Category Archives: behaviour design

The American Health Care Act’s (dis)Incentives 

http://www.commondreams.org/views/2017/03/09/american-health-care-act-wealth-grab-not-health-plan

The Republicans have recently released their proposed alternative to the Affordable Care Act (ACA), entitled: the American Health Care Act (AHCA).

One of the prime concerns they hoped to address was the Individual Mandate, as defined by the ACA. Their replacement, however, appears set to miss the behavioral objective which the enrollment incentive was designed to achieve.

Behavioral principles such as Prospect Theory, Certainty Effect and Present Bias define the short comings of their proposed legislation.

 

The Ongoing Challenge

After 7 years of fighting against the ACA, which the Democratically led 111th Congress enacted and President Obama signed into law in 2010, the Republican Party, under the 114th Congress, has presented their first detailed plan to replace the ACA. They are calling it the American Health Care Act.

The ACA is a complicated bit of policy, which in large measure reflects the nature of the problem(s) that it tries to address. Equally, the objections that people have with the ACA are complex. There are any number of aspects to the conversation regarding health care in America, and to both of these policies in particular, that might benefit from a behavioral science perspective. At the risk of taking a reductionists approach to a systemic issue, I’d like to focus on just one of those concerns.

The ACA enacted an individual mandate which said, in principle, if you don’t enroll yourself in an approved health insurance plan, the federal government will fine you with a tax penalty. For each full month that you forego health insurance coverage, the tax penalty would equal, roughly, $58.00 per adult. The maximum penalty for going without coverage for a full year would be $695.00.

For the ACA to work, from a purely economic perspective, healthy/ lucky people, who do not really need insurance, would need to pay into the insurance system so that unhealthy/ unlucky people can benefit. This is how insurance of all stripes works, generally. One of the challenges that the ACA was trying to address with the individual mandate was: ‘how to encourage young, healthy people to buy into the insurance system’ so that the system might function as a whole.

 

Prospect Theory & Bounded Rationality Aligned

From a behavioral economics perspective, the disincentives of the ACA seemed to align with the desired behavioral outcomes. The economic and emotional logic being: “As a healthy person I can either pay the government a small tax penalty, which will help subsidize the system, and forego health insurance. Or, I can purchase an approved insurance plan, which will help subsidize the system, and receive some benefits of being insured.”

The bounded rationality of the trade-off is pretty simple: “I know that I’m going to pay something, no matter what. I can either pay a penalty and receive nothing, or I can pay for a plan that at least covers me for the unexpected.” In both cases there is a certain near-term loss (either the insurance premium or the tax penalty). But, if I choose to go uninsured, there is a higher degree of uncertainty in longer-term outcomes. Whereas, if I choose the insured route, I have the certainty that I will be covered (relative to the chosen plan).

One of the caveats to this disincentive, however, was uncertainty regarding the relative effectiveness of the tax penalty. At $695 per year, it was significantly lower than the cost of any given insurance premium, then or now. People therefore criticized it, speculatively, as lacking the economic muscle to be an effective disincentive of foregoing insurance. While others made the argument that the tax penalty worked more from an emotional utility perspective, creating a new social norm through rules based signaling.

 

Alternative Assumptions, Alternative Penalties

The American Health Care Act, on the other hand, attempts to eradicate the individual mandate, as this was a major ideological sticking point with Republicans. (Not to mention that the Republicans promised to repeal the whole of the ACA in its entirety). What they propose in place of the individual mandate is to increase the insurance premiums on those Americans whose insurance coverage has lapsed for more than 60 days.

For example, assume you must forego health insurance for more than 60 days; this may be due to a chronic economic situation in which insurance is normally beyond your budget, or a shorter-term concern related to unemployment or other temporary factor. You won’t be fined by the government right away under the AHCA. In fact, nothing will happen until you attempt to insure yourself again. At which time you will face the prospect of a 30% increase in premium cost on whatever insurance plan you propose to purchase. That 30% increase would be in effect for the next 12 months of insurance coverage.

 

Consequences of Structure and Timing

From a behavioral design perspective, the proposed structure of the Republicans replacement for the individual mandate appears set to satisfy nobody’s interests. In fact, it may have potentially devastating impact on both individual health outcomes (as fewer people will be able to afford coverage) and on the bottom line of the insurers (as an insurance death spiral may ensue).

For young, healthy people who have never had an insurance plan before, the AHCA disincentive appears set to achieve the opposite of it’s stated goal. A 30% increase of an insurance policy that these young people never had equals zero in their accounting. They have no idea what the difference in cost (the true cost of the disincentive) would be because they have no baseline with which to make a comparison. Additionally, the penalty is off in the distant, uncertain future in which they may eventually need insurance. Given the impact of our present bias, this more or less insures that the additional cost is out-of-sight and out-of-mind, therefore rendering the disincentive wholly ineffective.

