to help their business, but that is often not the case. When you identify your problem, we are better set up to solve it. There are different analytic methods for classification problems, association problems, and other questions that are not necessarily answered through correlative means. Getting to the right question will help you establish what data sets are important.
Then you need to figure out your budget. There will always be noise in your data, especially data from business intelligence. We can build a model to take the noise into consideration. However, using more data is obviously expensive, so that goes back to what are you trying to solve for. We can exclude data that will not answer your question, which saves you time and money. As such, you want to keep return on investment (ROI) in mind as you think about the question you are asking. Ask yourself, “If I answer this question, how much money with I gain/save?” The answer to the ROI question gives you a ballpark on what it might be worth regarding your investment in a data model.
2) It seems to me that a lot of ad hoc advice about using data for business intelligence is disseminated on broad-based assumptions derived from general population data. However, is this not one of the follies of “Big Data”? Companies are basing important decisions on arguably misleading benchmarks, rather than creating a narrative specific to their population (or at least a sample from their specific population); What are strategies to ensure we are making the best decision based on our company’s unique attributes?
[Mark Newman]: The most important thing is to trust your own expertise. You should intuitively know the customers you are trying to attract. You should have an idea of what strategies you are trying to pursue. You should already know what the important problems are you need to solve. What you don’t want to do is look to data to validate some preconceived answer to your problem. Instead, you want to devote your own educated guesses as to what to do — and then you want to use data to test those rigorously to keep yourself honest.
I think there are two ingredients to doing that. The first is to agree with your colleagues on the definitions of the terms that you are using in your data. If all the stakeholders do not agree on the definition of the numbers, then you all are not going to have an organized lexicon/narrative to work with. You have to agree on key metrics that you are going to use to allow for the monitoring of health and progress within your organization.
The second ingredient that you want to have is to follow an experimental approach that is constantly evolving. Your customers and prospects are going to react differently to your products and services over time. Reasons:
They might have more experience with you as your brand matures
As consumer groups mature, they change their goals
Your previous pitches are now stale, and customers react to them differently
Different competitors in the marketplace
What works today does not work tomorrow. Instead of some one-and-done, super solution to what you are trying to accomplish — instead you want to have some kind of innovative, incremental approach in the beginning. If you follow that, then over time, the data is going to have a narrative that reflects who you are, and what you are trying to do, and what works best for you.
3) Until recently, most data aggregation efforts have told a fairly unsophisticated narrative, and inspired relatively unremarkable initiatives in an effort to capitalize on data mining. How can we improve our use of data? And, how can companies do better at making data more actionable?
[Keith Catanzano]: What is the question the company is trying to answer? It is important to not just say, “How do you make data actionable?” We are probably all guilty at some point of looking at a data model and saying, “Look at the results, they’re awesome!” I think intriguing insights can be challenging in terms of making data actionable. There is a ton of data out there. Once you find ways to bring yours together, there is a lot you can see using data by way of insights. At some point you need to do something with the insights. In order to do that, obviously, it’s important to know who your customers are [assuming trying to influence their behavior is your goal], but also why are they customers. However, in this use case the why is more important than the who. The “why” is ultimately what you are going to try to make actionable, because to take action you are going to need to pull some type of lever to influence consumer behavior. There are lots of ways to work with communication or outreach in an attempt to accomplish this, but the effort requires the company to take a deliberate approach regarding how data is used to take action.
It is also important to note that making data actionable is generally not a one-shot deal, and architecting a campaign that changes an entire group’s behavior in some way probably will take a series of events that includes multiple levers I mentioned. So to make data more actionable, an organization should sit down and say, “What is the level of energy I want to put into solving or addressing this problem?” And that’s probably both a financial decision and a brand decision. For instance, a brand manager might ask, “Is this the kind of consumer group that we want to continue to attract? Yes; OK, well … indicators show we may be struggling with this particular group, so let’s double down because from a brand perspective, that’s how we want to be seen.” An alternative scenario here is the data suggests (to the brand manager) that too much effort is being spent focusing on the wrong group. Without asking the right questions, the data just suggests that marketing is ineffective. To finish, a company really needs shared responsibility to make data truly actionable. Ultimately, as an organization you determine what resources you want to put against data analytics, but knowing what question(s) you wanted answered first is important to making data actionable.
