Predictive Analytics helps organizations leapfrog their competitors. Well-informed prediction models, to inform decision making, are essential during times of change.
Assessments and analytics are increasingly used to predict employee behavior, engagement, performance, and risks of attrition. In this article, Eric Shepherd explains what predictive analytics is and how this will revolutionize our thinking.
We see examples of predictive analytics in our day to day lives. Credit scores, product recommendations, dating apps, and supply-chain management systems all use predictive analytics. Credit scores predict how likely we are to repay a debt. Finely tuned algorithms can predict products that we're like to purchase. Dating apps use personal data to connect people that could be a match. And supply-chain management systems can pre-order and pre-position products that are likely to be consumed. Unlike the 2002 movie Minority Report that uses "precogs" to predict crimes, we use machines to crunch data in making predictions.
The social media giant Facebook uses predictive analytics to predict which user is likely to buy a product and place ads, based on the data collected from their profiles and the posts. It is a technology that uses historical data and predicts future events or outcomes.
The question arises, how does it work? Predictive analytics are data-driven and use statistical techniques to forecast and analyze the outcome. A mathematical model or algorithm is created by analyzing the data collected to project potential futures. For organization’s leaders and HR teams, this enables them to build predictive models to understand the possible engagement and effectiveness of its workforce.
Managing a golf club provides a useful example. Playing golf is most enjoyable with perfect weather conditions. If the manager tracks reservations, course usage, weather predictions, and actual conditions, over time, there is a possibility of predicting bookings and usage. Armed with this information, a manager could prepare staff and equipment for the busy times and reduce the facility's capacity based on the data collected.
Does the manager have enough data to predict course usage reasonably? The answer is yes and using a decision tree predictions can be more useful.
A decision tree is a tree-like model of decisions and consequences; it is a powerful tool used in analytics, where each leaf, or node, denotes an attribute, and each branch indicates the potential effects.
In the case of the probability of golf course usage, let's think about two predictors to keep the model simple, i.e., sunny day vs. rainy day. The likelihood of playing golf diminishes if it rains. Whereas the possibility of playing golf increases when the day is sunny. In short, weather forecast data can be used to predict the likelihood of golfers playing golf. Weather forecasts are not entirely accurate and so keeping an eye on the weather is another useful predictor. The leaf is the data, such as its raining, and the brand is the consequence, we need less staff and less equipment. This simple case of managing a golf course helps us understand the principles. Now imagine that we have hundreds of data inputs, and we are trying to predict if someone will enjoy a specific movie. And now imagine that we're trying to provide that service for millions of individuals. The problem becomes exponentially more complicated. Machine learning, which is a technique for computers to produce their own statistical models, can help here by digesting numerous data points and making sense of the patterns to come up with predictions. When organizations apply it to their workforce, it can provide useful insights on engagement, risk of loss, and productivity.
Data stored by organizations in their Human Resource Information System (HRIS) can be used to develop predictive models for employee behaviors. HR predictive analytics can help formulate policies for employee well-being, engagement, and efficiency, and to predict the performance the organization is likely to achieve.
Here are some examples:
All organizations have a level of regretted attrition, that is losing employees that an organization truly regrets losing. An employee's tenure will depend upon their circumstances and the nature of the work. Employee turnover may be benchmarked against similar job roles and industry sectors. Regretted attrition has many negative consequences which include loss in revenue, added cost of hiring, unwanted distractions, and reduced productivity.
Employees that enjoy their work and fit in with the culture and have good managers are likely to stay with organizations. Calculating a "Flight Risk Score" using mathematical models can help to predict the possibility of a worker resigning. Over time these models will improve to help the organization understand additional predictors for attrition.
There are privacy-related issues with accessing flight risk scores. That means access to this data must be restricted on a need to know basis. The power of the flight risk score is to help a manager intervene to avoid a regretted resignation and give them a game-plan in cases where an employee's departure is inevitable.
Statistics play an important role in predicting hiring success; many large organizations have accepted this. When recruiting, there are times of feast and famine. When there are more jobs than people looking, assessments can promote interest by using clickbait on social media to engage a qualified person who isn't yet looking. When more people are looking than jobs available, assessments can screen candidates into, or out of, the process.
Assessments, and the data collected, can streamline the engagement and interview process to find the right candidate. Using data helps determine cultural fit, i.e., does the candidate's values, motives, and preferences, match the organizational culture. Assessments can also predict job fit by testing to see if the person has the abilities required for the job. Assessments can promote better hiring practices but do not guarantee success.
Just as an organization wants to learn about the candidate to determine cultural and role fit, the candidate is making judgments about their potential employer. Using data to drive an active engagement process means an organization has a better chance of winning the heart and mind of the candidate. Predictive analytics can use data from multiple sources to guide the recruitment process and ensure that first-class candidates are properly engaged.
