Michael Wong is an Emeritus Board Member of the Harvard Business School Healthcare Alumni Association.

Michael Wong

Michael Wong: As the MIT Sloan Center for Information Systems Research (MIT CISR) has shared, “The goal of a digital business transformation is to improve customer experience and be more efficient; we call the companies that have learned to do both "’future ready.’" These future-ready companies are top performers, reporting estimated average revenue growth of 17.3 percentage points, and a net margin of 14 percentage points above their industry average—a big premium. As you lead the MIT CISR data research, along with the center’s Data Research Advisory Board, what steps should readers take to build such a future-ready culture and organization?

 C-suites need to take the lead by recognizing and communicating that their data assets need to be used in ways that produce financial returns. In other words, they need to ensure that their company’s data assets are monetized. The term data monetization is not a bad term, but a neutral one. All companies—from Fortune 500s to non-profits—are amassing loads of data, and it would be irresponsible not to create value from such an important and prevalent organizational resource. Future-ready companies naturally engage heavily in data monetization to achieve their customer experience and efficiency outcomes. But it’s never too soon for any company, regardless of where they fall on the digital spectrum, to begin learning. Our research found that top-performing companies of all kinds attribute 10 percentage points more to data monetization than bottom-performers.

Smarter organizations appreciate that it takes investment and time to establish and activate a data monetization strategy. For instance, Anthem (now Elevance Health) spent a year laying foundations to monetize its patient health data. It had to deidentify, cleanse, secure, and establish permissioning for millions of patient records to enable researchers, start-ups, and other partners to collaborate on artificial intelligence (AI)-based solutions for disease prevention. The resulting innovation platform led to new capabilities and solutions that the company could use to achieve better patient health outcomes. Data monetization efforts like this one can help companies develop more efficient work, craft better customer (patient) experiences, and even deliver new solutions (via new business models) that can be sold to others in the industry.

Wong: While several C-suites highlight the future potential value of digital transformation at their firms, actually monetizing the assets is often a different story. What are your top three practical recommendations for the monetization of assets which readers can begin deploying during this second half of 2023?

 I’ll give you one practical recommendation: start now. But I will give you three practical ways to make that happen. Here is a simple but effective framework that has resonated with my students and data board. You can monetize data in three ways: improving, wrapping, and selling [as I note in my book, “Data is Everybody’s Business”].

First, improving leverages data to create efficiencies in work from better, cheaper, or faster operations. For your sector, consider how forward-thinking organizations are using data to improve daily operations such as by reducing staffing needs (nurse response optimization), lowering the cost of medical product expenses (spend analytics), and improving hospital recovering times (infection rate reduction). Realizing value from such efforts requires removing or redirecting the slack created by the efficiencies so that they flow to the organization’s bottom line.

Second, wrapping draws on data to enhance an existing offering such that clients buy more, stay longer, or are willing to pay a premium. With the continued changes in the bio-pharma industry such as the recent momentum to broaden access of certain medicines via over the counter versus the historical model of needing a physician’s prescription, how can data and insights motivate target audiences to make that change? Moreover, how can a company leverage data insights to provide new experiences? Think informative patient portals and smart-hospital room interactions.

Third, selling is the exchange of an information solution for some form of money. By doing so, realizing value is straightforward and appears in the form of new financial inflows. Back in the day, selling meant selling data sets. Today, companies prefer to keep and protect their data and instead sell information solutions (patient health monitoring) based on their data assets.

How can you get started learning? Pick a data monetization approach that fits best with your company’s financial needs. Need to lower costs? Consider improving. Need to improve customer satisfaction scores? Consider wrapping. Need to grow? Maybe selling can help. Then, as you develop, execute, and monitor data monetization activities, you will build capability muscle that will serve you well in a “future-ready” world. My hope is that “Data is Everybody’s Business” will be a helpful tool for leaders as they develop managerial acumen in converting their loads of data into fruitful data assets.