4) How will health club and health club member data evolve over the next several years — what will prove to be important signals for our industry in addition to financial, transactional and activity data?
[Jeffery Cooper]: So besides activity data from wearables, there will be a lot of contextual data the health clubs can now potentially get. With corporate wellness taking off you are going to see deep integration with insurance companies and insurance data. I believe, along those lines, health clubs will also be integrated more with the medical industry. As prevention becomes more associated with a basic level of fitness, I believe you will see medical data become relevant.
In that regard, I think prevention of chronic diseases is eventually going to drive a lot of people toward health clubs from the medical side of things. Right now, in most cases, doctors cannot write a prescription for a health club, but that could change as more complex sensors begin to validate the efficacy of fitness interventions.
Genomics data is another revolutionary area. You already have things like 23andMe, but there is a company Helix, which has been recently funded. Their idea is to sequence your genes, and license this data back through health care providers and fitness applications. With genomic data, consumers can make better choices (and health clubs can cater to them better). With this data, people can ask:
Am I suited for bodybuilding?
Am I suited for endurance?
From the limited time I have, where am I going to see the best results?
As science becomes more advanced, these companies will snapshot your genome once, and then as the science learns more and more about the genome — health clubs can take preemptive, proactive actions from that data to keep their members healthier longer, keep them out of the hospital and improve their overall quality of life.
5) Why does “Big Data” often fall short on delivering on its value promise?
[Mark Newman]: Personally, I feel that part of the problem is the way output data get reported. I feel that in data science to deliver a static report, it is potentially a sign that we have not done our job properly. The reason for that is because when we deliver a page of numbers, there is often no context to the end-user. When you are able to create/refine a business question, you generally make the presumptive problem simpler than it first appeared. Before you set off looking to get value from data, your organization should come up with your desired thresholds and metrics. Then instead of looking at static reports that, at best, will give you trailing indicators — build a dashboard that gives you real-time intelligence based on the most important metrics for your business. This dashboard should be something that your employees can always go to — not just some report that gets delivered on your desk — but something that is readily available on an ongoing basis. You also need to evaluate and monitor the efficacy of this dashboard on an ongoing basis. For instance, if you have a forecasting dashboard and there is a forecast your company is trying to meet, is the dashboard valuable and helping you meet your forecast?
I believe both dashboards that monitor things that drive your business forward, as well as insights that are actionable, are at least two things that give you some evaluation of whether “Big Data” is helpful and valuable within the context of your own particular situation. The other thing is that you really want to be doing analyses all the time. You want your data strategy to evolve past sending out graphs and numbers — to actually be working to build a story of what’s going on in your organization — and back up your story with reliable and meaningful communication so every stakeholder is seeing the same thing and you can all agree that your chosen data model(s) is providing value and is meaningful within the context of your particular business.
Dr. Henry DePhillips is the Chief Medical Officer of Teladoc. At Teladoc, Dr. DePhillips is responsible for maintaining the exceptional delivery of clinical care delivered through Teladoc’s telemedicine digital health platform. Prior to Teladoc, Dr. DePhillips held several high-level leadership positions in health care. His positions included a previous role as the Chief Medical Officer at MEDecision, working as the Senior Medical Director at Independence Blue Cross of Pennsylvania, and a role as Head of Business Development, North America for McKinsey’s international Health Systems Institute. Dr. DePhillips is a health technology fanatic who is passionate about telemedicine and shifting health care from a provider-centric model to one that better values the needs of the patient.
1) How do you see telemedicine affecting employee burnout and workplace wellness?
