Category: Technology

Is Applicant Tracking System The Future Of Hiring Process?

 “Hiring the right employee has always been the key element for a successful organization. When you choose the best, you automatically get the best results!” _ Deepu Prakash, Senior Vice President, Process and Technology, Fingent

While candidates come aplenty, finding the right talent from the pool has always been an enormous challenge for recruiters and staffing agencies. Thankfully, technologies like AI-powered Applicant Tracking Systems are changing that in a big way.

An Applicant Tracking System (ATS) is a software that automates the recruitment process. It electronically filters, organizes and streamlines job applications according to job postings. ATS simplifies the complex process of recruitment by providing a centralized platform to view applicants. AI-powered Applicant Tracking Systems enable filtering applications based on set criteria and helps recruiters a big way, in tracking the advancement of applicants through the hiring process. In this article, we will consider how ATS can prove beneficial to recruiters and staffing agencies in particular.

How Does ATS Transform Hiring Norms?

ATS collects and maintains a database of candidate resumes and applications within itself. ATS tools help in hiring managers and corporate recruiters track and filter resumes in the hiring funnel. The major difference between traditional hiring and hiring with the help of ATS can be compared to the difference between fishing with a hook and fishing with a net. The benefit of the latter is a much bigger catch! ATS allows recruiters to track hundreds of applicants more efficiently rather than handle each applicant manually.

 Companies that outsource talent can benefit greatly from ATS. Since they are not limited by geography, they can cast their net globally. It is not uncommon for a company to receive thousands of applications for a remote job they have posted. With ATS, they can filter out the right candidates for the job and save time and cost. 

How HR and IT Combine to Deliver Real Value to the Enterprise

 How Does ATS Empower Corporate HR?

ATS empowers the recruitment process in the following ways: 

• ATS enables recruiters to post jobs online, receive and sort applications, screen out unsuitable candidates, process applications, communicate with candidates quickly, organize interviews and even handle the hiring process online.
• The AI integration enables ATS to identify patterns and segregate resumes/candidate profiles according to various departments and customized fields.
• One of the most important benefits is that it saves time. It is estimated that resume screening and candidate shortlisting can take 23 hours and making a hire could take four months. ATS can make this task easier, faster and automated, thus reducing the cost-per-hire and the time-to-hire.
• ATS allows corporate recruiters to be proactive and create jobs on platforms, which can be published on social media networks as well as targeted job boards. 
• ATS assists corporate recruiters to screen candidates, to ensure they progress through the workflow process and store all the documentation in one place. It helps them to monitor applications at each stage and identify any issues early on thus reducing the time-to-hire period.
• Another important recruiting goal and challenge are accessing the right candidate skills. ATS includes features for customizable interview scorecards and questions. It allows recruiters to customize them based on the most important characteristics. This makes candidate evaluation easier and efficient.
• With AI-enabled ATS, recruiters can also set match levels for various job roles under different departments.
• An ATS with good reporting functionality will be able to help corporate recruiters measure the effectiveness of marketing. A good reporting engine will help recruiters, quickly pull out reports which show things like diversity statistics and the source of the application.
• Online job boards make it quick and convenient for candidates to apply for open positions resulting in a load of unrelated applications. An ATS is capable of quickly weeding out those unqualified candidates even before humans open a resume.

Related Reading: Check out how Odoo can help meet HR requirements.

How Does ATS Empower Staffing Agencies?

 More than 98% of Fortune 500 companies are using ATS. This is a clear indication that ATS is an indispensable software for staffing agencies. Here are a few reasons why:

• An ATS helps staffing agencies grow their business. The bigger the staffing agency, the more complex their database. Communication, tracking candidates, and other recruiter activities can become difficult to manage. AI-enabled ATS identify patterns and sorts resumes according to job profiles helping recruiters choose the best candidates among the large pool.
• ATS empowers staffing agencies to source candidates more efficiently. The existing candidate pool within an ATS is often a very good resource for finding quality candidates. 
• A good ATS has an open ecosystem where you can match solutions to needs effectively. This allows users to customize ATS to meet a client’s specific needs by adding partner extensions, integrating third-party vendors, and building new applications on the platform. 
• ATS improves the candidate experience. According to key findings in a Global Recruitment Insights and Data study, respondents said that “candidates will matter most in 2019, with sourcing (61 percent) and candidate engagement (36 percent) leading the pack.”  ATS along with its integrations can help in this regard by simplifying and enhancing every step of the candidate experience.  
• It helps agencies keep their clients happy by improving client management. ATS can log all of your conversations with a client automatically. 
• ATS helps staffing professionals to be more productive because it allows team members to work from anywhere and still collaborate effectively. 
• The conventional recruiting process causes a lot of friction between hiring managers, the HR department, and others involved in the process. An effective AI-powered ATS will help smooth things out and reduce disagreements, thus making it easier for all involved to work together. 
• A shorter time to hire always works better for the organization. Not only does it save resources, but it also ensures that suitable, qualified candidates are selected and hired quickly before the competition has a chance to snatch them away.

Power Charge Your Hiring Process with ATS

As discussed, a good ATS will illuminate and guide all aspects of the recruitment process. It will help corporate recruiters and staffing agencies better understand their candidate pool and make quicker and more effective hiring decisions. It is reported that 86% of staffing professionals were able to hire faster with the help of ATS. Understanding and using the candidate database to improve hiring performance helps the business act more quickly. Quicker onboarding process results in increased productivity, which translates to more profitability.

At Fingent, we understand the need to keep pace with the requirements of today’s market. Bringing together smart AI and recruitment practices, we create purpose-built software to help you reach your ideal candidates faster. So let’s get you started with an Application Tracking System that will transform your business and beat the competition.

Watch more about Applicant Tracking System.

Can Equipment Maintenance Be Simplified With Augmented Reality?

“If I had six hours to chop down a tree,” said Abraham Lincoln, “I’d spend the first four hours sharpening the axe.” Wise words which emphasize the fact that there is no substitute for consistent, preventive maintenance. And yet, it isn’t high on the priority list of many. Sure, equipment maintenance isn’t a ribbon-cutting event. A short-sighted CEO could argue that it increases cost and hinders the speed of growth, but effective maintenance is what will hold the business together in the long run.  