Barbara Wixom, PhD leads the MIT CISR Data Research Advisory Board, comprised of data and analytics executives from MIT CISR organizations. The board prioritizes, informs, and participates in data research activities in ways that influence findings and insights at MIT CISR and in the broader global academic community. Dr. Wixom received her PhD from the University of Georgia.

Michael Wong is an emeritus board member of the Harvard Business School Healthcare Alumni Association.

Articles

MIT’s Barbara Wixom, PhD, outlines the importance of data-powered research in producing financial success. 

Why Data Should Be a Top Priority

With at least 13 different companies announcing staff reductions resulting in hundreds of layoffs during Q1-2023,1 many biopharma C-suites have doubled down on evolving technologies like generative artificial intelligence (AI) as panaceas to turnaround their fortunes. I sat down with Ayelet Israeli, PhD, a Marvin Bower associate professor of business administration at the Harvard Business School Unit, to discuss the capability for businesses to successfully utilize these technologies.

Michael Wong: Big data, machine learning, next best action, next best experience, and generative AI; if we only had a dollar for every time that one of these terms was referenced in a biopharma’s annual report. Technology buzz words have been around for decades, so, given your research findings over the years, what is the realistic potential for companies to leverage and scale these evolving areas and deliver quantifiable returns?

 At the heart of these evolving technologies is the simple principle of leveraging data for informed decision making; be it from pilot to scaled production. For example, I wrote a case study on how GAP’s CEO considered how they might leverage big data, versus creative directors, to predict what consumers want to wear next.2 And what was interesting to me was to think about which tasks are big data and AI are suited to do, and which tasks are less appropriate for data and AI. As we think about store and supply chain operations, integration between a seamless online and offline shopping experience, restocking sizes across stores, all of those can be better executed with algorithms. However, predicting trends and the success of new products is an extremely challenging task, especially in fashion, and we cannot expect that simply using historical data will help us predict future preferences and trends.

To your point, tech buzz words have been around for a while, but what is exciting to me is that generative AI could be something as big as the first Industrial Revolution. This assertion is based upon my own research and other field studies where large language models (LLMs) have successfully created value for everyday tasks like improving coding, enhancing professional writing (emails), and driving greater end-user self-sufficiency via call centers’ sophisticated chatbots. These examples are no longer just pilots but deployed in some Fortune 500s like Microsoft and Google where they have integrated LLM into office products and Internet Search.

While it is great to hear of the potential, what are your top three recommendations to help biopharma C-suites pragmatically deploy evolving solutions like LLMs and other technologies?

While different industries within the Fortune 500 will have various strategies, I would recommend a three-step playbook for your biopharma colleagues given the safety aspects of this vertical.

First, as many of these firms have thousands of employees spread around the globe, their C-suites need to provide simple but clear directives around what their teams can and cannot do around generative AI. Frankly, given the risks of well-intended but dangerous employee actions (for example, around data security and privacy and protection of proprietary data), I would recommend that most employees are banned from using generative AI on their company-provided computers. While there might be some test areas that are closely supervised, start small during this learning process. Assign specific teams that will evaluate different use cases across the company and see where these new tools can be deployed responsibly.

Second, provide continuous training and explorations around these new technologies for your employees. While it is great that many people have enthusiasm around the potential to use LLMs and reduce the time to bring life-saving drugs to patients, it is crucial to consider that many of the generative AI tools that we are seeing these days (such as ChatGPT) were not meant to reveal the truth or to display correct knowledge. Rather, LLMs were built to generate content like text that displays the words that are most likely to come next. In turn, one cannot expect the outcome to necessarily be true statements. Managers and employees need to understand the risks that LLMs are known to make things up or hallucinate and therefore cannot be used without audits for correctness.

Finally, invest in change management and communications during this journey. For the former, recognize potential biases if pilots are being trained on data with underlying biases contained in them, and figure out how to circumvent these issues. For the latter, continuous C-suite communications of expectations of behaviors with ideally the CEO’s and the CIO’s or CDO’s signatures on the email should be the norm. This simple approach will help set the guard rails for the entire organization to carefully crawl, walk, and eventually run with these powerful new tools to drive profitable growth.

