We are accelerating fast into an Artificial Intelligence (AI) driven digital era. Not a moment goes when digital is not part of our daily lives. And that’s not just about smart devices at home or collaborating on MS Teams or Zoom meetings but extends to cars we drive, payments we make or shopping we do. While so much of our lives are surrounded and enhanced by digital experiences, when it comes to the most crucial resource that helps companies achieve goals and scale to new heights, that is human resources, AI is a tiny component. It will be a pity if we can’t extend and use the very tools that make our lives so much better when it comes to talent or human resources management.

In fact not just on Earth, even when we have people spending time in outer space (space tourism might take off this decade) an array of AI powered sensors all over the smart space crafts are informing people on board about what’s happening. So why when scouting for bright talent why do we just limit the digital experience to sending the CV online and do the rest manually? That’s like a whole lot of tasks from shifting through hundreds or thousands of CVs, matching profiles to candidates, identifying training needs or even checking out body language and speech quality in an informal way, when AI tools can give us scientific, unbiased answers.

Think of AI as a sensor capturing the daily activity of each individual of the workforce without interfering in their routines. At the end of the year it can give a better picture on how people delivered, what roles can they be moved into, who all need training requirements and areas in which they need and overall how do organisation goals match to the talent that the company has, which will help deliver those goals. Much like in some hospitals now X-Rays and other reports are being diagnosed by machines, freeing up radiologists to focus on more complicated cases.

What is done by the HR team alone based on information shared by employees, their department heads, colleagues could be prone to biases (so common it is to hear: he likes him more than me so I got a bad rating!) and this is where AI steps in to give a smart, intelligent, unbiased output on talent metrics of the company.

AI helps get the right candidates as well. Recruiters have often found that going through individual resumes is not only time consuming but may not be error free. As a detail could be overlooked. While chances of an AI making such errors is almost zilch.

Employee skills are of 2 types: – Domain and Soft. Domain skills are tangible in nature and easy to detect the presence or absence of. For example, a data analyst in the oil and gas industry will be aware of all types of products (petrol, diesel, kerosene, furnace oil etc), their subtle differences and what to look for. Soft Skills on the other hand are every hard to nail down. How does that oil industry analyst handle stress? Can he work long hours without a break and how does he collaborate with colleagues? No wonder research shows that on an average an organization loses up-to $100 million a year because of in-effective leadership and communication skills. Clearly since humans are not machines, they cannot be-embedded, with sensors which can signal the health of their soft skills.

Besides, how did you deal with a conflict? Whether it’s your written word or your spoken word, how effectively and astutely were you able to get it right? AI can identify individual behavior patterns and the environmental triggers which promote the right and or wrong behaviors.

And it helps both employees and companies. To an employee it can provide in time, on the job coaching and at the CEO /CXO level it can give deep insights into aspects of organization culture which are enabling versus hindering your growth. For companies, who invest considerable management time and resources in getting the right person for the job, a misfit in a role can impact not just that department but others who might be dependent on that department to deliver. AI platforms can empower companies and employees alike to fathom skills, capabilities and potential.

In a world where search for talent today starts on AI powered digital platforms, not using the same tools throughout the lifecycle of the employee would indeed be very surprising. Why leave that out for guesswork or chance? AI tools can not only improve individual performance but also company performance.

The post Artificial Intelligence: A Workmate for the Human Resource Department appeared first on Artificial Intelligence.

“Deep-learning will transform every single industry,” said Andrew Ng, a Chinese-American scientist excelling in machine learning and AI. McKinsey’s forecast on machine learning backs up his statement claiming that by 2030, AI will have a significant impact of $13 trillion on the global economy.

The Human Resource department will also witness the influence of AI. HR professionals understand the importance of optimizing the combination of the human mind and machine learning for a seamless workflow and intuitive work environment.

AI has the capacity to make decisions in real-time, based on pre-installed algorithms and efficient computing technologies. With an HR department encompassing the human element and AI, companies can provide an enhanced experience for their candidates and employees.

