Rethink Work: Breaking Down Healthcare’s Hierarchies ft. Kaveh Safavi


Season 2, Episode 7

It’s hard to make progress in consumer engagement without a happy, satisfied workforce. The pandemic forced us to rethink the time and place of work, but it has only led to more questions such as how to look beyond pandemic recovery, and how we describe work in the first place. 

Join Dr. Kaveh Safavi, Senior Managing Director of Global Health Business at Accenture, and Chris Hemphill as they discuss the bigger question of what work looks like in the long term, and how it impacts healthcare consumer engagement efforts. 

Video Chapters
01:53 The Big Question about The Future of Work
03:33 How The Pandemic Changed the “Present” of Work
07:37 What Even IS Work? Defining What’s Expected to Retain Employees
11:37 Should People Fit Jobs or should Jobs Fit People?
16:28 Adding AI to Your Team: How Do Humans Get the Most from Machines?
20:20 Personalized Medicine vs Practice Patterns & Standards
24:34 How Healthcare Leaders Can Beat Old School Hierarchy

This conversation is brought to you by Actium Health in partnership with the Forum for Healthcare Strategists.

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Chris Hemphill

VP, Applied AI & Growth
Actium Health


Kaveh Safavi

Sr Managing Director of Global Health


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Kaveh Safavi, MD (00:00):
The pandemic caused an acute change in the place of work. And as companies were trying to think about how to return to work, they realized that if they just thought about it in the context of how do I recover from the pandemic, they would have answered the wrong question. Actually, there’s a much bigger question which is what does work look like in the long term? And what we’re seeing now is companies are using the opportunity of pandemic recovery to address in a much more fundamental way, what does work mean for them and their employees and how should they think about it in the long term?

Chris Hemphill (00:43):
Hello Healthcare, we are excited to be on the floor at HMPS, bringing a lot of the experience, bringing some of these topics to you on YouTube online, so that if you weren’t able to attend a conference, or if you did attend and you wanted a little bit more, we can get deeper into that. And you might have heard a lot of themes around consumer experience, patient experience, patient engagement and patient outreach, but none of that is possible without a happy and satisfied workforce. And there’s a lot of changes in the way that workforce is going to be structured. We might have seen some hints and glimmers of these changes over the past decade, but that really got accelerated with the pandemic of the most recent 24 months. So to suss out these changes to study the new state of work, to understand what the relationship is with our employees, no better than Kaveh Safavi, who is the Global Managing Director of Healthcare at Accenture. Kaveh, could you just give us a little bit of background on your relationship with the subject and what you’re doing at Accenture?

Kaveh Safavi, MD (01:53):
Well, what we’re seeing now is really the confluence of several big forces. One is demographics, aging affecting who’s working. Technology, which is affecting things like what you can do in terms of work. And then we have the broader economic realities, as well as things like the pandemic, which are causing both the demographic issues and the technology issues to remodel themselves. All of these things are really raising to the forefront, this question about what does work look like in the future? We already knew that there was a big question as to what work would mean with things like Artificial Intelligence on the horizon. We knew that we were having a demographic issue that was going to change the contours of the labor force. The pandemic forced people to start working from wherever. And the net of those is really a rethinking of the nature of work and the meaning of work as well as the location of work. And that’s what I talked about a little bit on my keynote.

Chris Hemphill (02:59):
Well, that’s fantastic to hear and kind of understand that we can get some perspective. I hope that this is an opportunity to step back and sit back and everybody watching probably has a different model that your employer has taken. You could be 100% work from home. You could be, let’s get butts back in the seat in the office, or it could be some sort of hybrid model to help get that perspective because we’re looking at so much choice and so much change at the same time. Could you give us just a perspective on what’s the state of work right now.