Layoffs Continue to Batter Biotech, with Big Pharmas Piling on the Pain,

https://www.youtube.com/watch?v=zsh7opE4QZE

Ayelet Israeli is the Marvin Bower associate professor of business administration at the Harvard Business School Marketing Unit. She is the co-founder of the Customer Intelligence Lab at the D^3 institute at Harvard Business School. She received her PhD from Northwestern University and her MS, MBA, and BS from The Hebrew University of Jerusalem.

In this latest Harvard Business School Healthcare Alumni Association Q&A, Ayelet Israeli, PhD, explains the potential—as well as limitations—of these offerings and pragmatic guardrails for deployment in organizations. 

Leveraging Data for Informed Decision Making

Michael Wong: As your book mentions, the 60-plus economy is vibrant and, in the US, it presents an $8.6 trillion opportunity.

Still, why has this new concept been so challenging for companies to understand and engage with, and pivot away from society’s obsession with younger population segments?

 Overtaking the baby boomers in 2015, the younger “18-to-34 years” age segment has been long considered the key target segment for advertisers. Still, with 10,000 people turning 65 each day in America, by 2050, the +65 cohort will surpass the under 18 cohort. It is not surprising, as the average life expectancy has increased by 30 years over the past 100. For those reaching 65 years old today, approximately 50% will reach their 90s. And for those babies born today, over 50% of them can expect to live into their 100s! Those over 50 contribute to earnings and spending to the longevity economy valued at over $22 trillion worldwide and presents an outstanding opportunity for smarter firms, which can reframe their mindset about historically prized demographic segments.

When you consider how biopharma firms share common missions of saving and improving lives, their C-suites should especially lean into serving this growing population segment. These executives should consider other companies which have already deployed strategies to uncover new clients such as Warby Parker with their creation of a whole product line focused on progressive lenses. Or consider Bank of America’s Merrill Lynch Wealth Management group which hired the industry’s first financial gerontologist in 2014 to help the more than 14,000 financial advisors better understand the needs of their clients and implement a framework that assumes them to be living to one hundred.

Besides reimagining their external business development opportunities, what longevity strategies should be deployed for their internal workforces as people are going to have 60-year career spans?

First, the historical “learn/earn/retire” mantra no longer applies. With a potential 100-year life span, continuous upskilling coupled with career breaks will become a new norm. In March 2022, LinkedIn shared a new feature that enables people to easily insert career breaks into their profiles. Surveying nearly 23,000 workers and 7,000 hiring managers, LinkedIn discovered that nearly two-thirds (62%) of employees have taken a break at some point in their professional career.

 So, employers need to change their mindsets around career breaks and the historical assumptions, often negative, around them.

Second, create programs, like returnships, that provide near-term solutions to your firm’s talent pipeline needs as well as build long-term employer of choice recognition. As Goldman Sachs has proudly communicated, “Pioneering the first program of its kind in the wake of 2008, Goldman Sachs has sought to listen and continuously innovate to increase the number of opportunities in the return to workspace and recruit the best talent regardless of resume gaps.”

 I’ve read that Goldman Sachs has even trademarked the term, “returnships” and I do believe this programming has secured positive results for the firm.

Finally, C-suites should consider reimagined terminology when it comes to considering new ways of engaging with their workforce. As I have shared with my students at Stanford as well as corporate clients, it is stage, not age.

 Specifically, it is the stage of life we are in that is most important. A 50-year-old and a 75-year-old could be in the same stage of life, the "reinvention stage", given a 100-year life span. And when these two people reinvent themselves via upskilling their capabilities, they can potentially create new value at firms which recognize the benefits that they might bring to the table.

