Last spring, Clark’s rolling spectacle seemed to signal a breakthrough. The national championship game, which Iowa lost to L.S.U., attracted some 10 million viewers, a runaway record for a women’s final. This month, Clark is poised to become the leading Division I college scorer in women’s history, a chase chronicled basket by basket on ESPN with a nightly fervor once reserved for touchdown passes and steroidal home-run marks. She is also threatening the overall Division I scoring record set more than 50 years ago by Pete Maravich, the master showman to whom she is often compared.
… For Iowa, the team and the state, Clark’s maybe-final season exists in a kind of liminal space. She is still theirs; she is also everyone’s. She is plainly ready to compete professionally but might well be better served staying put. She is a 22-year-old who unwinds with video games and ESPN in the cluttered two-bedroom apartment she shares; it just happens that the ESPN sessions sometimes include her highlights (“Her Beakness,” one anchor calls her, referencing the team mascot), and the clutter comes from her corporate partners.
Daily Word Challenge
Can you correctly use the word liminal in a sentence?
Based on the definition and example provided, write a sentence using today’s Word of the Day and share it as a comment on this article. It is most important that your sentence makes sense and demonstrates that you understand the word’s definition, but we also encourage you to be creative and have fun.
If you want a better idea of how liminal can be used in a sentence, read these usage examples on Vocabulary.com. You can also visit this guide to learn how to use IPA symbols to show how different words are pronounced.
Students ages 13 and older in the United States and the United Kingdom, and 16 and older elsewhere, can comment. All comments are moderated by the Learning Network staff.
AI is everywhere. It influences which words we use in texts and emails, how we get our news on X (formerly Twitter), and what we watch on Netflix and YouTube. (It’s even built into the Codecademy platform you use to learn technical skills.) As AI becomes a seamless part of our lives and jobs, it’s crucial to consider how these technologies affect different demographics.
So, how do we prevent bias in AI in the first place? It’s a big question that all developers and people who interact with technology have a responsibility to think about.
There are avenues for bias to occur at every stage of the development process, explains Asmelash Teka Hadgu, a Research Fellow at the Distributed AI Research Institute (DAIR). From the very beginning, a developer could conceptualize a problem and identify a solution space that doesn’t align with the needs of a community or an affected group. Bias can also show up in the data that’s used to train AI systems, and it can be perpetuated through the machine-learning algorithms we employ.
With so much potential for bias to creep into AI, algorithmic discrimination can feel inevitable or insurmountable. And while undoing racial biases is not as simple as building a new feature for an app or fixing a bug, there are proactive measures we can all take to address possible risks and eliminate bias to the best of our abilities. Ahead, Asmelash breaks down how these biases manifest in AI and how to prevent bias when building and using AI systems.
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How do racial biases manifest in AI, and what threats do they pose?
Asmelash: “If we zoom out a bit and look at a machine learning system or project, we have the builders or researchers who combine data and computing to create artifacts. Hopefully there’s also a community or people that their systems and research are intended to help. And this is where bias can creep in. From a builder’s perspective, it’s always good to assess (and possibly document) any biases or assumptions when solving a technical problem.
The second component is biased data, which is the first thing that comes to mind for most people when we talk about bias in machine learning. For example, big tech companies build machine learning systems by scraping the web; but we know that the data you find on the web isn’t really representative for many races and other kinds categorizations of people. So if people just amass this data and build systems on top of them, [those systems] will have biases encoded in them.
There are also biases that come from algorithm selection, which is less talked about. For example, if you have imbalanced data sets, you should strive to use the right kind of algorithms so you don’t misrepresent the data. Because, as we said, the underlying data might be skewed already.
The interplay between data and algorithms is difficult to tease apart, but in scenarios where you have class imbalance and you’re trying to do classification tasks, you should explore sub sampling or app sampling of certain categories before blindly applying an algorithm. You could find an algorithm that was used in certain contexts and then, without assessing the scenarios where it works well, use it on a data set that doesn’t exhibit the same characteristics. That mismatch could exacerbate or cause racial bias.
Finally, there are the communities and people we’re targeting in machine learning work and research. The problem is, many projects don’t involve the communities they’re targeting. And if your target users aren’t involved, it’s very likely that you’ll introduce biases later on.”
How can AI developers and engineers help mitigate these biases?