Additionally, artificial intelligence can help businesses understand their target market and promote result-oriented sales strategies.

AI is the ability of machines to imitate human intelligence. AI technology allows machines to learn and adapt automatically based on the data analysis to provide more refined responses to the situations. So, the question is how does AI impact Human Resource, a department that relies on its human factor.

Let’s explore the influence of AI in HR:

Talent Acquisition

The most prominent use of AI in HR is seen in the talent acquisition processes. From screening candidates, maintaining databases, scheduling interviews, and answering job seekers’ queries, it reduces manpower spent on mundane tasks.

It reduces hiring time significantly, allowing the HR team to be more productive in other areas like sourcing, recruitment marketing, employee management, and more. The AI-enabled screening will help in picking out the candidates with the most suitable skill set, relevant experience that fit the company’s requirements.

AI-based chatbots can communicate with potential candidates and match their profiles against the position requirements. It will narrow down the list to only those aspirants that fit the job description. The AI-enabled system will then schedule interviews and hire the top applicants.

It will save time and effort of the HR team, allowing them the opportunity to focus their energy on other tasks. 

Onboarding

After the hiring processes, the AI-integrated system will introduce the new employee to the company information on their first day. From job profile to company policies, the reporting authority, team members, task assignment, and other information, will be automatically relayed to them through an app or laptop. The entire process is defined as onboarding.

Onboarding is a vital part of improving employee retention rates and increasing HR productivity. One study by Click Onboarding states that there is a higher probability of employees staying with a company long-term if they experience a superior onboarding.

Artificial intelligence allows customization of the process to cater to individual employees and their respective positions. Algorithms can be integrated within the software for:

• Explaining job profile, duties, and benefits.
• Relevant and important contacts within the company.
• Answering frequently asked questions by new employees.
• Document verifications
• Device requests, and more.

Learning and Training

AI-integrated systems can also help in teaching and training the employees in their respective domains. The skills required by a job position are constantly changing with time. With new innovations and software in the market, it is imperative that we learn and adapt to the new technologies to stay on top.

AI will assess the employees’ skills and recommend videos or learning programs based on their job requirements. It will automatically read documents or analyze an employee’s activities and create appropriate learning programs.

AI technology can analyze the data collected from years of experience and inform the HR team which employee needs training and in what field. With intelligent algorithms, it will also recommend the best strategy to help people learn better and faster.

Additionally, companies can leverage AI technologies with e-learning platforms to enhance employees’ skills. It will devise a custom training regimen for individuals based on their skills and the company’s requirements. The e-learning platforms will help employees learn new techniques, polish existing characteristics, and more at a pace they find comfortable.

Moreover, an AI system can be integrated with an algorithm that determines the career path for individuals based on their training plan. The managers can use the results to turn their team into a more cohesive workforce.

Cognitive-Supporting Decision-Making

IBM conducted a study in 2017 over how cognitive computing will influence HR. The research revealed that artificial intelligence can help professionals make quick decisions on day-to-day matters.

The Human Resource department is responsible for the mental, emotional well-being of an employee apart from their work contributions. AI-enabled systems will take over the task of observing and analyzing employees’ mood before and after a client call. The HR can then decide if the individual needs a break or can continue.

AI can also detect anxiety in a person’s behavior and tone of voice. It will help the employers decide if they should look into the matter and resolve it before it is harmful to the employees and the company.

Leadership

As AI helps improve employee productivity, it can also help train leaders to excel in their position. AI-enabled systems will ask the leaders’ team members and assess their remarks to determine a customized coaching module for the leaders.

Additionally, the leaders can access online dashboards and view a comparison of their management against their peers. It will help them understand the effectiveness of their methods and how to improve.

Administrative Tasks

AI-based software can automate repetitive, administrative tasks. It can play a role in HR strategy, employee management, analysis of company policies and practices, manage payrolls, and more. It can automate the workforce, investigate corporate compliance, and litigation strategies.

From screening to interview scheduling, AI can speed up hiring processes. Additionally, it can also allocate office space and equipment allowing HR staff to direct their time to more valuable tasks.