Studies reveal that there will be a decrease in morale and productivity should toxic employees be recruited or retained. Behaviors indicating disrespect, drug use, alcohol abuse, and sexual harassment need to be investigated before they fester. Predictive analytics can help spot the signs of toxic employees to promote an early intervention to discover the root cause of their behaviors.
Studies have uncovered that an increase in employee engagement leads to higher revenues. More engaged workers are more creative, less tardy, and work harder to achieve their goals resulting in greater productivity with higher levels of quality.
Measuring employee engagement and taking actions to create an extraordinary situation for individuals at work will positively impact an organization's performance. Using pulse surveys (a short, frequent survey with simple questions to give a quick insight into an organizations health) and other data sources, organizations can use predictive analytics to improve the workplace, engagement, retention, and performance.
An increasing and vital role for HR is to be an advisor to managers. HR, using data and predictive analytics, can help managers better understand themselves, others, and how to intervene to encourage behaviors required for success. Assessments and analytics are transforming the way HR is helping managers and employees and their work. Predictive analytics is also helping them forecast and optimize policies for employees and organizational growth.
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$We see examples of predictive analytics in our day to day lives. Credit scores, product recommendations, dating apps, and supply-chain management systems all use predictive analytics. Credit scores predict how likely we are to repay a debt.$
When normality returns, we will be facing a different set of challenges and opportunities than we had back in 2019. Martin Belton takes a look at the mindsets we're going to need from a personal and a business stance.
At Talent Transformation, we've been calling attention to the new world of work for quite some time before COVID-19. But the changes to work processes and the speed of those changes, signaled by the virus, have surpassed almost everybody's expectations. A good example, from a member, where they had a significant three-month project scheduled to introduce Microsoft Teams company-wide. With the advent of COVID-19, and the mass introduction of home working, they reduced that schedule down to three days. And so far as we are aware, it is all working well!
Of course, the broader definition of the new world of work is about a lot more than just working from home and taking on-board new tech to do your job. Even before the virus, so much was changing already; businesses are experiencing increased expectations in terms of social responsibility. Many organizations have been experiencing new stresses as millennials enter the workplace. The increased use of AI and robotics have also brought new opportunities but fears as well.
Given how well people have been adapted to new ways of working, it is tempting to say that these other issues will also be dealt with confidently and swiftly. But not everyone can change so quickly. It still requires a genuine change in mindset from us all to embrace such speedy changes. Not everyone is comfortable with such changes. And unquestionably, more changes are on the horizon. When normality returns, it is likely to look a lot different than it did back in 2019.
In the first instance, here is some practical advice from a personal point of view. These thoughts are mostly taken from the advice of experts in psychology and personal enrichment. They are designed to help those still struggling to adapt to working from home and the changes in their environment. We hope that this counsel will help prepare you for what's to come when the 'new normal' hits us:
As well as re-evaluating your personal goals, now is the time to do the same with your business goals. As we've already noted, so much was changing already with new technology and social responsibility becoming center stage. The influence of these factors will almost certainly increase now. So what does that mean for your business?
Here are some thoughts that might help you navigate these new challenges and opportunities:
This is clearly the ideal time to properly understand these new opportunities as new roles, products and ways of working are emerging
The world is in a different place now to where it was in 2019. It is how we deal with the new paradigms that will make the difference in the long run.
So many of today’s job roles have been thrown into confusion because of COVID19. Many other roles are being questioned as a result of the progress of AI and automation. But a timely new report from the World Economic Forum (WEF) might just be the blueprint we are looking for in a post-pandemic world. Eric Shepherd reviews its finding.
The new forces shaping jobs in the new world of work will affect millions worldwide. The Fourth Industrial Revolution (4IR) is giving rise to unprecedented prospects for economic prosperity and communal progress. But Coronavirus threatens to undermine this progress in a big way. On the other hand, it may also lead to the acceleration of acceptance of new ways and opportunities. In this rush to embrace ‘the new’ however, timely measures must be taken to ensure that unequal opportunity and income inequality do not arise and lead to unrest in an already shaken up world. Governments, industries, and workers may need to align their efforts to rethink market policies, employment arrangements, and skills development. Bringing about a positive outcome to the pandemic is contingent on all parties being able to espouse a strategic mindset and spirit of lifelong learning.
In a post pandemic world, existing jobs will continue to be augmented by new technologies. New professions will certainly appear. But these changes will entail a challenging transition. It will demand proactive investments in workers and a suitable framework to manage these changes. These endeavors need to be based on reliable data derived from thorough research into these emerging roles. This can then feed into solid action to prevent talent shortages on one side and unemployment on the other.
