The Happiness Index

A decade or so ago, when Ira Bedzow was building his career in real estate, he could scarcely have imagined the path his career would have taken since then. Bedzow no longer works in the same industry, which is fairly normal, as the modern generation changes jobs more frequently than ever before. The most fascinating thing about Bedzow’s career change – he’s now working in a role that was barely conceivable even a decade ago.

Today, Bedzow is the Executive Director of the Purpose Project, part of the Student Flourishing initiative at Emory University in the US. The initiative helps students get the most out of their time at college by supporting them in four pillars: academic experience, community and wellbeing, purpose and meaning, and professional pathways. It’s an example of the new, modern approach to student wellbeing at universities: one that goes beyond surveys and towards a more complex, data-driven approach.

“The intention behind the Student Flourishing initiative was to reimagine university education [as a wider experience], as opposed to university education being simply giving students information in their classes,” Bedzow tells QS Insights Magazine. For instance, Emory’s community and wellbeing pillar isn’t just about providing mental and physical health services to students, he points out. “It’s also about social atomisation and alienation, and the effects they have on our health. Looking at it in terms of what health and wellness looks like as communities and not simply as individuals.”

The initiative starts from day zero of a student’s time at Emory. When they first set foot on campus, they will have the opportunity to attend a pre-orientation meeting with more senior students. In these meetings, students discuss their personal motivations for coming to Emory and what they’re hoping to get out of their degree beyond a piece of paper. This approach differs from the norm – students don’t go to a purpose class or attend a wellbeing workshop. Instead, the four pillars are integrated within existing curriculumand become part of each university programme.

Bedzow is responsible for the pillar of purpose and meaning, where he works with students to strategise on achieving things in life that are “meaningful to them and consequential for their world”. While it might sound intense for 18-year old undergrads, Bedzow argues that it’s absolutely necessary for the current generation of students. “It gives them the confidence and the contentment to pursue things that speak to who they are and who they want to be, with the empowerment that they know how to get there. Or at the very least, we’re helping to show them how they can get there.”

Yet one of the many challenges surrounding student wellbeing is that it can never take on a one-size-fits-all approach. What works for a first-year fine art student may not work for a 30-year old MBA student, who are at different points in their lives and careers. Universities are now starting to understand that. Life Design for the Modern MBA is a new course at Emory, which aims to help MBA students find a better work-life balance after they graduate.

”When you are graduating from your MBA program in the US, you are getting really close to having a family – if that’s the choice you’re making,” explains course leader Marina Cooley, who is also Assistant Professor in the Practice of Marketing. “So we have to prepare students a little more for what a good work-life balance looks like, and what different options are available to manage both family and career.”

Work-life balance isn’t the only consideration of the Life Design course, however. It also factors in the responsibilities that these students will have in their post-MBA career. “Everything about the curriculum is geared towards people that will be middle managers, almost immediately on hire,” Cooley explains. “They will have direct reports straight away, and they will be managing the Gen Z workforce, who have much different expectations of work-life balance. It means you have to learn how to motivate people to work the hours that they’re willing to work.”

It’s still early days as Student Flourishing was launched in 2021 and Life Design for the Modern MBA began in 2023, but the initial signs suggest these initiatives are working well. Cooley’s course is already oversubscribed, while Bedzow’s measures of success – student satisfaction, retention, contentment – are all on the rise. Emory was also recently ranked as the 7th happiest university in the country by The Princeton Review.

Wellbeing initiatives in higher education are not just limited to single university departments. The Happiness Business School is – as you can probably guess – an entire business school dedicated to happiness. Students at the Lisbon-based institution can learn how to implement an Organisational Happiness Plan, become an officially-certified Happiness Manager, or even study an entire MBA in Organisational Happiness. According to Executive Director Madalena Carey, the idea behind these courses is that they will have a knock-on effect on future generations of workers.

“When people are fulfilled, they perform better, innovate more and build stronger, more sustainable businesses,” she says. “When universities prioritise wellbeing, they don’t just create happier students: they create future leaders who demand the same from their workplaces.”

Although Carey, Cooley and Bedzow are approaching the topic from different angles, one issue binds them together: the difficulty in measuring happiness. Traditionally, schools might have just used surveys, where students are asked to rate their happiness out of 10. But such surveys only reflect their happiness at that given moment, and doesn’t really reflect its complex nature. “Happiness isn’t an end point – it’s a journey,” points out Carey.

