Solving the Job Application Black Hole with Chatbots

Written by Bailey Newlan, Content & Growth Marketer at Wade & Wendy.

ATS Black Hole

Applicant Tracking Systems (ATS) are not inherently bad — for the hiring manager. They are critical to managing massive amounts of resumes and establishing an efficient workflow. However, the candidate experience suffers. A survey conducted by CareerBuilder found that 52% of employers responded to less than 50% of candidate applications. With such little communication, candidates are left frustrated and unsure of where they stand. This is referred to as the “ATS Black Hole.”

By incorporating Conversational Intelligence into the existing process, better engagement, better communication and transparency can be realized.

Conversation with Wendy in Facebook Messenger screenshot
This is how a conversation with Wendy, our conversationally intelligent chatbot, begins in Facebook Messenger.

Here’s How the ATS Fails Candidates

When an individual applies for a job, his or her resume is sent into a company’s ATS. Through matching algorithms and keyword extraction, a shortlist of candidates is generated for the hiring manager to review. These algorithms fail to take into account spelling errors and deviances in word choice (explained in more depth here). Because matches are generated exclusively through one-dimensional data, hiring managers’ understanding of candidates is distorted.

The result: Very few qualified candidates make it past the ATS and to the interview stage.

This problem is further compounded by the ease of the application process. In response to mounting candidate frustrations with lengthy applications, many employers now offer “Quick Apply” or “1-Click Apply” options. While this significantly lowers friction for applicants on the front-end, they are actually worse off in the long run. Employers are receiving more and more resumes, but, due to the simplicity of new application processes, they now have less data from which to draw conclusions.

In a world where candidates expect engagement and transparency, they are getting less and less.

On average, a single corporate job opening receives 250 applications. With an influx of resumes to review and no uptick in resources with which to process them, hiring managers cannot possibly respond to each individual applicant. In fact, of those 250 applications, only four to six will be called in to interview. As a result, most candidates receive zero communication, experiencing what has ubiquitously been labeled the “ATS Black Hole.”

Here’s Where Conversational Intelligence Comes In

Conversational Intelligence transforms the application process from something static to dynamic. At Wade & Wendy, we believe artificial intelligence is at its best when used conversationally. Our two chatbot personalities are built with this in mind. By creating a space in which conversations can occur, chatbots have the power to drastically improve the application experience.

Chatbots can engage every single applicant at any point in time.

Immediately following submission of their resume, candidates are directed to have a conversation with a chatbot through either text or Facebook Messenger. This introduction allows for a much friendlier first point of contact. Rather than receiving a “Thank You for Your Application” message from a “do not reply” email address, you meet Wendy. Here, candidates can inquire further about the company and the job itself.

At Wade & Wendy, we have designed each of our chatbot personalities to be conversational and inviting. Conversational Intelligence has the power to make a notoriously stressful and automated process fun and distinctly personable, especially when emojis are involved 🙌.

Chatbots give every candidate an equal chance at landing an interview.

Chatbots provide context and depth around the static data gleaned from the ATS. Because every candidate can be engaged via chatbot, algorithm mismatches, various misspellings and differences in keywords no longer hinder a strong candidate from getting in front of the hiring manager. Chatbots, like Wendy, allow candidates to provide context to their resume; they have an opportunity to explain properly a successful project that would otherwise be summed up in a mere bullet point.

Candidate Chats with Wendy
Here, the candidate is able to give Wendy more details about her experience with open source projects.

A candidate’s experiences and skills cannot always be properly communicated in a resume. On top of that, the ATS responsible for gauging a candidate’s ability to do a job utilizes flawed algorithms and thus provides flawed recommendations. Conversational Intelligence allows candidates to best communicate who they are and what they can do, while also overcoming algorithm flaws within the ATS.

About the Author:

Bailey Newlan, Content & Growth Marketer at Wade & Wendy

Bailey Newlan is the Content & Growth Marketer at Wade & Wendy, a New York City-based startup on a mission to make hiring more human. Wade & Wendy’s artificially intelligent chatbot personalities bring clarity and simplicity to the hiring process. Wade is an always-on career guide for job seekers, while Wendy assists hiring managers throughout the recruitment process. To connect, reach out to Bailey via LinkedIn, Twitter or Medium and don’t forget to join the beta list.✌️


If you want to share this article the reference to Bailey NewlanWade & Wendy and The HR Tech Weekly® is obligatory.

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How Machine Learning is Revolutionizing Digital Enterprises

How Machine Learning is Revolutionizing Digital Enterprises

According to the prediction of IDC Futurescapes, two-thirds of Global 2000 Enterprises CEOs will center their corporate strategy on digital transformation. A major part of the strategy should include machine-learning (ML) solutions. The implementation of these solutions could change how these enterprises view customer value and internal operating model today.

If you want to stay ahead of the game, then you cannot afford to wait for that to happen. Your digital business needs to move towards automation now while ML technology is developing rapidly. Machine learning algorithms learn from huge amounts of structured and unstructured data, e.g. text, images, video, voice, body language, and facial expressions. By that it opens a new dimension for machines with limitless applications from healthcare systems to video games and self-driving cars.

In short, ML will connect intelligently people, business and things. It will enable completely new interaction scenarios between customers and companies and eventually allow a true intelligent enterprise. To realize the applications that are possible due to ML fully, we need to build a modern business environment. However, this will only be achieved, if businesses can understand the distinction between Artificial Intelligence (AI) and Machine Learning (ML).