In an attempt to balance out the costs of maintenance with their goals to increase business growth, businesses are looking to Augmented Reality for a solution. With the power to augment reality and machines, AR is the perfect solution for firms looking to simplify equipment maintenance and increase their growth. This article provides an overview of how AR can achieve that.

Continue reading “How Augmented Reality Can Simplify Equipment Maintenance”

Key Differences Between Machine Learning And Deep Learning Algorithms

Artificial Intelligence is on the rise in this digital era. According to IDC’s latest market report, global investment of businesses in AI and cognitive systems is increasing and will mount to $57.6 billion by the year 2021. 

Artificial Intelligence holds a high-scope in implementing intelligent machines to perform redundant and time-consuming tasks without frequent human intervention. AI’s capability to impart a cognitive ability in machines has 3 different levels, namely, Active AI, General AI, and Narrow AI. Artificially intelligent systems use pattern matching to make critical decisions for businesses.

Related Reading: Know the different types of Artificial Intelligence.

Categories Of Artificial Intelligence

Machine learning and Deep learning are 2 categories of AI used for statistical modeling of data. The paradigms for the 2 models vary from each other. Let us walk through the key differences between the two:

• Machine Learning: Process Involved

Machine learning is a tool or a statistical learning method by which various patterns in data are analyzed and identified. In machine learning, each instance in a data set is characterized by a set of attributes. Here, the computer or the machine is trained to perform automated tasks with minimal human intervention. 

To train a model in a machine learning process, a classifier is used. The classifier makes use of characteristics of an object to identify the class it belongs to. For instance, if an object is a car, the classifier is trained to identify its class by feeding it with input data and by assigning a label to the data. This is called Supervised Learning. 

To train a machine with an algorithm, the following are the standard steps involved:

• Data collection  
• Training the Classifier
• Analyze Predictions 

While gathering data, it is critical to choose the right set of data. This is because it is the data that decides the success or failure of the algorithm. This data that is chosen to train the algorithm is called feature. This training data is then used to classify the object type. The next step involves choosing an algorithm for training the model. Once the model is trained, it is used to predict the class it belongs to. 

For instance, when an image of a car is given to a human, he can identify it belongs to the class vehicle. But a machine requires to be trained via an algorithm to predict that it is a car through its previous knowledge. 

Various machine learning algorithms include Decision trees, Random forest, Gaussian mixture model, Naive Bayes, Linear regression, Logistic regression, and so on. 

Machine Learning- Deciphering the most Disruptive Innovation : INFOGRAPHIC

• Deep Learning: Process Involved

Deep learning can be defined as a subcategory of machine learning. Inspired by ANN (Artificial Neural Networks), deep learning is all about various ways in which machine learning can be executed. Deep learning is performed through a neural network, which is an architecture having its layers, one stacked on top of the other.

A neural network has an input layer that can be pixels of an image or even data of a particular time series. The next layer comprises of a hidden layer that is commonly known as weights and learns while the neural network is trained. The final layer or the third layer is that predicts the result based on the input fed into the network. 

The neural network thus makes use of a mathematical algorithm to predict the weights of the neurons. Additionally, it provides an output close to the most accurate value. 

Automate Feature Extraction is a way in which process performed to find a relevant set of features. It is performed by combining an existing set of features using algorithms such as PCA, T-SNE, etc. For instance, to extract features manually from an image while processing it, the practitioner requires to identify features on the image such as nose, lips, eyes, etc. These extracted features are fed into the classification model. 

The process of feature extraction is performed automatically by the Feature Extraction process in Deep Learning by identifying matches. 

Related Reading: AI and ML are revolutionizing software development. Here’s how!

Key Differences Between Machine Learning And Deep Learning Algorithms

Though both Machine Learning and Deep Learning are statistical modeling techniques under Artificial Intelligence, each has its own set of real-life use cases to depict how one is different from the other. Let us walk through the major differences between the modeling techniques.

1. Data Dependencies

Machine learning algorithms are employed mostly when it comes to small data sets. Even though both machine learning and deep learning can handle massive amounts of data sets, deep learning employs a deep neural network on the data as they are ‘data-hungry’. The more data there is, the more will be the number of layers, that is the network depth. This increases the computation as well and thus employs deep learning for better performance when the data set sizes are huge.

2. Interpretability

Interpretability in Machine Learning refers to the degree to which a human can understand and relate to the reason and rationale behind a specific model’s output. The major objective of Interpretability in machine learning is to provide accountability to model predictions. 

Certain algorithms under machine learning are easily interpretable, such as the Logistic and Decision Tree algorithms. On the other hand, Naive Bayes, SVM, XGBoost algorithms are difficult to interpret. 

Interpretability for deep learning algorithms can be referred to as difficult to nearly impossible. If it is possible to reason about similar instances, such as in the case of Decision Trees, the algorithm is interpretable. For instance, the k-Nearest Neighbors is a machine learning algorithm that has high interpretability.

3. Feature Extraction

When it comes to extracting meaningful features from raw data, deep learning algorithms are the most suitable method. Deep learning does not depend on binary patterns or a histogram of gradients, etc., but it extracts hierarchically in a layer-wise manner. 

Machine learning algorithms, on the other hand, depend on handcrafted features as inputs to extract features. 

4. Training And Inference/ Execution Time

Machine learning algorithms can train very fast as compared to deep learning algorithms. It takes a few minutes to a couple of hours to train. On the other hand, deep learning algorithms deploy neural networks and consumes a lot of inference time as it passes through a multitude of layers. 

5. Industry-Readiness

Machine learning algorithms can be decoded easily. Deep learning algorithms, on the other hand, are a black box. Machine learning algorithms such as linear regression and decision trees are made use of in banks and other financial organizations for predicting stocks etc. 

Deep learning algorithms are not fully reliable when it comes to deploying them in industries. 

Both machine learning and deep learning algorithms are used by businesses to generate more revenue. To know more about how your business can benefit from artificially intelligent systems and which algorithms can be leveraged for a positive business outcome, call our strategists right away!

What Is Augmented Reality?

Do you fancy playing Nintendo’s game Pokemon Go? Or used the IKEA mobile application? These are 2 examples of how Augmented Reality technology has taken over the digital world to heights. 