Asmelash: “DAIR’s research philosophy is a great guide, and it’s been really helpful as I practice building machine learning systems in my startup, Lesan AI. They explain how, if we want to build something for a community, we have to get them involved early on — and not as data contributors, but as equal partners of the research that we’re doing. It takes time and trust to build this kind of community involvement, but I think it’s worth it.
There’s also accountability. When you’re building a machine learning system, it’s important to make sure that the output of that project isn’t misused or overhyped in contexts that it’s not designed for. It’s our responsibility; we should make sure that we’re accountable for whatever we’re building.”
What can organizations and companies building or employing AI tools do?
Asmelash: “There’s a push toward open sourcing AI models, and this is great for looking into what people are building. But in AI, data and computing power are the two key components. Take language technologies like automatic speech recognition or machine translation systems, for example. The companies building these systems will open source all of the data and algorithms they used, which is fantastic, but the one thing they’re not open sourcing is their computing resources. And they have tons of it.
Now, if you’re a startup or a researcher trying to do something some meaningful, you can’t compete with them because you don’t have the computing resources that they have. And this leaves many people, especially in developing companies, at a disadvantage because we’re pushed to open source our data and algorithms, but we can’t compete because we lack the computing component and end up getting left behind.”
How about the average person using these tools — what can individuals do to help mitigate racial bias in AI?
Asmelash: “Say a company creates a speech recognition system. As someone from Africa, if it doesn’t work for me, I should call it out. I shouldn’t feel ashamed that it doesn’t work because it’s not my problem. And the same goes for other Black people.
Research shows that automatic speech recognition systems fail mostly on Black speakers. And when this happens, we should call them out as users. That’s our power. If we can call out systems and products and say ‘I’ve tried this, it doesn’t work for me’ — that’s a good way of signaling other companies to fill in that gap. Or letting policymakers know that these things don’t work for a certain type of people. It’s important to realize that we, as users, also have the power to shape this.
You can also contribute [your writing skills] to machine learning research. Research communication, for example, is such a big deal. When a researcher writes a technical research paper, they’re not always interested in communicating that research to the general public. If somebody’s interested in this space, but they’re not into coding and programming, this is a huge unfilled gap.”
Conversation has been edited for clarity and length.
If you’ve been poking around in the comment sections of this high-impact workplace skills series, you’ll notice one theme has come up on several occasions, and that’s empathy. The ability to empathize—to really hear, understand, and feel for other people—is a core interpersonal skill that unlocks deeper capabilities and drives effectiveness when working with others.
Think about it this way:
You can use analytical thinking to find solutions to problems, but you can’t convince your stakeholders to act on your recommendations if you don’t consider their needs.
You can motivate yourself to prioritize your professional development, but in order to set a career advancement strategy, you need to understand the outcomes your boss values.
You can demonstrate leadership by doling out assignments to your team, but if you want to encourage everyone’s best work, you need to recognize the conditions your team needs in order to operate at their best.
So even though empathy and active listening sit in the 8th spot on the top skills of 2023 list, these skills can find a way to enhance all of them.
How to show empathy
Empathy is a step deeper than sympathy. When you express sympathy, you might acknowledge the way a person is feeling and know how you’d feel if you were in a similar situation. When you express empathy, you’re able to imagine what it feels like to be that person in that situation.
When you empathize, you understand the web of circumstances that surrounds another person and influences the way they feel. Sympathy is noticing an intern struggling to complete a project; empathy is recognizing that an intern is struggling to adapt to their first work environment and that adjustment period is making it difficult for them to navigate their tasks.
Active listening and empathy have a symbiotic relationship. Active listening is a practice of hearing, interpreting, and reflecting when communicating with someone else.
To illustrate the relationship between these two skills, let’s return to your intern:
During an introductory conversation, the intern told you that this is their first work experience, and through their body language and the questions they asked, you picked up on their nerves around finding the right contacts for the various teams they’d be working with and etiquette for reaching out.
This previous conversation informed your empathetic response when you noticed their missed deadline—this was exactly what they’d been worried might happen. Now, you go back to the intern and reflect: “How are you feeling about your project? Can I help you find appropriate points of contact?”
Now, your intern feels like you heard them and understood their blockage, and you’ve provided a path forward (that’s leadership). Empathy and active listening not only helps you feel connected to others, but can help your peers feel connected to you in return.
Practicing empathy and active listening
You likely already have empathy and active listening skills—you may notice them the most when you’re interacting with loved ones—but these skills can be difficult to tap into in different environments or situations. In order to really master these skills, it takes practice.
