Month: July 2020

HR directors expect 70% of their workforce will have flexible working once coronavirus restrictions are lifted, a 45% increase on current levels.

More than 13 million people across the UK plan to ask their employer for changes to their long-term working pattern, according to research from Direct Line Life.

HR is therefore already preparing to receive more flexible working requests once the pandemic has eased, with over two fifths (43%) of HR directors giving the option to work from home five days a week.

Cost of travel and being at work was a key reason behind changing working styles for around a third (31%) of people, as well as commuting time at 23%.

More than a quarter (28%) of those hoping for more long-term flexible working said they have demonstrated they can do this successfully during the pandemic, a sentiment no doubt shared up and down the country.

Spending more time with family and wanting to lead a healthier lifestyle was also cited as a key reason for the change.

One in six said they were concerned over pollution levels and 5% said they plan to spend more time exercising and becoming healthier.

Chloe Couper, business manager at Direct Line Life insurance, said coronavirus has changed the mindset of millions of workers in the UK.

She said: “Many people wouldn’t have considered their employer would accept a flexible working request, despite it being legal to make one but now companies and employees have become used to home working as the ‘new norm.’

“Going through such a serious pandemic will understandably make some people want to reassess their lives and priorities going forward. Protecting health and family are vital and it is great to see so many wish to spend more time doing both.”

Working from home two days a week was the most popular option when looking to carry on flexible working arrangements.

Given office space is a large cost for most businesses, the opportunity for more staff to work remotely may reduce overheads for organisations.

Research was collected by Opinium among a nationally representative sample of 2,002 UK adults in April and by Pure Profile of 100 UK HR directors.

Souirce : https://www.hrmagazine.co.uk/article-details/hr-directors-predict-wave-of-flexible-working-requests-1

What hasn’t changed in the last five months when it comes to how we do business? Surely, that list of things is shorter than the list of things that have been impacted by COVID-19. How we work, how we communicate and how we measure the effectiveness of our work is all adapting to the new reality this pandemic has thrown the world into.

Human resource metrics are no different. The pandemic has HR leaders looking at everything from remote work performance to employee wellbeing through a different lens. The role of HR leaders in this pandemic is vital, or as The Economist recently noted, “the role of the Chief People Officer in the pandemic is like that of the Chief Financial Officer during the financial crisis.”

“There’s a level of focus on our people that I have never seen before,” said Rana Stanfill-Hobbs, Director of Insights at Ultimate Software, during a session titled “HR Metrics: Measuring What Matters in and After a Global Pandemic” as part of our recent HR Tech North America Digital Summit.

“The things that we have been talking about around trends in mental health, thinking of our whole selves and taking a holistic approach to the workforce is all driving toward the same place of recognizing the workforce as human beings and thinking of how we can provide better support and resources.”

The Employee Experience Takes Center Stage
Looking at the trends emerging from the COVID era, the ones that stand out focus on AI augmentation, health as a driver of productivity and the importance of the employee experience. HR is playing a central role in creating a connected and collaborative culture across the enterprise and with that, comes an obligation to measure to the effectiveness of such an effort.

“We’ve all been working to address these things, but they have such a magnitude now that I could never have predicted,” Stanfill-Hobbs said. “Who we’re measuring has not changed, but how we do it, how often we do it, what we’re measuring and how we’re providing those insights is all changing. It’s been changing, but it’s happening in ways that either we did not predict or at a much faster rate than we expected.”

The focus of those questions is aimed at uncovering who the people are that make up the organization, what their employee experience is like and understanding the organizational brand beyond what it’s known to do as a business.

Many of the metrics being used by HR haven’t changed, but the reason for collecting them and the impact of the findings has been greater than ever before.

“Now is an interesting time because the humanistic components of brands, how they support their employees and their community, has come to mean something different,” Stanfill-Hobbs said. “The way that organizations are responding (to the current environment) will have a very long tail to it. It’s not just their relationship with their employees, it’s going to impact future recruitment and their relationships to their customers as well.”

Another piece of the experience puzzle is understanding how the organization meets its people both physically and psychologically. Mental health and diversity and inclusion are two areas that are of high importance right now and part of that more holistic approach to employees.

“Because we’re now thinking about the physical and psychological environments we’re interacting with our employees in, and the fact that we may not be able to control the setting, we see a lot of inconsistency in their experiences,” Stanfill-Hobbs said. “So how do we meet them, how do we understand what’s important to them? How do we make sure we’re taking care of them and understanding what they need?”

Workforce Planning
In answering the question of who are our people, the next part is to determine what skills and attributes people have that will help the business cope with the new reality or transition to new business models. It’s a necessity for businesses to know who their people are and who needs reskilling. Organizations then need to offer learning in effective ways and inspire a culture of learning that helps people develop skills that will see the business through the crisis and into its new future on the other side.

“All of that is now in a totally different cadence than I’ve ever seen,” Stanfill-Hobbs said. “Workforce planning has traditionally been structured around a subset of jobs that we know are most important to keep our business successful now and to keep us achieving our goals. So now we have to start thinking about new tasks and positions that have to be done and take inventory of who we have that can do them. There’s a real opportunity to assess what can be done by technology, what can be done by non-traditional workforces and be creative and far more democratized in our approach to who can do this work.”

A lot of this data driven transformation was on a timeline to become reality in the next 2-5 years for many organizations. Now, that timeline has tightened to a matter of weeks and months. Stanfill-Hobbs emphasized how important it is to not lose the momentum that has resulted from such a fundamental shift.

“I’ve talked to so many organizations who have said they couldn’t go to remote work, the business model doesn’t work for that, culture doesn’t work for that,” she said. “Now many of them have had to do that and the nature of work has fundamentally shifted. I think that’s really exciting, because we’ve been forced to have a more distributed leadership model, and that means we’re working in a distributed data environment.”

The word opportunity is important here. A distributed workforce is a big opportunity to embrace technology such as AI, machine learning and sentiment analysis. AI is capable of augmenting the business, for example, through personalization of learning content and pathways, recruiting and candidate matching, increasing retention by identifying employees at risk of attrition, chatbots and sentiment analysis.

That technology thrives on data, meaning now is the perfect time to create more data through surveys and new modes of communication that will help organizations understand their employees better and simultaneously make the technology more effective.

Source : https://www.hrexchangenetwork.com/hr-tech/articles/a-closer-look-at-the-influence-of-hr-metrics-in-a-global-pandemic-1

We’re midway through 2020, and suffice to say, the year hasn’t gotten off to a great start. But as we look ahead to the next two quarters, leaders across every sector know that while the immediate crises may have abated, the tough work remains to be done.

Now, leaders are not only tasked with trying to stabilize their operations and drive growth, but they also know that in whatever form they seek to rebuild their organization’s culture, it must be with a committed effort toward diversity, inclusion and equality.

It shouldn’t take social movements like #MeToo or #BlackLivesMatter to awaken a collective consciousness around long and justly held grievances or systemic biases, and reactionary responses or promises that pay lip service to the problem as opposed to doing the hard work to forge sustainable and systemic solutions don’t help.

