Too often, recruitment departments are sidelined as simply a call center or cost function of a business, with the sole purpose of getting people to attend interviews and accept offers. This attitude and practice couldn’t be further from the truth, as quality hiring provides the foundations for cohesive and successful teams. Many companies stick to old hiring processes, which often prevent their recruiters from getting their hands on top talent.
Outdated Hiring Practices Can Derail Your Recruitment Efforts
This year, an astonishing 82% of US employers are planning to hire new people. Yet, recruiters still face an uphill struggle to find the right fit: 61% of recruiters say that their biggest challenge is finding qualified experienced hires. It’s time for businesses holding onto outdated hiring practices to scrap them completely—and start seeing recruitment as the strategic function it is.
Though, of course, getting rid of outdated practices means replacing them with new ones. There are four core areas where hiring needs innovative, new solutions: talent discovery, candidate experience, data and reporting, and talent decision making.
Let’s dive into which age-old practices should be resigned to the history books, and how companies can leverage technology to strategically drive their hiring efforts.
The Right Tools to Power Top Talent Discovery
Many recruiters are still manually searching for quality candidates on job boards, but it’s difficult for them to be an expert in all the job roles they are expected to fill.
A lack of understanding of the position on the recruiter’s part leads to missing out on good candidates.
For example, if potential candidates don’t use the exact keywords that the recruiter is searching for, they might slip through the cracks.
Here’s where technology can help. AI-powered resume screening tools can parse through resumes, use past data on successful hires, identify the top applicants, and put them through to the next stage of the hiring process.
Getting to the next stage boosts the potential for recruiters to find the best candidates, as they are no longer relying on their own intuition—they have the historical data of hundreds if not thousands of applicants to rely on.
How to reduce the chance of bias
One crucial thing to note here is that to minimize the chance of bias, it’s important to keep track of any tendencies that might emerge as a result of skewed data and adjust the algorithm accordingly. We all remember Amazon’s sexist recruitment tool and how that turned out.
Candidate Experience: From Disjointed to Seamless
Candidate experience has never been more critical than in the virtual realm. And with 80% of respondents to our Remote Hiring Trends 2021 survey saying their interviewing and hiring process is now fully remote, this means stepping away from disjointed technology experiences and building a seamless funnel for candidates.
The truth may be harsh, but it’s important to hear: Organizations that are still using multiple recruitment management systems and interviewing tools neglect their candidate experience.
In dealing with all of these different platforms at different stages of the hiring funnel, candidates often get confused and disillusioned with the sheer number of platforms they’re grappling with.
The applicant might interact with the applicant tracking system to submit the application, complete an assessment on a separate tool, take the video interview on Zoom or Google Meet, and manage communications via email.
Now the recruiter’s multiple tools
Meanwhile, on the other side, the recruiter is also forced to deal with multiple tools and switch between platforms to gather information, inevitably impacting efficiency in the process. Having this data strewn across different platforms makes it more difficult to locate, and can result in recruiters missing it completely.
The answer here is simple: Organizations that invest in an all-in-one platform that takes care of everything.
An all-in-one platform is going to save you a ton of money in the end. You want your platform tool to take you from screening to interviewing. You will set yourself and your company apart from your peers when it comes to candidate experience while making life significantly easier for hiring teams too.
These tools can automate the process from one stage to the next.
For example, they can automatically schedule an interview for someone who passed the skills assessment or automatically sends an offer email to someone who was successful in their final interview.
Not to mention, adopting a single tool allows companies to curate the online environment to match their own branding, which is crucial for consistency and professionalism in the candidate’s eyes.
Organizations that adopt whitelabel recruitment platforms can create a more accurate image of their company in the absence of a physical workplace to visit.
Data is King — for Recruiters Too
The reality is the majority of recruiters do not have access to comprehensive data insights to drive decision-making. And that needs to change.
Recruitment often gets short-changed when it comes to investing in data and reporting technologies.