Here are some starting points:
Lastly, to close out this high-impact workplace skills series, we’ll offer one more recommendation: IBM’s People and Soft Skills for Professional and Personal Success Specialization. Over six courses, you’ll explore how to develop and implement what IBM calls “success skills”—all of which will look familiar to you after these last five issues.
With that, another Career Chat series comes to an end. Thank you for showing up and sharing with us. We’ll be back next week with another special issue. See you then!
Welcome to another special issue of Career Chat. This week, we’re shining our career spotlight on the world of data analytics. We’ve discussed data analysis skills in a past issue, but what might it look like for those skills to take center stage in your career?
Well, it can look a lot of different ways. A title like ‘data analyst’ can be pretty vague because data analysts work across many industries and business segments. Business analysts, financial analysts, marketing analysts, and health care analysts are all examples of people who use data to find solutions—the main difference between them is the type of problems they aim to solve.
Because data analysts exist across so many industries, it can be a good option if you’re thinking about changing careers. Having established industry knowledge can enhance your ability to examine and interpret industry-related data. For example, let’s say you work in customer service for a clothing retailer. Given your years of experience responding to customer concerns about delayed and inaccurate orders, you may be uniquely positioned to interpret problems and find solutions in a supply chain analyst or operations analyst role.
That is, as long as you know how to use data analysis tools and can move through the data analysis process: identifying your question, collecting information, cleaning data, conducting your analysis, and interpreting your findings. But those are all learnable skills. Angie Rudduck, a data analytics leader at Microsoft, recommends starting with a diverse array of certification courses and blogs. “Learn from as many people and sources as you can,” she says.
Rudduck also advocates for hands-on learning, expressing the importance of trying, even knowing you may fail, and learning from others. “If you want to get a job, go stand next to the person in that role today,” she says. “Learn by seeing, and then learn more however you can.”
To explore using data analysis in a business setting, check out Microsoft’s Power BI Data Analyst Professional Certificate. Here, you’ll learn how data analysts and business intelligence analysts use Power BI, a powerful analysis tool, to solve business problems. By the end of these courses, you’ll be prepared to take the industry-recognized PL-300: Microsoft Power BI Data Analyst certification exam, and you’ll be eligible to receive a 50% exam discount voucher.
For an introduction to the data analysis process, start with Google’s Data Analytics Professional Certificate. These courses cover the basics of starting a career in data analytics and guide you through the data analysis process using Google Sheets, SQL, and R.
To build your data analyst programming skills, try the University of Michigan’s Python for Everybody Specialization. Data analysts use Python to gather, clean, analyze, and visualize data—in other words, you can use Python at every stage of your analysis.
Keep learning about becoming a data analyst
To keep exploring a career as a data analyst, take a look at some of our most popular guides:
Drop any lingering data analyst questions in the comment section below and we’ll do our best to point you in the right direction. Otherwise, we’ll see you next week!
During a recent dinner at a cozy bar in Upper Manhattan, I was confronted with an age-old question about gender norms. Over bowls of ramen and sips of gin cocktails, my date and I got into a debate: Who should pay for dates?
My date, a 27-year-old woman I matched with on Hinge, said gender equality didn’t mean men and women should pay the same when they went out. Women, she said, earn less than men in the workplace, spend more time getting ready for outings and pay more for reproductive care.
When the date ended, we split the bill. But our discussion was emblematic of a tension in modern dating. At work and on social media, where young people spend much of their personal time, they like to emphasize equity and equality. When it comes to romance and courtship, young people — specifically women and men in heterosexual relationships — seem to be following the same dating rules their parents and older generations grew up learning.
Contemporary research, popular culture and conversations I had with more than a dozen young Americans suggest that a longstanding norm still holds true: Men tend to foot the bill more than women do on dates. And there seems to be an expectation that they should.
The article continues:
Shanhong Luo, a professor at Fayetteville State University, studies the factors behind attraction between romantic partners, including the norms that govern relationships. In a paper published in 2023 in Psychological Reports, a peer-reviewed journal, Dr. Luo and a team of researchers surveyed 552 heterosexual college students in Wilmington, N.C., and asked them whether they expected men or women to pay for dates — and whether they, as a man or a woman, typically paid more.
The researchers found that young men paid for all or most of the dates around 90 percent of the time, while women paid only about 2 percent (they split around 8 percent of the time). On subsequent dates, splitting the check was more common, though men still paid a majority of the time while women rarely did. Nearly 80 percent of men expected that they would pay on the first date, while just over half of women (55 percent) expected men to pay.