Both Bedzow and Cooley admit that it may take several years to gather enough data to really measure the success of their programmes. And even then, there are so many metrics out there that it can be difficult to focus on the right ones. Many universities are therefore leaning on external companies to help them gather and analyse the right data.

Leo Hanna is the Executive Vice President UK of TechnologyOne, a firm which develops software solutions for large organisations such as universities. He says that many universities are still struggling to “connect the dots” when it comes to student wellbeing.

“When engagement data sits alone, early warning signs – like a drop in attendance or missed deadlines – can be overlooked,” he says. “But when schools take a proactive, data-driven approach, they can intervene early and take meaningful action.” He adds that this not only helps students feel supported, but can also improve retention rates and overall course satisfaction.

Being able to accurately measure happiness will be increasingly important for universities in the coming years. Students today are facing a unique cocktail of challenges – economic uncertainty, financial stress, digital overload – and growing drop-out rates across the globe suggest that universities aren’t dealing with them well enough.

Yet there’s more to it than that. This increased focus on happiness also reflects a generational shift in attitudes towards work and study. Whether or not universities can adapt to it will surely prove to be their biggest challenge. “Students today are so savvy about the kind of lives they want to live,” says Cooley. “And I think they’re looking at a lot of people in my millennial generation and Gen X and they’re like: whatever that is, I don’t want that. I want to build something different.”

Read more stories from QS Insights Magazine. 

Keeping an eye on your data

Every business today is a technology business, each generating vast amounts of data. This has created remarkable opportunities and challenges.

The datasphere, the term for all the data we’ve created so far, is around 100 zettabytes and it’s going to double in about three years. A zettabyte, a term unfamiliar to many, is a large number. It’s one followed by 21 zeros. To put this in perspective, you’d need one billion terabyte hard drives to store one zettabyte of data. This scale of data and the velocity in which it is being created is consequential for every organisation.

Data is the most valuable asset

A consensus has formed in the business and data communities that data has now reached a point in which it is the most important asset in every organisation. My own research validates this.

Quality data at scale can contain remarkable answers and insights. With the right skills and tools, organisations can leverage data to enable improved decision-making and optimised operations. They can use data to drive competitive advantage, unleash innovation, and solve a wide range of intractable problems for business and society.

But achieving these results with data doesn’t happen without deliberate effort. The power of data is only realised through skillful governance.

The importance of governance

Whether we call it data governance or not, every organisation has some form of oversight for the data it handles. It could be as simple as knowing that data is being backed-up, or where certain data is located and who has access to it. Data governance, informal and formal, spans a wide continuum of approaches. However, it all comes down to this: is data being fully managed in the organisation and is its value being realised?

So, what does this actually mean in practice?

Defining data governance

At a high level, we can define data governance as data that is managed well. In aspiring to achieve high performance in managing data, we must ask to what degree are there agreed policies and processes for handling, for example, sensitive, legal, and regulatory data requirements? Are there documented accountabilities, formal decision structures, and enforcement rules for data? The right talent, processes, and technologies must exist. These are some of the many core attributes of good governance.

Today, the governance and management of data has become an actual science. There’s a wide range of data science professions and supporting educational programs. Software for supporting these professions has exploded in recent years, including incredible solutions for analytics, visualisation, and more. Increasingly, they are being powered by artificial intelligence.

Governance is a choice

In the absence of quality data governance, an organisation will never fully realise the potential of data and in fact, may subject itself to increasing levels of risk over time. These risks include inadvertently using bad data, experiencing privacy challenges, and suffering from the consequences of weak cybersecurity.

The demand for high-quality data governance and its promise is quickly making it a core function of an increasing number of organisations. Data can create important value for every organisation and to achieve this in an optimum fashion requires high-performing data governance. If it’s implemented well, it can be transformational.