Let’s face it: Despite millions of dollars and years of effort to address diversity and inclusion, most organizations haven’t moved the dial far or fast enough. What’s needed is a different approach. So, as we head back to the drawing board, we’d be well served to change course on a few fronts:

1. Stop Framing The Issue As A Problem
For too long, we have framed the issue of diversity and inclusion as an intractable problem, debating whether quotas are right or targets are fair. Instead, we need to reframe it as a catalytic, powerful solution, focusing on the competitive advantage our organizations stand to gain if they were made up of truly diverse workforces.

How White People Can Talk To Their Kids About Racism
When you think about the unprecedented challenges today’s businesses contend with, not to mention the intensified competition across the globe, how can we ever hope to “win” if we only have the input of a subset of the population? When organizations lack diversity, a huge part of the innovation spectrum is missed. To look beyond the obvious requires a broad range of perspectives from a diverse set of people.

Think about all the voices and opinions that are not reflected in the products we design and the services we offer. Think about the silence (of the majority) that’s literally coded into the future as a result of imbalances in workforce representation. The Global Gender Gap Report by the World Economic Forum in 2018 found that only 22% of the global AI workforce is female. With numbers like that, it’s all but inevitable that artificial intelligence will end up amplifying the unconscious and unexamined biases of society today, and at an industrial scale.

It’s scary to think about all the amazing ideas and answers to thorny questions that will never be considered simply because the right people aren’t around the table to even hear the question.

Without true cognitive diversity, we’re placing an invisible ceiling on our capacity to create and innovate. In industries such as technology, we must remain committed to widening the aperture of who gets to participate in the shaping of products and services upon which the world will depend. If we don’t, we run the risk of putting humanity’s digital future on a plane that’s flying on only one wing.

2. Don’t Just Solve For One Variable
As more organizations commit to addressing inequality, we can’t allow the pendulum to swing too far in the direction of one “diversity” variable, at the expense of others.

As an example, the past few years have seen a major uptick in efforts to increase gender balance on corporate boards. It’s been a welcomed effort, but with it comes the risk that we “check the diversity box” by increasing the percentage of female representation. But if those women are disproportionately white, there’ll be even fewer openings for which women of color may be considered.

Another issue with optimizing around one variable such as gender or race is that we pay less attention to the nuances that go into creating true cognitive diversity in our organizations. So much goes into shaping who we are and the perspectives we bring to the table—but too often the factors that make us different on the inside take a back seat to the ones that make us different on the outside. For instance, it’s rare that we factor in things like socioeconomic upbringing or overcoming extreme adversity as sources of cognitive diversity, and yet anyone, of any color, will tell you that growing up poor or experiencing tragedy shapes your worldview in immeasurable ways.

As we look to create workforces fit for purpose in the future, let’s ensure we see people for everything they are, as opposed to narrowing them to single variables.

3. Give Diversity Its Due
The real elephant in the diversity room, which few openly admit, is just how hard diversity can be to do and to do well. We encourage managers to go out and hire diverse teams, making the above arguments about how much better off we’ll be as a business. At the same time, we bestow upon them aggressive quarterly targets. I’ve had more than one sales leader over the years point out that they could hit their quarterly sales quota if they were able to simply hire who they wanted and hit the ground running.

It’s not an unfair comment. Diverse teams take longer to recruit and can be more difficult to manage. It’s obvious that if every team member has the same view, went to the same few colleges, thinks the same way, and ostensibly rows in the same direction, it can make for smoother managerial sailing. But it’s also likely that you’re reaching the same, limited, conclusions.

Moreover, when your company does hit rough waters, you’ll be worse off if you can’t call upon broad and varying skill sets.

Along with insisting on diverse slates of candidates for jobs, we also need to ensure that a diverse panel of people is conducting interviews. A recent study by McKinsey found that 39% of respondents say they had turned down or decided not to pursue a job because of a perceived lack of inclusion at an organization. (Note that’s not an absolute lack of inclusion, merely a perceived one.) In competitive talent markets, no organization can afford to attract only 60% of prospective candidates.

However, simply recruiting diverse talent is insufficient. We also need to develop managers so they have the capabilities required to lead diverse teams and to instill in them the (soft) skills required to create cultures of openness, empathy, and psychological safety, where each individual feels they can bring their best and be their best. In other words, we must build cultures of belonging.

4. Understand That Inclusion Won’t Matter Without Belonging
The last way in which we need to reorient our mindsets and efforts around diversity and inclusion is to understand that there’s a monumental difference between being included in a room and actually feeling like you belong.

Every human being can think of a moment in their lives when they felt they didn’t belong. It’s not a feeling you forget. But for some, that feeling plays out every single day. If there is a difference between who you are on a Sunday versus who you must be at work on a Monday, then you’ll never perform at your best because you’re only bringing a fraction of yourself to the job each day.

McKinsey’s study found that “respondents who feel very included in their organizations are nearly three times more likely than their peers to feel excited by, and committed, to their organizations.” Alternatively, in cultures where people don’t feel they belong, they self-sensor, they act small and they play it safe.

Think of the wasted potential when you or your colleagues are sitting there wondering if they should voice their opinion or share their idea, for fear of being judged. On the other hand, a culture of belonging unleashes people’s creativity and potential and tells them it’s safe to take risks—an obvious prerequisite to innovation and change.

The degree to which employees feel they belong drives meaningful results and affects the bottom line. It correlates highly with higher retention, fewer sick days, greater productivity, higher employee satisfaction scores, and a stronger talent brand.

Moreover, it’s a culture of belonging that allows you to leverage and gain the benefit from the diverse team you’ve worked hard to recruit and retain in the first place. Put another way, if diversity is a seed and inclusion is a crop, then belonging is how you harvest them.

This is a watershed moment for leaders, especially here in the United States where it’s clear that communities, employees, and society writ large, is desperately seeking capable and courageous leaders who’ll rise to the occasion and drive sustainable and lasting change. While nothing we do now can erase the egregious wrongs of the past, everything we do can make a meaningful difference in the future.

Let’s make that a future where all belong, and one that belongs to all.

Source : https://www.forbes.com/sites/anitasands/2020/07/27/the-real-leadership-challenge-of-2020-creating-cultures-where-everyone-feels-they-belong/#699d67e54cb4

During times of geopolitical and societal unrest, when many employees are isolated and struggling to balance their personal and professional responsibilities, inclusiveness becomes even more vital to support the wellbeing of staff and help promote the long-term success of the organisation.

Programs focused on underrepresented people of colour are particularly critical considering the disproportionate effect of the pandemic on these groups.

A study by APM Research Labs showed the overall COVID-19 mortality rate for Black Americans is more than double the rate for other ethnic groups, an inequity that is mirrored in England and Wales.

Like all aspects of business, diversity and inclusion initiatives have begun to shift to a remote approach.

The good news is that groups and programs designed to support employees can meet and communicate virtually, such as Employee Resource Groups (ERGs).

While there is no playbook for how to support employees during a pandemic, there are ways to cultivate and nurture diversity and inclusion when working apart.