Surprisingly, views on gender norms didn’t make much of a difference: On average, both men and women in the sample expected the man to pay, whether they had more traditional views of gender roles or more progressive ones.
“The findings strongly showed that the traditional pattern is still there,” Dr. Luo said.
Do you or any of your friends ever go on romantic dates? If so, who generally pays — and why? If you feel comfortable sharing your own experiences, did the question of who would pick up the check feel awkward, stressful or confusing? Did it make the date less enjoyable?
Who do you think should pay for dates? Do you have a hard and fast rule, or doesit depend on the date?
The article states that in L.G.B.T.Q. relationships, who pays for dates has less to do with gender norms and more to do with specific relationship dynamics. Is this a more helpful way to approach the issue?
Mr. Nerkar writes that members of Gen Z seem to follow the same dating rules their parents and older generations grew up learning, regardless of whether they have more traditional or progressive views of gender roles. Do you find this surprising? What do you think accounts for the “persistent tradition of men paying”?
Scott Bowen, a 24-year-old accountant in Charlotte, N.C., profiled in the article, said that, although he would like to see the status quo changed to be more of an even split, his parents made it clear to him when he was growing up that he should pay for dates. What kinds of messages, expectations and guidance have you received about dating norms? Have they been useful? Have you ever discussed the issue of paying for dates with friends, parents or romantic partners?
Mr. Nerkar went on 11 dates while working on the article, paying for five and splitting six. On one recent outing, his companion argued that men should foot the bill more often since women earn less than them in the workplace and spend more time getting ready for outings. How persuasive is the case that men should pay for dates?
Do you tend to follow relationship norms? Or do you often question or even break them? On the whole, do you think that relationship norms are a helpful way to navigate and negotiate our romantic lives? Or do they get in the way of forming meaningful and satisfying partnerships?
Use your imagination to write the opening of a short story or poem inspired by this image or, describe a memory from your own life that this photo makes you think of.
Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public and may appear in print.
The word oblivious has appeared 138 times on NYTimes.com in the past year, including on Jan. 10 in The New York Times Magazine article “Why Are American Drivers So Deadly?” by Matthew Shaer:
Langer is not wrong about the efficacy of stronger enforcement. A country like France is proof. In 2003, the French government began installing a network of speed cameras on its roads and ratcheted up fines. As a result, rates of speeding steadily dropped in the first decade of implementation, as did the number of severe injuries and fatalities. And many provinces in Canada more or less revoke the license of impaired drivers, often impounding the driver’s vehicle for good measure. Years ago, my wife and I took a trip to Australia and rented a car to drive from Melbourne to Sydney. I remember flying down the undulating highway, marveling at the tortoise-like pace of the cars around us. Then I got home, opened my email and discovered a $400 ticket passed on to me by the rental-car company. Attached was a picture of me behind the wheel, oblivious to the reality that the other drivers had already internalized: The highway was studded with speed cameras.
Daily Word Challenge
Can you correctly use the word oblivious in a sentence?
Based on the definition and example provided, write a sentence using today’s Word of the Day and share it as a comment on this article. It is most important that your sentence makes sense and demonstrates that you understand the word’s definition, but we also encourage you to be creative and have fun.
If you want a better idea of how oblivious can be used in a sentence, read these usage examples on Vocabulary.com. You can also visit this guide to learn how to use IPA symbols to show how different words are pronounced.
Students ages 13 and older in the United States and the United Kingdom, and 16 and older elsewhere, can comment. All comments are moderated by the Learning Network staff.
4. After you have posted, read what others have said, then respond to someone else by posting a comment. Use the “Reply” button to address that student directly.
On Wednesday, March 6, teachers from our collaborator, the American Statistical Association, will facilitate this discussion from 9 a.m. to 2 p.m. Eastern time.
5. By Friday morning, March 8, we will reveal more information about the graphs, including a free link to the article that includes these graphs, at the bottom of this post. We encourage you to post additional comments based on the article, possibly using statistical terms defined in the Stat Nuggets.
Reveal
We’ll post more information here on the afternoon of Thursday, March 7. Stay tuned!
• Learn more about the notice and wonder teaching strategy from this 5-minute video and how and why other teachers are using this strategy from our on-demand webinar.