Understanding the Distinction Between ML and AI

Machines that could fully replicate or even surpass all humans’ cognitive functions are still a dream of Science Fiction stories, Machine Learning is the reality behind AI and it is available today. ML mimics how the human cognitive system functions and solves problems based on that functioning. It can analyze data that is beyond human capabilities. The ML data analysis is based on the patterns it can identity in Big Data. It can make UX immersive and efficient while also being able to respond with human-like emotions. By learning from data instead of being programmed explicitly, computers can now deal with challenges previously reserved to the human. They now beat us at games like chess, go and poker; they can recognize images more accurately, transcribe spoken words more precisely, and are capable of translating over a hundred languages.

ML Technology and Applications for Life and Business

In order for us to comprehend the range of applications that will be possible due to ML technology, let us look at some examples available currently:

  • Amazon Echo, Google Home:
  • Digital assistants: Apple’s Siri, SAP’s upcoming Copilot

Both types of devices provide an interactive experience for the users due to Natural Language Processing technology. With ML in the picture, this experience might be taken to new heights, i.e., chatbots. Initially, they will be a part of the apps mentioned above but it is predicted that they could make text and GUI interfaces obsolete!

ML technology does not force the user to learn how it can be operated but adapts itself to the user. It will become much more than give birth to a new interface; it will lead to the formation of enterprise AI.

The limitless ways in which ML can be applied include provision of completely customized healthcare. It will be able to anticipate the customer’s needs due to their shopping history. It can make it possible for the HR to recruit the right candidate for each job without bias and automate payments in the finance sector.

Unprecedented Business Benefits via ML

Business processes will become automated and evolve with the increasing use of ML due to the benefits associated with it. Customers can use the technology to pick the best results and thus, reach decisions faster. As the business environment changes, so will the advanced machines as they constantly update and adapt themselves. ML will also help businesses arrive on innovations and keep growing by providing the right kind of business products/services and basing their decisions on a business model with the best outcome.

ML technology is able to develop insights that are beyond human capabilities based on the patterns it derives from Big Data. As a result, businesses would be able to act at the right time and take advantage of sales opportunities, converting them into closed deals. With the whole operation optimized and automated, the rate at which a business grows will accelerate. Moreover, the business process will achieve more at a lesser cost. ML will lead businesses into environs with minimal human error and stronger cybersecurity.

ML Use Cases

The following three examples show how ML can be applied to an enterprise model that utilizes Natural Language Processing:

  • Support Ticket Classification

Consider the case where tickets from different media channels (email, social websites etc.) needs to be forwarded to the right specialist for the topic. The immense volume of support tickets makes the task lengthy and time consuming. If ML were to be applied to this situation, it could be useful in classifying them into different categories.

API and micro-service integration could mean that the ticket could be automatically categorized. If the number of correctly categorized tickets is high enough, a ML algorithm can route the ticket directly to the next service agent without the need of a support agent.

  •  Recruiting

The job of prioritizing incoming applications for positions with hundreds of applicants can also be slow and time consuming. If automated via ML, the HR can let the machine predict candidate suitability by providing it with a job description and the candidate’s CV. A definite pattern would be visible in the CVs of suitable candidates, such as the right length, experience, absence of typos, etc. Automation of the process will be more likely to provide the right candidate for the job.

  • Marketing 

ML will help build logo and brand recognition for businesses in the following two ways:

  1. With the use of a brand intelligence app, the identification of logos in event sponsorship videos or TV can lead to marketing ROI calculations.
  2. Stay up to date on the customer’s transactions and use that behavior to predict how to maintain customer loyalty and find the best way to retain them.

How Enterprises Can Get Started Implementing Machine Learning

Businesses can step into the new age of ML and begin implementing the technique by letting the machines use Big Data derived from various sources, e.g. images, documents, IoT devices etc to learn. While these machines can automate lengthy and repetitive tasks, they can also be used to predict the outcome for new data. The first step in implementation of ML for a business should be to educate themselves about its nature and the range of its applications. A free openSAP course can help make that possible.

Another step that can bring a business closer to ML implementation is data preparation in complex landscapes. The era of information silos is over and there is an imperative need for businesses to gather data from various sources, such as customers, partners, and suppliers. The algorithms must then be provided open access to that data so they can learn and evolve. The Chief Data Officer of the company can oversee the ML integration process.

To start with completely new use cases for Machine Learning is not easy and requires a good understanding of the subject and having the right level of expertise in the company. A better starting point for many companies would be to rely on ML solutions already integrated into standard software. By that it will connect seamless with the existing business process and immediately start to create value.

Lastly, businesses should start gathering the components necessary for building AI products. Among the requirements would be a cloud platform capable of handling high data volume that is derived from multiple sources. The relevant people are as important to this step as are the technology and processes. After all, they would be the ones who will be testing the latest digital and ML technologies.

If you want more information on SAP Machine Learning, then go here to subscribe to the webinar on Enabling the intelligent Enterprise with Machine Learning.

The presenters include Dr. Markus Noga: VP Machine Learning Innovation Center Network, SAP SE. You can follow him on Twitter. Ronald van Loon is the other presenter for the webinar. Mr. van Loon is counted among the Top 10 Big Data expert and is an IoT Influencer. You can also follow him on Twitter.


Source: How Machine Learning is Revolutionizing Digital Enterprises | Ronald van Loon | Pulse | LinkedIn

Most popular HR software: How location and business size affects app choices

Most popular HR software: How location and business size affects app choices

Written by Karen McCandless, GetApp.

