COVID-19 and the Post-Pandemic Economy: Energy Impacts, Winners and Losers — Implications and Economic Recovery
In the first episode of a three-part series, BRG Managing Directors Roger Kaiser and Greg Russo talk with host Michael Whalen to discuss potential ways to forecast the COVID-19 pandemic’s effect on the economy and the energy sector. They weigh in on factors companies and policymakers should consider in taking a first step toward normalcy.
TRANSCRIPT
MW 00:02 [music] Welcome to be BRG's ThinkSet podcast. I'm your host, Michael Whalen, an expert in BRG's Energy and Climate practice. BRG is a global consulting firm. We help organizations in disputes and investigations, corporate finance, and performance improvement and advisory. We're a multidisciplined group of experts, industry leaders, academics, data scientists, and professionals. Around the world, BRG delivers the inspired insights and practical strategies our clients need to stay ahead of what's next. For more information about BRG, please visit thinkbrg.com.
In this part one of a special three-part series, we'll discuss COVID-19 and how to forecast the pandemic's effect on the economy and the energy sector. Joining us from Chattanooga, Tennessee, is Roger Kaiser, an expert in BRG's Healthcare practice and a medical doctor. Also from our Healthcare practice is Greg Russo, an expert in modeling and data analysis. Greg works from BRG's Washington, DC office. … Let's start with you, Roger. The energy industry is driven by economic activity, but the global economy has been in standstill mode as many countries have adopted what is called non-pharmaceutical interventions to slow the pace of COVID-19. Many of these have been highly disruptive to the economy. What are your thoughts surrounding the timeline of developing vaccines and effective drugs?
RK 01:42 Before we get to answering that specific question, I think that there's some context that we need to consider as we look at how we got to this point that will help us find some guidance as to what the exit will look like coming out of this current shutdown. And there are really two key dynamics at play here. One is the medical data, which I'll discuss in a second, briefly. And then the other is the psychological and political response. The medical data. Very early on in March, it was clear to some of us that this COVID-19 disease was not going to be as severe as some of the modeling was indicating. And early data off of the Diamond Princess cruise ship out of China, out of Italy, and out of Iceland. Now, there were three key takeaways from that early data. One was that this was a virus that targeted a very specific population, and that was the elderly and those who had underlying medical conditions. The other takeaway was that the vast majority of cases were mild, and up to 98 or more percent of those who tested positive completely recovered. And then lastly, when you adjusted the mortality rates out of places like Italy and China, it was apparent that early indicators were that the death rate would be very similar to the influenza A and B annual seasonal outbreaks. And then as modeling kind of simultaneously came out with projections of 1 to 2.2 million deaths in the United States, those have all been grossly revised downward. And that led to the psychological and political response.
RK 03:46 We now were confronted with a disease that's going to have a significant mortality rate, and it is going to overwhelm our hospitals. And that led to the shutdown and a lot of the misinterpretation of the data and the impact of these modeling on a very high level of anxiety across the world. And now we find ourselves where we have an enormous unintended consequence of this shutdown—increase in suicide, opioid overdoses, child abuse—all because of the shutdown. And the exit strategy, and this will impact when and how we come out, is that our political leaders and our medical experts have now painted themselves into a corner where there's got to be a way for them to save face to come out of this. So to answer your question about the vaccines and the medical therapeutics, that is one of the four levers I am looking at as to when we emerge from this and how we emerge from this. Vaccines are not the panacea. It's going to take, best case, six to nine months before we have one. And even if they do come out—even with the influenza vaccine, we still have 30 to 60 thousand deaths per year from influenza. And even with a vaccine, it is still possible that there will be significant mortalities from COVID-19 in the future. There are some promising early anecdotal findings around some of the other therapeutics. There are some antivirals that appear to be effective, and also, some plasma therapies for those who have the more serious impact of the COVID-19 look to be effective. And all those, we'll be rolling out in a much larger scale over the next 60 to 90 days.
MW 05:49 So, Roger, Dr. Fauci and others have been talking about what factors need to be considered in coming out of the lockdown, and President Trump has organized a task force to advise him. What kind of factors do companies and policy leaders need to keep in mind to resume something, which approaches normalcy?