There has historically been a lack of emphasis on leveraging data insights within the function to drive strategic decisions, unlike other departments like Sales or Marketing, which are equipped with such technological capabilities as standard.
However, data and reporting are crucial for successful hiring, and the often sidelined business function of recruitment shouldn’t be left out of the data revolution.
Actionable insights can drive recruitment decisions.
Consider the time an average candidate spends in the hiring funnel. Look at the rate of high-quality candidates from various sources and all the data about the candidate. Each step in the information process takes time. Look at your application form conversion rates — and each candidate experience scores.
Armed with these insights, recruiters will be able to determine the success of their hiring efforts.
You’ll want to ensure they are reaching diverse groups, evaluate their candidate experience, and more. Especially given the importance of diversity and inclusion (one of Monster’s key hiring trends for 2021), companies must leverage data insights to support these efforts.
Remove the Bias in Talent Decision Making
Humans are inherently subjective beings—and the same goes for recruiters, no matter how fair they determine themselves to be. This, in turn, means that decisions made in large part based on interviews are ultimately subjective.
There are several different unconscious biases that the interviewer could exhibit in that process. Unconscious biases can include:
- affinity bias (when you prefer people who share qualities with you or someone you like).
- attribution bias (our flawed ability to assess the reasons for certain behaviors)
- conformity bias (allowing your views to be swayed by others).
Unknowingly, recruiters often take a pass on qualified applicants and take on unfit ones, all because of their internal biases.
What’s more, much of the data on candidate interview performance is not captured and used holistically and assessed objectively to make decisions. Rather it exists in bits and pieces across platforms and documents, further convoluting the process.
AI-powered interview platforms can provide objective behavioral insights to recruiters during video interviews and fairly assess candidates’ soft skills and learnability.
These tools augment the human decision-making power as they highlight areas where the interviewer’s judgment may be biased.
Advanced AI platforms can evaluate interviewer performance, providing data on time spent on each interview topic, the time the interviewer spent talking vs. the candidate, or whether or not inappropriate questions were asked.
All of this enables the interviewer to identify gaps in their approach and drive their performance.
It’s time for recruitment departments to leave age-old practices at the door and embrace technology to advance strategic hiring. With the growth of virtual hiring and remote work showing no sign of abating, what better time to start than now?
How Augmented Reality Continues to Transform Customer Experience?
Augmented reality (AR) is continuously paving the way for more engaging interactions between businesses and their target customers. In more ways than one, AR-based customer experience can ensure increased customer satisfaction and business conversion.
According to a study, a whopping 71% of customers have very favorable opinions about AR in the shopping experience. They say it would urge them to buy from the store more often.
Augmented Reality (AR), which works as an overlaying aspect over the appearance of the physical objects and the world at large, can enhance the perception of the real world and thus can revolutionize the customer and shopping experience.
With the present mobile support for a three-dimensional view of the objects, delivering AR-powered shopping and customer experience across online stores and mobile stores has become more accessible.
According to a Tractica report, by 2022, the number of monthly active users for mobile augmented reality apps is likely to reach 1.9 billion.
Augmented reality-based customer experience promises a digital shopping and browsing experience transforming the entire customer journey with either immersive attributes or more meaningful interactions or more layers of information. Businesses that employ a developer to build an AR app equipped with AR experience should insist on making things easier for the customers.
Since AR, for improving the customer experience, offers so many promises, it is essential to look at the key ways AR can transform customer experience altogether.
Removes All Pre-purchase Uncertainty and Confusion
Despite the rapid growth story of e-commerce and mobile commerce stores across all niches and categories, the confusion and uncertainty about making purchases are still dominant for most customers buying online.
Since while buying online, people cannot try the products in person, the rates of product return and abandoned carts are considerably high compared to the brick and mortar stores.