Communicate and engage often

Employers proactively initiate communications and engagement. For instance, we started by talking with the leaders of our ERGs and launching a series of sessions to keep the lines of dialogue open among our community, with several of our black and brown employees sharing perspectives on their life experiences.

These sessions are most successful when leaders ask employees for feedback and then use that information to shape upcoming programming.

Listening is the key to establishing new levels of trust and transparency. In fact, leaders should over communicate with their teams to enhance engagement and to maintain a sense of community.

Commit to D&I

Outward vocal commitments followed by concrete actions and responses demonstrate to employees that an organisation is committed to diversity and inclusion.

While political and societal unrest can bring discomfort, it also provides growing resources for employers to sign onto initiatives and advocacy efforts and make public statements, internally and externally, for example, around racial injustice for people of colour.

However, these actions are meaningless unless rooted in action. Employers must implement a robust program to grow, cultivate and support diverse talent while providing learning opportunities designed to foster a supportive and inclusive environment.

Hire with D&I in mind

While building a robust pipeline of diverse candidates can be challenging, given that the traditional method of engagement via conferences and venues is limited, organisations must embrace new technologies to engage with potential employees through virtual meetings or proprietary events.

For instance, the Spelhouse Symposiums, which connect candidates from historically black US colleges to employers, moved to an online event with revised content advising attendees on how to navigate the marketplace during a pandemic.

Companies should leverage these opportunities to talk about COVID-19 with candidates and outline future plans, information that is especially crucial when speaking to candidates of colour who may have concerns that they’ll be further marginalised as a result of the pandemic’s impact on working life.

With the impact of COVID-19 putting a squeeze on many organisations, employees may have concerns that groups and programs they rely upon for support, development and empowerment could be deprioritised or eliminated.

By shifting inclusion initiatives to a virtual model that includes proactive communication and creative approaches to hiring, company leadership can demonstrate to all employees that they are a valuable part of the business’s success and future.

Keisha Bell is managing director and head of diverse talent management at financial services company DTCC.

Source : https://www.hrmagazine.co.uk/article-details/fostering-diversity-and-inclusion-in-a-remote-environment

In 2019, 70% of Americans felt their personal information was not as secure as it was five years ago
HR administrators are most likely to be the first to address requests for data access and erasure.
Most organizations plan to spend more than $100,000 on privacy solutions, training and workforce.

If you believe in horoscopes, the year 2020 was predicted to be “quite challenging, especially health-wise, but also financially, with obstacles, impediments, and unpredictable situations, which will mainly occur during the first half of the year.”

Maybe we should take astrologers more seriously.

2020 began with the California Consumer Privacy Act (CCPA) providing California residents with data privacy rights like those for EU residents under the General Data Protection Regulation (GDPR). Much like other transformative events including the COVID-19 pandemic, this landmark law is changing the way we live and work. With personal and professional security top-of-mind, concerns around data privacy and protection only continue to increase.

In a 2019 survey by Pew Research Center, 70% of Americans felt their personal information was not as secure as it was five years ago. And while most Americans support the “right to be forgotten,” they admit they have little to no understanding about privacy laws and their data rights.

Individual Privacy Rights
While CCPA defines several individual rights, HR administrators are most likely to address requests for access and erasure. Individuals should be able to call, email or submit these requests on a website or at a physical location.

The Right to Request Access to Information gives individuals the right to request that an organization disclose their personal information in an easily accessible and readable format.

The Right to Deletion entitles individuals to request that a company delete their personal information. There are exceptions like in cases where the data must be retained to comply with business or legal obligations.

Individuals may bring a Private Right of Action against a business for not appropriately protecting their data allowing them to seek damages. An organization may also receive civil penalties for intentional violations of non-compliance.

Data Privacy: The Cost for Employers
Californians have seemingly taken advantage of their new rights. With more people at home and spending time online, the volume of requests has been higher than anticipated. Results from a Truyo study indicate that most companies surveyed honored privacy requests not just from California residents, but from all individuals. In addition to responding to requests, companies must ensure these requests are tracked appropriately including maintaining records of request details and outcomes.

With elevated concerns, tight deadlines to respond and more laws on the horizon, the need for a well-defined privacy strategy is imperative. As a result, most organizations plan to spend more than $100,000 on privacy solutions, training and workforce.

“Adding further to the complexity is the expansion of regulatory compliance. Coming up to two years after the European Commission’s introduction of the General Data Protection Regulation (GDPR), more than a quarter (26%) of IT executives cite ‘ensuring compliance with GDPR and other data protection laws’ among their top-three external challenges.”

– Adobe 2020 Digital Trends Report
Future Predictions
The horoscope concludes with, “Nothing should be left to chance in 2020, and money, earnings, businesses, and careers need to be protected.” At Ultimate, we’ve developed technology so our customers don’t have to leave the protection of their employee and business data to chance. Plus, it doesn’t require clairvoyance to see how UltiPro® handles privacy management.

Source : https://www.humanresourcestoday.com/?open-article-id=14181319&article-title=was-data-privacy-written-in-the-stars-for-2020-&blog-domain=ultimatesoftware.com&blog-title=ultimate-software

First up, the term “athlete” in this post is meant to describe hiring those who are generally smart, intellectually curious, quick on their feet, learn quickly, are great communicators and have DNA for drive/initiative – rather than hiring someone with domain experience in a job as your first concern.

With that description in mind, do you and/or your company favor athletes over specialists? Sometimes? Never? In what circumstances?Hfm

I’m drawn to the question since I read this passage from Diary of a Very Bad Year: Interviews with an Anonymous Hedge Fund Manager by Anonymous Hedge Fund Manager:

“HFM: I didn’t go to business school. I did not major in economics. I learned the old-fashioned way, by apprenticing to a very talented investor, so I wound up getting into the hedge fund business before I think many people knew what a hedge fund was. I’ve been doing it for over ten years. I’m sure today I would never get hired.

n + 1: Really?

HFM: Yeah, it would be impossible because I had no background, or I had a very exiguous background in finance. The guy who hired me always talked about hiring good intellectual athletes, people who were sort of mentally agile in an all-around way, and that the specifics of finance you could learn, which I think is true. But at the time, I mean, no hedge fund was really flooded with applicants, and that allowed him to let his mind range a little bit and consider different kinds of candidates. Today we have a recruiting group, and what do they do? They throw résumés at you, and it’s, like, one business school guy, one finance major after another, kids who, from the time they were twelve years old, were watching Jim Cramer and dreaming of working in a hedge fund. And I think in reality that probably they’re less likely to make good investors than people with sort of more interesting backgrounds.

n + 1: Why?

HFM: Because I think that in the end the way that you make a ton of money is calling paradigm shifts, and people who are real finance types, maybe they can work really well within the paradigm of a particular kind of market or a particular set of rules of the game—and you can make money doing that—but the people who make huge money, the George Soroses and Julian Robertsons of the world, they’re the people who can step back and see when the paradigm is going to shift, and I think that comes from having a broader experience, a little bit of a different approach to how you think about things.
When you think about hedge funds, the book quote above displays a common trend. In the early days of any industry or specialty, it’s easier to hire the best athlete available, mainly because domain experience doesn’t really exist or is generally unavailable. The industry is too young.