RK 06:16 Well, there are four things I am looking at as indicators as to when we can go back to whatever the new normal is going to look like. And one of those is the data. And I think the data is pretty clear now. That we have reached the peak across the world. That social distancing, which a lot of the experts will give credit to this downturn, is probably not as important as we think. If you look at states like Florida, compare them to California that was early and then Oklahoma, which didn't shut down at all, it's looking like there's not a lot of correlation with the shutdown and the impact of the disease progression. It's looking like there's not a lot of correlation with the shutdown and the impact of the disease progression. So the first one is the data. The second one is the testing. And what I believe will be most important to help us understand where we are in this disease process will be when we roll out on a large scale the antibody assay where we can look at and study how many people truly were exposed to this virus, had this virus, and either were asymptomatic or very, very mild cases. That'll be very helpful because once we know that denominator, we have a much better handle on the mortality rates. And the lower that mortality rate can be, the more confidence in the general public that we'll have to get us back to a normal situation.
RK 07:55 And so I think we're pretty close to that. I saw Stanford is rolling out a 10,000-individual antibody assay that won't take very long. We should have that information within the next month. The third metric I'm watching is the hospitals. It is obvious that the surge that everybody was expecting that was the real cause for the shutdown to so-called flatten the curve has not happened other than in a few extremely small pockets. I am in constant contact with a lot of our clients and physician colleagues around the country. The vast majority of hospitals are sitting there empty. Elective surgery has been canceled. There is considerable data and evidence that that ban on elective surgery should be lifted immediately. And then the fourth metric I am looking at is the therapeutic interventions, and we've kind of spoken to that previously. So all of my four metrics have been met, and I think President Trump is leaning the same way. And he's pushing to get this thing open and back to normal sooner. That all being said, there is still this psychological overlay that we're going to have to work through and regain people's confidences to get back on planes and go back out in public, travel. And that will be the more difficult to crack to return to whatever this new normal is going to look like.
MW 09:31 Thank you. Let's turn to Greg. Greg, I can't recall hearing more discussion about the workings of models and forecasting outside of election season. And what have we learned about the models that have been deployed to forecast the effects of COVID-19? What have we learned about their methodologies and different approaches they've taken and the types of results we've seen?
GR 09:57 Well, as a graduate of a school of public health, there is something heartening about this situation, which is that never before has public health and epidemics and doubling time been so widely discussed. And for that, there's sort of a silver lining in it for me. Now, unfortunately, we needed this sort of a situation for everyone to discuss the real implications that public health has on our economy and on our daily lives. And it's been very interesting to see the amount of focus that has been brought to the different models that have been out there to look at COVID-19's impact on different populations. This is a disease much like many others where hindsight is 20/20. We'll have the ability years from now to sit back and really understand many of the nuances of the disease. And as we understand more of the nuances of the disease, we’ll have a far better time predicting and modeling what the outcome is. And that has led to many of the constraints early on in dealing with this pandemic. We in the public health sector as well as within governments across the US or across the world, we're doing our best to model what the projected impacts would be. But doing so with imperfect data, we were attempting to get the latest and the best resources. But as you can imagine, those resources change sometimes daily, sometimes even hourly in the case of doubling times as countries reported more and more statistics.
MW 11:48 So you're highlighting the extent of the uncertainty in this. And it certainly has struck me that a number of models make assumptions about COVID-19 projecting, for example, that it responds the way seasonal flu does to different weather patterns such as summer weather in the northern hemisphere. How have the models dealt with these uncertainties, and how do we think about the results of these models in light of the inevitable uncertainties associated with them?
GR 12:17 What I think is really interesting when you look at the models is the high degree of variability that you get in them. There is a model that is relied upon through many different circles. It's called the IHME model, and that model has predicted that we are already past the peak of resource utilization and cases in the United States. But there are other models that have come out of the University of Pennsylvania and come out of Harvard that don't have a similar prediction. So what is really interesting, I think, about these models is that there is a model to support whatever conclusion you would like. So if you'd like to buy into the hypothesis that COVID-19 will follow a similar trajectory to a seasonal flu, there are models and results to support that. What is shown through all of these is there are many aspects of this where it is anyone's best guess. We can look at the data, and we can try to predict. But as I said, hindsight is 20/20. If we had the ability to predict as well as we would like to think we would, then this crisis never would have been upon us in the first place. Now, it's important, though, that we look to the models to try and understand where we can go from here. So as Roger was talking, how can we begin to open back up the country or parts of the country to businesses as normal? And the modeling is far more consistent for shorter periods of time, and it's the longer periods of time where the models create much more fluctuation. So, as I mentioned before, as you talk about the summer months, there is much more variation. But if you focus on the next fifteen days, what we have is we have the real-time data as Roger had mentioned, talking to hospitals throughout the country, understanding what their current need is. And then we also have an understanding of the number of current cases. The next fifteen days seem more consistent throughout the models and more manageable.