HR Employee Management

Once upon a time, the HR market was dominated by a few big name players. The likes of ADP, Oracle, or SAP were the main choices available to businesses, large and small. This has all changed, with cloud HR solutions becoming mainstream, and a raft of new entrants shaking up the status quo.

To find out more about exactly what criteria small to medium businesses in different countries are using to select their HR solutions, we turned to data from GetApp users to find out which were the most popular apps.

We found that businesses of 1-50 employees favor cloud-based HR software from startups like themselves, that are new to the market but that promise innovation, and simple pricing plans – often with freemium option.

There is some continuity with businesses of 51-500 employees, with these size of businesses still choosing smaller HR outfits, but ones that have more of a presence in the market, such as Jobvite and Greenhouse.

As businesses grow, it makes sense that they would favor companies that cater towards that end of the market, and that is exactly what we saw with GetApp users of 501-1000 employees. Another interesting trend was this was the first learning management systems featured among the most used apps.

In terms of country HR software usage, British and Canadian users favored apps either based in their own country, or that had a strong presence there.

HR software usage trends

With this in mind, we at GetApp – a startup ourselves with an agile, cloud-based HR system – wanted to find out just whether this would hold true for for our users – whether small businesses in different countries are really choosing these new entrants to the market over the big-name brands.

To test this theory, we used data from the “I Use This” feature on the GetApp website (screenshot below) to find out what is the most popular HR software among our users. (For a detailed methodology on the way that we collected and analyzed this data, see the methodology section at the bottom of the article.)

The approach we took to this was two-pronged: we looked at apps used by different business sizes – varying from solopreneurs to companies of up to 1000 employees – and also at software used in different countries (the U.S., UK, and Canada) to see what insights we could glean.

We grouped together HR apps of all flavors – from talent management, to scheduling, to performance management, and more – to analyze the approach that companies are currently taking towards managing their human resources.

Key Findings:

  • Businesses with 1-50 employees favor newer, more agile HR apps, with lower pricing points
  • Companies with 51 employees and more look for more well-known HR names, combined with innovation
  • Businesses are still adopting point solutions for areas such as recruitment, rather than all-in-one HR apps
  • Adoption of learning management systems is much higher in companies with more than 500 employees
  • Outside of the U.S., companies favor local HR solutions.

Most popular HR software by business size

When splitting HR app usage according to business size, what became apparent was that there is no clear market leader for companies of up-to 1,000 employees. Each size of business had its own preferences, with no runaway leader in any category. This differs from other industries such as accounting, where a few big-name vendors dominate.

There is also no mention of the legacy HR heavyweights that were initially built on premise, such as Oracle, ADP, SuccessFactors (now part of SAP) – or newer cloud-based market leaders such as Workday. Halogen TalentSpace is the only HR app popular among GetApp users to feature in analyst firm Gartner’s Magic Quadrants for HCM or Talent Management, which are focused on the enterprise market. Businesses across the board (up to 1,000 employees) are favoring newer, native cloud software for the HR market.

Where we can see a trend start to emerge is in the type of HR apps used by businesses of less than 50 employees, compared to companies of 51-500, and then again with organizations of 501-1000 employees. We’ll dive into these trends in more depth now.

Businesses of 1-50 employees: startups for startups

When looking at the apps used by businesses of 1-10 employees and 11-50 employees, the most used HR software is consistent, with Zoho Recruit, Breezy HR (formerly Nimble HR), Workable, and Crelate Talent all featuring in the top five for both company sizes.

Delving more deeply to find out why this may be, we noticed that all these HR apps all recent entrants to the market. Breezy HR was founded in 2014, Workable in 2012, Crelate Talent in 2012, and while Zoho as a company was founded in 1996, Zoho Recruit was a more recent addition in November 2009.

All of these apps are natively built for the cloud, cater to small businesses, and market themselves as relatively straightforward and simple software.

Pricing options

Another similarity with the most popular HR software for businesses of 1-10 and 11-50 is pricing. Several solutions offer a free option with limited features, making them useful for startups and small businesses with budget constraints.

In terms of Zoho Recruit pricing, it currently (as of April 2017) offers a free plan for one recruiter with basic ATS functionality, such as scheduling interviews. Even for the most expensive price plan, it’s only $50 per recruiter per month. Zoho can also be seen as a safe pair of hands, with its long company history and large suite of products.

Breezy HR keeps its pricing plans simple, with all of them including unlimited users and candidates. The plans differ according to the number of active jobs. As of April 2017, for one active job, the HR app is free.

While Crelate Talent doesn’t offer free options, its pricing is affordable for small businesses.

Hiring platform Recruitee – one of the most used apps by businesses of 11-50 employees- doesn’t offer a free version, but has competitive pricing options covering the varying needs of different company sizes. It’s still a very new company – set up in mid 2015 – but has already been garnering a lot of positive coverage in publications such as Entreprenuer and Inc.

Workable doesn’t cater solely for this end of the market, but its simple tools, mobile-first approach, and raft of integrations make it an attractive choice for small businesses.

All-in-one HR

Zenefits is the only piece of software on the list (third most popular HR app by businesses of 1-10 employees) that isn’t strictly targeted at simplifying recruiting or talent management. While it originally focused on benefits management, it has since expanded to cover onboarding and employee scheduling. Despite experiencing several scandals and setbacks in 2016, Zenefits emerged as the most well-funded HR tech company in 2016.