Kaveh Safavi, MD (03:34):
Well, it’s really interesting because the pandemic caused an acute change in the place of work. And as companies were trying to think about how to return to work, they realized that if they just thought about it in the context of how do I recover from the pandemic, they would have answered the wrong question, because actually there’s a much bigger question, which is what does work look like in the long term? And that required them to rethink not just the location, but what it means, for example, for people to work, why do they stay with me? And what we’re seeing now is companies are using the opportunity of pandemic recovery to address in a much more fundamental way. What does work mean like? What does work mean for them and their employees and how should they think about it in the long term?

Kaveh Safavi, MD (04:21):
So while you’re seeing immediate things like what is our policy behind it is a much bigger question. So for example, we know that we had been thinking, for example, that because of things like Artificial Intelligence, we would be able to take some tasks away from our human workers and give them to machines. The truth of the matter is that Artificial Intelligence is a big innovation in the sense that it allows us to do some non-routine tasks. This was a capability that didn’t exist with technology prior to automation, and that a lot of healthcare workers do non-routine tasks. So we never really were able to take advantage of technology as a labor productivity or a labor extending kind of utility until recently, but it wasn’t really whole jobs. It was just tasks. And so what do I do with the person when 20% of their work is done by a machine, but 80% is not. I need that person.

Kaveh Safavi, MD (05:29):
I can’t let go of that person. The machine didn’t replace the job. The machine just made the job different. And I started to invest in those technologies because the pandemic forced me to, but now I have to confront this on a long term basis. That’s not going away. And I want to capitalize on this investment. And, oh, by the way, if you think about something like the nursing shortage, we had a nursing shortage that was evolving before the pandemic, the burden of work in the pandemic caused retirements to go faster. We’re seeing a rise in the minimum wage that’s giving people opportunities to work outside of healthcare for levels of wage that might be commensurate with healthcare.

Kaveh Safavi, MD (06:07):
So some of the lower level nurses are going so suddenly what was simply a shortage because of aging has been wildly accelerated by burnout and economic competition with other industries. So I will never solve that shortage problem by thinking that I’m just going to be able to backfill with nurses, I’m going to have to rethink completely how I’m going to solve this labor problem in a completely different way. That’s the reason why this conversation has become bigger than just, how do I return to the pre COVID world?

Chris Hemphill (06:37):
An excellent perspective. I kind of latched onto that when you were first talking. A lot of strategy, a lot of what people’s thinking is, how do I react to what happened during the pandemic? But what you’re saying is that the pandemic is an example of change that’s been happening for a lot of different reasons, such as changing demographics and changing age. So it’s not the question of how do I react to what just happened, but how do I adapt to where work is going.

Kaveh Safavi, MD (07:05):
What it tells me is how do I make my organization resilient to what our larger factors? All the pandemic did was it pushed the gas so hard that it shined a light on what the real problem is. Now that I know the real problem, I need to go address that problem.

Chris Hemphill (07:24):
Sometimes on this podcast, I like to get extremely basic about concepts that we think we know about. And during this conversation, this is a literal real question on my mind. What is work?

Kaveh Safavi, MD (07:38):
That’s a fantastic question. I think that’s almost an existential question for us. It ranges from, and this is psychologists and philosophers have been dealing with this forever. Is work something that you do largely as a means of economic capability or is work… It’s all the way to the other extreme, which is if you love what you do, it’s never work. I think that one of the things that, there’s probably an interesting metaphor that Jim Collins talks about in the context of success, from a business perspective, which can be applied at a personal level, which is it’s the overlap of three things. Work is the overlap of things you’re good at, things that you have a passion for, which may not be the same thing and things that society will pay you for.

Kaveh Safavi, MD (08:32):
And if you take the “pay you for” out, you’re in hobby land, and you may or may not be good at it, but that’s sort of the intersection of those three things. So I often think about work in the context of having all three of those overlap. That’s how you know it’s work. And if you take particularly the pay part of it out, you might not be in the land of work, but some people would say you can work and not have money. So I think part of it is really for people is, gets back to what is the meaning of work. And that actually is a really interesting commentary because we used to think that work was something you do to make money that you would then use in the rest of your life.