Dr. Jonathan Reichental is a multiple-award-winning technology and business leader whose career has spanned both the private and public sectors. He’s been a senior software engineering manager, a director of technology innovation, and has served as chief information officer at both O’Reilly Media and the City of Palo Alto, California. Reichental is currently the founder of advisory, investment, and education firm, Human Future, and also creates online education for LinkedIn Learning. He has written three books on the future of cities: Smart Cities for Dummies, Exploring Smart Cities Activity Book for Kids, and Exploring Cities Bedtime Rhymes. His latest books include Data Governance for Dummies and a Cryptocurrency QuickStart Guide.

Read more articles like this from QS Insights Magazine, Issue 13.

Can higher ed fill the graduate data skills gap?

The divide between the skills employers require and the skills graduates have obtained is widening, or at least it appears to be. New and emerging needs centred predominantly around data science are asking questions of universities and their ability to prepare future workforces. Paul Thurman considers whether higher ed is up to the task.

A great deal of discussion in higher education recently has been focused on the gap between what data analytics skills are needed by employers compared with what data science skills graduates have upon completion of their programmes, both at the undergraduate and graduate. This perceived gap has been accentuated by both the emergence of quick-hit certifications in data science offered by predominantly online training academies and by some non-degree programmes from universities, as well as by employer perceptions that more focused training in analytics is a prerequisite for employment.

In fact, many employers complain that graduates arrive to work with only basic quantitative analysis skills and require on-the-job training, at the employer’s expense, to remediate such skills gaps. While this may not always be true, the fact that a ready supply of online data science academies have sprung up to meet this demand or fill these perceived gaps from employers only further puts the spotlight on this apparent deficiency in data science acumen, whether it be real or imagined.

As such, the gap between “supply” of and “demand” for data science skills is widening in higher education. More and more employers are demanding higher levels of data analysis skills and competence based both on their own emerging needs and on the relatively unskilled labour forces graduating from institutions of higher learning. This is one reason why so many universities and colleges are offering an array of non-degrees online, certificates, and credentials courses to alumni. A secondary benefit, of course, is to manage this negative perception of their own data science pedagogy. One of the first online “upskilling” courses Columbia Business School offered to its alumni, for example, was a course in data science and analytics.

Degree-programme directors are also responding to this demand for more data science skills by including boot-camps and other deep-dive courses and programmes to students before commencing studies, sometimes as a requirement for admission or as part of orientation. In the past these orientation programmes focused on Excel, basic accounting and finance principles, and perhaps some marketing and operations basics. As these topics are increasingly covered during secondary school, higher education institutions’ need to include them is diminishing. Instead, what universities are finding is that students still need a bit more depth in newer tools and applications before they can successfully complete an MBA program, for example. Some degree programmes now require first-year students to take courses in both data science and coding basics as a way to close this perceived skill gap with employers and to differentiate their programmes from the competition.

The gap between “supply” of and “demand” for data science skills is widening in higher education.

But employers are the ones really driving the demand for analytics. They are coming to universities and colleges looking to recruit graduates and now making completion or certification of such data science skills a prerequisite to obtaining a job interview. For their existing labour forces, they are asking schools to provide the aforementioned credentials and certification opportunities.

For example, some technology-focused US companies have come to local universities requesting things such as 200 workers certified in cybersecurity. Others are asking for hundreds of workers with credentials in data science and coding for employment in six months. These are very different demands being placed on traditional academies and formal degree programmes. In fact, this raises a huge question: should universities pivot, or at least extend, to become training academies for the next generation of labour forces? Should my university, Columbia, offer not only formal degrees in business administration and computer science but also be a place employers can come to get 100-200 people training in basic coding and business analytics skills in a matter of months without requiring them to obtain formal degrees? Should the academy that confers degrees to white collar workers also, simultaneously, offer training and certification or credential opportunities to blue collar workers as well?

This is a broader question that many universities are facing right now, and the choices are not easy to make. What does a faculty comportment look like that handles both degree and non-degree training? How do admissions work when employers drive some needs but deans and department chairs drive others? The data science skill gap is likely only the first of many that institutions of higher education and their corresponding non-degree training academies will struggle with as more and more employers eschew degreed graduates in favour of focused, skilled workers. Until such gaps are closed, perhaps via employer-school partnerships, filling these gaps will be a challenge for employers but also an opportunity for schools and training academies that can offer quick-hit, non-degree upskilling for a broader labour force over time.

This article was from the 2023 QS Higher Ed Report: A New Normal?. Download the full edition.