Prior to the current pandemic, leading thinkers at the WEF put together a report titled ‘Jobs of Tomorrow: Mapping Opportunity in the New Economy’ that serves as a roadmap for this process. Although this does not include an appraisal of today’s situation, the plans are still hugely, if not more, relevant than ever. It includes plans for spearheading a “reskilling revolution” to create new possibilities for almost a billion people over the coming decade. It looks at the way employment is drifting towards emerging professions, the underlying reasons, and the skills needed to thrive under such circumstances. In that sense, this report is a supremely timely call to action for governments and organizational leaders to deal with the challenges of a post-pandemic economic environment.
The WEF report uses innovative metrics together with researchers from three associate firms. The collaboration paints a realistic picture of up-and-coming occupations and the mindsets and skillsets needed for individuals to grasp these opportunities. Amongst the key findings, perhaps the most crucial is that both human talents and technology will drive growth in the future. The adoption of new technologies is imminent, even accelerated because of Covid 19. They will raise the profile of green economy jobs as well as creating new roles in engineering, cloud computing, and AI. But the human element needed for leadership, management, innovation, healthcare, marketing, content production, and cultural undertakings will remain indispensable.
The report names seven professional clusters and 96 jobs of tomorrow most likely to gain prominence. Statistics can gauge the relative significance of the clusters in the broader labor market. It claims that they will feature in 611 out of every 10,000 career opportunities by 2022. We guess that this figure may have increased still further since the start of March 2020. The WEF forecasts that this will translate into over 6 million new jobs worldwide over the course of the next two years. The roles expected to display the highest growth rates within high-volume jobs are artificial intelligence specialists, data scientists, and full-stack engineers. Where lower-volume jobs are concerned, we should expect growth for green marketers, social media assistants, and growth hackers.
The new world of work displays vibrant demand for an assortment of skills that will underpin these professions. This includes both cross-functional and technical skill sets, divided into five distinct categories. They are:
The ability needed for a role depends on the exact requirements and nature of the job. The kind of job opportunities that will arise largely depends on the demographic, economic, business model, and technological evolutions. A sizeable chunk of new jobs maybe created in new occupations or current ones that are undergoing an overhaul in terms of mindset and skills. The potential impact of these developments on future economic activity is considerable. Out of the total job churn precipitated by these events, new roles will account for 27% of all jobs by 2022. As 4IR accelerates change, the new tasks and types of work could chart pathways to upward social mobility.
The consequences of these transformations will affect all sectors of the workforce. The WEF has been tracking these variations for the past five years to assess the scale of labor displacement. The work was performed to enable workers to shift from declining to abundant roles. The Forum also examined ways of mapping outmoded jobs onto emerging ones to ensure a smooth transition for workers. The WEF agreed that prosperity in the changing marketplace would depend on transitioning to a skill-based hiring system focused on continuous improvement.
The approach adopted by this report of ‘real-casting’ employment trends was done in collaboration with two organizations that hold authoritative data on job opportunities: Burning Glass Technologies and LinkedIn. The former organization traces the number of job openings posted online, and the latter keeps track of how many professionals are being hired for new opportunities. They classified emergent professions as those that experienced record growth over recent years. Applying these methods produced seven characteristic occupational clusters: data and AI, cloud computing and engineering, care economy, green economy, product development, people and culture, as well as sales, marketing, and content. It is notable that individual growth rates and extent of employment prospects vary across all seven clusters.
The clusters in which the absolute number of job projections have the highest probability of changing in line with shifting business practices are the care and green economy. The green economy is susceptible to fluctuating government regulations due to upgrading of the services infrastructure to accommodate renewable energy. It has also fared less well during the pandemic outbreak as people’s attentions have turned to more immediate concerns. As far as the care economy goes, we have seen world events focus attention on to these challenges. But influences also include other demographic and society trends such as increasing numbers of women entering the workforce, aging populations.
Occupations registering high growth often require diverse competencies. The skills taxonomies used to delineate these competencies have been standardized by the WEF’s partners but only up to an introductory level. International cooperation is necessary to formulate a common language for the labor market to transcend geographic boundaries. Data scientists at online learning provider Coursera have drawn on users’ insights to devise a taxonomy of skills as a pre-requisite for online assessments. Keeping up with the learning preferences of people working in emerging professions helps to find patterns for upskilling in those fields. Coursera has also created a global skills index to appraise learners across a set of crucial future-oriented skills ordered into the three clusters of computer science, data science, and business skills.
Much of the past decade is defined by the rapid technological disruption that raised the threat of massive job losses and unsustainable skills inflation. Coronavirus has magnified this disruption ten-fold. This has naturally caused real concern and livelihoods are no longer guaranteed. Analysts that have previously tried to solve this puzzle concluded with a call for prudence but they also offered hope. A few analysts surmise that technological advancements will anyway shrink the size of the corporate playing field. But, encouragingly, most propose that many new opportunities will materialize. This stipulates that efficient training mechanisms must be in place to ease the transition of workers to the new world of work.