The other segment of the population that is most likely to forego insurance coverage are folks that are in the unenviable economic situation as to be unable to afford a policy in the immediate term due to circumstances. They would be balancing a near-term certainty (“I can’t afford it right now.”) with a distant uncertainty (“Will I absolutely need insurance in the next X# of days?”). The certainty effect in this case encourages a wait and see approach.

 

Intent is the Key Word in Communication

What the penalty might fully accomplish, however, is a guaranteed death spiral as the incentives seem structured to encourage people of all kinds to accept a lack of coverage in the short-term and to raise the bar-to-entry over the long-term.

How is such an incentive design supposed to be interpreted? Is this an unintended consequence resulting from chasing some other objective? Or is this the intentional application of a dark pattern? Your answer to that question probably depends on your political inclinations…

Dealing with Fraud

blog-dealing-with-fraud-wells-fargo-scandal

The incentive structure of Wells Fargo has been rightly criticized for the fake account scandal. The roasting of Wells Fargo CEO at the Senate panel hearing has also brought to question the responsibility of the senior executives. However, the overall narrative may be missing an important component – Perception of Risk.

We can safely assume that the front end employees, who carried out the transactions, were largely aware of the illicit nature of their actions. Most likely they also knew the potential consequences such as losing their job, facing charges or even serving prison time. How did the employee’s perceive these risks? What factors moderated their risk perceptions?

These are difficult questions. Unlike the incentive system that is tangible and easier to measure, risk perception is not. Risk is a feeling and feelings are hard to quantify. Our feelings may be moderated by our goals, our ability to deal with outcomes, our past experiences etc. They are also influenced by our social context. The social norms prevalent can easily override the written rules and policies. If people around us are performing deviant behaviors such as the one we are dealing with in this case, we are more likely to follow them. With over 5000 employees implicated, we can expect this issue to be present.

Alternatively, employees may be managing a very different kind of risk. For example, fear of losing their job in the immediate future. The temporal aspect of this risk may amplify it even further and employees might rate it significantly higher than the risk of getting caught in the far future.

So while we are discussing changes to structural aspects such as incentives and punishments, we also need to give adequate attention to the softer side of the issue. We need to design strategies to moderate the risk perceptions. Conventional tools such as awareness / education based trainings have limited impact. This is especially true when the behavior in question is fairly obvious. After all, there is nothing gray about opening a fraudulent bank account. Interventions that provide continuous feedback closer to the work context might be more effective.

This still leaves us with the question of measurement. One way to do that may be identifying lead behaviors. For example, are employees more forthcoming in discussing or informing potential issues? Are managers rewarding such positive behaviors? Are we seeing an increase in minor deviances? Measuring these behaviors can provide organizations the relevant prediction capabilities and also the time to activate preventative strategies. 

Managing organization risks requires focusing on both top-down and bottom-up issues. While we hold the executives responsible to develop the right kind of organization structures, we also need to design tools that ensure alignment of behaviors across the system.

Image Source: The Intercept

ESOMAR Excellence Award for the Best Paper 2015/2016

We are delighted with the news that our paper: Red Alert: Understanding the demand and supply side of girl child trafficking using a behavioural science approach has won the ESOMAR excellence award for best paper.

“The ESOMAR Excellence Award is given to the best paper from ESOMAR conferences throughout the year that best reflects the broad aspects and challenges faced by the market research industry today. All nominations are judged by an independent international jury and carries an ESOMAR-sponsored prize of €4,000”

Of the 6, Final Mile had 2 nominations.

One paper was based on our project to improve demand for Voluntary Medical Male Circumcision and the  winning paper was based on a project we did on finding behavioral science based approaches to prevent child trafficking.

“Trafficking in women and children violates the basic human rights to life, liberty and freedom to chart one’s own life course. Instead, it subjects the victims to cruelty, torture, dangerous and de- grading work, and inhumane living conditions. It is estimated that there are 20 million commercial sex workers in India, and around 80% of these are victims of trafficking”

Our project focus was on preventing trafficking by better understanding at risk populations, both on supply and demand side. Insights from this work have lead to new campaigns and on on ground initiatives that are showing promising results.

We thank ESOMAR for recognizing this work and deeply appreciate their efforts in providing us a platform to share this work which we are very passionate about.

Here is the press release from ESOMAR

https://www.esomar.org/utilities/news-multimedia/news/press-releases.php?idpress=132

 

India’s behavioral science policy unit – Challenges and wayforward

Two recent stories that appeared in Indian media suggest that the Indian Central (Federal) Government is looking to set up a behavioral sciences policy unit under the Niti Ayog, a Government of India policy think-tank established by the Narendra Modi government.