Kaveh Safavi, MD (09:12):
And therefore the obligation of your employer is simply to make sure that you get paid fairly and you get professional development. But what we’re seeing in our research around engagement is that people are actually asking or expecting that their place of work leaves them net better off. That’s actually a term that we coined in our research, net better off basically means that my interaction with you, my relationship with you leaves me better off in every dimension of my life, which includes money and professional development, but includes mental health, physical safety, sense of wellbeing, sense of belonging, all of these sorts of things. So on a very specific level, we see, for example, that people that are recruiting young people out of college to work for them are finding that the recruits are asking the employer, “What causes do you care about and how do you prove that?” just absolutely nothing to do with the job or the pay.

Kaveh Safavi, MD (10:10):
And they’re saying, “I’m going to choose who I work for based on whether or not your value system and my value system aligns.” And for a lot of leaders who were used to recruiting talent the old way, this is completely out of left field for them. That your decision to come work for me has absolutely nothing to do with the work you’re going to do here. It has to do with how my company behaves in this realm of society that we’re not even responsible for in terms of a direct production. So it’s really important concept. That’s people want, they see work as part of an extension of themselves as a human being.

Chris Hemphill (10:48):
And when we look at it that way, when we look at it beyond just a salary, or when we look at it as like what this company represents to me in totality, then it’s adding a lot more dimensions to the equation. Whereas like the earlier example that you gave, like somebody looking for a job 50 years ago concerned primarily with the pay, but now there’s a whole slew of new dimensions that employers should seem to need to be concerned with.

Kaveh Safavi, MD (11:18):
They have to be, because if they’re not, what will happen is the people will be dissatisfied and they’ll look for other jobs even at competitive pay. And that’s what we’re beginning to see now.

Chris Hemphill (11:27):
And another question about the the nature of these jobs and kind of like the nature of what is work. Is it fair for like if I’m a leader or an employer, should I look at work as a set of tasks to be accomplished? And like do we allow technology to accomplish set tasks or people, or how should we look at the kind of the mix of different opportunities to get these tasks-

Kaveh Safavi, MD (11:55):
That’s a fabulous question. It’s actually how we advise companies who are looking at organizational and operating models. So you actually start with what’s the company’s objectives. Because the company’s objectives is going to define company activities and outputs and those activities and outputs are going to define capabilities and that’s going to define tasks and that’s going to define jobs. And the fact of the matter is that you can skin the cat as a company, several ways. Once you understand what your objectives are as to how you want to allocate the tasks to different people who are then going to have different roles. The two companies don’t have to have the same model for what a job is. They just have to have clarity around what the outcomes are and then make sure that those jobs, those tasks map to jobs somewhere to somebody. So increasingly we really say, jobs is not the right lens. Tasks is the right lens and tasks are really a function of a company’s objectives and what work they need to have done, which then gets translated back to tasks.

Chris Hemphill (13:00):
Fantastic. So if we have a clear understanding, what are our objectives, and then you have objectives, strategy, tactics, what feeds to those objectives, I love it. And I kind of present to the idea, but now I want to attack it just a little bit.

Kaveh Safavi, MD (13:14):

Chris Hemphill (13:14):
Because I’m concerned that is there a potential that we get too rigid in that thinking and not allow for the blossoming thoughts, like somebody comes in to complete one of those tasks, but they have different ideas about the relationship work. I’m wondering how we can pursue that without becoming too rigid.

Kaveh Safavi, MD (13:33):
Well, so it’s an interesting way to say it because arguably historically, one of the challenges we had and the rigidity was because we made people fit jobs, as opposed to making the jobs fit the people. And we made people fit the jobs because we aligned the tasks in a particular way. So there are five tasks, I need to find one person who can do five of these tasks correctly. And it became hard to find someone. And if you had that job, that’s what you had to do. And increasingly particularly in quest for specialized talent, people started saying, “No, no, no. I start with who I have.” And I figure out how to match my problem to their skillset and their job is the best match of those two, rather than having them do a list that I had assembled and called a job. So I think there’s actually introducing flexibility when you stop thinking about jobs and thinking about tasks, because you can reallocate them.