Key takeaway: Businesses with less than 50 employees broadly go for the same kind of HR apps that are cloud-based, have affordable pricing plans (often with a free version), and are relatively new to the market.

Businesses of 51-500 employees: innovative new entrants

As the business size grows, the trend swings towards HR software that, while more established than the above startups, is still making waves in the industry due to its innovation and high-profile customers. The most popular HR software for this company size also caters for a wider range of business sizes than the favored apps for businesses of 50 and under.

Jobvite and Greenhouse are two applicant tracking and recruitment apps that are popular with companies of between 51 and 1000 employees.

While Greenhouse is a relatively new entrant to the market (founded in 2012), thanks to a raft of positive media coverage and some high profile customers (Airbnb, Evernote, and Pinterest), it has already made a name for itself in the recruitment industry. Part of Greenhouse’s strategy is based around having an open platform that easily integrates with any other tool you might use for recruitment.

Analytics-driven recruiting platform Jobvite has been around longer (since 2006), and is aimed at both small businesses and enterprises. The app also boasts an impressive client roster, including LinkedIn, Spotify, Etsy, and Verifone. Jobvite’s product offering aims to cover everything from sourcing to hiring to onboarding.

The company continues to innovate by partnering and adding new features, such as integrating with Accurate Background services to allow companies to carry out employment background checks, drug testing and verification services from within Jobvite.

Workable is the one constant across businesses all the way up to 500 employees, as it is another app that caters for a wide range of business sizes.

HR suite adoption

One trend that we see solely with businesses between 51 and 200 employees is a higher adoption of all-in-one HR suites, with BambooHR and Namely both ranking in the top five.

This contrasts with the higher adoption of recruitment and talent management suites among smaller businesses, and a focus on learning management systems in businesses of more than 500 employees (more on that later).

Key takeaway: Businesses of 51-500 look for software that caters for a wide range of business sizes, and that may already have well-known clients. They also put more emphasis on all-in-one HR systems.

Businesses of 501-1000 employees: household names

The trend we see as company size increases is to go for software from more established companies that have been on the market for longer. One example of this is Bullhorn, which is favored by companies of 500 employees and over. Bullhorn originally made a CRM for staffing and recruiting firms, before moving into applicant tracking systems.

Further evidence of this is Halogen TalentSpace, which is the fourth most popular app among companies of 201-500 employees. This software, which came to market in 1996, is regularly named as a visionary in Gartner’s Magic Quadrant for talent management. Testament to its success, it was acquired by Saba in early 2017.

Another data-driven recruitment app that is popular with larger businesses is JazzHR (fourth most popular among businesses of 501-1000 employees). Formerly known as The Resumator, it positions itself as a scalable recruitment system, suitable for small businesses but also applicable for growing companies.

Emergence of LMS

Learning management system software makes its first appearance in the most used apps among companies of 501-1000. Mindflash and Accord LMS’s appearance on the list at this points suggests that smaller businesses may be slower in their adoption of LMS.

Key takeaway: Businesses of 501 employees and up tend to favor more well-known and established HR software, and they also start recognizing the importance of learning management systems.

Most used HR software by country

Using data from the U.S., UK, and Canada across all businesses from 1-1000 employees, we found that Breezy HR and Zoho Recruit were particularly popular among GetApp users in all three of these countries.

Zoho Recruit was a favorite in both the U.S. and U.K. (even placing just out of the top three in Canada), while Breezy HR was popular among users from both the U.S. and Canada.

America first

Given the wide range of choices for apps headquartered in the U.S., it was interesting to see India-based Zoho Recruit there in addition to U.S.-based Breezy HR and Crelate Talent.

Canada’s choices

Looking at the choices for Canada, Toronto-based hiring solution Fitzii is popular among businesses in this country, suggesting that there is a preference for local software providers in the HR market, or at least those that have a strong presence there.

Further confirming this, Bullhorn is the second most popular HR software in Canada. While it may not be based in Canada, it has a strong presence in the country, through its partnership with Workopolis, which is Canada’s leading career website. It also already provides applicant tracking functionality to many leading firms based there, and has an office in Vancouver.

UK-based software

In the UK, aside from Zoho Recruit, Workable and Calamari leave management software are the most popular HR software in the country. While neither of these companies are British, both were founded in Europe and have a strong presence in London.

Workable was founded in Athens, but opened an office in London shortly after, before expanding to New York, Boston, and now San Francisco.

However, a plethora of British-based HR software companies such as CakeHR, CIPHR, WeThrive, PARIM, and Findmyshift just missed the top three position, further highlighting the preference for local companies in the market.

Key takeaway: In markets outside of the U.S., countries are showing a strong preference for local software to help manage recruiting and HR needs.

Conclusion

Our findings from analyzing data from GetApp users indicated that the original hypothesis was true: that small to medium businesses in the HR space are opting for new entrants to the market over the more-established brand names, and that they are choosing apps built for the cloud.

Our data also indicated that these companies prefer HR apps based in their own country, or that have a very strong presence there.

If, after reading this report, you’d like to invest in a cloud-based HR app for your business size or from your country, we can help. Here are the next steps.

From our list of HR apps, you can filter by country:

You can also filter by business size:

For a full list of the most popular HR software in these categories, or to reuse any of the charts above, please contact karen@getapp.com.

Methodology

To put together this report, we analyzed data from signed in GetApp users that had selected the “I Use This” option for a particular app on the site. We counted the number of individual users that had selected these apps and segmented according to business size and country. The sample size for each segment differed and we used absolute numbers on our graphs to represent the most used. We then looked into the three most used apps per country, and five most used per business size.