The much-hyped AR technology has had a technological breakthrough in recent years and has witnessed many innovations. Snapchat Lenses are yet another example of AR technology implementation. AR keeps the real-world focus. It adds virtual elements to improve the user’s experience. 

The AR technology superimposes a CG (Computer Generated) image of the real world for the user. For instance, the Pokemon Go game provided its users with superimposed images, allowing the users to catch Pokemon simply by looking at their smartphones. The game had 65 million users as it gained popularity. 

What Is Virtual Reality?

If you have used VR devices such as Play Station VR (PSVR), you would understand how Virtual Reality technology completely provides an immersive experience by completely shutting you off from the rest of the world. 

VR technology is a display technology to create a simulated environment for the user. The key players in VR technology include Oculus Rift, HTC Vive, and so on. 

Augmented Reality And Virtual Reality: Game-Changer For The Real Estate Industries

AR and VR technology has seen immense growth in recent years and is continuing to grow rapidly. According to recent Statista reports, by the year 2025, the total revenue in the VR/AR industry is estimated to be $2.6 billion. 

Initially, the real estate sector has been using 3D Video and 3D Photography for creative interactions with their clients. They used to portray this technology for showing their clients the interiors of the buildings etc. Virtual reality, thus enhanced the viewing experience for the clients of real estate builders and agents, without the viewers having to visit the premises physically.

From helping the construction industry to market, improve and maintain sites to train the workforce on security, Virtual Reality is a game-changer for the real estate industry! Let us see how:

Why The Real Estate Sector Needs AR And VR Technology Implementation

Virtual and Augmented Realities are Immersive Technologies that can create a new reality altogether by leveraging the 360 space. These technologies save time and expenditure significantly for buyers, sellers, agents, etc. Technological advancements have contributed to the increased use of immersive UX (User Experiences), thus easing the process of selling and/ or buying residential and commercial real estates. Implementing these advanced technologies in Real Estate will ease both buying and selling of properties.

Related Reading: Check out how real estate technology helps predict property prices

AR And VR Technologies: Benefits In The Real Estate Industry

A recent survey by the National Association Of Realtors stated that 95% of users search the Internet before buying a property. The major benefits that can be leveraged out of AR technology are as follows:

• Better Clarity Over Properties

Augmented Reality technology makes everything real and interactive with its ability to carry blueprints and images in real-time. AR mobile applications offer users a visual walk through the properties.

• Cost-effectiveness

AR replaces traditional marketing techniques offered by realtors to reach out to potential buyers. In addition to saving cost overheads, AR technology improves brand loyalty as well.

• A Better Reach-Out Platform

An AR mobile application on your smartphone offers a better reach-out than having to physically be present in worksites.

• Offers A Global Reach

With VR, arranging virtual visits, showing users the properties virtually, and negotiating costs with the users are made easy, even to long distance buyers.

Related Reading: Check out how smart home technology is creating an impact on real estate.

AR/VR technologies allow users to refine searches and avoid unproductive visits to any property. Let us walk through the key benefits that the technology of Virtual Reality has to offer:

• Virtual Visits

VR technology allows people to visit properties virtually which not only saves cost but time as well. Putting on a VR headset, users get an immersive experience by having 3D walk-throughs of properties. There are 2 types of 3D virtual tours. They are as follows:

1. Guided Visits – These are for existing properties that lets you capture a 360-degree video. Users can wear a VR headset or a gadget such as Google Cardboard to view the properties. This does not require any programming or complex rendering. 
2. Interactive Visits – Users can decide where to move within the property, by choosing specific hotspots in their field of view. 

• Virtual Staging

According to the statistical report by the National Association Of Realtors, 77% of real estate agents prefer to use virtual staging to help potential buyers to associate with a property they intend to buy. VR technology helps realtors to market-specific staged properties with minimal investment. 

With the advent of technology, 3D tools are used to create a virtual representation of spaces with required furnishings. For this, the 3D photographs are taken and further staged with the help of a 3D scanner. 

• Visualizing Architecture

Architectural Visualization has become immersive with the advent of VR technology. Potential buyers can imagine how their future properties will look like. The 3-dimensional computer-generated environment helps realtors create full-scale models of buildings and properties. VR technology thus helps in pushing thresholds without the risks associated with time and costs.

• Efficient Communication With Tenants 

3-dimensional tours in real-time with tenants can help landlords and real estate agents communicate with their tenants effectively. The VR technology is found to be more efficient and productive in case of vacation rentals especially. This is because businesses that offer short vacation rentals have high turnover rates associated with it, compared to others.

• Virtual Commerce

According to a recent eCommerce statistic report, 77.24% of potential buyers who intend to buy online, abandon their idea of purchasing. This shows a lack of convincing customers to go ahead with their initial choices. Virtual Reality technology finds use in these situations with its immersive capability.

With the mobility element of the VR technology, around 24 million VR devices were estimated to be sold globally, according to insights from CSS. 

With VR technology, after taking a virtual tour of the property, users can order from the virtual store as well.

Related Reading: Read on to know What Not To Do In Real Estate Business.

AR And VR Technologies – Future Game-Changer For The Real Estate Industry?

Immersive AR and VR technologies provide users the benefit of Analytics. This feature allows realtors to now derive critical insights and enhance the buying decisions of potential customers.

Providers of Analytics can offer web-page related KPIs (Key Performance Indicators). This includes page views and web sessions. Nuanced buyer behaviors can be better judged with data analytics. 

To conclude, AR and VR technologies reduce unnecessary expenditures associated with staging and scheduling visits. It helps users visualize properties and reduces the overall costs. 

Use of VR to support USA smart cities are forecasted to reach $330 million by the year 2024. 

AR and VR technology is surely the next big technological breakthrough in the real estate industries. For more insights on how to transform your real estate business digitally with immersive technologies, call our strategists right away!

Chatbot or Chatbaby: Why Chatbot Technology Needs Time To Mature?

Automation is at its height in this digital era and artificial intelligence is the core technology behind successful industries today. A chatbot is a computer program that interacts with human users via the Internet. These auto-operating conversational bots, artificially replicate the patterns of human interaction. This is made possible via Machine Learning algorithms.