Kaveh Safavi, MD (14:22):
That being said, I think you’re asking us maybe a different angle on the same question, which isn’t really addressed directly, which is how do I permit creativity? Because inevitably I’ve created a described a job in terms of me as an employer, what I need to get done. And that’s already limited by my hypothesis about how things are done. That’s a more of a cultural issue where employers have to decide if they’re going to permit creativity. And increasingly we see that high performing employers have to allow some level of creativity and autonomy or people are not going to be engaged. People don’t want to be machines. They don’t want to do repetitive things and just be told to do, they want to understand. And part of a sense of engagement is if I’m looking at my work and I have a better way of doing it, who do I talk to?

Kaveh Safavi, MD (15:14):
In fact, one of the things that we’re seeing increasingly as a driver of engagement is for employees to have the ability to voice better ways of doing their work and have that be recognized and building models that actually… And recognized doesn’t mean put a piece of paper in a suggestion box that goes into the ether. Recognized means some active feedback loop that says, “We’re hearing you, we’re even thinking about these topics.” People raise this issue, identifying individuals, letting the whole organization see that we are actually hearing these ideas and looking for the good ones and encouraging them.

Chris Hemphill (16:01):
Excellent. I’m really loving the way that you’re describing this because it’s a dance that you’re describing where like we have an understanding of our objectives and there are tasks that we kind of aligned with that, but there’s still an openness to steer the ship. Like maybe there are other ways that we can hear from our employees on how to better steer that ship towards those objectives.

Kaveh Safavi, MD (16:28):
This actually is being amplified in the era of Artificial Intelligence because what Artificial Intelligence does is it creates this environment where the workforce is a team of humans and machines working together with an allocation of tasks. But there’s actually a set of skills. They’re called middle skills, which is how does the human get the most out of the machine? And in fact, how does the machine get the most out of the human, so to speak? That kind of an interaction is that is not a fixed, rigid answer. And the reason I say that is because the technology who’s your partner is continuously changing. That’s the nature of Artificial Intelligence, the technology changes without any explicit coding, because of the feedback loop of data. That would be no different than two human beings working next to each other, where you’re my partner and we’re doing a task and you figure out something differently.

Kaveh Safavi, MD (17:20):
I have to react to it. Whereas the old, the sort of pre Artificial Intelligence, the machine kept doing the one thing. And if you gotten away, you got your hand cut off because it didn’t know you were there and didn’t care. You just had to work around the machine, but the machine didn’t adapt to you. I make that point because whether it’s a physical robot or a cognitive robot, let’s say it’s a question answering kind of a thing. What works looks like between the human machine dyad is never the same when you go to two different places because by its nature, the machine has changed and therefore the human has changed in response to that and they’ve iterated.

Kaveh Safavi, MD (17:58):
So one of the challenges we have in health oftentimes is people are looking for what’s the playbook, what’s the rules, just tell me what to do. That got really hardwired in the last 20 years because 20 years ago when the Institute of medicine came out with its observations about medical errors and it identified unexplained variability in the way people are cared for, there was a real movement, both because of quality and safety, as well as affordability to get variation out of the healthcare system and to get everybody to do the same thing with the spirit of that’s the safest and most cost effective.

Kaveh Safavi, MD (18:33):
We’re now entering into a world where your work is actually different every day, because the technology, which is your coworker is different every day. And what we’re telling people in that environment is you have to actually continuously change. And the response often is, wait a second. I thought that we were about high reliability and that meant doing the same thing over again. And what we’re actually saying is, nope, it’s actually not right. What we said was we wanted high reliability around the outcomes, but we didn’t know how to do that so we focused on high reliability around the activities.