The World Economic Forum’s 2020 report embraces a quantitative, data-driven method to arrive at professional classifications for the future job market. AI is used to augment human estimations in this regard and offer unparalleled insights into the labor market. The development of standard metrics shared by public and private firms will be a powerful tool to help employers position themselves for a successful upskilling agenda. Exactly the kind of agenda we will need to help us all get back on our feet again once the current disruptions are over. The methodology adopted for matching skills to new jobs can be piloted to create sustainable systems that can supply information on the labor market in real-time. We need more attention to conceive skills taxonomies that reflect the demand for baseline and new disruptive technical skills. Although disruptive technological skills like data science are vital, so is the ability to give personalized care and supply bespoke learning and development. The diverse opportunities set to appear in the market will open multiple avenues for both low- and high-skilled careers.
The progression of these careers will be directly influenced by the decisions that governments make. This report shows that the means to inspire positive change in the labor market is within reach. More than ever, this will be in the best interests of everyone to create new opportunities and efficiencies for tomorrow’s post pandemic environment.
Martin Belton checked out there for the best and greatest advice for you all working from home and got some great advice from our Twitter followers.
Transport for London, (with an illustration by Kera Till) started us off well, giving us sound directions for getting to our desks on time. Though as Peter Harrison points out, don’t imagine your journey will always be free of challenges:
Our sporting heroes are have also been quick to remind us that there are still opportunities to make sure you get the recognition you deserve for your hard work:
Planning ahead is also important. Stock answers can be a boon says Marie-Christine:
Of course setting up your laptop at home can be a challenge. Hannah Wetherill is clearly into re-purposing existing facilities:
Paul Nazareth on the other hand has really got into the spirit of things:
That said, Marcel Cardillo is also organised but is still complaining that his international conference calls aren't going too well.
We hope you enjoyed our April 1st post enjoying the creativity of everyone from home. And as we work form home let's take a moment to thank our scientists and healthcare workers that are using their talents to inform us in the short term, cure us in the medium term and keep us safe for the long term. Thank you.
Critical tools and indicators need refreshing. This article from Eric Shepherd suggests new data sets that are needed to evaluate the organization’s health.
C-Suite executives are used to managing organizations with the help of Key Performance Indicators (KPIs) and Objective and Key Results (OKR’s). But, during a crisis like we’ve never seen, these critical tools and indicators will need refreshing.
Information and data are the lifeblood of decision making especially during times of crisis. But the data, KPIs and dashboards the C-suite need to manage during this pandemic, will look very different from those of the past. After engaging in calls for the last few days, we have compiled a list of crucial questions to tease out data that the C-suite can use to help with decision making during and after the pandemic.
Data is never perfect. But the more detailed information you can collect, the better the chances of the analytics and projections being accurate. Medical data is sensitive, and most countries restrict access to such data. A sick employee can volunteer their diagnosis, but it is not good practice to ask. In many countries, employers cannot even ask for a projected ‘return to work date,’ which can complicate analytics and predictions further.
There are several ways we can empower the C-suite with useful data. One useful indicator for our model is to take is the average number of days out sick. Given laws and good practice, this data could be sourced from:
Analyzing 2019 data can provide a useful indication of the norms for your organization. When analyzing more recent data, you can factor historical norms into your models to help determine the effects of the coronavirus.
However, historical norms must be used with care as they will not reflect the current norms for non-coronavirus related illnesses as more hand washing will reduce colds and flu infections as these are transmitted in the same way as the coronavirus.
The actual questions and data collected will be specific to your organization. We present the following list to help you brainstorm through the process of identifying the data and information that your C-Suite will need to review to make decisions and perhaps add to the organization’s KPI’s and OKRs.
1. Historical trend data segmented by geography and team for how many and the percentage of people are employed and:
3. Population trend data (from trusted sources) by geography and age, for the number of individuals and percentage of the population:
4. How ready are we for remote working?
5. Historical trend data and predictions of revenue-generating capacity considering:
Data harvested from this data will help the c-suite understand:
Predicting is never accurate, especially when it is about the future! However, we hope that this article provides a stimulus to help you use data-driven-decision making during this pandemic.
And please let us take a moment to thank all the scientists and healthcare professional that are using their talents, to inform us in the short term, cure us in the medium term and keep us safe for the long term.
Working from home is an essential part of the new world of work. But COVID-19 has seriously accelerated this practice. Experienced homeworker Martin Belton gives managers 10 tips to help them successfully manage the transition.
Homeworking is nothing new. But for reasons we all recognize, the concept is now being extended to new groups of employees, managers, and leaders. For all of them, this brings a new raft of responsibilities, actions, and tools to learn. Specifically, it falls on our managers and leaders to create an environment to support these new workers. Let alone ways of encouraging best practices in this new world. This is important. A poor homeworking environment will lead to a lack of motivation and understanding beyond anything we see in normal day to day office workings. I have therefore provided 10 easy-to-follow tips to help you provide a great homeworking ecosystem. They are as follows:
1. Arrange daily conference calls: Many experienced homeworkers and managers will tell you that a short pre-arranged call every day is the single most powerful tool you can have. This can be a group call for a large team. It teases out opportunities and challenges like no other tool and connects everybody instantly. Note that they don’t have to use video; voice will be fine. Attendance is the key.