Amazon’s Alexa and Apple’s Siri are well-known examples of chatbots. They respond to queries based on the data they are provided with.  Since a chatbot is programmed to perform tasks independently, it can respond to queries based on predefined scripts and machine learning applications as well. 

Enterprises that have enhanced IT infrastructure, implement chatbots in varying departments. For instance, ERP, on-premises to cloud, etc., improve customer experiences and increase business value. 

Chatbots As Conversational Tools In The Workplace

The potential benefits that chatbots provide to companies are immense. On one hand, when chatbots provide personalized and efficient search results, on the other hand, companies find cost savings a prominent feature on implementing chatbots. 

Enterprises enhance their workflows and operations increasingly with the help of chatbots as co-workers. This helps companies in serving a larger market segment. Chatbots automate redundant tasks that sap the productivity and efficiency of the workforce and enable them to focus on their core functions. Chatbot technology enhances customer experience by providing them with personalized content. 

Chatbots: Influence In Industries Today

• Enhances Customer Service 

According to a recent survey, 83% of customers need online assistance to complete their shopping. Customers will need online real-time assistance from a real store. The assistance required by customers include areas like during registration, logging in, adding products into the cart, payment, checkout, etc. This is where chatbots serve as a salesperson by interactively communicating with customers via text, voice and so on and provide them with rich content. 

Additionally, chatbots provide automated answers to redundant queries of customers. It also forwards the queries to real sales personnel when the need arises. This saves the time of human customer service resources, avoiding the need for customers to wait for responses. This scales up operations of enterprises to new markets globally as well. 

Customer service that chatbots offer is proactive. This means that chatbots facilitate a 24/7 service for interacting with its customers real-time. Initiating communication with the customer periodically, is another benefit of the prevailing chatbot technology, thus enhancing your brand perception considerably.

• Monitors Data To Provide Critical Insights

An enterprise benefits from gaining traction of customers on its website’s landing page. But it is equally important to ensure that the landing page also generates enough organic traffic. Chatbots reaches out to the customers who visit the landing page and gathers critical data as to why the customer left the page without a purchase and so on. 

Online customer behavior and buying patterns are tracked effectively via monitoring the data thus derived. 

• Generate Leads Effectively

Chatbots ensure a better lead generation by helping in determining leads via KPIs such as timeline, budget, etc. Chatbots thus ensure higher conversion rates.

• Saves Costs 

Implementation of a fully functioning chatbot is much faster than hiring individual employees for each task. With great speed, chatbots also ensure error-free operations. It is also easy to implement and maintain. This reduces costs and other overheads significantly. 

Related Reading:  Read on to reveal the top Chatbot Security measures you need to consider.

Chatbots In Its Chatbaby Phase: Conversational Limitations In Current Chatbots

Chatbots have evolved into a phase where it can integrate Natural Language Processing or NLP technology to support the workforce in performing extensive searches. That being said, chatbots currently face a limitation. AI-based chatbots, for instance, are restricted to duplicate results. For example, a flaw in a chatbot can result in the chatbot responding to a high engagement level content such as an office party album instead of retrieving business-related documents. 

Related Reading:  Can ChatBots redefine your real estate business? Read on to know more!

Why Do Chatbots Need To Mature?

Though chatbots support customer services, they lack a human element in them. A full-fledged implementation of a matured chatbot requires addressing numerous technological gaps. Only then the services of these chatbots can be extended from a chatbaby level, offering just employee assistance to a serious enterprise level. 

Even when chatbots interact in an automated manner, they sometimes cannot answer even simple queries. For instance, chatbots lack becoming conversational in a detail-oriented manner. Thus, it is necessary to learn the complex machine learning technology and its bottlenecks initially before you proceed to implement it in your business.  

Around-the-clock support is what customers look forward to while they search via queries online. This 24/7 ability to converse with the customers real-time is what is yet to be achieved. 

In 2019, chatbots are still in their chatbaby phase and need to mature. 75% of global consumers prefer human interaction rather than a chatbot or any other automated service at the time being. 

The data required to establish a fully conversational chatbot is immensely huge. This explains the need for a much higher understanding of machine learning and challenges around natural language processing technique implementation. 

Can There Be An Alternative To Chatbots?

Chatbots can handle simple tasks to help the human workforce. But when it comes to complicated tasks, assistants that can proactively work to streamline interactions with customers, are required. For this, employees must be able to access from a centralized location.

Employee Intranets, for instance, are hubs that allow organizations to access data in real-time and whenever required. This not only allows them to store data in an easily accessible manner, but also help in connecting with resources and tools at a fast pace. This now becomes a perfect collaboration system. 

https://www.fingent.com/insights/portfolio/using-chatbots-to-create-an-enhanced-and-engaging-learning-experience/

As more and more employees become tech-savvy and with the growing requirement of companies to expand their mobile technologies and strategies, connecting remotely is a necessity. With the growing remote working, it is important to implement social media features into various communication channels as well. This enables a human element to be present and can act as an alternative to chatbots.

2019 can be seen as a year to understand machine learning technology and to develop the digital workplace. With evolving technology, it is also important that an organization ensures a perfect environment where resources and tools support these digital assistants and help in making critical data simple and accessible. Call our strategists right away to learn more about how chatbots can improve your business effectively and productively.

Top Five Barriers To Growth and Adoption Of Virtual Customers

“There is only one boss. The customer. And he can fire everybody in the company from the chairman on down, simply by spending his money somewhere else.”

Wise words from Sam Walton, the founder of Walmart. Yes, customers can either make or break an organization. The key then is to know how to treat them the way they want to be treated. In this blog, we will discuss a particular segment of these customers – virtual customers. We will also consider some of the challenges for growth and adoption of these customers.

The Customer Is The Only Boss

Every day, we see significant developments in technology. The rate at which consumers and companies are adopting such technology is astonishing. For example, the adoption rate for computer technology grew from 0% to 50% in just a five year period, and the use of tablets grew from 3% in 2010 to 64% in 2017. 