Stage (Not Age): How to Understand and Serve People Over 60--the Fastest Growing, Most Dynamic Market in the World, 

Harvard Business School Press, June 14, 2022

2. Golden, Susan Wilner; Carstensen, Laura, 

How Merrill Lynch Is Planning for Its Customers to Live to 100

LinkedIn Members Can Now Spotlight Career Breaks on Their Profiles

https://www.goldmansachs.com/careers/professionals/returnship/

5. Susan Wilner Golden | Stage (Not Age) | Talks at Google – YouTube: Susan Wilner Golden explains the major demographic shift currently taking place in the workforce; YouTube: Reskilling America’s aging workforce to meet the demands of the future (Full Stream 4/25)

As the founder and director of the dciX initiatives at the Stanford Distinguished Careers Institute, Golden engages experienced professionals who are focusing the next chapter of their lives on building innovations for both social and economic impact. Golden is the author of the book “STAGE (Not Age),” published by Harvard Business Review Press in June 2022. Golden received a Doctorate of Science from the Harvard School of Public Health.

In this latest Harvard Business School Healthcare Alumni Association Q&A, Susan Wilner Golden, DSc, lecturer at the Stanford Graduate School of Business, reveals an untapped $22 trillion global opportunity for all companies and others supporting healthy aging and longer life spans.
 


Embracing the 60-Plus Economy

Michael Wong: With US-based employers’ 77,770 job cuts in February, the total was the highest for the month since 2009, when 186,350 cuts were recorded.

 While technology cuts have gained the most attention, J&J, Pfizer, and other biopharmas have executed downsizings as well during these turbulent times. Given your expertise on human capital, what are your thoughts around these recent C-suite decisions to reduce their biopharma headcount?

If biopharma C-suites, and frankly their Fortune 500 peers as well, have critically evaluated the need to potentially pull the layoff lever, and it is necessary; then they should proceed. However, some recent announcements have continued poor layoff decisions for the following reasons.

Decades of research have shown that few layoffs do any good for performance.

 While layoff announcements often are embraced near term by Wall Street, rarely do C-suites get questioned months later to see if their “announced” layoffs were actually even executed. Still, even actual layoffs can have huge and unanticipated detrimental effects. As one study shared, “…downsizing a workforce by 1% leads to a 31% increase in voluntary turnover the next year.”

 The most powerful evidence is that companies that delay layoffs as long as possible do better financially in the long run because they are prepared for upturns in business.

So while it is an easy short-term lever to pull, it often does not address some of the real pain points that a firm is encountering as well as creating a potential near-term retention challenge.

Moreover, announced layoffs distort our perception of the reality of the job market. Especially in tight labor markets, turnover averages about 30% per year, and average tenure is about four years for employees. It is not that difficult to cut the workforce by say 10% simply with attrition. We forget that even with the 77,000 job cuts in February, employment grew by 311,000 workers that month, a very brisk pace. When the public is bombarded with the recently announced layoffs at tech darlings and historically stalwart Fortune 500s, it is natural for fear, uncertainty, and doubt to cause employees to begin diverting time toward exploring new career options when it may not even be needed. When employers are already faced with employee retention risks, as one report pointed to how seven of 10 workers have considered a major career move in 2022,

 layoffs should be considered as a last resort.

There are some firms which have already embraced your advice for layoffs to be avoided. For instance, at one firm which had delayed a promotion opportunity for a high-potential employee, it was commendable to hear that this person, while disappointed for the delay, had expressed that it was more important that the company preserved jobs for her teammates during these turbulent times. Still, building a culture andworkforce like this instance must be incredibly challenging. What are your three recommendations for biopharma C-suites which are striving to do so?

First, C-suites leading large biopharmas that are earning profits and have a solid balance sheet need to set the appropriate tone and culture for their firms. If you have R&D employees working on drug approvals that could be 10+ years in duration, why would you put unnecessary stress of announcing job cuts to improve current financial performance when you want your staff focused on getting safe and effective products approved for the long term? If it is a start-up with no profits and an unhealthy balance sheet, then a layoff might be necessary, but you need to craft a narrative explaining the facts around the decision, as well as why things will get better after the restructuring. Moreover, for the survivors, one needs to create a narrative explaining why they were chosen to be retained, be it for some specific capabilities or other reasons and why things will be better for tomorrow. Otherwise, they will think they could be next and will panic at that possibility.