This is exactly where AR can play an essential role by bridging the gap between the physical shopping experience and the online ones. Thanks to AR, online stores and mobile commerce stores can deliver a truly feel-real impression of the purchased products.
Already many stores have started to incorporate AR for the express purpose of offering an immersive shopping experience. The IKEA furniture store right on our smartphone allows you to see each furniture piece in your room.
Similarly, several garment and fashion accessory brands enable you to visualise the items on your body. For example, Gucci offers an AR trial feature so that customers can see their sneakers adorning their feet just by capturing the feet with the smartphone camera.
Delivering a Detailed Layer of Product Information
Augmented Reality (AR), besides offering an immersive and engaging way of trying the products before purchases, also ensures feting very detailed product information to the customers instantly. The best thing is this ability made AR-powered shopping popular for offline stores as well.
No wonder that in Japan, a whopping 66% of customers now expect regular brick and mortar stores to provide AR experiences. As far as understanding the production cost of the app with AR experience is concerned, this can ensure better business conversion and hence is worth the cost.
AR-based shopping and customer service can offer a lot of information instantly and guide customers navigating in a commercial space or a destination. No wonder travel companies are now utilizing AR to deliver guided tours to their customers.
While booking bus tickets or booking tickets for a sports arena or booking tickets of flights, now AR-based displays can show you the details of every seat along with the facilities to make highly informed purchases.
Already sprawling museum premises and large indoor sites in many parts of the world are helping the incoming visitors to navigate their ways with augmented reality-based interactive maps. Airliners can also guide their customers to navigate to the right gates in quick time.
Adding More Value Through Interactive Packaging
In a multitude of ways, augmented reality (AR) is making a positive impact on customer service, starting from pre-sale orders to the actual purchase experience. Interactive packaging is the latest example of this impact.
When scanning the product packages with their smartphone camera, customers can see very detailed and multilayered visuals with a lot of additional and helpful information. This results in more purchase decisions for the customers.
Heinz uses AR-based packaging to allow customers to get a lot of helpful information when purchasing tomato ketchup, an excellent example of this AR-powered interactive packaging.
There is no dearth of brands that allow customers to scan the QR code to get more detailed information about the products they are going to purchase. In business-to-business (B2B), customer communication can be highly useful. Instead of carrying brochures, visiting cards, or business presentations, you can allow your audience to scan a code to get the details.
Futuristic AR Based Dining Experience
For food and restaurant chains to receive a continuous flow of new customers and retain old customers, providing a smooth and frictionless experience became the established norm. Augmented reality (AR) in the food and beverage industry has already proved to boost customer engagement and improve brand loyalty.
There are already AR-based menus that are transforming food ordering for customers. Besides offering interactive 360-degree visuals of the food items, the latest AR-based food menu provides multiple layers of information and interactive overlays for the customers to customize before placing the orders.
Thanks to AR scanning, the food package labels have also become more accessible than ever before.
AR Powered Travel and Hospitality
If one industry we need to name has received the most significant impact of AR technology, none other than the travel and hospitality industry. AR-powered information overlays or navigational guidance appearing right on the smartphone screens completely revolutionized the traveler experience.
The Interactive virtual tours of travel sites, hotels, and restaurants offering an immersive, 360 degrees interactive visual of the sites and ambiance of premises added value to the travel experience in a never-before manner.
AR is also ensuring a highly reliable travel guide offering route and navigation guidance in real-time. Last but not least, modern translation apps providing a real-time translation of displayed signs is another excellent example of AR’s impact on the travel experience.
AR to Revolutionize Post Sales Support
In today’s competitive business environment, every brand needs to establish its reliability through robust and uncompromising post-sales support. Such support refers to all the activities after a product is sold or a service is offered to the customers.
Some of the crucial post-sales support mechanisms that matter for branding and customer appreciation include installation, upgrades, warranties, repairs, troubleshooting, and answering customer queries.