Customers create customers, and so will virtual customers. Virtual customers will be able to communicate with each other and encourage knowledge creation and knowledge sharing, thus aiding the growth of the business. In this regard, innovation and new ideas are rising at an exponential rate. Here is where dealing with virtual customers become extremely important.  Many large firms have integrated virtual customer assistants (VCA) or chatbots as part of their strategy.

Emphasizing the support operations, which integrate VCA, the managing vice-president at Gartner, Gene Alvarez says: “As more customers engage with digital channels, VCAs are being implemented for handling customer requests on websites, mobile apps, consumer messaging apps and social networks.”  He adds that “this is underpinned by improvements in natural-language processing, machine learning, and intent-matching capabilities.”

According to Gartner research, companies report a reduction of up to 70% in calls, emails and/or chat inquiries after implementing a VCA. They also reported greater customer satisfaction and a 33% savings per voice engagement. Yet, we may have to wait for several years before we can create autonomous virtual customers that can function without human intervention. Meanwhile, certain hurdles need to be acknowledged and overcome by live customer support and services. Consider a few of them.

Related Reading: Check out how AI is redefining the future of customer experience.

Barrier 1: Brand Strategy

Without the benefit of face-to-face interaction, businesses will need to work out how to maintain their relationship with the customer. A business might design a VCA and forget it. Instead, they should continue to check if their design is functioning as they would like it to function.

Brands should continue to collect data from their customers and ensure that they treat them not just as a number. In this regard, algorithms play a major role. Engaging aspects of humanism provide the best virtual customer support.

Barrier 2: Capability and Capacity

One of the advantages of having a virtual customer is the ability to record and process data quicker and more efficiently than humans. For it to be fully automated there are two things to consider. The first is the capacity to understand a customer’s preference and the second is the capability to influence the actions of the customer. Both of these are equally important to balance business transactions.

In machine-to-machine communication, compatibility issues may run the risk of slowing down the pace of acceptance and deployment with virtual customers. Employing VCAs that can learn from each interaction, detecting preferences, and making recommendations based on past requests is the solution to this challenge. 

Related Reading: Read more on how Machine Learning is boosting customer experiences. 

Barrier 3: Legal Impact

Legal liability can become a major issue if the virtual customer assistant goes ‘rogue,’ and offers wrong information or misguides a customer. Internal policies will have to be put in place and disclaimers should be considered for failed transactions and adjudications which could follow. 

Barrier 4: Data Privacy 

According to Gartner, 80% of all internally developed software are now cloud-native or cloud-enabled. In the course of interaction with the virtual customer, VCA may be exposed to and may collect a vast amount of personal data and other commercial information. Therefore, it is very important to be careful about security and privacy. Companies should ensure that their data controller registrations and privacy policies are up to date. It must be clear where the data is collected and if it is protected under constitutional law. Data protection measures must be put in place to safeguard data.

Appropriate measures must be taken to safeguard copyright-protected data. Companies should ensure that the virtual customer is real and that they can understand and use the equipment. Also, they should decide if they want to provide virtual customer support to devices which may affect their sales and service channels. 

Related Reading: Is Big Data evolving retail customer experience? Read on to know more!

Barrier 5: Human Acceptance

No technology can ever replace or replicate human empathy. Though VCA can eliminate the awkwardness of technology, it cannot really emulate the human element. Ultimately, humans will make the decisions. When customer service is on the spectrum of high-emotion and high-urgency, getting people to trust technology will undoubtedly be a challenge. 

Virtual customer communities affect the relationship between absorptive capacity and organizational innovation. Many firms are investing in virtual customer communities as they are capable of reducing communication barriers between firms and costumers.

Get On the Virtual  Path Now

Companies would do well to consider these five challenges and use them to advance their virtual customer services. While this is an aspect of technology that is sure to grow by leaps and bounds, organizations would need to act wisely to stay on the cutting edge, or they risk being thrown off the bus, or losing out on the possible benefits, at great loss to themselves. Give us a call if you need help with getting this started for your business.

How Is Augmented Reality Revolutionizing Education Industry?

Augmented reality is the latest breakthrough technology in the digital space. It has been almost half a century from when the concept of Augmented Reality first appeared in 1968, and as Augmented Reality (AR) is penetrating deeper, its uses continue to increase. 

By 2022, worldwide shipments of smart glasses are estimated to reach 32.7 million units. And by 2025, the global augmented reality market is anticipated to grow noticeably to about 198 billion U.S. dollars. With such significant growth, it makes sense to consider how AR can benefit our daily lives. In this blog, we will discuss its impact on the education sector in particular. Let’s begin by understanding what AR is.

Read More:

What is Augmented Reality?

Augmented Reality is the bridge that connects the real world with the virtual world. Its popularity is growing rapidly in every industry from social media filters to surgical procedures. As the word augment suggests, AR enhances what we hear, see and feel. It has categories based on various technologies. Some of those categories are marker-based AR, markerless AR, projection-based AR, and superimposed AR. This makes AR useful for various industries. 

There are various industries such as public safety, tourism services, entertainment and so on that are leveraging AR. For example, AR aids the automotive industry by assisting with various parameters such as navigation and speed. It helps people not to lose focus while driving because the application can be projected from a console on the glass which only the driver can see. In Healthcare, there are numerous AR applications that support the video platform and can project augmented hands on the patient. Wherever the surgery is taking place, a senior surgeon can guide a beginner in his surgery.

With many more industries benefiting from AR, let’s see how the education industry is revolutionizing with AR.

The Role of Augmented Reality in Education

AR is set to revamp the world’s conventional learning model. It can bring about a positive change in the location and timing of classes and make learning more engaging. Today’s learning process is becoming much more tuned to bring in the elements of interaction and creativity. By providing visual representations, AR helps students acquire, process, and remember information. Thereby, it helps them to test out their knowledge in practice.

AR technology has also helped students to learn and understand their surroundings. The British Museum has already begun using AR technology to help students understand certain displays. It has proved useful in providing students practical knowledge of subjects such as math or science. Let us look into a few more benefits of AR in the educational sector.

1. Edutainment versus Education

AR makes lessons fun learning. Today’s generation is not a chalk and board generation. Studies reveal that students are easily bored with standardized methods of teaching. The reality is that students tend to remember what they see more than what they learn by rote.  AR takes them to the next level by helping them not just to see, but also experience and participate. As a result, AR delivers a positive impact on the students by giving them edutainment.