Second, while emerging technologies in people analytics are a shiny new penny for C-suites, smarter executives will recognize that many of these offerings are about monitoring (checking on employees’ work habits, etc.) that erode employee engagement and commitment. Frankly, it is the classic divide between engineering (measurements) and psychologists (trust). While I can appreciate the value of both positions, my research and experience in this sector leans towards the high-trust model.

Finally, biopharma boards of directors need to set the correct tone for their C-suites and their direct reports if they want to build a high-trust culture that drives innovation and performance. It requires large investments of time with employees. Focusing instead on high-profile deals and other initiatives which support their own ambitious career goals may not be as valuable for the company’s workforce. For a biopharma to build the type of culture and workforce that your case analog highlighted, biopharma C-suites and their direct reports need to engage directly with their teams and communicate transparently why certain decisions are being made, such as when discretionary expenses have been cut to the bone, in order to preserve jobs. While these ideally in-person discussions might seem mundane, they are crucial to building a highly engaged workforce, which research has shown to create value for employee retention and shareholders.

; Highest YTD Since 2009 | Challenger, Gray & Christmas, Inc. (challengergray.com).

, Harvard Business School, February 25, 2020.

The Short But Destructive History of Mass Layoffs

4. Wayne F. Cascio, Arjun Chatrath, and Rohan A. Christie-David. 2021. 

Companies that Delay Layoffs Fare Better for the Long Run

People at Work 2022: A Global Workforce View

In this latest Harvard Business School Healthcare Alumni Association Q&A, Dr. Peter Cappelli, Professor of Management at The Wharton School and Director of Wharton’s Center for Human Resources, explains how biopharma C-suites can lead their teams through 2023’s turbulent times. 

Traversing the Biopharma Career Landscape 

For decades, how many of you have read resumes with people proudly mentioning how they are fortunate of being able to work “at the intersection of technology and life sciences/healthcare?” With 2023’s accelerating layoffs across Fortune 500s, including Verily Life Sciences’ (an arm of Google's parent company, Alphabet) recent 15% staff reduction, these are challenging times for our readership. To learn more about potential practical steps for your career sustainability, please see Jasmin Patel’s (Senior Partner at a-Connect) thoughts in this latest Harvard Business School Healthcare Alumni Association Q&A.

Michael Wong: Although we are only days into the New Year, massive layoff announcements—including Amazon’s 18,000 targeted reduction and Salesforce’s 10% restructuring—have created angst across Fortune 500 workforces given how these firms had successfully performed over recent years. With many of my bio-pharma colleagues still recalling their respective firms’ pipeline droughts and associated downsizings in the past decade, what do you see on the career landscape for them in the next 11 months?

: Firms have had a rough year—Roivant announcing laying off 12% of their employees and Novartis plans to lay off more than 7% of their global workforce, to name a few. Given my conversations with industry executives, candidly, 2023 will most likely be a challenging year with the spread of cost constraints and more headwinds across other pharma and biopharma. Of relevance to your US-based readers, global employers have become increasingly comfortable with shifting operations from North American and European locations to Asia Pacific (APAC) countries. As global workforces engaged remotely quite effectively during the COVID-19 pandemic, past C-suite assumptions around tapping into emerging economies for highly skilled workers at lower costs have changed.

With these factors in play, your friends should make sure that their 2023 efforts have a clear line of sight towards creating tangible value and impact via their upcoming projects/initiatives. While achieving timelines and crossing stage-gates are important, each initiative should also craft upfront an aspirational Amazon-style Future Press Release summary that includes the pain points, solutions, and benefits that the project team seeks to secure; once the initiative is completed such communications should be conveyed internally (eg., via Slack, Teams, company newsletter). Of equal importance is the ability to build personal connections in a workplace that continues to change. Per some of a-connect’s research, “…We have experienced, across the board, that the challenges of wherever, whenever and however seem to be easier to overcome than those of whoever, as building new relationships remains a key area of concern.”