Source: Most popular HR software: How location and business size affects app choices (GetApp report)

How Conversation Bridges the Gap Between Job Description and Job Seeker

How Conversation Bridges the Gap Between Job Description and Job Seeker

Written by Bailey Newlan, Content & Growth Marketer at Wade & Wendy.

From Ambiguity to Clarity, Through Conversation

Resumes, social profiles and job boards are two-dimensional tools used to present four-dimensional individuals. Each is incapable of communicating your whole story. You are more than a string of keywords and you are more than the templated “Experience” section on LinkedIn.

When people are boxed into these two-dimensional frames, valuable context is lost, leading to a series of frustrating interactions between job seeker and hiring manager. On average, it takes 52 days to fill an open position — a drawn out process wrought with miscommunication and missed opportunities.

How do you communicate the abstract in one bullet or less?

For any given bullet point on a resume, there are a hundred ways to say it. For example:

  • Used Java to build features for a platform
  • Supported a platform with Java
  • Chose Java to build a platform on

Each effectively showcases experience with Java. But, what is a job seeker’s relationship to Java and how does that exhibit what they can really do? Yes, the Java requirement is met, but what kind of person is best-suited for the role? The keyword “Java” falls short of showing how a job applicant and the job itself fit together. This form of static representation is fundamentally limited due to the job seeker’s inability to provide context around their skills, passions, motivations and career goals.

How can you land your dream job when using vague language to apply to an equally vague job description?

Job descriptions are two-dimensional and fall short of providing job seekers clarity around a position. To cast a wide net, job descriptions are often written with vague requirements — carefully crafted with generic keywords, so as not to discourage anyone from applying. Naturally, this results in unclear expectations. Another issue arises when goals and needs shift, yet the job description remains the same. Unfortunately, this kind of moving target is all too common.

This widening chasm between what a job description says and what hiring managers are really looking for in an applicant causes job seekers to create vague resumes and profiles to ensure they will not be overlooked.

By summing oneself up in a string of bullet points, laden with just the right keywords, context is lost and true understanding is clouded. Having to position yourself to meet a set of vague requirements, neutralizes the magic of you.

What can we do about this?

On both sides of the hiring process, there are fundamental flaws. Only by bridging the information gap that presently exists between hiring managers and job seekers, can we:

  1. Facilitate better understanding of a job outside of its description
  2. Better understand a job seeker outside of his or her resume

This is best achieved through conversation. Flowing dialogue and follow-up questions are effective mechanisms for drilling down and extracting the “Why” and the “Who are you really?” Going past the resume and job description allows both job seekers and hiring managers to make better decisions. We must go beyond the two-dimensional modes of expression. We must find clarity. We need better conversations.

About the Author:

Bailey Newlan, Content & Growth Marketer at Wade & Wendy

Bailey Newlan is the Content & Growth Marketer at Wade & Wendy, a New York City-based startup on a mission to make hiring more human. Wade & Wendy’s artificially intelligent chatbot personalities bring clarity and simplicity to the hiring process. Wade is an always-on career guide for job seekers, while Wendy assists hiring managers throughout the recruitment process. To connect, reach out to Bailey via LinkedIn, Twitter or Medium.


If you want to share this article the reference to Bailey NewlanWade & Wendy and The HR Tech Weekly® is obligatory.

Is AI Really A Threat To Jobs?

Artificial Intelligence | The HR Tech Weekly®

Has the future obliteration of jobs by automation been over-exaggerated? At the end of last year Bank of England Governor Mark Carney warned that up to 50% of UK jobs could be wiped out by automation. A recent report suggests that so far the AI-jobs apocalypse has yet to materialise.

Recent research from the Chartered Institute of Ergonomics and Human Factors (CIEHF) together with CV-Library found that two thirds of businesses had not yet witnessed job losses due to automation. Over a third believed that automation had actually increased the number of jobs available.

This is a view broadly supported by Deloitte. In 2015, it highlighted the benefits of automation and its ability to create better quality jobs by removing tedious and dull work which increases the potential for errors due to boredom and distractions. Its research also noted that as a result of automation:

  • 3.5 million low risk jobs have been created since 2001, compared to 800,000 high risk jobs lost.
  • Each new low-risk job pays a salary £10,000 higher than the high risk job it replaced.

This does not alleviate concerns over automation. The CIPD’s Employee Outlook Survey also notes that nearly a quarter of employees are concerned that their job – or parts of it – may be automated within the next five years. Similarly, PwC’s UK Economic Outlook predicts that 30% jobs in the UK are at risk from automation by the early 2030s. Like Deloitte, however, it notes that the nature of available jobs will change. Sectors at highest risk of job losses through automation include transport, manufacturing, and wholesale and retail. Education and health and social work and education are at the lowest risk of being replaced.

Ongoing resistance to AI

The CIEHF/CV Library survey reports a ‘resistance’ among employees to automation as employers are failing to communicate its benefits effectively and HR remains one of the most reluctant to positively embrace automation within talent management strategies. Deloitte’s 2017 Human Capital Trends Survey found that progress towards people analytics in the last year remains stubbornly slow. This is perhaps unsurprising as nearly half of recruitment professionals are still not using applicant tracking software in hiring processes.