2. Simplify Complex subjects and Exemplify Abstract Concepts

AR breathes life into complex subjects that students are expected to learn. It can bring added creativity, interactivity and engagement to complex and abstract subjects. It simplifies the learning process. Both the teachers and the students likewise can thus take control of the educational process through AR. 

Each student’s level of understanding and the pace of learning differs. Certain AR apps allow you to create personalized learning materials. Such apps allow the tutor to create content for the individual needs of each student. This way, students will get to learn complex subjects quickly and easily.

3. AR-Enabled homework

AR can also help students do their assignments and homework better. The fact that today’s generation is tech-savvy can be harnessed to promote education in a way that will appeal to the students.

AR emphasizes important concepts. By making images and information “pop out” of a textbook, AR can break the boundaries of textbook learning, which has been sidelined as boring and tedious and make it interactive and absorbing.

4. Use what they already have

According to the Pew Research Center, 95% of teenagers have access to smartphones. It makes sense to use this to their advantage in education as well. Neither parents nor teachers have to spend extra dollars on buying gadgets for AR learning. The AR app on an existing smartphone is all that is required for interactive learning.

5. Practical Knowledge at AR Labs

For various reasons, schools may choose to limit the scope of practical demonstrations. This is another fact that will change through the use of AR technology. With AR, students can perform practical experiments without the need of the physical lab. This is extremely helpful for professional courses. Students can also gain knowledge about safety procedures and potential hazards in the lab. 

Augmented Reality is the Real Future of Education

According to a survey on the impact of interactive technology on marketing students, it is said that 87% were likely to attend the class, 72% were likely to participate and 70% students said that they improved their understanding of specific concepts. If this is true with interactive technology, how much more of an impact would AR have on the student’s attendance, participation, and understanding? 

The children of millennials who are born between 2010 and 2025 are called Generation Alpha, which is considered the most technology-infused. AR education is poised to be the norm rather than the exception. According to the forecast, the AR market is expected to reach $60.55 billion by 2023, growing at a CAGR of 40.29%. Undeniably, AR is the real future of education. 

Watch more on how Augmented Reality is creating an impact on the Education Industry.

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Fingent is on a go, to revolutionize education sectors with AR technology. With various education application platforms, Fingent is already helping organizations create effective collaboration between students and teachers. To know more about how Fingent can help you provide an effective and efficient learning ecosystem with emerging and trending technologies, get in touch with our experts today!

Can Smart Home Technologies Reshape The Real Estate Industry?

“Mid pleasures and palaces though we may roam, be it ever so humble, there’s no place like home,’ sang American actor and poet Howard Payne back in 1822. He never could have imagined back then what a home, more specifically, a smart home could be 200 years later. From smartphones to smart homes, smart is the buzzword. Automation, ease, and freedom – that is what a smart home provides and that is what people are looking for today.  In this article, we will consider how smart home technology is creating an impact on real estate now and will continue to do so into the future

What is Smart Home Technology?

Automation is a major factor in smart home technology. When your coffee pot goes off at a pre-set time or a sprinkler system goes on and off when you’re out of town, you are using automation. But “smart home automation” goes a step further in that it includes remote monitoring and programming. They become “smart” when you can control and communicate with several devices from great distances. With the rise of tablets and smartphones, you can now connect everything from phones, TVs, lights and much more. These are invented with the intent to make the home comfortable and safe. The question is, are common people interested in smart homes?

The Merger of Real Estate and Lifestyle

In this day and age, owning a home defines your way of life. When people invest in real estate, they look for comfort and security. Somehow real estate and lifestyle have always been intertwined with each other. And just as technology has had a positive and powerful impact in improving lifestyles, it has also had an impact on the housing sector. Now real estate is not only about owning a patch of land, but it is also no more about where you are located. Rather, it is more about what you can do within the given area on a more digital level. Would this have an impact on real estate?

According to the forecast by the International Data Corporation’s (IDC) Worldwide Quarterly Smart Home Device Tracker, the global market for smart home devices is expected to grow by 26.9% year over year in 2019 to 832.7 million shipments. As consumers adopt multiple devices within their homes, we can expect this sustained growth to continue with a compound annual growth rate (CAGR) of 16.9% over the 2019-2023 forecast period. And they expect double-digit growth in the market of smart homes.

Talking about Canada, for instance, IDC estimates that half of the Canadian population will be 55 and older in just one generation from now. And most of these potential buyers would prefer an age-in-place or an independent or assisted living environments, which would invariably lead them and their families to invest in smart homes.

Smart home services provide a whole range of benefits. Some are related to monetary benefits while others are related to comfort, all factors that would greatly impact real estate. This has bought some great benefits to real estate firms in closing deals and generating more revenue.

How Realtors Are Winning Tenants With Innovative Mobile Apps

It is Easier to Resell a Smart Home

A vital consideration for an investor is the resale value of the property. The greatest impact home automation systems and devices have on real estate are that they increase the resale value. They usually raise the home value in terms of curb appeal. As smart home technology becomes more prevalent, home-buyers will see the benefits of investing in a smart home.

Adding home automation features and amenities can only do good. Along with location, market, condition, neighborhood, and age of the home, technology is also factored in when determining the market value of that property. Surely a home with smart home devices will have a greater value than a home that doesn’t.

Quicker Selling Time

The formula for selling your house fast is figuring out how to appeal to home-buyers. Multiple factors such as the location of your house, the condition it is in, the price and the features of the property can determine how quickly it will sell.

Marketing your home effectively, featuring smart home technology is another critical step in selling your home fast.  A home buyer would be more inclined to buy a ready to move-in home than having to install smart home features after purchasing the property. Real estate listings with smart home technology upgrades sell faster than homes of a similar price per square foot.

Attract a Variety of Potential Buyers

Smart homes were believed to fit the lifestyles of the rich and famous or technologically gifted few. But now smart home products and systems are adopted by consumers across generations and communities. 

According to statistics, the largest home buyers are millennials. Many of them are attracted to homes that have smart home technology features.  Installing smart home products in a house can provide a millennial home buyer with a “wow” moment when they enter the home and thus improve the chances of attracting them.