MW 14:27 Greg, do you think-- going to Roger's point on the impact of uncertainty and the concern in the population perhaps in interpreting some of the scariest and worst-case scenarios that have been projected by some of the models, one would expect in forecasting the future that there would be underestimation and overestimation. Has there been a bias toward overestimation in the results that we've seen?
GR 14:55 I think that there definitely has been a bias towards overestimation when you look throughout many of the different models. Especially early on, I think there was a bias towards overestimation. Now, some of that was, as I had mentioned, due to imperfect data. When you look at some of the initial studies that the CDC had pushed out, there were hospitalization rates in the twenty percent range. Now, that was due largely to the fact of the patients that were showing up to the facilities where those that were already sick and had a number of comorbidities. And when you have inflated values in those early statistics, it causes you to inflate the impact of the virus. What we don't have early on in the course of a pandemic of this sort is wide-scale testing where you can understand the infection rate in the population and the true amount of hospitalizations and the true amount of ventilators that are needed to serve that population. And once we get through this pandemic, we will have that information. Iceland is doing a broad scale testing regime where they're testing a far higher percentage of the citizens of their country than any other country in the world. That's going to really give us a sense of how prevalent the virus has been throughout the country and what percentage of those patients actually needed hospitalizations.
MW 16:24 At BRG, we're all data-minded people, and I think we've all been maintaining kind of our own databases or data tracking systems as we've been tracking the pandemic and trying to contemplate its effects. I noticed that some of the models that I was working on or maintaining took a big spike when New York City decided to count suspected COVID-19 deaths in addition to those that had been attributed to COVID-19 on the basis of individuals who had previously tested positive. How has this affected your analysis to date? Because it's one thing to have wrong data. At least it's consistently wrong. It provides some information on trends. But how do we deal with the fact that there's not even a common agreed definition of what a cause of death is?
GR 17:10 Yeah, it's something that we're going to struggle with I think for years to come, not only in terms of the modeling of the pandemic but also as we deal with the healthcare industry's implications of what the cause of death might be and payment for those services. There are a number of individuals that have not had ready access to testing. And when you don't have ready access to testing, how do you know that you actually have the disease? So I do anticipate that the numbers will spike. But I do think that there's also going to be spikes in the number of infections as we go through and understand more of the disease and do some more testing.
RK 17:51 So Greg mentioned that there's been this tendency towards over inflation in the modeling. And what we're seeing in the United States, and it's the first time I've ever seen this happen, is the CDC has come out and provided guidance that any patient that tests positive that dies is listed as a COVID-19 death. The rest of the world is not doing that. And the second thing that the CDC has done specifically here is that it is allowing the physicians to list the COVID-19 as a death if they suspect it, even if they don't have the positive test. So when the dust all settles, we'll find that our death rate from COVID-19 compared to other infectious diseases will probably be overstated.
MW 18:44 So let's switch to a discussion on the implications of the disease and of the responses to it that have been driven in part by these forecasting models. Charlie, you've been operating at the intersection of economics, the energy sector, regulation, and statistical analysis through your career. Tell me, in what ways have you found the COVID-19 crisis to be similar or dissimilar to your experience in other situations where we've been trying to assess the balance between risks and economic costs?
CC 19:17 Well, I think at the highest level, the similarities can be drawn between a dramatic effect of stay at home, and empty streets, and empty shops, and sidewalks, etc. And these only pale in comparison. But you have to go back to the bread lines of the Great Depression, maybe the gas lines of the two energy crises that hit in the 1970s. When you look at those things, you realize that this is a major change. And when you look for solutions, the dissimilarities are where I think we have to start to focus. So we really haven't seen anything like this. In terms of the main difference that I see, it's that the depression in the economy is caused by government action, essentially command or coerce people to stay at home. Businesses quickly followed. State governments followed. School systems followed. Indeed the rest of the world started to follow pretty dramatically after the US took that action. So demand is way down, and the real uncertainty out there is what will happen to demand once we start to issue some assurances to the public and to businesses and to governments that employ lots of people that it's safe to go back to work? And I think we've already heard from Roger that the availability of testing and the availability of the information that could allow individuals to make that decision is going to be lacking for at least a period of time.