Smart chatbots are another AI-based technology that can help in HR’s decision-making. It can relieve the HR staff of relaying company-related information to employees, simultaneously providing them with an overall view of the organization. With proper algorithms, AI-enabled systems can give prompt responses to employees’ queries, doubts, and manage the submission and processing of leave forms.

Wrapping Up!

Artificial intelligence requires a lot of data to work efficiently for which it needs proper storage and management. Companies would need extra personnel to operate and maintain the advanced software. Additionally, with the rising preference of SaaS solutions, the low datasets for AI will also pose difficulty in the worldwide adaptation of the technology.

The ideal strategy to employ AI in HR management would be to use AI software to analyze the data collected and leave the decision-making to the human staff. Before implementing AI within HR operations, examine the areas where AI could be useful. If the primary reason is to improve the overall employee experience, it could increase productivity and decrease operational costs.

The post The Impact of AI in Human Resource Decision-Making Processes appeared first on Artificial Intelligence.

Data science can be applied to the hiring process to help human resources work smarter — and be more successful in finding those elusive candidates.

Today’s unemployment rate in the U.S. stands at 3.9 per cent. Talent managers, recruiters, and human resource professionals understand that the realities of the current labour market require using every available tool to fill the seats on the bus. One tool these professional career placement experts didn’t have in the past is data science. Data science can be applied to the hiring process to help human resources work smarter — and be more successful in finding those elusive candidates. Here is how HR and data science can team up to grow your business.

 Solving the employment problem with data science

Finding the right fit for the job when the best candidates are probably already employed is the current challenge facing talent teams. In this difficult environment, recruiters and talent acquisition managers must find new ways to gain a competitive edge. Data science can help.

According to SHRM, 47 per cent of HR leaders cite employee retention and turnover as their top workforce management challenge, followed by recruitment and corporate culture management. Furthermore, Allegis Group found that 83 per cent of employers believe attracting and retaining talent is a growing challenge. Data science can help relieve these problems for HR departments.

Data science is an exercise in analytics made actionable; it’s a way to look at the “what” and “whys” of the current processes to determine what activities are working and what should be discarded. It can replace manual processes with computer-aided efficiencies, allowing human talent teams to focus on one-on-one candidate screens.

To do this, of course, HR managers must have a way of consistently tracking the activities of their recruiting team. Most enterprise organisations have applicant tracking systems, but even the data from a simple Excel spreadsheet can yield actionable insight.

Once this data is captured it can be analysed in the following ways:

• To look for candidate profiles based on prior hiring trends. Start by reviewing data on current employees that have been successfully hired for similar roles. Once this data is collated, the hiring manager can create a portrait of the “perfect candidate” based on real metrics of past successful hires.
• To understand how much the hiring process is really costing the company. Data science can be used to create budgets and cost estimates tied to talent acquisition. Cost per hire, cost by department, onboarding costs, and certainly, the cost of failing to retain current employees can all be calculated by using data. Data science can help predict how many resumes it will take for a particular role and the candidate-to-employee conversion ratio. HR can be a numbers game; data science can help managers make sense of the metrics.
• To craft better job descriptions and advertisements for job boards and match them to the venue where they had the best response in prior years. Data science can help cull resumes by looking at keywords, then compare applicants to that “perfect candidate” persona the team developed.

Another area where data science can help is through employee retention. Using predictive models, data science can predict when an employee might potentially leave so that management can take steps to keep that employee happy. According to Kronos, 46 per cent of HR leaders say employee burnout is responsible for up to half of their annual workforce turnover. Data can track employee’s work hours so they understand who is working too many late nights and are at risk for burning out. Management can then give that person relief in their workload or days off to make sure they stay happy.

Using data modelling and predictive analysis, data science can be used to accurately project how long it will take to fill a particular role. This forecasting can affect every department, from sales to finance. It can help companies better plan for their future talent needs while helping forecast costs associated with filling these roles.