Kaveh Safavi, MD (19:08):
And now I’m telling you high reliability on the activities is guaranteed to give us the wrong outcome. What I need you to do is to get the best outcome by continuously adapting what you do to the technology that you’re working with. That is a test and learn model. And at its surface, it feels like test and learn and high reliability are in direct conflict with each other other and we’re going to have to actually help our healthcare workers reposition their thinking because they’ll never succeed without a test and learn approach because that’s what their work is going to look like.

Chris Hemphill (19:46):
Yeah. It did feel a lot safer and easier when the responsibility was in an a preexisting process. But it sounds like your argument now is that the way that we have to think about our approaches, the way that we have to adapt is not to follow a letter of the law because the situation is continually adapting so the average is not good enough. We have to [inaudible 00:20:09].

Kaveh Safavi, MD (20:08):
And the goal is the best outcome, not the standard process. And increasingly as we understand the complexity of outcomes, we realize that it’s a very different, I’ll give you the maximal example on the biological side, we talk about personalizing medicine. And if we perfectly executed that and we thought about both the biology and your preferences, and my goal was to give you the most personal experience, both from a biology and from an experience perspective, one could envision a world where no two people were treated the same in any dimension. So what does that mean around concepts like practice patterns and standards and variation when the end state, the perfect end state is no two people are treated the same.

Chris Hemphill (20:57):
So yeah. In that thought exercise, it seems like whatever system would be developed would have to be resilient like the individual context of the in person involved.

Kaveh Safavi, MD (21:09):
Right. It starts with the requiring people to understand that the goal is the result and then working your way to get out of healthcare and go to customer service examples that are well recognized. The customer service companies like what you’ll get for example, if you reach a customer service agent on Amazon, they have have huge discretion to solve your problem. It’s not rule based. They call in based on the dollars and based on your history, they can decide to give you a refund and not ask you to send the item back. Well, I mean, in healthcare, that would be completely in an anathema, that the person is just going to decide on the fly what they think is right. Now, the organization has boundaries around what outcomes they’re trying to achieve.

Kaveh Safavi, MD (21:55):
But one of the outcomes they’re trying to achieve is a satisfied customer who keeps coming back. So the answer is, well, let me figure out what it’s going to take for that person to come back. Let me figure out, let me understand what I know about the economics that we’re trying to solve for. And then my job is to figure out what the right answer is for this person. When I understand outcomes, there have been other models that have illustrated this, the military and general Stan McChrystal wrote a book about this called the Team of Teams coming from our learnings in Afghanistan, that why is the greatest military power was failing. And it was largely because we were continuously running this command and control hierarchical model. And by what our success in the surge was we basically gave much more freedom to individual units to understand the environments they were operating in.

Kaveh Safavi, MD (22:47):
To give up hierarchy, you have to do a few things. Basically everyone has to have the same objective. The mission has to be the same and clear to everyone. Everyone has to be working off of the same exact set of information. So you have to have full information and it has to be completely transparent. You can’t give different facts to different people. And sometimes organizations do that because they don’t think people can deal with the facts that were, you know, so they give them sort of a variation on that theme. And then the third thing is that you have to build a model where you rely on people to make decisions without seeking approval. Otherwise they can’t go fast enough. And so in order to have this kind of test and learn, there’s a equivalent kind of agility. In fact, we’ve borrowed the term agile from software development where software development used to be what was called a waterfall.

Kaveh Safavi, MD (23:43):
You have a long plan and then you start coding and then you test and the modern way of doing software is what’s called Agile which is Sprints where everything you’re setting a near term objective, you’re doing it, you’re testing it. You’re iterating. You don’t have the full plan when you start, you have a sense of what the objective is. I know the problem I want to solve. I don’t know the code path and I’m going to start to do it in sprints. That metaphor has been moved into business and management and leadership, which is if an organization needs to move past it, can’t have the whole plan and then work the plan. It has to have clarity around the objective, clarity around the information and autonomy, and then all the groups have to keep iterating toward it. So that’s the kind of world we’re shifting to.