This news item that appeared in The Economic Times  suggests that the government has tied up with The Bill & Melinda Gates Foundation to set up the unit.

There have been several examples of Behavioral Insights units, starting with the one in the UK cabinet office. The Behavioral Insights Team is now partly owned by the cabinet office and calls itself a social purpose company. 

Niranjan Rajyadhyaksha of Mint had written this compelling piece on why the Modi government needs a Nudge unit. The Indian Prime Minister himself on occasions alluded to the behavioral nature of some of the problems, particularly sanitation.

Needless to say there are several advantages of such a unit. This well written editorial in Mint takes a more balanced view to such a unit. Incidentally, 4 of the problems outlined in the opening paragraph of the piece are problem areas Final Mile has experience using Behavioral Sciences.

The piece also points out some potential limitations of such a unit. There are areas where a nudge simply is not good enough, behavioral scientists themselves are not immune to bias and the fact that India is complex. We though believe that the complexity argument is over stretched. There is diversity in every country. Successive governments have been making policies  accounting for the complexity. Our experience in general has been that there are more similarities than there are differences. Dilip Soman, a well know behavioral economist suggests that “Complexity makes it more likely that soft interventions will work better than other options”.  A good next step  would be to recommend such a policy unit at the state level as well.

As pioneers in the field of applying behavioral science to solving real world problems, this is highly encouraging news. There are some challenges such a unit needs to navigate and, based on our experience, these are some of those. We understand that most of these if not all, would have been taken in to consideration by the decision makers.

  1. There is an inherent danger in assuming that a particular behavioral science principle is universally valid. There have been cases where using a principle blindly have backfired. There was a recent experiment where a company used social norms with a view to increase savings by it’s employees. It proved counter productive. In context testing is therefore key.
  2. One of the big crisis that hit the world of behavioral sciences and psychology is where many ‘successful’ experiments could not be replicated. This was particularly true of social priming. This paper co-authored by one of the senior employees at Final Mile has more detail  . There is a need to generate strong evidence before a policy or an intervention can be deployed. Rigorous testing is vital. As Richard Thaler, widely considered the father of behavioral economics says “You can’t have evidence based policy without evidence”
  3. Complex and wicked problems need a multi-disciplinary approach. A nudge unit team needs to bring in diverse skills. One that if filled with Behavioral Scientists may not be the best approach. In our experience, integrating design thinking with behavioral sciences can lead to powerful results. Equally important are measurement and evaluation experts
  4. Navigating through the government system and particularly the famed Indian bureaucracy is going to call for incredible amount of patience and tact.  
  5. Establishing value of such a unit is obviously critical. At a conceptual level, all this makes sense but government officials and ministers are keen on quick results. There are realities of electoral politics. A good approach would be take one or two areas and demonstrate value rather than trying to spread thin across ministries. Peter Kalil, Deputy Director for Technology and Innovation, Office of Science and Technology policy in the white house made some observations on this subject at the recently held Behavioral Science summit. It is far easier to take life sciences in to application. It’s tangible and we have experience and set systems. Taking behavioral science to people is not the same.  Framing results and writing for policy makers is quite different from writing an academic paper. And that working with existing programs is a much better way to overcome Status Quo bias. Launching new programs may not be the best way to go. 
  6. Libertarian Paternalism is a phrase that Prof. Richard Thaler and Case Sunstein coined. It might sound like an oxymoron, but it isn’t. In their own words “The idea of libertarian paternalism might seem to be an oxymoron, but it is both possible and legitimate for private and public institutions to affect behavior while also respecting freedom of choice. Often people’s preferences are ill-formed, and their choices will inevitably be influenced by default rules, framing effects, and starting points. In these circumstances, a form of paternalism cannot be avoided. Equipped with an understanding of behavioral findings of bounded rationality and bounded self-control, libertarian paternalists should attempt to steer people’s choices in welfare-promoting directions without eliminating freedom of choice.”  However, such a unit is likely to come under criticism from both the right and left of the political spectrum. The left would argue that you cannot call poverty a behavioral problem, the right might term this a “nanny state” initiative. These are extreme arguments but ones that have been made several times. Considering the possibility of sensationalism by the Indian media, such a unit needs to be prepared to effectively deal with criticism.

Ultimately, the success of this unit depends on government support and patience. The mandate needs to come from the highest level, like the White House Social and behavioral science team where President Obama issued an Executive order “that directs all Federal agencies to use insights from the behavioral sciences to make government programs easier to access, more user-friendly, and more effective” 

Obama also notes that “Adopting the insights of behavioral science will  help bring our government into the 21st century in a wide range of ways – from delivering services more efficiently and effectively; to accelerating transition to a clean energy economy; to helping workers find better jobs, gain access to educational opportunity, and lead longer, healthier lives”

The Indian unit could do with a similar endorsement from Prime Minister Modi.