CC 20:53 And we heard from Greg that the models are in dispute. The willingness of people to have confidence in a scientific adviser to the president or to scientific advisers to governors is going to be out there and lacking. So the idea of recreating the demand by announcing the economy is open is something that I think there's some very serious doubt about. And that then leads to really a challenge for everybody. The government's pretty good about stopping things. It's even pretty good about commanding specific entities to do something or stop doing something, but it's not very good about orchestrating the recovery of a complicated economy like we see in the US. And so it's going to really take confidence. That's going to have to come from people. It's going to come with some assurances that the liability of lawsuits and risk that might be placed upon people who return their employees to work and some of them end up getting sick and maybe die. We have to control those things and unless we do, we're going to have I think a very slow and drawn-out recovery. The only good news is that it probably won't be any worse than it is now. But the buildup, the coming back, the return, that's going to take quite an effort.
CC 22:21 We have to restore the faith that business has in experts. We have to restore the faith that people have in believing assurances. And all of that is looking at a very slow drawn-out recovery. The only exception to that—and unfortunately, Harry Truman said he wanted a one-handed economist so he didn't get conflicting advice from the person giving him the optimistic view and the pessimistic view. But the optimistic view is the rebound in the stock market makes it look like without anybody going out and trying to drum up investors or confidence among investors, investors are seeing that opening the economy is going to have a positive effect, and it's not going to be drawn out. But everything else is pointing to a very slow drawn-out recovery, and the rest of the world is in no better shape because it takes consumers to drive the opening of business just as much as it takes getting the employees back to work. And unless those consumers are willing to start to spend money, then we don't see that. And we also have a system that we put in place to help people during this down period and the shutdown period that essentially paid people not to work. And we have to undo that quickly because we're incentivizing people to stay at home and not work, and therefore, simply saying, "You can go back to work now," may not get the response that we think it will unless we start to untangle some of the things that we've also put in place.
MW 23:54 So, Charlie, one of the most favorite sayings of economists is, "On the other hand." The other one that I like is in the long run that we're all dead. But if I look at the long run relative to this crisis, the physical plant of the globe hasn't been destroyed unlike a major conflict or a world war. Human capital has been clearly affected to some extent by the pandemic but put into context of other diseases as Roger was describing, it doesn't seem to be an extinction-level event. The financial market responses and the mechanisms that have kept the financial markets running perhaps based on lessons we learned from the great financial crisis seem to have prevented financial market collapse. Does that suggest green shoots or an optimistic scenario?
CC 24:53 That's what the stock market seems to be saying, looking back at the last crisis that we had which was the financial crisis in 2008 and 9. And that says we haven't destroyed anything, and therefore, it's just a question of addressing the inherent flaws and problems. And the case of the financial crisis was to clean up the mess with unsecured loans. Here, it's getting people healthy and safe and reducing or mitigating the consequences of COVID-19. But the problem is that we've never seen four weeks of 22 million seeking unemployment compensation. The closest we have to a four-week number is one-tenth of that. A little over two million peoples went for unemployment during a four-week period. We haven't seen a seventy percent decline in retail sales. We haven't seen the amount of worldwide under or reduced activity throughout the economy.
CC 25:55 So that's where the similarity and the dissimilarity issue becomes very, I think, critical. If we think it's like the financial crisis, it will snap back. But if we think it's more like the Great Depression or even the energy crisis, those things took a decade or more before we started to get back to normal and put the crises behind us. And so I think it is a matter of on the one hand, it could be this, and on the other hand, it could be that. But increasingly, when you look at the ideas that we're seeing in this country of phase return to work where states will get to decide and they'll come up with different answers—in some industries, you'll be told they can go back to work, and we'll phase it in as we think that things are either under control or can be mitigated in those particular industries. That's not going to necessarily translate into consumers doing things. We can say the airlines are safe because we're cleaning them differently, but that doesn't mean people are going to get on a plane. We can say that the restaurants are now able to be reopened, but that doesn't mean people are going to go back to eating in restaurants and if they do, they're going to hang around and socialize within those restaurants. But one thing I can tell you, the more government tries to control and set the pace, history tells us it won't work. It's about getting people motivated, enthused, and willing to do things. That's going to, I think, be the path ahead that if we follow it will lead to the best results.