In this respect, remote augmented reality-based customer support has already proved to be a significant way to push changes. It helped increase call resolution at the first instance by at least 20%, and the AR-based support also helped reduce the rate of dispatching technicians by at least 17%.
AR is transforming post-sales support for brands in two significant ways through AR-powered self-service and AR-powered technical support.
Business brands are increasingly using AR to help customers with self-service support. On their smartphones, customers can get guidance through highly interactive visuals and media, screen overlays on technical aspects and quick FAQ answers.
- AR-based Technical Support
The AR-based visual support can also help customers understand the technically demanding aspects of various products, parts, the ways they function, and the particular measures of troubleshooting and problem-solving. An AR-based screen overlay can give details of all parts along with the model number, manufacturing details, versions and the problem resolution timing.
All those bulky user manuals written in multiple languages are already on their way to exit. They are being replaced by interactive AR-powered user manuals showing minute details of every component and how to operate a device with switches, buttons and other controls. For instance, a new car owner can take interactive visual guidance on different systems and car mechanisms after purchasing the vehicle.
Quite convincingly, AR has transformed the customer experience across e-commerce stores, brick and mortar stores and all other B2C and B2B interactions. AR has proved to be the most critical value addition impacting the customer experience.
The Hitchhiker’s Guide To Survival Analysis
Survival analysis is the best thing in the world since sliced bread! However, in most machine learning circles, it’s pretty much synonymous with an “# it’scomplicated” relationship status.
Survival Analysis is an Extremely Valuable Branch of Statistics.
We want our guide to better serve you as a straightforward go-to/how-to, eliminating any confusion. The guide provides a valuable resource on how survival analysis, which can be applied to — well, almost anything.
However, survival analysis is wrought with misunderstanding and misuse.
What else should I know about survival analysis?
Also referred to as “time-to-event” analysis, simply put, it’s what we find when we analyze the time it takes for something like buying a new home (an event) to happen after getting a promotion -which we call “an exposure.”
Basically, it’s modeling or a set of statistical stratagems which measure the time as mentioned above to an event. Literally how long it takes for something of interest to happen. Depending on what you are studying, observing, researching, or just finding interesting- you want to know, and we can now actionably determine how long it takes to happen.
To get started, first and foremost, you need to set and formulate your research question aptly to perform a survival analysis approach.
Often, researchers will simply use ‘when’ and/or ‘whether’ terminology. But, first, the information is given — as a prediction of when and/or whether something will happen.
Then the conclusion is in a yes, or no determination. Finally, the conclusion is an analysis about how long it takes before what we want to see (the subject of interest being examined) will happen, and whether what we’re looking for will happen or not.
When you’re analyzing how long it takes for an event to happen and whether it will happen at all, it is imperative that what you want to eventually see and find is the same (equal) for all the subjects you examine.
In other words, you don’t want a sample with elements that have no chance of experiencing the event. It just won’t work.
Exposure is the point when we’re off to the races and start the proverbial research clock in order to analyze any time-to-event.
The event itself, in this case buying a new home, means simply the time needed to process and develop from the exposure which is getting that promotion– the moment when we stop the “clock.”
The time elapsed between these two points is the focus of interest which we call “the survival time.”
Survival analysis is a game-changer for a diverse variety of disciplines and areas of research.
Most experts, however, mistakenly consider survival analysis a tool solely applied to study death and disease, an accurate method to measure relapse of a medical condition, the potential hospitalization of a patient, and the mortality rate in medicine and biomedical disciplines.
Survival analysis application has thankfully spread to serve a variety of fields and disciplines, including engineering, social and behavioral sciences, even professional sports.
In engineering, this process is known as “failure-time analysis” and is mostly applied to test the durability and quality of products.
Incorporating survival analysis in engineering is valuable. For example, we see a manufacturer wants to test how long it takes for light bulbs to burn out, how often the company’s computers crash, even predict when a mechanical part like an engine head gasket will crack.