Growth in the design economy

Design Economy

The limited ability of economists to account for the value addition given to goods and services by design (as well as other emerging disciplines) leads to an underestimation of growth figures.

In recent months, methodologies to measure GDP- traditionally the sole concern of the most grave and solemn of economists- has become a topic of mainstream debate in India. The Central Statistical Office (CSO) made two changes in the way GDP was measured: the base year was shifted from 2004-05 to 2011-12, and market prices of products, instead of factor prices, were now included in the formula. As a result, GDP growth figures shot up to 7.9% in the final quarter of FY2016- a figure that has been viewed with skepticism within India as well as abroad. On the other hand, growth figures in the industrialised West- usually in the neighbourhood of 2%- have been known to be routinely underestimated. What causes these discrepancies can largely be explained by the complexity of methods employed to calculate economic growth.

Government statisticians and economists are tasked with assessing, independent of political constraints, various measures to describe how much a nation’s economy and its constituents have grown in a particular year. Aggregations at a national scale and repetitions in counting are obvious difficulties bureaucrats have to deal with, but major complications arise in measuring real economic growth after accounting for price inflation. This amounts to ascertaining whether Rs.10,000 spent in 2016 provide consumers with as much utility or value as they did in the previous year. Conversely, if Rs. 10,000 helped derive a certain utility for consumers one year ago, the CSO attempts to determine how much more it will cost consumers to derive the same satisfaction today.

Even in a theoretically ideal, static economy where the nature and relative role of goods remains constant, these measurements are fraught with multiple problems. But  when the nature of products or services changes drastically, things get so fuzzy that even the ubiquitous ceteris paribus is rendered helpless.

Picture the development of a radical medical procedure that brings respite to the patients of multiple sclerosis, or a new form of chemotherapy that can kill cancerous cells more efficiently. The introduction of such a technology into the economy means that units of currency (dollars, rupees) are worth more than what they were before the new procedure was invented. In most cases there exists a lag for this change to be reflected in GDP calculations, and growth methodologies (to some extent) account for it. But more damningly, the only change reflected in official figures is the change in the the price of the treatment, not for the increase in utility or satisfaction experienced by patients and their families.

Paradigm-shifting medical cures, moreover, are not a commonplace occurrence- the last revolutionary breakthroughs in patient healthcare came with laparoscopic surgery and HIV cocktails in the previous decade. This laconic pace of change is not different in sectors such as automobiles, consumer electronics and telecommunications. The core technology of the internal combustion engine, for instance, has shown little change in over a hundred years. However, even the most Luddite commentators would admit that goods and services have shown value addition over the previous decades particularly in one aspect: design. A large share of the increase in factor inputs employed to produce a car in 2016 come from product and automobile designers that enhance its utility not only in terms of aesthetics, but also with regards to ergonomics, passenger safety and navigation technology.

The real price of automobiles, however, has not risen proportionally. In some cases, there may be a marginal change in the cost of the car year upon year, but all the increase in value addition from design and energy efficiency still contributes towards producing one additional unit of a car- a statistical constraint that partly explains deflated growth figures in regions such as London, whose design industries have grown to an advanced stage and hold a significant share in the overall economy. The increase in value to products and services by using different disciplines of design is said to have contributed 7.3% of the UK’s exports (£34 billion) in 2013, and designers now account for 24% of the wage bill in its information and communication sectors- showing breakneck increases in the last decade. In contrast, UK’s overall GDP growth has languished at 1.4% since the official end of the 2008 recession.

Analysts and economists attribute this slowdown in aggregate demand and growth figures in OECD economies to a drop in overall productivity. In a panel discussion at the London School of Economics earlier this year, RBI Governor Raghuram Rajan admitted how these figures may seem surprising to many at the beginning of their careers- considering they are surrounded by stories of innovations, about problems being scaled in ‘faster, cleverer ways’. The present cohort of workforce entrants is seeing potential improvements to productivity all around them, but these do not seem to translate into concrete growth and employment- summarising a lamentable paradox in today’s economy.

The design-growth contradiction also explains issues that affect developing economies like ours. Simply reversing the argument shows how we overestimate inflation by measuring it nominally, whereas real inflation isn’t as high- partly because of the increase in purchasing power of the currency due to contributions from exciting new fields like design. In other words, your Rupee has a greater ability to purchase better cars than in the past because of the work of an an automobile designer- think of the ways in which the Suzuki Alto is better than the  Maruti 800, even in the latter’s most nostalgia-inducing moments.

Image Source: The Design Sketchbook/Youtube