The same research also says that single women are also investing in real estate. Installing a smart home security feature in a house can be attractive to a single parent who might be especially interested in security for their home and themselves. 

Related Reading: Check out how Fingent can enable property managers, streamline their operations with PropTech.

Getting Smarter

Smart homes are now the norm. Home automation elevates the wow-factor of a real estate listing. The addition of smart home technology is very attractive to a potential buyer. And we can be sure that as technology continues to evolve, home buyers will continue to be attracted more towards smart homes because of the conveniences it offers.

Along with equipping homes with smart home technology, real estate firms can benefit from other technologies specifically designed to streamline the way they work and bring in business. Contact us for more information on that.  

Understanding The Types Of AI Systems To Better Transform Your Business

In this digital era, industries are witnessing the ability of multifaceted artificially intelligent systems performing tasks that mimic intelligent human behavior or even beyond. Artificial Intelligence today, manage large chunks of data and perform redundant tasks, allowing the human workforce to focus on core tasks. This saves cost and time and improves productivity significantly. 

According to Gartner, the number of industries adopting AI has grown over 270% in the last 4 years. Technology giant, Google pledges $25  million USD in a new AI challenge named ‘AI For Social Good’. Understanding Artificial Intelligence Types, is important to get a clear picture of its potential. 

Related Reading: Check out how Artificial Intelligence is revolutionizing small businesses.

Types Of Artificial Intelligence Calculation: Two Main Kinds Of AI Categorization

AI makes systems imitate human capabilities. Though AI can be classified into different types, the 2 main categories are defined as Type-1 and Type-2 and are based on AI capabilities and functionalities. Let us walk through the major classifications of AI types. 

Type 1: AI-Based On Capabilities

1. Weak or Artificial Narrow Intelligence (ANI) 

Weak or Narrow AI is a type of AI which performs assigned tasks using intelligence. This is the most common form of AI available in today’s industries. The Narrow AI cannot function beyond what is assigned to the system. This is because it is trained to perform only a single specific task.

ANI represents all AI machines, created and deployed till date. All artificially intelligent systems that can perform a dedicated task autonomously by making use of human-like abilities, fall under this category. As the name suggests, these machines have a narrow range of responsibilities. 

Apple’s Siri, for instance, is an example for Narrow AI. Siri is trained to perform a limited pre-defined set of functions. Some other examples include self-driving cars, image and speech recognition systems.  

The category of complex artificially intelligent systems that make use of deep learning and machine learning, fall under the category of Artificial Narrow Intelligence systems. These machines are categorized under the ‘Reactive’ and ‘Limited Memory’ machines, which is discussed in detail going forward in this article. 

Know more about the key difference between deep learning and machine learning.

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2. Artificial General Intelligence (AGI)

General Artificial Intelligence is a type of AI which can perform any intellectual tasks as humans. AGI machines are intended to perceive, learn and function entirely like humans. Additionally, the objective of devising AGI systems is to build multiple competencies which can significantly bring down the time needed to train these machines. 

In a nutshell, AGI systems are machines that can replicate human multi-function capabilities. Currently, researchers around the globe are trying to design and develop such AI. Since there is no example as of now, it is termed, General AI. 

3. Artificial Super Intelligence (ASI)

Artificial Super Intelligent systems can be best described as the zenith of AI research. ASI is intended not only to replicate multi-faceted human intelligence, but also possess faster memory, data processing, and analytical abilities. 

This is a hypothetical concept of AI where researchers are trying to develop machines that can surpass humans. This is an outcome of General AI. 

Top Artificial Intelligence Trends to Watch Out for In 2019

Type 2: AI-Based On Functionalities

1. Reactive Machines

The reactive machines perceive the real world directly and react according to the environment. The intelligence of Reactive Machines focuses on perceiving the real-world directly and reacting to it. An example of reactive machines is Google’s AlphaGo. AlphaGo is also a computer program that plays the board game. It involves a more sophisticated analysis method than that of DeepBlue. AlphaGo uses neural networks for evaluating game strategies. 

2. Limited Memory

Limited memory machines are those that can retain memory for a short span of time. These machines have the capabilities as that of purely reactive machines. Additionally, limited memory machines can learn from previous experiences to make decisions. For instance, self-driving cars are limited memory machines that can store data such as the distance of the car with nearby cars, their recent speed, speed limit, lane markings, traffic signals, etc.

The observations from previous experiences are preprogrammed to the self-driving car’s system. This data, but is transient. That is, it is stored only for a limited period of time. This is because it is not programmed to be a part of the self-driving car’s library of experience, compared to the experience of human drivers.

Nearly every artificially intelligent system today uses limited memory technology. For instance, machines that make use of deep learning is a prime application of limited memory. These machines are trained with huge volumes of data sets which are stored in their memory as a reference model. An example of this is the AI that recognizes images. Image recognition AI is trained using a multitude of pictures along with their labels, as data sets. 

Artificial intelligent systems such as chatbots and virtual assistants are also examples of limited memory machines. 

3. Theory Of Mind Machines

Theory of Mind can be defined as a simulation. To be crisp, when a person considers himself in another person’s shoes, his brain tends to run simulations of the other person’s mind. Theory of mind is critical for human cognition. Additionally, it is crucial for social interaction as well. A breakdown of the theory of mind concept, for instance, can be illustrated as a case of autism.

Instead of a pre-programmed engine, AI scientists are looking forward to developing a series of neural networks. This series will be used to develop the ‘Theory Of Mind’. 

‘Theory Of Mind’ machines are aimed at figuring out someone else’s intentions or goals.  

4. Self-Awareness Machines

Self-Awareness machines exist hypothetically today. As the name suggests, these machines are supposed to be self-aware, like of the human brain. The machines can be described as the ultimate objective of AI scientists. 

The goal of developing self-awareness machines is to make these capable of having emotions and needs as of humans.

Related Reading: You may also like to read about building an Intelligent App Ecosystem with AI.

To learn more about AI capabilities and how it can benefit your organization, drop a call to us right away and gather strategies to implement AI for positive business outcomes!