In social sciences, survival analysis is known as “time-to-event” analysis. This is because there have been scientific studies to answer queries such as how long it takes for one to get married, get a first tattoo, buy a first home, or to graduate.
Medicine and biomedical research
In addition to medicine and biomedical research, JADBio can definitively perform survival analysis on several out-of-the-box and even what one may consider ‘weird’ cases, including:
Health – Obviously, when analyzing health disciplines, we can actionably determine values such as the time to: death, device failure such as a heart pump, or simply the readmission rate of a specific subset of patients.
Market – We use survival analysis more and more in marketplace areas of research such as manufacturing or sales when we want to determine the time to: a component failure in machines, whether a certain device becomes obsolete, and how long it will take to obtain a certain patent for example.
Finance – A valuable tool in the evermore elusive waters of finance, survival analysis can be applied to calculate the time to predict when a hospital may turn a profit or report loss, calculate costs, and how often staff present burnout or should be promoted.
Social Sciences – Especially helpful in social sciences, where experts now can analyze the time to: divorce, new couples having their first or second child, and how long it will take new families to buy their first home.
Government and Social Services – Helps determine the time to: child welfare and to match children with appropriate foster parents. Used to optimize the length of stay of children in the program, to estimate participation time in various social programs, and to estimate the time it takes for various policies to take effect.
Law Enforcement – Predicts the time to: estimate the likelihood of recidivism in criminal offenders.
Marketing Operations – Performed to assess the time to: the length of participation in loyalty programs.
Sports – Sports is a field where survival analysis can really be your golden goose. Sports — that’s right. In professional sports, survival analysis will change the game when it comes to delivering results like time to: mechanical failure of race car engines, or tires in F1, and the time it takes athletes to be substituted in team sports like football.
A coach can know the best time to switch out a soccer player. Team doctors and government health authorities can accurately evaluate and certainly limit the rate of Chronic Traumatic Encephalopathy (CTE) –a degenerative brain disease observed in professional athletes, military veterans, and anyone with a history of repetitive brain trauma.
In essence, there is no differentiation to survival analysis being used as a tool whether we consider health disciplines, the global market, social and behavioral issues, or professional sports.
When researching for survival analysis — survival time is the main driving interest.
We perform survival analysis on subjects that present a delayed onset of events where our goal is to observe that specific timeframe, how long it takes for the event to happen.
It is irrelevant whether there is a positive or negative correlation attributed to the event. The event may very well be death (negative), yet it can also be a new promotion (positive).
Although initially developed in the biomedical sciences to analyze time to death either of patients or of laboratory animals, survival analysis is now widely used in engineering, economics, finance, healthcare, marketing, and public policy. Survival analysis can be used to predict when a patient will expire; when cancer will metastasize, or on anything you are trying to predict time-wise.
Our Secret Special Sauce
At the core of this work is JADBio. JADBio systematically compares the performance and stability of a selection of machine learning algorithms and feature selection methods that are suitable for high-dimensional, heterogeneous, censored, clinical and other forms of data. The data set is used in the context of providing specific, accurate, and actionable predictions.
Leveraging the advances in modern data collection techniques will produce ever-larger clinical and other large data sets. It’s imperative to identify methods that can be used to analyze high-dimensional, heterogeneous, survival data.
JADBio has a world-class team and constructs a range of machine learning algorithms capable of analyzing vast types of data providing clients with the power to make decisions and steer their respective objectives in the direction of success.
Definitions of standard terms in survival analysis:
- Event: Death, disease occurrence, disease recurrence, recovery, or other experience of interest.
- Time: The time from the beginning of an observation period (such as surgery or beginning treatment) to (i) an event, or (ii) end of the study, or (iii) loss of contact or withdrawal from the study.
Image Credit: Provided by the author from The Hitchhikers Guide to Survival Analysis; thank you!