HR must first acknowledge the advantages of automation in recruitment to communicate its benefits more effectively. In hiring processes, this means the automation of mundane procedures, including personalised e-mails to job applicants, effective, streamlined screening to reduce unconscious bias and insights into key hiring metrics that impact your ability to hire. It also enables hiring teams to create a more effective onboarding processes to improve retention of new hires.

But why is HR so reluctant to embrace technology?

An article in the Harvard Business Review suggests that the resistance to AI is twofold. To accept and take advantage of automation, consumers must trust both in the technology and in the business delivering the innovation. In recruitment that means HR must have confidence in the supplier of recruitment software and its ability to deliver benefits to its hiring process.

The article also highlights three key points which are essential to gaining that confidence:

Cognitive compatibility : In other words, make it easy to understand. The more complex the nature of the technology, the less likely consumers are to trust its ability achieve desired goals. For HR, that goal is to streamline hiring processes to ensure not only faster hiring but a better quality of hire.

Trialability : A trial of potential new technology helps to understand the benefits and reduce any reluctance to embrace technology.

Usability : To encourage buy-in among tech-resistant hiring teams, technology, especially HR software, must be easy to use.

Recruitment software aside, as companies continue to invest in technology it is vital to maintain employee buy-in and foster trust by investing in upskilling employees to equip them to use digital skills in the workplace. The UK faces a significant digital skills crisis in addition to a wider talent shortage but employers are failing to invest in the necessary training to equip employees with vital skills. Training and development is essential for businesses that wish to not only retain but to continue to attract talent to their brand. It will also go some way to overcoming ‘resistance’ to technology in the workplace.

Ethical concerns

Overcoming ethical concerns is an issue that HR must consider in the future.

The EU[1] has proposed the creation of a European agency to provide technical, ethical and regulatory advice on robotics and AI, including the consideration of a minimum income to compensate people replaced by robots and a ‘kill switch’ for malfunctioning AI systems. A similar concern was recently expressed by the International Bar Association which warned that AI could ultimately lead to the introduction of legislation for quotas of human workers in the future[2].

While the debate over the benefits of AI at work continues, there is no doubt about the struggle that employers face to hire and retain qualified candidates. HR software is HR’s first step towards embracing the benefits of automation and creating more effective talent management strategies.

[1] MEPs vote on robots' legal status - and if a kill switch is required

[2] Rise of robotics will upend laws and lead to human job quotas, study says

A version of this article first appeared on Advorto’s website.

 

Benefits Of Working From Home | The HR Tech Weekly®

Benefits Of Working From Home

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Working from home is not an easy walk. It’s different from what other people think about a remote worker. It requires more discipline and responsibility, more self-motivation, self-engagement, and self-control. It gives you less freedom while many think opposite. And finally it may give you more working hours in fact with an early start, later end and less breaks.

So, why a lot, lot of people make their choices for working from home? Why companies tend to hire remote workers? What benefits it gives to both sides? How it is influenced by the economy and technology? What is the best way to organize the remote work both for employers and for employees? A lot of questions…

Gig-economy or on-demand economy and digital technologies give people new exciting opportunities, from one hand, and determine their choices from the other one. Relations with remote and contingent workers and organizations became more contractual, more entrepreneurial, and more like with the third parties before the world of work has changed.

Modern HR technologies allow organizations to keep people engaged, stay connected, let them feel on board and be a part of the team while staying miles away. But it’s harder than just control over the process and results. It requires new hard and soft skills from HR and line managers.

The new infographic from Nucleus gives us an overview on a phenomenon of the remote work as well as some insights about new challenges for managers and workers, and technologies that could help to organize it better.

Nucleus Smart Office Solutions


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3 Ways HR Will Evolve in the Future

3 Ways HR Will Evolve in the Future

Believe it or not, automation is changing our entire lives, the way we live, think and work. As quoted by Mr. Abhijit Bhaduri, author of Digital Tsunami, “Humans resist change, machines don’t.” We are at a age where we no longer can nor should resist change. That said, technology is also massively impacting the HR functions. Most of the traditional support functions of HR, such as payroll, attendance etc. are being automated. Adding to the progression, chatbots are further driving more engagement with its personalized attributes, and is further adding up to redefining the HR role.

Ripples in the Water

One might wonder, will the rapid pace of digitization re-define HR? Of course yes, with millennials making up more than half of the current workforce — and predicted to make up 75 percent by 2020 — HR has to embrace technologies to keep at par with employee and business demands.

The Effect of Big Data

A lot of work in HR used to be related to adherence to compliances and therefore, huge amount of work related to paperworks was involved. But, now things have changed. Online portals and platforms provide HR with all the information that they need. Today’s technology gives HR professionals access to the power of Big Data and changes the way businesses understand their customers, build their own brands and communicate to prospective employees.

One of the boons of Big Data is Predictive Analytics. In big corporations, it is very difficult to keep a track of each employee. Predictive analytics enables HR to understand which employee needs an additional training.

High Up in the Clouds

Another technology which is impacting HR in a big way. Gathering and storing of information has always been a major function of the HR department, and the stack of files not only waste office space but are very difficult to trace as well. Can you even imagine, a millennial, who is always glued to his smartphone will have the patience to go through all the piles of paper?

High Up in the Clouds

Thanks to cloud technology, all of this information can instead be stored in the cloud. No longer does an employee need to tick the boxes while filling up a feedback form which again runs the risk of getting lost. All the employee information like tax documents, payroll, feedback etc can be stored online securely.

Cloud-based systems and Big Data go hand in hand. With Machine Learning emerging steadily, all these data will make a lot of sense few years down the line, it all depends how well can one derive relevant information out of it.