Tips To Help You Choose Between ERP & Digital Transformation

If you are a business aiming for delivering value to your customers and willing to accept challenges to integrate technology for a better tomorrow, then Digital Transformation is your Nirvana!

Small to large enterprises, require digital transformation to remain ahead of their competitors. The increasing value offered to your customers and digitally transforming your business goes hand-in-hand. According to IDG, State Of Digital Business Transformation, 89% of businesses have accepted their first business strategy as digital transformation. This includes 95% in Services, 93% in Financial Services, and 92% in Healthcare Services, followed by other industries. 

Related Reading: Here’s a guide to help your organization digitize with IoT.

Key Objectives Of Digital Transformation

Digital Transformation is undoubtedly one of the biggest buzzwords of today. Enterprise leaders are looking for strategies to digitally transform their business to leverage the benefits. According to IDC, as per the Worldwide Semiannual Digital Transformation Spending Guide, the worldwide spending on digital transformation, by the year is forecasted to reach $1.97 trillion by the year 2022.

 The major objectives of digitally transforming your business include the following:

• Improved Customer Experience
• Increased Operational Workflow And Agility
• Enhancement Of Workforce
• Better Work Culture
• Integration Of Digital Technology

Related Reading: Check out how Artificial Intelligence Revolutionizes Small Businesses.

How Is Digital Transformation Different From ERP Implementation?

ERP or Enterprise Resource Planning software is a suite of applications that can be customized to allow businesses and enterprises to manage their processes. 

However, with the Lidl software disaster followed by the National Grid lawsuit, enterprises are skeptical about ERP implementation, to the core. Some people consider ERP implementation as a broader form of Digital Transformation. But, both are different in various ways. Let us walk through the following key differences between the two:

• Differences In Technology

Core ERP vendors such as Microsoft, SAP, and Oracle rely on technologies that automate back-office functions. On the other hand, digital transformation makes use of a variety of technologies that include ERP, Artificial Intelligence, Internet Of Things, Industry 4.0, to transform their existing business models. 

ERP is a typical enterprise application that integrates phases of business operations such as product planning, manufacturing, sales, financials, inventory management, marketing, and human resources within a single MVC architecture, that is, in a single user interface, application, and database. 

• Differences In Business Process Management

ERP systems approach business processes by incremental steps towards business processes for incremental benefits. On the other hand, digital transformation approaches business process improvement by “quantum leaps”. That is, only digital transformation supports a reengineering of business processes. 

Business processes can be processed such as customer onboarding, managing insurance claims, etc. The difference lies in the approaches as well. ERP systems take a holistic approach altogether, whereas, on the other hand, digital transformation requires a strategy. 

Additionally, ERP systems aim at providing data and functions to deliver products and services more efficiently to customers. On the other hand, digital transformation enhances the way products and services are delivered to customers. Digital transformation additionally changes even the products delivered to the customers. 

In a nutshell, ERP implementation is automating the existing business processes, whereas digital transformation involves taking quantum leaps for improving business value. Transforming businesses digitally involves business process re-engineering and optimization. Additionally, digital transformation relies on disruptive changes in existing business processes and are open to new business models and strategies on doing business as well.

• Differences In Organizational Change Management

Though there are MNCs are adopting technologies such as SAP HANA, Oracle Cloud ERP, or any other ERP implementation, is likely to witness an organizational change management challenge. Organizational change management associated with ERP implementation aims at training people on how to perform the same processes and transactions in a new system. 

According to its definition, Enterprise Resource Planning Organizational Change Management (ERP OCM), is a framework to manage the impact of new business processes along with the organizational changes in an enterprise. 

However, digital transformations aim at helping the workforce change their job roles to support new business models. Digital transformation makes use of disruptive technology rather than automating the status quo. This is because while ERP systems provide an incremental improvement, digital transformation aims at materially disrupting the existing business model for improvement. This leads to the provision of better products and services to customers. 

In a nutshell, Organizational change management in ERP systems aims at addressing the people side of change management in enterprises. It can be also defined as strategies that help stakeholders and employees migrate from their existing state to a new system altogether. On the other hand, digital transformation changes the existing business model with a disruptive technology mechanism. 

While ERP implementation focuses on achieving greater efficiency with an enterprise’s existing business model, digital transformation disrupts or changes the existing business model. 

• Differences In Providing Business Value And ROI

A recent HBR survey was conducted for certain companies that invested in digital transformation. This survey that polled 2216 employees illustrated that these companies invested in digital transformation and embraced an annual revenue of $500 million. This figure shows that strategic planning on transforming their businesses digitally resulted in increased revenue and reduced costs. 

ERP implementations can deliver a good ROI for enterprises within a few years with all business processes going well. Whereas on the other hand, digital transformation potentially delivers an exponential increase in revenue and considerably reduced costs. This, in turn, leads to enhancements in business value, significant ROI increase, customer loyalty and satisfaction, improved efficiency and other benefits.

• Differences In Employee Strategies

Enterprise Resource Planning systems focus on getting their employees trained on new systems. This transactional training addresses organizational change management concerns. On the other hand, digital transformation aims at employee acceptance strategies of the new systems. Enterprises adopting digital transformation perform so by making use of comprehensive organizational changes and employee transition methodologies.

ERP systems hardly, invest in organizational change management strategies. This, in turn, leads to high failure rates in enterprises adopting ERP implementation. Whereas on the other hand, digital transformation invests largely on organizational change management strategies. This increases the people side support considerably. This largely explains the success rate and improved ROI as well as the increased business value in enterprises adopting digital transformation strategies. 

Related Reading: Check out the Global ERP Technology Trends For 2019.

ERP Implementation or Digital Transformation – Which Is Better For Your Business?

To automate business operations entirely, some enterprises choose a single technology platform. Leveraging on the plethora of technology advancements is the key solution to improving business processes. 

A right Risk Mitigation strategy can work wonders in managing your business processes irrespective of which strategy you choose to implement. To this strategy, it is also required that all employees be equally aligned to this strategy as well.

There is no universal or all-purpose solution as to a perfect business strategy implementation. This is where our experts can provide you with the best roadmap for your business. Our experts can guide you with step-by-step guidance for implementing the best technology that suits your enterprise. Call our strategists right away to learn more about which strategy is best to implement for your business!