Chris Hemphill (24:23):
So we see ourselves shifting towards an outcomes focused world and a world where we’re moving in small iteration, testing, learning each step of the way, but it’s a state and transition. I’m curious, I want to take a little bit of a step back and ask about, it could be the healthcare leader or it could be any sort of leader, but if you have a healthcare specific example, all the better, just curious about that leader who is used to that kind of super process oriented world that was less focused on the outcomes. What are the steps personally that one could take to start transition to that new mindset?

Kaveh Safavi, MD (25:00):
Well, first of all, the one thing I’ll modify is those leaders were interested in outcomes, but they didn’t actually state the outcomes. So they substituted the processes for the outcomes. So if you told them that, they would believe that when you told them the outcomes, they would describe processes. So there are a few steps that go into that. The first step is the recognition of the three elements I just described. Clarity around purpose information and some kind of autonomy and decision making. Now you can’t necessarily do that to your whole organization at once, but you can get the objectives clear. So typically what we see the first big problem is you got to get the objectives clear. Then the next big problem is the information that everyone works of. And then and only then do you start really thinking about creating autonomy around decision making because you don’t really want to release control, particularly around things that have clinical issues.

Kaveh Safavi, MD (25:59):
And that’s one of the things in healthcare when we are working with clinical issues, there is no doubt that there are things we do in healthcare that have life and death consequences in a literal way, but not everything we do is. And one of the challenges we have is we take the quality argument and the safety argument that applies for some of the work and make that the excuse for all of the work. And so part of it is unpacking the tasks and deciding, let’s take off the table first, anything that might hurt a patient and we’ll have so much to work on in all of the settings. Like for example, you think about a patient in a hospital bed and you put aside the diagnosis and treatment and think about housekeeping and think about food service and think about transport.

Kaveh Safavi, MD (26:50):
Those will primarily play themselves out in terms of inconvenience, not in medical outcomes. But we could start fixing those things. And so being able to take your business, respecting the quality argument, taking the issues off the table that are too harder, too risky, and working on others, giving people the ability to see success and then feeding that back in. The third thing that we’ve seen really clearly is when you’re trying to do big changes like this, you don’t actually try to change the whole organization at once. You have to take a particular part of the organization.

Kaveh Safavi, MD (27:26):
And the real goal is to help them get to a place where success is demonstrable and the levers that got you there are both knowable and can be stated to other people and then show that success to others. The biggest mistake is you have a concept on a PowerPoint and you start everyone doing it at once. That will fail. And that will cause people to rethink whether this made any sense or not. So we try not to have people get preoccupied with going fast in the whole organization and focus on getting success, finding the levers of success and then using that to expand.

Chris Hemphill (28:03):
Excellent. Excellent. I think that provides some clear actionable steps. And at the same time, you presented a big idea, but you broke it down in a way that’s like you said, “Hey, you can’t go,” and it’s completely changed based on this big idea that I just presented to you, but you can start, find a place, identify the potential risk of the outcome. Don’t treat everything as the same problem. Don’t treat everything as a clinical issue and find out where you can start making movements, find out where you can start making change.

Kaveh Safavi, MD (28:34):

Chris Hemphill (28:36):
Well Kaveh, this has been an excellent conversation. A lot of these concepts are very new to me and I’m excited to kind of see how these play out, post our conversation.

Kaveh Safavi, MD (28:49):
Great. My pleasure. Thanks for having me here, Chris.

Chris Hemphill (28:52):
All the people that want to continue this conversation, me included, because there’s some stuff that I wanted to ask about on Artificial Intelligence, but what’s the best way for people to get in touch with you?

Kaveh Safavi, MD (29:03):
Easiest way is on LinkedIn. First name, Kaveh, last name, Safavi or you can follow me on Twitter, @drkavehsafavi.

Chris Hemphill (29:10):
All right. Well fantastic. And thank you for being open about this conversation, sharing a lot of the research and a lot of the work that you all are doing on the ground. And again, we hope you appreciate this slice of HMPS.

Kaveh Safavi, MD (29:23):
Great. Thanks.

Speaker 3 (29:24):
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