But as the industry matures, risk taking on new hires goes down – because candidates with domain experience are widely available.

We could all probably stand to hire more athletes who are capable of not only doing the job in question, but become an agile talent asset for the company. But just saying that you’re open to hiring an athlete doesn’t mean you’ll have success.

For best results in hiring “athletes”, you’ll need to define what makes someone an athlete. You won’t generally find that on a resume, you’ll need an assessment package. For me, a candidate would qualify as an athlete if they have a high cognitive capability, low rules orientation (because I want to throw them at anything I want, they can’t be hung up on that), high details (drives execution) and great writing and verbal skills.

They’d also have to be familiar with the term, “fake it ’til you make it”, which I think is the mindset of any “athlete” worth her salt as defined by this post.

Source : https://www.humanresourcestoday.com/?open-article-id=14193639&article-title=are-you-willing-to-hire–athletes–rather-than-specialists-at-your-company-&blog-domain=hrcapitalist.com&blog-title=the-hr-capitalist

Mia Ricci’s first day was off to a bad start. She’d been excited about her new role as a program manager at Rescue, the oldest and largest aid organization fighting global poverty. She’d risen early; walked her dogs; eaten breakfast with her boyfriend, Mateo; packed a lunch; and still managed to get to the office before 9:00. She’d thought arriving early would make a good impression.

When Mia walked into the lobby, she saw a few familiar faces from her previous visit, but the receptionist was the only one to greet her. His name was Anthony, and although she thought they’d bonded last time, he looked up at her quizzically. “Can I help you?” he asked.

“It’s great to see you again,” Mia said. “I’m Mia, the new program manager.”

“Oh, right,” Anthony said, unsmiling. “Take a seat, and I’ll give you some paperwork to fill out while I grab your manager. It’s Michael, right?”

Mia had been in the building for less than five minutes and already she felt discouraged. Things didn’t improve from there. Anthony couldn’t find Michael, so he escorted her back to a dim room full of cubicles. The one person already there, a support team coordinator named Jessie Carbone, introduced herself quickly, explained that IT hadn’t set up Mia’s desk yet, suggested that she sit at a vacant workstation, and went back to typing.

At 10:30 Michael finally stopped by to hand Mia a stack of reading material and explain that his day was packed but he hoped to catch up with her later that afternoon. He never did.1

CASE STUDY CLASSROOM NOTES
1Studies show that people ignored by their managers feel more alienated than those who are overtly treated poorly.
Mia spent five hours coordinating with HR and IT via her cell phone and personal email account. She ate lunch at the borrowed desk. A few other employees came in and out during the day, and she smiled warmly and waved, but no one seemed to know who she was. Finally a technician arrived with a laptop and a monitor, which he installed at the desk farthest from the window.

Mia found herself thinking wistfully about her previous workplace, Azzurro, a start-up that used IoT-enabled container sensors to help retail businesses better manage waste. She’d joined it just after graduating from the University of Bologna with a degree in international management and had been promoted to business analyst in less than four years. She liked the work and the people.

But then she met Saul Rizzo, a senior HR director at Rescue, at a networking event. He mentioned a role at the organization’s new outpost in Bologna—one of its 92 offices worldwide—and Mia was immediately intrigued. The job would include setting up data and reporting systems and working with a seasoned Rescue manager to outline critical business processes and identify key performance indicators.

At an interview a few weeks later, Saul had offered her a salary nearly double what Azzurro was paying her and promised that she would not only have a personal growth plan but also be able to work on the ground once a month helping populations in crisis. It had seemed like a no-brainer to make the move. Mateo agreed.

Now, considering whether she should book a meeting with Michael for the next day—basically forcing him to onboard her properly—Mia wondered if she’d made the right decision.2

2A primary reason new hires leave is bad onboarding. And organizations with standardized processes to welcome employees see 62% greater new-hire productivity and 50% greater new-hire retention.
Just then she got a text from Mateo: “How was it???”

She replied with a thumbs-down emoji and “I need a drink. Let’s meet at the usual spot.”

Venting
“It was a disaster,” Mia said after recounting her workday. Mateo nodded empathetically.

“Do you think I made a mistake? I mean, I really liked Azzurro, but the humanitarian work sold me on Rescue.”

“Don’t forget the pay!” Mateo said jokingly. Mia sighed. As the primary breadwinner in their household (Mateo was a struggling artist), she was already feeling the pressure.3

3People under stress often suffer from emotional exhaustion, making it hard to find the energy to change their situation.
“Seriously, though,” he went on. “It’s too early to know. It’s such a different culture, and Rescue is a huge organization. How many employees did Azzurro have?”

“A hundred,” she said. “Rescue has thousands.”

“Right. And they’re just setting up this branch. It may be a particularly chaotic time.”4

4How much slack should Mia give Michael because the office is newly opened?
“It’s just so weird to have no official welcome, no onboarding, not even any real assignment. I’ve spoken with Michael only twice—on the phone during the interview process and very briefly this morning. You’d think he’d want to at least have a conversation with me on my first day.”

“I’m sure it was an anomaly,” Mateo said. “Tomorrow will be better. Rescue is reputable, and on paper this is a good career move.”

“I know, I know. You’re right.” Mia gulped her wine. She just couldn’t shake the feeling that something was off.

An Annoying Assignment
The following afternoon Mia finally met with Michael. “Mia, welcome,” he said brusquely. “Sorry I couldn’t get to you earlier—I’ve been tied up in strategy meetings. As you can see, we’re still getting our systems in order. Let’s talk about your first project.”

He said he wanted her to audit the processes of three departments—warehouse, supply chain, and delivery—that were essential to Rescue’s missions. Each unit combined employees transferred from other Rescue offices and recent hires brought in to help experiment with new strategies. Mia’s job was to see whether those strategies were more efficient than Rescue’s current ones.

The assignment was not what she had expected, but she nodded and smiled.

“Anything else?” Michael asked, turning back to his laptop.

“Actually,” Mia said, “when I was recruited, Saul mentioned that I’d have a chance to participate in some field projects.”

Michael looked surprised—and a little annoyed. “Hmm. I don’t mean to disappoint you, Mia, but that’s not what I had in mind for this position. We’re just building this operation, and we need internal staff members to stay focused on their responsibilities here.”

He shook his head. “I’m sorry, but I don’t see that happening anytime soon.”

“OK,” Mia said, trying to hide her dismay.5

5Some HR experts say that before starting a new job, people often focus more on the potential of their role than on the actual tasks they’ll be doing—which is why they are often disappointed.
More Frustration
Mia spent the next three weeks toiling away at the auditing project, but it wasn’t easy. Michael had forgotten to introduce her to a few department heads, so although some were friendly and forthcoming, others ignored her repeated emails or only reluctantly shared information. She’d asked Michael for advice several times, but he’d basically blown her off. And when her work was finished, it took her five days to get half an hour with him to present her findings. He’d been complimentary but then asked her to track some new metrics. She asked about broadening the scope of her duties, but his phone rang, and he waved her away. “Sorry, I have to take this. Let’s discuss next time we meet.”6

6How should Mia approach a boss who is shutting her out?
Desperate to confide in someone besides Mateo, Mia asked Jessie if she’d ever had any problems getting Michael’s attention.