• Sign up for our free weekly Learning Network newsletter so you never miss a graph. Graphs are always released by the Friday before the Wednesday live moderation to give teachers time to plan ahead.
• Go to the American Statistical Association K-12 website, which includes teacher statistics resources, Census in the Schools student-generated data, professional development opportunities, and more.
Students 13 and older in the United States and the Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public.
A large interview panel, long waits in between rounds, take-home assignments — should you be running for the hills? At the risk of sounding like a Senior Engineer, it depends. When you submit a job application, there are a lot of processes happening behind the scenes that can cause delays, says Nadia Vatalidis, Director of Talent Acquisition at Camunda, who has worked in recruitment and talent acquisition for more than 20 years. It’s been a tumultuous few years in the tech job market, with widespread layoffs leading to more competition for each role. A long job interview process isn’t always cause for concern, but it can be a clue into how the team operates and what it’d be like working at an organization.
So, what’s the holdup, and what can you do if things are taking too long?
What happens after you submit an application?
The stage between applying and hearing back from the company is often the longest. “For any role, there could be 50 applicants, 3,000, or even 8,000,” Nadia says. “Some companies use AI, assessments, or some form of automation to filter candidates for the right experience and competencies, but others might be filtering manually in the applicant tracking system.”
In addition to the large number of candidates, multiple people may be giving input and assisting in the candidate filtering process, says Nadia. All of this can add time, especially if the company works asynchronously across multiple time zones.
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So, how long should you expect to wait for a response to your application? “Between five and seven days is reasonable,” says Nadia. “Trying to reduce that review time to, say, 24 hours may mean that the talent acquisition team rushes the process, losing out on great candidates.” It’s tough to stay patient when your future career is on the line but think of it this way: You spent a lot of time working on your resume and portfolio, and you’d want the same attention and care given to your application.
It’s also worth mentioning that some automated emails from recruiters can inadvertently end up in your spam. “Some applicant tracking systems send notifications from ‘no reply’ email addresses, which often land in your junk folder,” says Nadia. So, if you are waiting on tenterhooks for a reply, it might be worth checking there.
Why can it take so long between interviews?
“If the hiring manager submits their feedback within 24 hours, I can get back to the candidate within 24-48 hours,” says Nadia. However, not every company you apply to will have a dedicated talent acquisition team or a formal applicant tracking system that notifies people that a candidate is waiting for next steps. “Sometimes a hiring manager might send a Slack message to the recruiter to say, ‘This went well, please move them forward,’ but we actually need them to complete the feedback form in the applicant tracking system before we can advance the candidate,” says Nadia.
Giving a deadline can actually help the recruiter to get the hiring manager to make a decision if they’ve been stalling.
Nadia Vatalidis
Director of Talent Acquisition at Camunda
If the process is taking a while and communication is erratic, this isn’t necessarily a red flag. Put it in context and consider the size and type of company you applied to and the complexity of the role. A well-established, post-IPO company probably has more regimented hiring procedures than, say, a series A startup with 50 employees. Empathizing with the hiring team can help to alleviate some of your frustration about waiting. (While they might use helpful AI tools to speed up the hiring process, they’re human too!)
This might also be a moment for you to reflect: do you want to work for a scrappy startup where you will probably be wearing many hats? Or would you prefer the structure of a big corporation? The hiring process can give you useful signals about what stage the company is at.
How many interviews is reasonable?
For a junior level position, Nadia believes up to four rounds of interviews should be sufficient to make a hiring decision. That might include a screening call, a technical interview, and a couple informal meetings with your potential team members. “If their interview panel is 10 people, something isn’t right; they might be looking for a standard that isn’t realistic,” she says.
The same principle applies if a company requires a long work sample or take-home assignment. “Their interview skills as a hiring manager or recruiter may be lacking if they can’t discover what they need during the interview process or by looking at your portfolio or body of work on GitHub, for example,” Nadia says.
Ideally, the company should be transparent about their hiring process and how many stages are involved before you apply. Feel free to ask the hiring manager at the start of the process how many stages of interviews you can expect. That way, you can decide upfront whether you’re comfortable with the amount of time and effort you’ll need to invest in it.
Why is it taking so long to get an offer?
It could be as simple as the person who signs contracts and approves salaries is out of office, says Nadia. “Another reason could be if you didn’t discuss compensation at any point in the hiring process, now the recruiter and hiring manager need to establish your expectations and if they can meet them,” she says.