Why isn’t everyone using data

Here’s the rub; Harvard Business Review says the majority of companies are failing to harness the power of data science to improve hiring. But using these tools requires companies to reimagine a human process that has evolved over the years. Change can be difficult. Also, there is a reluctance to let software take over a very human-driven process.

However, we know that data science helps HR teams find the best match in the least amount of time possible. While no one is saying that data analytics will replace human gut instinct in the hiring process, data science is one tool to help talent acquisition managers actually find talent — a needle-in-the-haystack process in today’s job market.

For example, it’s always been difficult and time-consuming to wade through all the applications received from candidates. Data science tools can help teams cut out some of this busy work by running analytics and culling resumes that don’t match pre-defined job specifications. With data analytics and a little machine learning, the hiring process can be faster and more accurate. It is in this way that data science can help human resource hiring teams find the right people and match them to the jobs that fit their skills more quickly than manual processes.

Data science can help managers glean critical insight into what techniques have worked in the past, and which didn’t. It’s the closest thing to a crystal ball that recruiting departments have today and these tools have been proven to help streamline workflows and improve processes.

The Future Workplace found that 97 per cent of HR leaders are planning to increase their investment in recruiting technology by the year 2020, including nearly a quarter (22 per cent) who anticipate a 30-50 per cent increase in spending. Many recruiting platforms use data to find and fit the best candidate, so we can expect this technology to grow dramatically in the coming years.

Let’s face it; talent has never been so critical to the success of a business, but there’s never been such a shortage of talent to go around. That’s why talent managers must collaborate with intelligent data science tools to help them meet the challenges of today’s shrinking labour pool. Without data science, human resource managers will run the risk of falling behind.

The post How to use data science to grow and manage your team appeared first on Artificial Intelligence.

Reskilling is the buzzword in the IT sector.

With the sector seeing huge churn due to automation and protectionism in the western markets, industry lobby group Nasscom’s president R Chandrashekhar told employees in May: Re-skill or perish.

Yes, that’s true. The sector is seeing layoffs and voluntary severances. Companies’ hiring is on the decline. One estimate even puts the likely job loss at a whopping 2 lakh over the next three years.

And in that, the sector is class agnostic. Freshers, middle management or the directors and senior management, as is the case of Cognizant, opt for voluntary separation packages which most IT firms offer employees.

Human Resource (HR) professionals in the information technology services companies sometimes seem to be using cruel means to lay off employees, as was evident from the leaked telephonic conversation between a IT professional in Tech Mahindra and an HR executive.

Clearly, Chandrashekhar’s advice for the IT staff is bang on.

Getty Images

Typically retrenchment around automation means the company is in a consolidation mode whereby talent with specific skills are given importance. “Those who lost their jobs due to lack of skills may not be absorbed back by the same companies as they will now have to prove their domain expertise again through work experience. A good option for such employees would be seek jobs in product/ internet, SaaS start-ups and global in-house centers (GICs) or become freelance consultants,” says Francis Padamadan, Country Director, KellyOCG India, a talent management solutions provider. Or go in for re-skilling.

According to a survey, Skill acquisition for the Digital Age by Simplilearn, artificial intelligence, machine learning, big data analytics and mobile and software development will be the top technology areas where the need for re-skilling will be the highest. The availability of online courses and certifications has increased exponentially in recent times. Organisations choose them for accessibility of self-paced learning, ease in integration into Learning & Development strategy and availability of updated learning content.

Firstpost spoke to experts in the field to find out what is happening in the re-skilling arena and determine its landscape. Here’s what we found out.

K Nageswara Rao, vice-president, India Technology Center, Unisys, says that the country will need 700 million skilled workforce by 2022 to meet the demands of a growing economy. An important area that has already seen blistering growth is Cyber security. Rao says for security professionals, the median salary packages are already 9 percent higher than other IT professionals, according to Job Market Intelligence. The overall demand for security professionals is expected to reach nearly 6 million jobs in the next two years, making it one of the hottest skills to watch out for in the near future.

Robotics, Internet of Things, blockchain and Xaas (Anything-as-a-Service) are the other areas where demand will shoot up, according to Rao.