“It’s not his fault,” Jessie said. “It’s this organization. It’s just such a bureaucracy. He has to run every new idea up the food chain. We’re always short-staffed because they’re always opening new offices. And they move people around so much that everyone’s constantly in learning mode, trying to get up to speed on a new geography. Don’t get me wrong—we do amazing work out in the field. We do help people. But inside, it’s a slog.”7

7Is Mia’s negative experience due to poor leadership, onboarding, organizational structure, or all three?
“Do you ever get involved in that outside work?” Mia asked.

“Oh, no. We’re the back office. Our job is to help the people who are experts at fieldwork do theirs.”

Her heart sank. Mia decided she’d email Saul and request a video call. To her surprise, he replied within the hour and said he had 30 minutes free at 5:00.

Mia was determined to be up-front about her disappointment. She outlined how unnecessarily difficult her initial assignment had been and how rarely she interacted with Michael, even though she thought part of her job was to partner with him on performance indicators. “Plus he doesn’t seem open to my doing any direct humanitarian work, even though that was a big pull for me,” she said.

Saul looked concerned. “I know, and I mentioned that to him. My sense is that the audits are just the first step and that you’ll get into the more interesting work soon. He may have forgotten our discussion because things are so hectic right now.” He asked her to be patient and promised to talk with Michael. “We’re lucky you’re here, Mia. Let’s see if we can turn things around.”8

8Are Mia’s expectations too high?
An Ambiguous Message
That evening Mia was doing the dishes after dinner when her phone signaled a new email. It was from Michael. She called Mateo into the kitchen to hear the message: “Dear Mia, I’m writing to let you know that I spoke with Saul this evening. We discussed your role and the misalignments that resulted in a negative experience for you. Given the demands of my role, it’s difficult for me to meet regularly with all the members of my team, but I’m happy to set up a weekly check-in to support you. There are certain tasks that will greatly benefit the organization that I’d like you to stick with. But there may be other responsibilities we can add that would be more in line with your interests. Best regards, Michael”

“Hmm,” Mateo said. “Is he sorry for being such a bad boss since you started, or is he angry at you for talking to Saul?”

“I’m not sure,” Mia replied. “He’s saying the right things, but it’s such a cold, formal email, so I can’t help feeling that he sent it only because he got in trouble. Maybe going over Michael’s head was a mistake.”9

9Leadership experts say it’s a good idea to try to talk to a new boss about your struggles. But they also say that bad managers are rarely open to hearing feedback about their failings.
“Well, you’ve tried talking to Michael and didn’t get anywhere. And it’s clear he didn’t understand what Saul promised you, so they needed to have a conversation. Even if he’s saying all this under duress, at least he’s saying it.”

“But can I trust him? Can I trust the organization? It has such a great reputation, but from the inside it seems like a mess.”

Mateo hugged her. “You’ve never been the kind of person to settle,” he said. “If it’s that bad, maybe it’s time to cut your losses.”

“And do what? I need a job.”

“Of course. We rely on your income. But what did your boss say when you left Azzurro? She said you could always come back.”

“Doesn’t everyone say that?”

“No. They loved you there.”

Mia smiled, but she was still conflicted. “I guess I could reach out to recruiters, too.”

“See—you have options.”

“I know. I need to think more about what I’m going to do.”

“Well, I’m here to talk whenever you need to. I’ll support your decision.”

Question: Should Mia stick it out or look for a new job? The Experts Respond
Lauren Barraco is the head of product marketing at Sendoso.
IF YOU DON’T like your current situation, you have the power to change it. I would encourage Mia to actively start looking for another job. She needs to reframe her negative experience at Rescue as an opportunity to consider what will really make her happy. Does she want to be more involved in a career track that includes fieldwork? Is an office environment with natural light and standing desks (as opposed to a dark space filled with cubicles) important for her mental health?

We already know she’s a marketable candidate. She was recruited and offered twice her salary to work at a respected nonprofit. And because she has a steady income, she has time to be strategic and consider other job options. Looking for a job is like a job in itself, but it will be worth it if Mia can find one better suited to her goals and personal needs.

I experienced a similar situation. A few years ago I joined a prestigious news outlet. Like Rescue, it was a large organization with serious bureaucracy problems. Processes weren’t streamlined, and people needed approvals at many levels to get things done. This lack of agility meant that the organization struggled with employee development.

As a result, my manager and I had different expectations regarding my role. Mia is facing the same thing. In a bureaucracy, without a supportive boss, it can take months, even years, for the situation to change. And Michael’s icy email implies that he already resents Mia for going over his head—a red flag that suggests he may not be open to change. Even if his reasons are justified, their relationship will probably continue to be emotionally exhausting for Mia.

What Mia can control is how she reacts. She can think about what she’s looking for in a work environment and culture and outline where she wants to be in five to 10 years. She can update her résumé and craft a story to explain her short time at Rescue. I’d recommend that she tell an honest one: “I was recruited, but in the end there were some misalignments between the role I was told I’d be taking on and the work I was doing.” She doesn’t need to go into a lot of detail.

I left the news outlet years ago and found a job at a much smaller company that was a better cultural fit. I was also given more leadership opportunities, which allowed me to launch my long-term career. Later on I learned that the structural problems at the news outlet ended up hurting the business because it couldn’t keep up with changing technologies.

If Mia stays at Rescue, she risks spinning her wheels and halting her professional development. She needs to be a self-starter and put her happiness first.

Danielle Piendak is the director of individual giving administration and donor information at the 92nd Street Y.
MIA SHOULD STICK with Rescue for a bit longer. She is only a month in and needs to give it more time. Change always comes with some challenges.

I’d encourage her to revisit what originally drove her to take this role. First, the organization is very much more in alignment with her interest in humanitarian work than Azzurro was. And although she is understandably excited by the prospect of actually working in the field, she will soon learn how crucial internal support staff members like her are to making this work possible. Nonprofits today depend on strong data and analytics to remain competitive in their fields and to present valid, evidence-based reporting to their partners.

Second, this role is more challenging than her previous one was. She is taking on new and different responsibilities, which naturally come with a period of discomfort. But that’s normal. At the end of the day, this job is going to stretch her in ways that her previous role didn’t. She will walk away with a much broader skill set in a field she is passionate about.

Without putting the blame on anyone in particular, it appears that there were some failures in the interview process that have led to a misalignment between Mia’s expectations and Michael’s. It doesn’t seem to me that this is the result of poor leadership or an issue of organizational structure, either of which would be of greater concern.

As written, Mia’s job description—setting up data systems and identifying key performance indicators—is a very internal one. If we could go back a month, I would caution her to take a closer look at what exactly she was being hired to do and to clarify her day-to-day responsibilities. For example, “Does identifying KPIs mean I’d be going into the field, or would that work take place in the office?”

What Mia can do now is revisit that job description to see whether it matches the tasks she’s been assigned so far. Recruiters do sometimes make promises to expand roles when they are trying to draw in candidates. Since Mia was indeed promised fieldwork by Saul, Michael has a responsibility to follow through. When and how that will happen needs to be made clear.