Of course, there is always the possibility that they are trying to choose between you and another candidate. “Sometimes the hiring manager is genuinely struggling to decide,” Nadia says. If you’re dealing with a lean tech startup where there are lots of first-time managers, there could be subconscious delays. “They might be dealing with 10 other things on their team — some bug, an application being down, someone leaving the company, or even something positive in their personal life,” she says. “All those things are distracting and can impact the timeline.”
How can you follow up?
It’s not needy to send a follow-up message to the hiring manager. “If you’re waiting a week or longer between stages, it’s fine to check in with your contact in a kind, direct, and clear way,” says Nadia. And you don’t need to have a competing offer to press them for a decision: “It’s completely okay to say, ‘I interviewed on this date and would love some feedback by Friday afternoon,’ and you don’t need to give a reason or add an ultimatum.”
Asking for a response by a specific date can help to nudge things forward. “Giving a deadline can actually help the recruiter to get the hiring manager to make a decision if they’ve been stalling,” Nadia says. (We have more great advice on what to do if you’re ghosted by a recruiter.)
The delay itself is not a red flag, but how the company responds to your request can be illuminating, Nadia says. “If they respond rudely or make you feel bad for following up after they’ve gone silent, maybe you want to find an opportunity to work for another great company,” she says.
If you’re in between interviews, it’s always good to stay busy. Check out our Career Center for resources to help you prepare. If you’re waiting on a decision, hopefully these insights will help you feel more empowered to take action when the time (and job) is right.
Make continued learning and development an integral part of your business and watch your employees – and your balance sheet – thrive. While making an effort to upskill your team involves positive action, in today’s fast-paced and ever-evolving business landscape, doing nothing is a recipe for failure. The rapid pace of technological advancement is such that it has never been easier to fall behind the competition. In this blog, we’ll explore why upskilling your team is essential for staying competitive and the costs associated with doing nothing.
Stagnation Risks
No matter what sector your organisation is operating in, there are new technologies and methods of working regularly emerging. Companies and organisations that are stagnant risk falling behind or even becoming obsolete. Employees deprived of ongoing learning and development initiatives may struggle to keep up with industry trends, and productivity and innovation can suffer. The news media is just one of many sectors that is thriving, thanks to embracing new technologies and upskilling staff to operate digitally.
Goodbye Competitive Edge
In today’s global economy, successful organisations are able to differentiate themselves from their competitors. Upskilling your team equips them with the knowledge and tools needed to stay ahead of the curve, whether that means mastering new software, adopting best practices, or acquiring in-demand skills. Take Amazon, the delivery giant. It actively supports employees to expand their skills, including training blue-collar staff in software engineering, and expanding their opportunities within the company.
Low Morale and High Turnover
Employees relish opportunities for growth and development. When an organisation neglects to invest in its employees’ professional development, the result can be gradual disengagement, low morale, and, ultimately, higher turnover rates. Recruiting, onboarding, and training new staff is an expensive business and is money wasted when you can upskill staff for nothing with Alison’s groundbreaking free learning management system (FLMS).
Errors and Inefficiencies
Staff who miss out on training and skill development may struggle to perform their duties effectively, leading to inefficiencies and costly errors. Upskilling your employees will not only enhance their performance but also reduce the likelihood of mistakes that could damage your organisation’s reputation and its bottom line.
Loss of Innovation
Upskilling your team can foster a culture of innovation where employees feel empowered to explore new ideas and approaches. Failure to invest in professional development stifles creativity and limits the organisation’s ability to adapt to changing market conditions and customer needs.
Unhappy Customers
Inevitably, a poorly trained team can lead to dissatisfied customers. The issue could be longer wait times, inferior products or services, or outdated solutions, but customers will notice if your team is falling behind or failing to deliver value effectively. With brand loyalty in seemingly permanent decline – down 50% during the pandemic, according to McKinsey – customers are less inclined to give an underwhelming product or service a second chance.
In conclusion, failing to upskill your team could cost your organisation everything. By investing in your employees’ continued learning and development, you not only future-proof your organisation but also foster a culture of innovation, efficiency, and excellence. Begin by registering for Alison’s free LMS. You can select from a curated menu of courses according to industry or topic and access expert training in a flexible format. With over 5,000 courses available, you can find everything from digital technologies to languages (including business English), sales and marketing, administrative skills, data analysis, business development skills, academic subjects and much more.
So don’t wait until it’s too late – start upskilling your team today and reap the benefits of a skilled and empowered workforce.