Given your years working directly for Novartis, what three career advice recommendations would you share with co-workers of the past as well as clients of the present day?

First, always expect the unexpected. While the past months of massive reorgs occurring across several Fortune 500s including bio-pharmas, can be stressful, I would encourage the readership to view such changes as opportunities masquerading as challenges. For instance, not too long ago, if you were a hiring manager, you were likely stressed about attracting and retaining top talent during the Great Resignation. In 2023, the current upheaval represents a unique opportunity to hire top tech talent into your firms. Just as I never imagined some 20 years ago when I was studying at Wharton that I would one day commence a decade-long journey working abroad across Switzerland and Asia; your readership should adopt an agile mindset to embrace changes that they cannot visualize today.

Second, similar to the “ABC” adage of “Always Be Closing,” I would recommend that your readership “ABN,” that is “Always Be Networking.” Especially if you’re in the enviable position of being gainfully employed, invest ahead of the cycles to help others, including colleagues in your current network, as well as contacts of the past from schools and prior jobs. It’s not only the right thing to do, but is a good way to build and maintain relationships which in turn may create future opportunities.

Finally, recognize that careers are no longer the straight path that was the norm for the Baby Boomer generation when someone may have journeyed along a 35+ year playbook of roles at Merck or J&J. Crossing sectors, like I did, starting in strategy consulting, then to Big Pharma, followed by Private Equity and now back in consulting, not only provided terrific learning and personal development, it was also a lot of fun. And so, for those bio-pharma readers who work side by side with consultants and always wondered about this career path, do scan the materials that I had co-presented at the 2018 HBS Healthcare Alumni Association panel event which are still relevant.

 You may very well decide that becoming an independent consultant is how you navigate through your next set of career moves!

https://a-connect.com/knowledge/looking-ahead-a-path-to-continued-professional-renewal/

https://a-connect.com/knowledge/bryn-mawr-panel-discussion-on-gig-economy/

Jasmin Patel is a Senior Partner at a-connect, the consultancy that pioneered the networked consulting model, engaging with 600+ independent consultants in the US and 2,400 across the world to advise and support a broad range of clients on some of their most pressing business challenges. Jasmin’s prior experience includes roles as Managing Director for Fidelity Growth Partners India, Chief Operating Officer of Novartis India, and Engagement Manager at McKinsey. Jasmin received a PhD from Duquesne University and an MBA from The Wharton School at the University of Pennsylvania.


Michael Wong is an emeritus board member of the Harvard Business School Healthcare Alumni Association.

Jasmin Patel of a-Connect provides insight on how to navigate the ebbs and flows of employment. 




Navigating One’s Bio-Pharma Career through 2023’s Turbulent Job Markets

Michael Wong: At the November 2022 HBS Healthcare Alumni Association’s annual conference,

 a spirited debate around the Inflation Reduction Act of 2022’s likely impact on prices and new medicine development took place; and although there were strong opposing views of a path forward, it was clear that change must occur within our healthcare ecosystem.

While long-term value might be the ultimate goal, short-term budgets have a finite set of dollars that need to be wisely allocated across a set of initiatives, be they in healthcare or other worthwhile but competing initiatives. As might be expected, emerging technologies are often seen as a panacea, but given your dual role as a practicing physician and business executive, what are pragmatic solutions for 2023?

Artificial intelligence (AI) is a frequently referenced panacea, so let’s start with some basics. AI is the simulation of human intelligence in machines programmed to think and work like humans. Other referenced elixirs like machine learning, deep learning, natural language processing, and big data are all branches of AI. As for the potential that AI might have as a useful tool in health care and the medical research space, some include:

AI algorithms are “taught” to identify and label data patterns, while NLP allows these algorithms to isolate relevant data. With deep learning, the data is analyzed and interpreted with the help of extended knowledge by computers.