MW 27:30 And from your perspective as a regulatory economist who focuses on costs and benefits and trying to weigh the costs against the benefits, has that analysis been at all helpful during this crisis or has it been abandoned?
CC 27:47 A benefit-cost analysis is only as good as the inputs. And the inputs we had of more than two million deaths, that suggests hey, staying at home, it's worth the loss of a month of economic activity or two months of economic activity. But now we're discovering that the assumptions that went into the model, the data being based upon, the likelihood of requiring hospitalization, the likelihood of requiring ICUs, the likelihood of death was all driven by the fact that the denominator where the people were showing up sick, as Roger has told us. And therefore, we over-exaggerated the outcomes that were going to be bad and terrible, both in terms of the load we place on a medical care system as well as the cost of human suffering in terms of sickness and death. So at the time, making the decisions that we made probably look pretty good, but they were driven by faulty data and assumptions that drove models that were perfectly fine. But the assumptions going into them led to exaggerated results. So I think from that standpoint, we're seeing that the decision to stay at home made a lot of sense. But now that we've got a clearer notion that the death toll is likely to be somewhere between 30,000 and 60,000, we're seeing that the healthcare industry has been able to take the wave. Under those circumstances, the idea of keeping the economy shut down and phasing it in just isn't there.
MW 29:17 So let's turn to energy, Charlie. Prior to the pandemic, one of the things that we in the energy sector had been clearly focused on was another global threat which is the negative effects of climate change. How do you think that COVID-19 is going to affect this transition and the conversation about how it can be best accomplished?
CC 29:45 Unfortunately, it seemed that I'm unable to break my fifty-plus years of training and practice as an economist. It's going to be optimistic and a pessimistic answer. The optimistic side is, like Greg, I appreciate the fact that we've got the general public and the talking heads addressing science and expert advice and information. And that leads me to be optimistic that this will be an opportunity to think about climate change in a more complete manner than simply having it be part of the political debate. So the reliance on science and expert is, I always thought, a crucial part to change the politics of climate change in a way that we start to take it seriously and address the issue. To be optimistic, there's no better time than when the economy is struggling to find ways to open to start to look to ways to restructure the economy. We got out of the Great Depression, and we got out of the oil crises and the energy crisis of the 70s by restructuring business by changing the technologies that we relied on to find different ways of organizing labor and capital together to do things differently than we had done in the past. So all of that says this is actually a good thing to be happening.
CC 31:07 On the other hand is that pessimistic side of me that I have to share, and that is that scientists and experts look like they might have overstated the problem at least in retrospect. And as we try to encourage people to get back to work sooner, we're having to have more and more public admission that maybe we acted too soon, and we did too much. But we save lives, and even one life matters. So, therefore, there'll be some pushback on science that's not going to help climate change. And the other thing that's really important to me is that I've been around the environmental issues and the energy-related environmental issues for decades now. And what I've seen is the nation's willingness and even the state government's willingness to take on ways of becoming more efficient to have cleaner energy, to change the technologies that we're using to get things done both more efficiently and in a cleaner fashion, a fashion that would make climate risk less than it otherwise would be. A willingness to do that is when the economy is strong and people have jobs and being green becomes affordable and therefore something that we can all rally around, taking a long-term view for our children and grandchildren because we're confident about our own current economic circumstances. When things start to turn brown in terms of the economy, meaning it slows down, there's greater uncertainty—when people are not sure if they're going to have a job or whether their kids when they finish school are going to have the same opportunities that they had—when those things happen, we tend to put environment on the backburner.
CC 32:55 And if you read the climate science and if you pay attention to the people who put their whole life into studying climate change, they're saying we're really at a critical juncture right now. That we have to really start to make decisions now. They're going to make a real change by 2030 and have to really get this thing under control by 2050. This is an ideal time to do that as we're trying to rebuild and reopen the economy, but it's also coming at a time when we're going to have tough economic problems globally and in this country. And if it lasts into the next two or three years, we may have missed what looked like an opportunity to act in this decade to make a difference in the following twenty years. It's going to make that more and more difficult to accomplish, politically. And we need the money. We've already spent a lot of money on dealing with COVID-19 and the employment effects or unemployment effects associated with it. That's going to make it more and more difficult to do the kind of things that have to be done. I would certainly hope that if Congress and the president decide that there'll be another initiative, that infrastructure will become restructuring the energy sector and getting into more renewable and electric vehicles and more efficient operations. But I can't see that happening easily if we're in a tough economic period which I think will be the case for the next two or three years.