What I am seeing is that telemedicine provides employees quick and inexpensive access to services that contribute to their well-being. Employees also generally perceive the telemedicine experience as more enjoyable than traveling to see a physician. Employees like what we provide, so our service grows as it is better understood by employees. When people get the care they need in a timely manner, this reduces workplace wellness issues — concerns like presenteeism — because employees now have easy access to care rather than “powering through” health conditions that could have unwanted consequences if ignored. These consequences range from getting other employees sick to compounding personal medical issues by not seeking treatment.
2) What are some of the aspects of American work culture you see uniquely contributing to issues of presenteeism and employees “powering through” illness?
There is a combination of cultural factors here in the United States. One is financial, many American employees can no longer afford to miss a day of work. A second is functional. In many U.S. companies that have downsized staff, if someone misses work then there is no longer anyone to cover their role/position — calling in sick is simply not an option. A third is cultural considerations. In America it is a sign of toughness and/or commitment if an employee powers through their illness. For instance, it can be viewed as a “badge of courage” if you come in with the flu. Lastly, there are logistical considerations. In many cases when someone should see a doctor, they are unable to do so because scheduling is difficult given other considerations. This last factor is where I see services like Teladoc playing an important role. With telemedicine it is no longer a burden to see a doctor. With the traditional approach you generally must take time off work, schedule an appointment, travel from work to see your physician. Now, if an employee is in need of care, it is as close as their keyboard or mobile phone. An experience that used to be three to four hours can now be accomplished in 30 minutes with telemedicine — and unless you need to pick up a prescription, your experience can all take place in a virtual environment of your choosing.
3) How do you see telemedicine playing a role in helping improve the patient experience?
With Teladoc you can update your electronic medical record in minutes, request a board-certified physician to meet with you at a time that works with your schedule, interact with your physician using the digital modality of your choice (phone, video conferencing, digital photos, etc.), and have prescriptions sent to a location that is convenient for you. In my opinion, it is simply a better experience.
4) There are reports that over 15 million people now use telehealth, which is a 50 percent increase in usage from numbers reported in 2013. Who is driving this growth?
Telemedicine is still perceived as a rather new way of receiving care, so we have plenty of early adopters (now) but you are going to see increased utilization blossom as we move into the early majority. Those that would rather take a conservative/traditional approach will likely become more open to telemedicine as the technology matures. “Try it once, and you will like it for life,” really applies to our technology. We see that once users try it once they often return, at least here at Teladoc. In certain populations it is a no brainer — single parents with kids, those that travel for business — again anyone with logistical considerations will likely become lifelong users once they try it once.
5) Why do you think there is a significant proportion of physicians that have an aversion to telemedicine?
It is an evolution. It is a work in progress. Health care as an industry tends to be fairly conservative when it comes to technology. Think back to the Marcus Welby, M.D. days and we have not evolved much since then in regards to care. Health care is still a very provider-centric experience. The provider tells you the times that work for them, you go to the provider’s place of practice, the provider basically makes you adhere to what is convenient for the provider. I see telemedicine as the first major shift towards a consumer-centric approach. Under the current antiquated paradigm, a patient has to say, “I am sick, where must I go to receive care?” However, with telemedicine the patient can now ask, “I am sick, how can I most efficiently get the care I need?” And now, care is as close as the smartphone sitting on the bed stand. The doctor now comes to you, at a time convenient for you. At Teladoc, the average time between requesting a visit and being able to see a physician is 10 minutes. My job as the CMO of Teladoc is to make sure that the quality of care that people expect [from the old model] is the best it possibly can be [in the new model] as we go through this evolution. It is important to note, telemedicine is meant to address a subset of medical problems that has been specifically selected to work with telecare, problems that can be accurately and successfully treated using this form. In most cases I believe telemedicine will provide the end-user a superior experience, but there are going to be some specialties where telemedicine doesn’t make sense, and that is okay too.