2. Ensure the technology is adequate: An obvious issue, not to be underestimated, is to make sure that everyone has access to the right hardware, software and internet connection speed from day one. I would encourage you to consider additional financial support to make sure systems are up to scratch. Short term lease schemes are available if you’re not keen to lay out capital at this time. Those costs will be nothing compared to the loss of productivity that can result from workers sitting idle or a data breach.
3. Assess suitability. Given the current crisis we might not have this luxury, but assessing an individual’s ability to work alone at home will pay dividends. It’s not always easy to work out who will or will not be comfortable working from home. Your assessments should be based on sound logic rather than invalid assumptions. Assessing the human factors involved such as personality traits, motivation, preferences, motives, values, and home circumstances will help determine if any accommodations are required. Some people may benefit from partial homeworking rather than losing all face-to-face interactions.
4. Check out all the legal implications: Working from home may demand additional written agreements. These may, of course, already exist. As well as covering remote work expectations, you may also need agreements to cover equipment, expense, confidentiality, and security issues.
5. Don’t skip the training: Likewise, it should also be obvious that everyone can access to the right software. In remote working, it becomes even more critical that these tools are used consistently throughout a team. This is not quite as easy as it sounds. For instance, leading tools that support homeworking are Microsoft Teams, Slack, and Zoom but there are many more. These systems are fairly intuitive but supporting user confidence will accelerate their speed to productivity. People are apt to use it and store information in different ways which might increase risk to data security and so training Is essential. For employee engagement, productivity, and data security a good degree of training and practice might be required.
6. Make sure support is available: In any group of employees, someone will struggle with new tech. And if it’s not the tech, it might be the isolation or the changing work environment that cause frustration. Whereas it’s easy to ask someone sitting next to you or by the water-cooler how they are doing, it’s more difficult when they are working at a distance. So make sure that you have a support structures in place to tease out and provide the support required.. Embrace this early as change can be unsettling and cause real problems – people don’t always like to admit that they are struggling with the new culture or can't use all the tech!
7. Metrics are critical for managing remote workers: This is true for both for managers and employees. Agreeing, setting and discussing expectations becomes more important when people work from home. Using and referring to scorecards, KPI’s or OKR’s regularly helps everybody understand your expectations and how they will be assessed. Note this should not be an excuse to change your organizational objectives and goals; there will be sufficient challenges to deal with anyway. But you should be aware that remote solutions call for the use of the fixed and objective methods which these tools provide.
8. Spread the news: The lack of an office means you have to provide other methods for social interaction. That interaction should include both information provided by the organization and personal information that anyone wishes to share. The tools are less important than the messages. It could be something as simple as a WhatsApp or Slack group. Sharing good (or even bad) news; maybe an account win, or big sale, employee award is motivational for employees working from home. You could also consider having a “dress up” for work day and start your day with a video conference, or creating an area for shared online positive experiences just for fun.
9. Townhall webinars: Weekly webinars are an effective way to share knowledge, ensure a consistent vocabulary and engage your employees This can be made stimulating and enjoyable by representing a wide range of views with different presentation styles. The leader will manage the call but bringing in presenters from other departments, team members, product managers, or support staff can be very effective. Alternatively, bring in an external expert to promote new working practices or to promote personal wellbeing such as mindfulness.
10. Buddy up and have mentors available: Inevitably, working from home can sometimes feel like you’re working alone. It helps if you have a buddy or a mentor to turn to and share your challenges and successes. In mentoring programs, both the mentor and the student often benefit. But mentoring may not always be appropriate. In which case, an ‘assignment’ buddy - someone working on the same or similar project – can be equally supportive. Evidence suggests that this both motivates and increases accountability on a project.
Ultimately working from home suits some people more than others, just as some people hate coming into an office or a factory every day. But by providing the right atmosphere, tools, and support, this can be more effective than feared.
As well as increasing the efficiency of organizations, Martin Belton explains how AI is helping us in the fight against coronavirus.
As fears over the Covid-19 coronavirus continue to grow, scientists are turning to artificial intelligence to help them understand more and combat it at every level. There are three areas that AI is helping us combat Covid-19:
Online technologies have already helped organisations to compile a number of online resources which provide up-to-date information about the disease. These include Healthmap from Oxford University and John Hopkins University’s Coronavirus Resource Centre.
And AI is already helping us to understand how we can reduce the spread of Covid-19. In the UK for example, the BBC modeled data on infectious diseases using virtually infected mobile phones. It was this that helped to validate the now widespread and accepted advice that by washing our hands thoroughly, we can dramatically slow the spread of Covid-19.