MW 34:22 Thank you. Before we wrap up, let's just go around with our panel and find out if they have any last comments on anything that was stated by the other participants.
RK 34:33 I think one of the outcomes of this COVID-19 situation that we're seeing in our Healthcare practice is that we're learning that we can interface with our clients pretty effectively without necessarily being on site. And I would not be surprised at all if our travel is cut significantly going forward. The other thing that I am hearing from my colleagues around the country is where they're finding that telemedicine is very effective, and it is safe, and the patients like it. And the cardiac surgeon that we talked to yesterday, his post-op open-hearts for their first post-op visit aren't going back to his office. They're doing it by telemedicine using Wi-Fi technology for heart rates and EKGs and pulse oximetry. So one of the fallouts from this will be that we'll probably have less face-to-face interaction than we have in the past.
MW 35:33 I can imagine that. Going to a doctor's office is not exactly high on anybody's list of even normal activity preferences. Greg, what about you?
GR 35:40 I would echo Roger's sentiments. Disruption is a good thing at times. And it's horrible when that disruption has to come at the expense that it came at in this crisis. But given that this crisis was really no one's fault, we have to look at disruption as having changed fundamentally the way that many of us have done business and the way that we've interacted. And I think that that's going to have some clear benefits that we will experience for many years to come.
MW 36:13 Charlie, parting thoughts.
CC 36:15 Yeah. I think, again, picking up on both Greg and Roger's ideas and comments, that we're probably going to see an increase in the private sector of healthcare professionals. And before that, I think we're going to see a growth in healthcare professionals where people go out and do the testing, who will help make certain that workplaces are clean and safe and maintained in a way that we never imagined before. I think back at 9/11 and the security and protecting things. And it wasn't just physically being safe, but it was protecting files, protecting access to facilities. I think we'll see some increasing amounts of that, and I think that'll tend to be the new normal, the new reality. It's almost like the school nurse that we grew up with will become increasingly important or equivalent to his equivalent today in terms of how businesses will function and operate. And then the second thing that I wanted to ask Roger about was—it strikes me that getting testing and getting the kind of testing that will tell you the risks to the population of getting COVID-19 if you don't have it, find out the people who have already had it. The risk, if you do catch it, of going further into the healthcare system in terms of requiring treatment and/or life support kind of activity. Is there a need for a coordinated national effort in that direction? The president seemed to be saying that the states should take that over. I'm wondering, you as a health care professional with many, many years of experience, what your views are on that. Is it something that one size is applied to all where sharing of information is a good thing, or is it a situation where we're better off trying different methods and procedures in different places and use what Judge Brandeis called the fifty-state laboratories of democracy and learn by the experiences of others?
RK 38:15 I think the answer, Charlie, is somewhere in the middle. One of the roles of the NIH and the CDC is to provide guidelines for all fifty states. To your point previously about wearing a mask or now wearing a mask, those guidelines have to be consistent, and they have to be based on facts and data. And there is a lot of finger-pointing at the federal government, specifically the NIH and the CDC, who are the lead agents on preventing this whole COVID-19 from happening and are now making missteps along the way that many believe are making the problem worse. And that leads you to the individual states saying, "Well, we don't have a lot of faith in our federal experts in this area." And that ends up with individual county health commissioners going off and doing whatever it is they want to do. We'll see certain states that will get this right coming out and other states that will not. And we will learn a lot from each other during this exit phase.
MW 39:20 Well, thank you. I really appreciate all of the BRG experts joining this podcast episode. A virtual handshake to each of you, which I think is the appropriate thing in this current environment. Thank you very much for lending us your knowledge, expertise, and insights.
MW 39: 35 [music] This ThinkSet podcast is brought to you by BRG. You can subscribe to the podcast and access other content from ThinkSet that magazine by going to thinksetmag.com. Don't forget to rate and review this show on iTunes as well. I'm Michael Whalen. Thanks for listening. The views and opinions expressed in this podcast are those of the participants and do not necessarily reflect the opinions, position, or policy of Berkeley Research Group or its other employees and affiliates.