Chat with the Bots

There are some information which are very subjective in nature, like how to fill the Form 19 or file for the income tax returns. It makes no sense if the employee walks up to the HR managers for day-to-day queries or any concerns they might have regarding their pay, leaves, performance etc. To narrow down the gap of communication between the employees and the HR, PeopleStrong recently launched India’s first HR chatbot ‘Jinie’. From a transactional interface with employees to a conversational interface, Jinie the India’s first HR Chatbot will be able to provide the next level of experience to its employees.

In the era of smartphones, this will be a great boost in employee engagement.

These are few of the many ways in which the HR domain will change and adapt itself to digitization. With the burden of a lot of paperwork gone from the shoulders and with new data in hand, HR department will be fully equipped to make the employees life much easier and will add more value in business.


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4 Ways Technology Is Changing Recruiting

4 Ways Technology Is Changing Recruiting

VR

Interest in HR tech has never been higher. According to CB Insights, there were over 350 deals and approximately $1.96B invested in HR tech startups in 2016 alone.

Today’s workplaces are being transformed by technology. HR tech specifically is automating and streamlining manual HR practices to become more efficient, cost-effective, and high-performing.

Here are four promising applications of technology that are helping to solve the biggest challenges in recruiting and hiring.

AI for recruiting

Industry statistics estimate 75 percent of resumes received for a role are screened out. This adds up to the hundreds of hours a recruiter wastes reading unqualified resumes per year.

As one of recruiting’s biggest bottlenecks, resume screening is in dire need of better tools to help recruiters manage their time more effectively.

This is why AI for recruiting is the biggest topic in HR tech right now. AI and recruiting are a natural fit because AI requires a lot of data to learn and large companies often have millions of resumes in their ATS.

Recruiting software that uses artificial intelligence can automate the screening process by learning the experience, skills, and qualifications required for the job and then shortlisting, ranking, and grading new candidates who match the requirements (e.g., from A to D).

This type of AI recruiting software can also be used to source candidates from external databases such as Indeed and CareerBuilder or find previous candidates in your existing ATS database by applying the same learning ability to match candidates to an open req.

By automating the manual processes of resume screening and candidate matching, companies who use AI recruiting software have reduced their screening costs by 75%.

Automation for candidate scheduling and outreach

According to SHRM, the average time to fill is 41 days. With LinkedIn reporting hiring volume is up 11% this year but only 26% of recruiting teams growing in headcount, interest in recruitment automation is only getting get stronger.

Today more than ever, finding top talent will depend on a recruiter’s ability to intelligently automate their workflow.

Recruitment automation can enhance a human recruiter’s capabilities in multiple ways. Low hanging fruit include automating your candidate outreach with tools that allow you to auto-email and auto-text interview requests to candidates your screening tool identifies as good matches (e.g., all candidates graded as an A).

These outreach automation tools help recruiters reduce their time to fill by integrating with major email and calendar providers and automatically finding time slots when the candidate and the interviewer are all free to meet.

VR for job testing and training

Another technology getting a lot of attention is Virtual reality (VR). VR is a realistic simulation of a three-dimensional environment that you control with your body movements.

A survey by Universum found that while 3% of people use VR currently, about 30% think that it will transform their workplace in the next ten years.

The most promising applications for VR in HR are candidate testing and training. Employers can use VR technology to create more realistic job tests to assess a candidate’s skills and personality. For example, a realistic simulation that tests a candidate’s social skills and problem solving abilities when dealing with an unhappy customer.

A survey by Korn Ferry found that 39% of employers state new hires leave within their first year because the role was not what they expected. VR could be an intriguing tool to help reduce employee turnover by provide candidates with a more realistic preview of what a day on the job would look like and get a better sense of the company culture.

The same technology can be used during new hires’ onboarding and training process. High-stakes environments such as hospital trauma bays are already employing VR technology to train residents.  

Wearable tech for engagement and productivity

According to Deloitte, one of 2017’s biggest HR trends is employee engagement. To help improve engagement and productivity, employers are starting to use wearable tech that tracks employees’ behaviors to learn more about how they communicate and interact at work.

Wearable tech such as digital employee badges are being used by companies such as as Microsoft and the Boston Consulting Group to track employees’ physical office movements, who they talk to, and the amount of time they spend talking to others.

These types of wearable tech collects data to provide employers insights to help optimize their physical office spaces, understand their employees’ communication styles, and manage team dynamics. The hope is these insights can help managers identify their employees’ needs and re-organize teams for better collaboration.

In the future, wearable tech may be used in the recruiting process to provide insights into a candidate’s personality and emotions during a pre-screen or interview.

About the Author:

Ji-A Min, Head Data Scientist at Ideal

Ji-A Min is the Head Data Scientist at Ideal, software that uses artificial intelligence (AI) to automate time-consuming, repetitive tasks and quickly move top candidates through the recruiting funnel.

Ideal’s AI can instantly screen and shortlist new candidates, uncover strong past candidates that are a great fit for a new role, and initiate candidate contact – all within your existing ATS. Learn more at Ideal.com.

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What Does Dark Data Mean For HR?

What Does Dark Data Mean For HR?

Dark data is predicted to be one of the emerging tech trends for 2017. As businesses explore more ways to transform talent management processes and slowly move towards analytics, the swathes of information contained in dark data may prove to be the missing piece in the recruitment jigsaw.