It’s a good sign that Michael addressed this issue head-on, even if he did so in an email. He may have been doing it grudgingly, but he seemed to be offering Mia an olive branch and a chance for the two of them to get on the same page.

If Mia chooses to stick it out for at least six months, she can take small, proactive steps to improve her situation. It is Michael’s responsibility to make time for weekly check-ins, but it is Mia’s responsibility to set the agenda for those meetings. Before going into them, she should outline what she wants to discuss, including questions she has about upcoming projects and how to overcome challenges she may be facing. She needs to take the initiative to get guidance from Michael rather than waiting for him to offer it.

Even if we weren’t in the midst of an economic downturn, I’d advise Mia to stay on for now. If she is still unhappy in the role after six months, maybe she does need to think about other possibilities. But she will walk away with a stronger résumé and a better skill set, which will position her to have more options.

Source : https://hbr.org/2020/07/case-study-stick-with-a-bad-new-job-or-cut-your-losses

In a 2018 Workforce Institute survey of 3,000 managers across eight industrialized nations, the majority of respondents described artificial intelligence as a valuable productivity tool.

It’s easy to see why: AI brings tangible benefits in processing speed, accuracy, and consistency (machines don’t make mistakes because they’re tired), which is why many professionals now rely on it. Some medical specialists, for example, use AI tools to help make diagnoses and decisions about treatment.

But respondents to that survey also expressed fears that AI would take their jobs. They are not alone. The Guardian recently reported that more than 6 million workers in the UK fear being replaced by machines. These fears are echoed by academics and executives we meet at conferences and seminars. AI’s advantages can be cast in a much darker light: Why would humans be needed when machines can do a better job?

The prevalence of such fears suggests that organizations looking to reap the benefits of AI need to be careful when introducing it to the people expected to work with it. Andrew Wilson, until January 2020 Accenture’s CIO, says, “The greater the degree of organizational focus on people helping AI, and AI helping people, the greater the value achieved.” Accenture has found that when companies make it clear that they are using AI to help people rather than to replace them, they significantly outperform companies that don’t set that objective (or are unclear about their AI goals) along most dimensions of managerial productivity—notably speed, scalability, and effectiveness of decision-making.

In other words, just as when new talent joins a team, AI must be set up to succeed rather than to fail. A smart employer trains new hires by giving them simple tasks that build hands-on experience in a noncritical context and assigns them mentors to offer help and advice. This allows the newcomers to learn while others focus on higher-value tasks. As they gain experience and demonstrate that they can do the job, their mentors increasingly rely on them as sounding boards and entrust them with more-substantive decisions. Over time an apprentice becomes a partner, contributing skills and insight.

 

We believe this approach can work for artificial intelligence as well. In the following pages we draw on our own and others’ research and consulting on AI and information systems implementation, along with organizational studies of innovation and work practices, to present a four-phase approach to implementing AI. It allows enterprises to cultivate people’s trust—a key condition for adoption—and to work toward a distributed human-AI cognitive system in which people and AI both continually improve. Many organizations have experimented with phase 1, and some have progressed to phases 2 and 3. For now, phase 4 may be mostly a “future-casting” exercise of which we see some early signs, but it is feasible from a technological perspective and would provide more value to companies as they engage with artificial intelligence.

Phase 1: The Assistant
This first phase of onboarding artificial intelligence is rather like the process of training an assistant. You teach the new employee a few fundamental rules and hand over some basic but time-consuming tasks you normally do (such as filing online forms or summarizing documents), which frees you to focus on more-important aspects of the job. The trainee learns by watching you, performing the tasks, and asking questions.

One common task for AI assistants is sorting data. An example is the recommendation systems companies have used since the mid-1990s to help customers filter thousands of products and find the ones most relevant to them—Amazon and Netflix being among the leaders in this technology.

More and more business decisions now require this type of data sorting. When, for example, portfolio managers are choosing stocks in which to invest, the information available is far more than a human can feasibly process, and new information comes out all the time, adding to the historical record. Software can make the task more manageable by immediately filtering stocks to meet predefined investment criteria. Natural-language processing, meanwhile, can identify the news most relevant to a company and even assess the general sentiment about an upcoming corporate event as reflected in analysts’ reports. Marble Bar Asset Management (MBAM), a London-based investment firm founded in 2002, is an early convert to using such technologies in the workplace. It has developed a state-of-the-art platform, called RAID (Research Analysis & Information Database), to help portfolio managers filter through high volumes of information about corporate events, news developments, and stock movements.

AI is very helpful during high-volume decision-making, when humans may be tired.

Another way AI can lend assistance is to model what a human might do. As anyone who uses Google will have noticed, prompts appear as a search phrase is typed in. Predictive text on a smartphone offers a similar way to speed up the process of typing. This kind of user modeling, related to what is sometimes called judgmental bootstrapping, was developed more than 30 years ago; it can easily be applied to decision-making. AI would use it to identify the choice an employee is most likely to make, given that employee’s past choices, and would suggest that choice as a starting point when the employee is faced with multiple decisions—speeding up, rather than actually doing, the job.

Let’s look at this in a specific context. When airline employees are deciding how much food and drink to put on a given flight, they fill out catering orders, which involve a certain amount of calculation together with assumptions based on their experience of previous flights. Making the wrong choices incurs costs: Underordering risks upsetting customers who may avoid future travel on the airline. Overordering means the excess food will go to waste and the plane will have increased its fuel consumption unnecessarily.

An algorithm can be very helpful in this context. AI can predict what the airline’s catering manager would order by analyzing his or her past choices or using rules set by the manager. This “autocomplete” of “recommended orders” can be customized for every flight using all relevant historical data, including food and drink consumption on the route in question and even past purchasing behavior by passengers on the manifest for that flight. But as with predictive typing, human users can freely overwrite as needed; they are always in the driver’s seat. AI simply assists them by imitating or anticipating their decision style.

It should not be a stretch for managers to work with AI in this way. We already do so in our personal lives, when we allow the autocomplete function to prefill forms for us online. In the workplace a manager can, for example, define specific rules for an AI assistant to follow when completing forms. In fact, many software tools currently used in the workplace (such as credit-rating programs) are already just that: collections of human-defined decision rules. The AI assistant can refine the rules by codifying the circumstances under which the manager actually follows them. This learning needn’t involve any change in the manager’s behavior, let alone any effort to “teach” the assistant.

Phase 2: The Monitor
The next step is to set up the AI system to provide real-time feedback. Thanks to machine-learning programs, AI can be trained to accurately forecast what a user’s decision would be in a given situation (absent lapses in rationality owing to, for example, overconfidence or fatigue). If a user is about to make a choice that is inconsistent with his or her choice history, the system can flag the discrepancy. This is especially helpful during high-volume decision-making, when human employees may be tired or distracted.