Expensive Coding Boot Camps are Limiting the Tech Talent Pool
Coding boot camps have soared in popularity since their inception in the early 2010s. Course Report, an organization that conducts yearly market studies on boot camps, reports that nearly 25,000 coding boot camp graduates entered the job market in 2020 — up 39% from the previous year.
With the growth in popularity, however, has come an increase in price. Course Report also reports that the average coding boot camp costs more than $14,000. As costs increase, new opportunities for students to defer payments have surfaced, such as income share agreements, or ISAs, in which students don’t pay tuition until after they land jobs.
Rising Costs Mean Greater Risk
But many payback models come with risks. For example, a recent lawsuit filed against a coding boot camp is based on claims of false advertising around job placement rates that directly impacted students’ ISAs. And throughout history, there have been many predatory educational programs that have sold lies to bring in more revenue. Such instances resulted in rulings and regulations to protect students. However, it’s still true that tech training programs in the U.S. from for-profit enterprises face a complex balance of wanting to help students access better careers but needing to generate profits and returns for investors.
The bottom line is that the tech industry needs to look to new models for teaching coding skills that reduce students’ risk and financial burden.
Workforce initiatives and skilling pathways need to be more accessible to all Americans. While traditional college or university career pathways are an excellent option for some, there’s a large and growing pool of people in the U.S. for whom earning a four-year degree is unfeasible. The cost and risk of taking out student loans is a huge barrier, and many students can’t commit the necessary time while they work other jobs or care for families.
It’s Time to Create Realistic Opportunities
But the time and money it takes to get a degree or go through a for-profit boot camp is often not an option for many.
For similar reasons, the same individuals who can’t take the traditional higher education pathways are still being left on the sidelines by boot camps.
It’s time to make opportunities more accessible and realistic for all. Exploring the following strategies can help the tech industry reduce the risk and financial burden of gaining new skills:
1. Create and support accessible, accelerated skilling pathways.
Coding boot camps do create a great talent pool. Still, to widen that pool for tech companies and create more accessible opportunities for job seekers, the tech industry needs to support other skilling pathways, such as free and accelerated digital job training courses, that open doors to individuals often shut out of other options.
Some options are not only free or affordable, but they also offer opportunities to learn skills part-time.
Because this format breaks down barriers presented by traditional education pathways and for-profit boot camps, it’s more accessible to those looking for career changes. It can produce a more diverse talent pool for tech companies.
Plus, getting more career changers into tech means bringing a wide and diverse set of transferrable soft skills into the industry.
2. Formalize apprenticeship programs.
Apprenticeship programs are great models for opening the door to more people. They allow entry-level workers to gain the specific skills they need to fill roles at a company while on the job and earning a wage. In this way, it minimizes risks for both employees and companies.
As employees learn precisely the skills they need while on the job, they can be sure they’re not risking time, money, and effort to learn potentially irrelevant skills or skills that could become irrelevant in the near future.
Companies benefit because they can mold apprentices to whatever skill sets they need. Instead of hoping candidates’ past experiences and education will serve them well in filling open roles, companies ensure candidates can do exactly what they need to fulfill current or future job responsibilities.
3. Upskill existing workers.
Even people who are already employed with a company might be interested in educational opportunities to learn new skills or sharpen their existing skill sets. Companies looking to fill tech roles can benefit from looking within their companies first to see whether anyone desires to learn new skills and move into a more technical career path.
When companies provide upskilling opportunities to current employees, they retain the talent they already have, provide accessible opportunities for employees to develop their careers, and contribute to a talent pool that will be able to fill future skills gaps.
Pursuing a career in technology has long been a hefty financial commitment for students — whether they’re following traditional university pathways or paying for coding boot camps.
Meanwhile, the tech industry has struggled for years to fill its skills gap and find adequate workers. Closing the gap will require the tech industry to support more accessible, financially viable opportunities for all.
Image Credit: pepi stojanovski; unsplash; thank you!