Many aspects of healthcare include elements of prediction, including diagnosis, treatment, administration, and operations.

One value proposition, whether I’m wearing my physician hat or executive one, is time savings. AI has the potential to streamline the notetaking process and admin tasks so physicians can focus on patients instead of their computers. Also, with AI able to analyze large amounts of data stored by healthcare organizations in the form of images, clinical research trials, and medical claims, it can identify patterns and insights often undetectable by manual human skill sets of clinicians or business professionals. I would note that despite well-intended forays into this space by many well-known Fortune 500s, the healthcare ecosystem is extremely complex, and various exits have taken place.

The good news is that progress in this area has occurred, and a specific example that comes to mind is a collaboration between the VA and DeepMind Health.

Acute kidney injury (AKI) can be difficult to detect by clinicians but can cause patients to deteriorate extremely fast and become life-threatening. With an estimated 11% of hospital deaths following a failure to identify and treat patients, the early prediction and treatment of these cases can have a huge impact on reducing life-long treatment and the cost of kidney dialysis.

In 2019, the Department of Veterans Affairs (VA) and DeepMind Health created an ML tool that can predict AKI up to 48 hours in advance. The AI tool identified more than 90% of acute AKI cases 48 hours earlier than with traditional care methods.

The logical follow-up question is if this is something that might be expanded to other life-threatening illnesses. Moreover, how might bio-pharma firms collaborate with home healthcare providers to see if an offering might be made available at the patient’s bedside or even potentially monitor the patient continuously at home (e.g., through a smartwatch)? With some predicting recession headwinds in 2023, strategic bio-pharma and home healthcare providers might consider collaborating and pooling their expertise and limited budgets to create scalable AI offerings for 2023.

Given your engagement with leading academic and business entities, what are your 2023 predictions for AI bringing meaningful impact for patients and the organizations which serve them?

It’s commendable to see many organizations pointing to how their AI efforts are striving to accelerate the discovery and development of new medicines, but the decades-long challenge of having diversity in clinical trials continues. Introducing automation might help bring efficiency gains for these firms, but the pain point of increasing diverse patients in their trials continues.

Strategic bio-pharma organizations will figure out how to collaborate with other entities for creative new ways to recruit and enroll such patients. For instance, I serve as a board member with Walmart Mexico and Central America, where in the US, the retailer Walmart has a store that is within a 20-minute drive of 90% of the US population. With the launch of Walmart Healthcare Research Institute SM (WHRI), the company is planning to increase community and equitable access to 

. Together, the firms will need to determine an engagement model built upon trust so potential enrollees can make an educated choice.

Finally, at least in principle, new technologies like machine learning can provide unbiased predictions based only on the impartial analysis of the underlying data. However, the logic used to generate a medical result or recommendation needs to be shared instead of developed in a “black box.” These change management efforts are often dismissed for strategic initiatives, so one should consider how to ring-fence limited investment dollars accordingly.

https://www.hbshealthalumni.org/s/1738/cc/21/page.aspx?sid=1738&gid=11&pgid=77789&content_id=11020

Dr. Liz Kwo is the Chief Medical Officer of Everly Health. Before joining Everly Health, she served as Deputy Chief Clinical Officer for Anthem, VP and GM of Provider Networks at American Well, and Entrepreneur in Residence at Harvard Medical School's Office of Technology Development. Board Certified in Preventive Care and Occupational Medicine, Dr. Kwo remains active as a practicing physician at Cambridge Health Alliance, of Harvard Medical School. Dr. Kwo has an MD from Harvard Medical School, MBA from Harvard Business School, MPH from Harvard TH Chan School of Public Health, and a BA from Stanford University.

Dr. Liz Kwo of Everly Health outlines 2023 predictions for AI, including how it can be beneficial to patients