Research in psychology, behavioral economics, and cognitive science shows that humans have limited and imperfect reasoning capabilities, especially when it comes to statistical and probabilistic problems, which are ubiquitous in business. Several studies (of which one of us, Chen, is a coauthor) concerning legal decisions found that judges grant political asylum more frequently before lunch than after, that they give lighter prison sentences if their NFL team won the previous day than if it lost, and that they will go easier on a defendant on the latter’s birthday. Clearly justice might be better served if human decision makers were assisted by software that told them when a decision they were planning to make was inconsistent with their prior decisions or with the decision that an analysis of purely legal variables would predict.

AI can deliver that kind of input. Another study (also with Chen as a coauthor) showed that AI programs processing a model made up of basic legal variables (constructed by the study’s authors) can predict asylum decisions with roughly 80% accuracy on the date a case opens. The authors have added learning functionality to the program, which enables it to simulate the decision-making of an individual judge by drawing on that judge’s past decisions.

The approach translates well to other contexts. For example, when portfolio managers (PMs) at Marble Bar Asset Management consider buy or sell decisions that may raise the overall portfolio risk—for example, by increasing exposure to a particular sector or geography—the system alerts them through a pop-up during a computerized transaction process so that they can adjust appropriately. A PM may ignore such feedback as long as company risk limits are observed. But in any case the feedback helps the PM reflect on his or her decisions.

Of course AI is not always “right.” Often its suggestions don’t take into account some reliable private information to which the human decision maker has access, so the AI might steer an employee off course rather than simply correct for possible behavioral biases. That’s why using it should be like a dialogue, in which the algorithm provides nudges according to the data it has while the human teaches the AI by explaining why he or she overrode a particular nudge. This improves the AI’s usefulness and preserves the autonomy of the human decision maker.

Unfortunately, many AI systems are set up to usurp that autonomy. Once an algorithm has flagged a bank transaction as possibly fraudulent, for example, employees are often unable to approve the transaction without clearing it with a supervisor or even an outside auditor. Sometimes undoing a machine’s choice is next to impossible—a persistent source of frustration for both customers and customer service professionals. In many cases the rationale for an AI choice is opaque, and employees are in no position to question that choice even when mistakes have been made.

Of course AI is not always “right.” That’s why using it should be like a dialogue.

Privacy is another big issue when machines collect data on the decisions people make. In addition to giving humans control in their exchanges with AI, we need to guarantee that any data it collects on them is kept confidential. A wall ought to separate the engineering team from management; otherwise employees may worry that if they freely interact with the system and make mistakes, they might later suffer for them.

Also, companies should set rules about designing and interacting with AI to ensure organizational consistency in norms and practices. These rules might specify the level of predictive accuracy required to show a nudge or to offer a reason for one; criteria for the necessity of a nudge; and the conditions under which an employee should either follow the AI’s instruction or refer it to a superior rather than accept or reject it.

To help employees retain their sense of control in phase 2, we advise managers and systems designers to involve them in design: Engage them as experts to define the data that will be used and to determine ground truth; familiarize them with models during development; and provide training and interaction as those models are deployed. In the process, employees will see how the models are built, how the data is managed, and why the machines make the recommendations they do.

Phase 3: The Coach
In a recent PwC survey nearly 60% of respondents said that they would like to get performance feedback on a daily or a weekly basis. It’s not hard to see why. As Peter Drucker asserted in his famous 2005 Harvard Business Review article “Managing Oneself,” people generally don’t know what they are good at. And when they think they do know, they are usually wrong.

The trouble is that the only way to discover strengths and opportunities for improvement is through a careful analysis of key decisions and actions. That requires documenting expectations about outcomes and then, nine months to a year later, comparing those expectations with what actually happened. Thus the feedback employees get usually comes from hierarchical superiors during a review—not at a time or in a format of the recipient’s choosing. That is unfortunate, because, as Tessa West of New York University found in a recent neuroscience study, the more people feel that their autonomy is protected and that they are in control of the conversation—able to choose, for example, when feedback is given—the better they respond to it.

AI could address this problem. The capabilities we’ve already mentioned could easily generate feedback for employees, enabling them to look at their own performance and reflect on variations and errors. A monthly summary analyzing data drawn from their past behavior might help them better understand their decision patterns and practices. A few companies, notably in the financial sector, are taking this approach. Portfolio managers at MBAM, for example, receive feedback from a data analytics system that captures investment decisions at the individual level.

 

The data can reveal interesting and varying biases among PMs. Some may be more loss-averse than others, holding on to underperforming investments longer than they should. Others may be overconfident, possibly taking on too large a position in a given investment. The analysis identifies these behaviors and—like a coach—provides personalized feedback that highlights behavioral changes over time, suggesting how to improve decisions. But it is up to the PMs to decide how to incorporate the feedback. MBAM’s leadership believes this “trading enhancement” is becoming a core differentiator that both helps develop portfolio managers and makes the organization more attractive.

What’s more, just as a good mentor learns from the insights of the people who are being mentored, a machine-learning “coachbot” learns from the decisions of an empowered human employee. In the relationship we’ve described, a human can disagree with the coachbot—and that creates new data that will change the AI’s implicit model. For example, if a portfolio manager decides not to trade a highlighted stock because of recent company events, he or she can provide an explanation to the system. With feedback, the system continually captures data that can be analyzed to provide insights.

If employees can relate to and control exchanges with artificial intelligence, they are more likely to see it as a safe channel for feedback that aims to help rather than to assess performance. Choosing the right interface is useful to this end. At MBAM, for example, trading enhancement tools—visuals, for instance—are personalized to reflect a PM’s preferences.

As in phase 2, involving employees in designing the system is essential. When AI is a coach, people will be even more fearful of disempowerment. It can easily seem like a competitor as well as a partner—and who wants to feel less intelligent than a machine? Concerns about autonomy and privacy may be even stronger. Working with a coach requires honesty, and people may hesitate to be open with one that might share unflattering data with the folks in HR.

Deploying AI in the ways described in the first three phases does of course have some downsides. Over the long term new technologies create more jobs than they destroy, but meanwhile labor markets may be painfully disrupted. What’s more, as Matt Beane argues in “Learning to Work with Intelligent Machines” (HBR, September–October 2019), companies that deploy AI can leave employees with fewer opportunities for hands-on learning and mentorship.

When AI is a coach, it can easily seem like a competitor as well as a partner.

There is some risk, therefore, not only of losing entry-level jobs (because digital assistants can effectively replace human ones) but also of compromising the ability of future decision makers to think for themselves. That’s not inevitable, however. As Beane suggests, companies could use their artificial intelligence to create different and better learning opportunities for their employees while improving the system by making it more transparent and giving employees more control. Because future entrants to the workforce will have grown up in a human-plus-machine workplace, they will almost certainly be faster than their pre-AI colleagues at spotting opportunities to innovate and introduce activities that add value and create jobs—which brings us to the final phase.

Phase 4: The Teammate
Edwin Hutchins, a cognitive anthropologist, developed what is known as the theory of distributed cognition. It is based on his study of ship navigation, which, he showed, involved a combination of sailors, charts, rulers, compasses, and a plotting tool. The theory broadly relates to the concept of extended mind, which posits that cognitive processing, and associated mental acts such as belief and intention, are not necessarily limited to the brain, or even the body. External tools and instruments can, under the right conditions, play a role in cognitive processing and create what is known as a coupled system.