AI has also played a pivotal role to help us understand this initial outbreak. One of the first organisations to identify this a new medical issue was Canadian infectious disease specialists Blue Dot. By using a combination of medical and airline data, their machine learning algorithms picked up information in Chinese about an unknown pneumonia centered around the market in Wuhan. Their team quickly recognized there were parallels to the SARS outbreak 17 years earlier. This helped us understand the risks involved; how contagious the disease might be and the wider risk to human life.
Other organizations are using AI to predict how the Covid-19 might be affected by seasonality. In the Northern hemisphere, upper respiratory pneumonias and viruses peak in the winter months, but then decline. AI is already being used to help us predict how the warmer summer weather might combat this spread.
But there is more to the contribution of AI than just tracking the virus. AI can also contribute to the creation of the vaccine as well as other drugs. It does this by providing a better understanding the mechanism of the disease. By correlating data on drugs, illnesses and their outcomes, AI can dramatically improve the amount of information on offer. This data, covering diseases, vaccines, symptoms and more is then crunched together to form new patterns and relationships which can then reveal surprising new information.
One result of this testing and searching is that, instead of looking for and creating new viral drugs to cure the disease, AI has identified potential existing drugs which may combat the disease. One drug in particular may be able to both inhibit the spread and reduce the effects of the disease on the lungs (the most common cause of death from the virus). Typically used to deal with Rheumatoid Arthritis, the drug must still be tested and approved before it can be used to combat Covid-19.
AI can also be used to understand the genetic sequence of a disease. That is where it’s come from and where it’s going to in the future. This can also be used to combat the spread of the disease.
AI cannot yet just be used to find a direct and immediate cure for the disease, however, it will be essential in evaluating proposed therapies to speed those to market. And let us take a moment to thank all of the human scientists, using their talents, to inform us in the short term, cure us in the medium term and keep us safe for the long term.
Do we trust robots and automation? In this article, Eric Shepherd discusses the studies that help us understand the changing relationship between employees, managers, AI, robots, and automation.
Employees, managers, and executives around the world now realize that artificial intelligence (AI) is real and here and emerging into the work environment. Attitudes towards AI are changing. Be they positive or negative; people are starting to recognize the power of these technologies.
Many studies have shown that these technological advances are affecting the output of managers. A recent survey by Gartner, the consulting, and advisory company, revealed that 69% of the tasks performed by managers will be delivered by artificial intelligence by 2024.
A study conducted by Future Workplace and Oracle found that the increasing use of AI at the workplace has a significant impact on the relationship of employees with the management. Their survey of 8,370 managers, employees, and HR representatives around ten countries discovered that 82% of participants said that robots or AI could do some tasks more effectively than their management. 64% said that they trust robots more than managers, and they have a positive relationship with AI; they are happy and thankful to have robot co-workers.
AI is growing stronger, with 50 percent of workers today using some sort of Artificial intelligence at work compared to 32 percent last year. In the study, they found that artificial intelligence has modified the relationship between humans and robotics at the workplace and reshapes the part that HR executives and teams have to perform in trying to attract, maintaining, and developing talent.
When participants were asked what made AI better than employees, they stated that the technology provides better impartial data, maintains working schedules, solves problems, and manages a budget. Survey participants said managers are better than robots in boosting their emotions as well as providing quality counseling and building a positive workplace culture.
Emily He, Senior Vice President, HCM Marketing, at Oracle, said: "I think one of the bigger themes from the study is that smart use of technology can actually bring humanity back to work." Emily continued, "The study found that workers perceive AI and bots to be better at certain things than humans, but that employees also would prefer their managers to apply technology where it makes sense so they can spend more time on things like showing empathy or providing personalized coaching."
This report represents a real shift by respondents. They’ve moved from voicing reservations about AI in the workplace to being far more interested in technological advancements.
The main two issues that discourage employees from using AI at work were security and confidentiality. But several respondents stated that they needed a more comfortable working experience with AI, with participants calling for improved user interfaces (34% demanded improvement), behavioral interactions (30%), and best practice learning (30%).
The long-term impact of AI at work is starting to become clear. Organizations can benefit by focusing on streamlining and securing AI in the workplace to take advantage of its benefits and new developments. By understanding what prevents people from using AI, organizations will then be able to build more effective and strategic approaches to address the challenges.
Understanding college, career, and work readiness is more important than ever in the new world of work. In this article Eric Shepherd highlights distinctions and explains why.
Why is it that students, leaving schools or college, so often seem to lack so many of the essential skills for the roles they want? Of course, organizations prefer someone that has already had a couple of years’ experience. But why is this so important – and so necessary? In seems that our students are not ‘job-ready.’ College graduates are smart and have plenty of potential. But they often fall short in terms of soft skills and behaviors required for the workplace.