Gartner defines dark data as the ‘information assets organisations collect, process and store during regular business activities, but generally fail to use for other purposes’. It is used, inactive information found in unexplored files including e-mails, messages, spreadsheets, pdfs, audio and video files. For many companies this data lies dormant and discarded but the insight it contains may inform and drive future talent management and hiring decisions.

Deloitte’s reportDark analytics: Illuminating opportunities hidden in unstructured data’ highlights the opportunities in dark data but warns that within three years’ time the sheer amount of data available may prove to be unmanageable. Veritas estimates the cost of managing ‘untamed’ data at up to $3.3 trillion per year collectively by 2020.

Dark data in hiring

Used effectively dark data can offer vital insights into talent sourcing and retention patterns. Data that is lost or ‘goes dark’ may disrupt hiring processes. It may be something as simple as the lost CV of a qualified candidate or a missing vital background check that extends your time to hire. Effective hiring processes require active, easily accessible data to reduce the amount of time employees spend duplicating or recreating information they can’t find.

In considering the potential use of dark data in your hiring processes, keep in mind the following:

Clarify your problem : Deloitte recommends identifying the problem you wish to address before delving into your dark, or unstructured, data and decide what data sources might help in resolving it. Focus questions on one specific area and ensure it is measurable and of value for your hiring process. Extracting samples from a selected data source will help to quickly indicate its potential value rather than attempting the impossible and time consuming task of pouring through an expanse of information. For example, a paper based onboarding system may contain invaluable insights into why new hires are leaving your business within the first six months of employment. Too broad an approach will be overwhelming.

Be aware of risks : Historical recruitment data that is not easily accessible or securely stored could expose your business to issues with data protection. Information on former employees for example may not be needed again but must be stored appropriately and securely. A formal policy relating to the storage of data during the hiring process is essential. Veritas found that that over 25% of employees store personal data in corporate resources which may infringe on data privacy or copyright rules. 20% of employees also use personal devices to store business data. That may be vital dark or unstructured data lost to HR.

Incorporate technology : Paper based or manual recruitment processes add to the expanse of dark data generated every day. Korn Ferry notes that less than half (48%) of businesses use applicant tracking software in recruitment. Without those systems or basic technology, dark data risks adding to inefficiencies in hiring processes rather than offering added value. This may still be a step too far for hiring teams inching towards the use of people analytics, or who have yet to harness the insight available in basic recruitment metrics. Deloitte’s Global Talent Trends report for 2017 shows that 85% of companies have usable data but only 9% have a ‘good understanding of which talent dimensions drive performance’. Dark data may be the key to understanding those dimensions.

About the Author:

Kate Smedley

Kate Smedley is a freelance copywriter specialising in HR, HR Tech and recruitment, with 18 years of previous experience as a recruiter. Kate also works with employers to identify problems in hiring processes, offering full support and advice throughout the recruitment cycle.


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How to Build a Data Science Team

Businesses today need to do more than merely acknowledge big data. They need to embrace data and analytics and make them an integral part of their company. Of course, this will require building a quality team of data scientists to handle the data and analytics for the company. Choosing the right members for the team can be difficult, mainly because the field is so new and many companies are still trying to learn exactly what a good data scientist should offer. Putting together an entire team has the potential to be more difficult. The following information should help to make the process easier.

The Right People

What roles need to be filled for a data science team? You will need to have data scientists who can work on large datasets and who understand the theory behind the science. They should also be capable of developing predictive models. Data engineers and data software developers are important, too. They need to understand architecture, infrastructure, and distributed programming.

Some of the other roles to fill in a data science team include the data solutions architect, data platform administrator, full-stack developer, and designer. Those companies that have teams focusing on building data products will also likely want to have a product manager on the team. If you have a team that has a lot of skill but that is low on real world experience, you may also want to have a project manager on the team. They can help to keep the team on the right track.

The Right Processes

When it comes to the processes, the key thing to remember with data science is agility. The team needs the ability to access and watch data in real time. It is important to do more than just measure the data. The team needs to take the data and understand how it can affect different areas of the company and help those areas implement positive changes. They should not be handcuffed to a slow and tedious process, as this will limit effectiveness. Ideally, the team will have a good working relationship with heads of other departments, so they work together in agile multi-disciplinary teams to make the best use of the data gathered.

The Platform

When building a data science team, it is also important to consider the platform your company is using for the process. A range of options are available including Hadoop and Spark. Hadoop is the market leader when it comes to big data technology, and it is an essential skill for all professionals who get into the field. When it comes to real-time processing, Spark is becoming increasingly important. It is a good idea to have all the big data team members skilled with Spark, too.

If you have people on the team that do not have these skills and that do not know how to use the various platforms, it is important they learn. Certification courses can be a great option for teaching the additional skills needed, and to get everyone on the team on the same page.

Some of the other platforms to consider include the Google Cloud Platform, and business analytics using Excel. Understanding the fundamentals of these systems can provide a good overall foundation for the team members.

Take Your Time

When you are creating a data science team for the company, you do not want to rush and choose the wrong people and platforms or not have quality processes in place. Take your time to create a team that will provide your company with the quality and professionalism it needs.

About the Author:

Ronald van Loon has joined as an Advisory Board Member for its Big Data training category. Named by Onalytica as one of the top three most influential personalities of Big Data in 2016, Ronald will contribute his expertise towards the rapid growth of Simplilearn’s popular Big Data & Analytics category.


Source: How to Build a Data Science Team | Ronald van Loon | Pulse | LinkedIn