In line with this thinking, in the final phase of the AI implementation journey (which to our knowledge no organization has yet adopted) companies would develop a coupled network of humans and machines in which both contribute expertise. We believe that as AI improves through its interactions with individual users, analyzing and even modeling expert users by drawing on data about their past decisions and behaviors, a community of experts (humans and machines) will naturally emerge in organizations that have fully integrated AI coachbots. For example, a purchasing manager who—with one click at the moment of decision—could see what price someone else would give could benefit from a customized collective of experts.

Although the technology to create this kind of collective intelligence now exists, this phase is fraught with challenges. For example, any such integration of AI must avoid building in old or new biases and must respect human privacy concerns so that people can trust the AI as much as they would a human partner. That in itself is a pretty big challenge, given the volume of research demonstrating how hard it is to build trust among humans.

The best approaches to building trust in the workplace rely on the relationship between trust and understanding—a subject of study by David Danks and colleagues at Carnegie Mellon. According to this model, I trust someone because I understand that person’s values, desires, and intentions, and they demonstrate that he or she has my best interests at heart. Although understanding has historically been a basis for building trust in human relationships, it is potentially well suited to cultivating human–AI partnerships as well, because employees’ fear of artificial intelligence is usually grounded in a lack of understanding of how AI works.
When AI Loses Its Way

In building understanding, a particular challenge is defining what “explanation” means—let alone “good explanation.” This challenge is the focus of a lot of research. For example, one of us (Evgeniou) is working to open up machine-learning “black boxes” by means of so-called counterfactual explanations. A counterfactual explanation illuminates a particular decision of an AI system (for example, to approve credit for a given transaction) by identifying a short list of transaction characteristics that drove the decision one way or another. Had any of the characteristics been different (or counter to the fact), the system would have made a different decision (credit would have been denied).

Evgeniou is also exploring what people perceive as good explanations for AI decisions. For example, do they see an explanation as better when it’s presented in terms of a logical combination of features (“The transaction was approved because it had X,Y,Z characteristics”) or when it’s presented relative to other decisions (“The transaction was approved because it looks like other approved transactions, and here they are for you to see”)? As research into what makes AI explainable continues, AI systems should become more transparent, thus facilitating trust.

CONCLUSION
Adopting new technologies has always been a major challenge—and the more impact a technology has, the bigger the challenge is. Because of its potential impact, artificial intelligence may be perceived as particularly difficult to implement. Yet if done mindfully, adoption can be fairly smooth. That is precisely why companies must ensure that AI’s design and development are responsible—especially with regard to transparency, decision autonomy, and privacy—and that it engages the people who will be working with it. Otherwise they will quite reasonably fear being constrained—or even replaced—by machines that are making all sorts of decisions in ways they don’t understand.

Getting past these fears to create a trusting relationship with AI is key. In all four phases described in these pages, humans determine the ground rules. With a responsible design, AI may become a true partner in the workplace—rapidly processing large volumes of varied data in a consistent manner to enhance the intuition and creativity of humans, who in turn teach the machine.

Source : https://hbr.org/2020/07/a-better-way-to-onboard-ai

While remote working has become the new normal for companies around the world, with many continuing to do so in the long-term, there are a number of employees who are eager to return to the office, a new report has found.

According to JLL’s recent Asia Pacific report, Home and away: the new hybrid workplace, out of 68% surveyed in the region who are working from home, more than six in 10 (61%) said they missed going into the office; and would favour a hybrid model combining more flexible work arrangements in the future.

While the respondents did enjoy the ‘freedom of working from home’, the three key reasons cited for missing the office were human interactions and socialising with colleagues; a professional environment with access to everything needed for work; and collective face-to-face work for collaboration.

Of all respondents, a majority who missed the office were Millennials, with 66% indicating so. This group had also noted what they enjoyed about working remotely, including flexible hours, reduced commuting, and work-life balance. At the same time, more than eight in 10 (81%) strongly agreed that they felt technology ready, while 52% felt more productive from home.

However, there were a few who said they could not afford accommodation with the space and amenities vital for successful home-working.

priya july 2020 jll report work from office screenshot

Commenting on the findings, Anthony Couse, CEO, Asia Pacific, JLL, said: “Employees across Asia Pacific have successfully transitioned to remote working, but our interactions also suggest that many now crave the office environment’s cultural and human experience. It is becoming clearer that the office is here to stay, but greater acceptance of remote working will force a new workplace model for many corporations regionally.”

80% of employees in India felt more productive working from home, while 43% in Singapore felt so

According to the survey, the quality of a person’s home surroundings, alongside their technology set-up, had a major impact on their remote productivity. Although 74% of employees surveyed had the basic technology needed to ensure business continuity and critical processes, approximately 50% of them did not feel more productive.

In the region, more employees in India revealed greater productivity while working from home (80%), when compared to its counterparts in the region, which scored between 21% (Japan) and 45% (Australia).

In Singapore, less than half said they were more productive working remotely (43%). That said, employees in this country were the third-most technology ready in the region, behind India and China.

How confident are employees in the future of their company?

Commenting on the findings, Anthony Couse, CEO, Asia Pacific, JLL, said: “Employees across Asia Pacific have successfully transitioned to remote working, but our interactions also suggest that many now crave the office environment’s cultural and human experience. It is becoming clearer that the office is here to stay, but greater acceptance of remote working will force a new workplace model for many corporations regionally.”

In fact, with the idea of hybrid work arrangements in mind, 29% of employees surveyed in the region were ‘very confident’ of their company’s future, while ‘27% were ‘very confident’ in their own prospects. Of these, Millennials emerged the most optimistic (35% and 34% respectively).

Among all who were ‘very confident’, employees in India once again led the way, with 59% indicating so; followed by 33% in China, and 30% in Australia.

priya july 2020 jll report work from office screenshot part 2

The future of the workplace: Offices will be reimagined as social hubs, and more

In line with the above findings, the survey respondents believed employers had a responsibility to foster this sense of optimism, whether their teams are working from home or in the office and as businesses, enhance human performance and productivity wherever their workers are.

Thus, the report highlighted some key considerations for employers to note, in exploring a hybrid work model:

The office space is here to stay: Higher acceptance of remote working will lead to a more distributed and diverse workforce but this will come with its own challenges on productivity and efficiency. Office space will continue to hold its importance, in most instances as the optimal working environment.

Offices will be reimagined as social hubs: The office provides a culture that can’t be replicated via remote working and serves as a social hub for employees to connect on common goals, purpose and vision. Repurposed or redesigned work areas will be required to provide infrastructure for collaboration among the split teams of remote and on-site staff.

The future footprint will facilitate choices and flexibility: Work-from-home saw many employees enjoy greater flexibility and control on their personal and professional lives. Corporates will have to redefine their real estate footprint, leveraging distributed and liquid spaces. At the same time, home offices, co-working places, satellite offices and the office HQ will all have to co-exist – leading to a truly hybrid office model.

Source : https://www.humanresourcesonline.net/66-of-millennials-surveyed-in-apac-miss-the-office-more-than-other-demographics