While the industry is taking a generational leap in training freshers in new generation technologies along with foundational technologies, the employee segment in the 3-15 year experience bracket is the main target for re-skilling, according to Arun Rajamani, country head, Pluralsight. Technology roles have also evolved today to becoming more multi-dimensional. A web developer today is expected to have expertise in 3-4 different skill areas like UX design, psychology, angular, full stack development. So the re-skilling has to focus on skill analytics to determine what the clusters of skills are today and how learning plans can be tailored to get the employee to a target skill level.

Digital skills are defined differently by companies. Rajamani says there are basically two forms of digital skills: 1) Digital experience-related skills – these skills revolve around designing and implementing digital customer experiences for clients; and 2) digital infrastructure-related skills – these skills can be bucketed into 5 categories linked to modernizing legacy IT infrastructure and IT processes – automation, cloud, devOps, cyber security and data analytics.

For Coursera, the world’s largest open online education i.e. MOOC provider, India is one of its fastest-growing markets and second-largest both in terms of learners and revenue (only after the US). The Coursera platform has over 2 million registered learners in India out of a total of 25 million globally. “We onboard close to 60,000 learners in India every month. We also are already seeing India take a lead in adoption of our enterprise platform that allows companies to partner with us on employee training and development,” said Nikhil Sinha, Chief Business Officer.

The most active learners for Coursera in India are young professionals in their 20s and 30s wanting to gain technical skills. Nearly half of enrollments are in technology domains such as computer science and data science. Since not all students with a job in hand can take time out for studies on a daily basis, Coursera is building a learning platform that makes it as easy as possible for people to fit learning into their busy schedules. For example, you can watch video lectures on your commute, submit assignments on your phone, and get immediate feedback on your code with their new in-browser coding feature.

Udacity, another online portal, found that the maximum demand for online courses in India is from Bangalore closely followed by Delhi, Mumbai, Hyderabad, Pune and Chennai. Ishan Gupta, MD, Udacity India, said Bangalore contributes the most to advanced skills like deep learning, self-driving cars and artificial intelligence. Delhi wants to learn more of artificial intelligence followed by machine learning and data analyst skills. Mumbai, on the other hand, is looking at machine learning, android and web development. Hyderabad wants to learn deep learning, data analysis and artificial intelligence. Chennai wants to learn data analysis, deep learning and android, while Pune is witnessing maximum search demand for deep learning, followed by android and artificial intelligence.

If you can think/predict what the customer will need that he/she does not know, rest assured you can find the skill — design thinking, the in-demand skill, will ensure you have a job that most companies are seeking. “Companies will hire design thinkers as they can predict what the consumer does not know and hence charge for the product/service from their clients,” says Ashwin Damera, Executive Director, Emeritus Institute of Management, Singapore.

Design thinking is a mindset. IT firms are trying to move up the curve. Higher-end services that companies can charge more is to provide value and for that you need to know that end-customers needs. For example, to provide value services to banking customers is to find out what the bank’s customer needs are in that country the banking client is based. Latent needs come from a design thinking philosophy where you observe customer data, patterns and provide a solution that the customer does not know. Idea in design thinking is to provide agile product creation or solutions.

“We have a popular course called design thinking by MIT which is taught by a professor whose students created Airbnb. Similarly, in a cloud-based model if you can provide the solution to a problem that does not exist then that is what you charge for,” said Damera.

Infosys’s new offering Aikido, formulated by CEO Vishal Sikka, focusses on design thinking, platforms and knowledge-based IT as part of its efforts to return to industry-leading growth numbers. “…Each of these by themselves help enterprises along a great new path, each of these helps bring together and tie together a lot of Infosys services we offer to clients today and together the three of these become even more powerful than the three individually by themselves,” Sikka had said while announcing Aikido.

Everything is changing in the once-buoyant and sunshine IT sector. To be relevant, constantly upgrading one’s skills is the only way to stay aboard.

The post From artificial intelligence to design thinking: How reskilling is changing Indian IT landscape appeared first on Artificial Intelligence.