The transition students must make between secondary and post-secondary education is one key milestone that can shape the future of a student. In recent times, efforts have been made to align with college and career readiness. Employers in need of a more skilled workforce are now entering the fray, trying to help align education to the skills required for the workplace and in line with global trends. Several institutes ably back these efforts to provide graduating students with the right mix of skills, knowledge, and industry-specific training to help them towards a fruitful career.
Educational and organizational development plans often discuss college, career, and work readiness. But what is meant by these terms isn’t always clear. The introduction of high school grades for workplace competencies and social skills provides a signal that academic qualifications are not enough. The next step must undoubtedly be assessing the inclusion of fundamental workplace competencies in the form of capabilities and behavioral skills. The fact that workplace competencies are paramount, along with core academic skills, is established. Competency frameworks are now aiming to bring these concepts together to help students progress educational outcomes to valuable workplace competencies.
Among the three readiness concepts, college readiness has far less ambiguity when it comes to the types and levels of skills that are needed to transition from secondary to post-secondary education successfully. As long as a student is deemed to be at a level of achievement where they can enroll and succeed, without remediation, in a first-year post-secondary course, they are considered to be “college-ready.” College readiness benchmarks and college education standards can help determine a student’s college readiness.
Some college readiness assessments represent the level of achievement required to succeed in post-secondary education. Success can be defined as a specific grade level in the relevant credit-bearing course. When assessments are based on national norms, benchmarks are expressed as median values for course placements. As such, they represent a set of expectations typical for such institutes. Combining college readiness benchmarks and standards can formulate academic expectations for students so they can succeed in post-secondary courses.
The latest college readiness benchmarks also include behavioral aspects aligning them with workplace readiness. Research shows that both career and workplace readiness demands attention for a person to be successful. That focus must include nonacademic factors such as motivation, interests, preferences, behavioral tendencies, and beliefs.
The current definitions of career readiness often revolve around static assumptions that students who completed the K-16 education pathway are career-ready. This not only excludes K-12 students but also overlooks the dynamic nature of today’s workplace. The workforce today requires many skills. One such skill is the ability to learn. Today the vast majority of people will hold various and different jobs in their lifetime. That means they will need multiple post-high school credentials to remain relevant in our ever-changing workplace.
A bare-bones definition of career readiness includes the level of foundational skills required to succeed in a career cluster or pathway. These definitions will also include the level of career planning skills necessary to progress within a chosen career path or to fork into other career paths.
Following are the Two Primary Factors of Career Readiness:
These two factors are foundational readiness criteria and are considered to be transferable skills. They are necessary for the workplace. But they also provide the base for more complex and advanced skill development. Irrespective of the career path or job, these skills apply to at least some level of almost every occupation. This makes them portable. Individuals who have developed functional skills and social-emotional intelligence become more successful in the job market and have a higher chance of succeeding in the workplace. Reading memos, listening to and following instructions, writing emails, delivering a presentation, and going the extra mile at work all require these foundational skills.
Career planning skills, on the other hand, inform an individual on their academic and career choices. Effective career planning leads to a more viable and exciting career pathway. It helps identify educational institutions that fit with their career of interest. These decisions impact the chances of an individual’s success in his career in terms of performance, job satisfaction, earnings, academic achievement, and lifelong learning.
Work readiness is directly tied with an individual’s fitment to a job. More precisely, it reveals whether an individual is a viable choice for a job. The level of foundational skills differs from one career to another. But within a single career path, the level and mix of foundations skills also vary significantly from one to another. The definition of work readiness suggests the minimum level of foundational skills needed by an individual to make then qualified for a job or occupation. Meanwhile, the job or occupation’s requirements are determined by job/task analysis or occupational profiles.
Workplace readiness covers workplace, behavioral, and functional skills. But unlike the skills needed in career readiness, the functional skills for the workplace are not so portable; they tend to be career or occupation-specific. For different occupations, the level and importance of these skills vary. They may also contain more and different skills and depend on the critical tasks needed to be completed in a particular job. As such, it is possible to achieve career readiness for a specific career before achieving work readiness for a specific role.
Work readiness benchmarks are based on work readiness assessment scores. These scores represent the level of skill the person possesses or needs to achieve to succeed in a particular job.
This is where competency definitions come in. They describe the key capabilities and behaviors needed for a job. Competency definitions and frameworks are developed through job analysis or identifying the critical tasks and their importance as they apply to a particular job role.
While readiness for college, career, and work readiness have distinctive criteria, they complement each other at each stage of an individual’s development. To be work ready for a specific job, an individual should plan to be career-ready. And they should acquire the necessary education, qualification(s), degree, and certifications to be considered for the role that they are seeking.
Today this is an ongoing process. Even within a specific career path, individuals need to enter and exit the career, education, and work readiness phases as new roles demand new learning requirements. The career path must include college readiness at some point. College readiness allows individuals to be successful in their first year in post-secondary education. Career and workplace readiness enables individuals to be successful in their first year of work. It’s that kind of preparedness that will benefit both individuals and organizations.
There was so much more to Davos 2020 than Donald Trump and Greta Thunberg. In this article, Eric Shepherd takes look at this year’s conference on capitalism.
It’s easy to imagine that attendees to Davos 2020 may be losing a little sleep after the event. In addition to the eye-watering ticket prices, they were confronted with presenters scaring them to death with tales of climate disasters and humans losing jobs as they are being replaced with machines in the workplace as the Fourth Industrial Revolution powers on.
Some of these are recurring themes of course. Ever since Professor Klaus Schwab, Founder and Executive Chairman of the World Economic Forum introduced us to the possibilities of the Fourth Industrial Revolution, we've been trying to make sense of it. Davos is the magnet for leaders and economists to assemble discuss global trends and catch up on all things to do with the new world of work. This year's discussions were no exception within influential experts contending that governments, organizations, and the broader community should join hands to impart the learning necessary to create a level playing field.
The issue of upskilling - on a massive scale – received much attention this year. The WEF launched an initiative to improve education and skills for a billion people by 2030. The OECD estimates that a third of all jobs in the world will be affected by technology in the next 10 years, and 42 percent of the core expertise needed to carry out existing tasks is likely to change by 2022. Demographic shifts and emerging economies only compound an already complicated situation.
With such divergent forces tugging away at our social fabric, there is clearly a question about how we can access the right pathways to provide the right social mobility? The answer is surely to offer more and appropriate training and building capacity for the right jobs. The stakes are higher than we might imagine; improving international social mobility by 10 percent results in an increase of almost 5 percent in economic growth over the following decade. Business leaders keen to do their bit to create fairer communities might look at working to close these gaps. The World Economic Forum consistently emphasizes the coming together of organizations, governments, and civil representatives so their core competencies can be harnessed for the greater good.
Davos presentations also noted that meaningful progress may be made by focusing on the professions that are likely to be most in-demand in the future but are presently undersupplied. A WEF report found that a lot of job growth will be in the areas of specialized HR, education, energy, transport, and digital infrastructure. While people will naturally be required to work with technology, not all of us need to become technical or scientific experts to succeed. As computing and data analysis grows in prominence, so will the necessity for real human qualities such as ingenuity, persuasion, and negotiation. A realization is hitting home that bringing personnel up to speed as far as hard skills are concerned is only half the story. It is the soft skills of adaptability and critical thinking that make training transformative.
But, it's not only workers who are concerned about updating their skills. Organizations are also on the lookout for ways to appeal to a diverse workforce. Different generations occupying the same space, and a narrowing gender gap have led to a remodeling of the relationship between employee and employer. Organizations need to retrain workers and rethink their approach to traditional structures and protocols. A PwC survey found that leaders who prioritized upskilling realized its benefits in the form of improved productivity and enhanced innovation.
Presenters at Davos also reiterated that private and public sectors need to join hands to empower individuals. A white paper proposed that public-private partnerships should concentrate on the critical areas of developing people, institutions, and the framework of rules regulating work. Both governments and corporations should be seeking new ideas that could satisfy both clients and employees. Many organizations have still not embarked on a digital journey because of a lack of skills required for change.
Equipping workers with new technological skills lays the foundation for fostering continuous improvement and lifelong learning. These kinds of initiatives enable people to access more economic opportunities by staying competitive while supplying organizations with better talent. Likewise, as the struggle to acquire top talent continues, organizations will need to move beyond traditional recruiting methods. Data and machine-learning algorithms can be put to good use in screening potential hires to yield the best results. A dynamic talent pool has now become a pre-requisite for organizations to handle diverse perspectives tactfully.
Less focus was provided perhaps on grass-roots Education. This of course remains a means for extending equal opportunity for all as technological disruptions continue to shake up our lifestyles and occupations. But only those who are agile enough to treat disruption as an opportunity for adopting new ways are the ones who will thrive. At a time when we are facing a scarcity of talent, the ability to find order in chaos may well turn out to be the crucial differentiator that wins us the future. Such an advanced level of human creativity and cognitive intelligence is practically impossible to automate.
Those of us losing sleep after the predictions of dystopia, where robots rule the world, should remember that it's always easier to describe away the existence of current industries than imagine the appearance of entirely new ones. A host of new jobs in STEM fields such as robotics and nanotechnology will need people with the right technical expertise to maintain them. It’s up to policymakers, governments and business leaders to make sure that people possess the right knowledge to be a useful part of the digital ecosystem.
In the absence of concrete action, our present skills crisis will cause a widening of the gap between the rich and the poor. It would no longer remain possible to achieve peace and prosperity in such a world. This is the time for the next revolution; the reskilling revolution.
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