distributed cloud

Distributed cloud is the new enterprise IT frontier

by | Jun 16, 2021 | IT Services

Cloud providers vie for pole positions as they gear up to compete in an upcoming hyperscale computing era.
Share to lead the transformation

A titanic struggle for control of the cloud has begun in earnest by the emergence of various distributed cloud architectures. The shift is being driven by the need for enterprises to move away from traditional infrastructure-aspect-management to ‘utility cloud’ models, which can be far more sustainable as long-term strategies.

Amazon Web Services, IBM, Google, and Microsoft are the giants whose bet in the development of such virtualization technologies has won them large shares of the cloud market. Several other companies are also active in this arena, and a closer examination of the main players may reveal a number of smaller players too.

distributed cloud

Multiple drivers are fueling growth

The star attractions of distributed clouds include (1) low latency due to proximity to user organizations (e.g., on-premises delivery or edge delivery); (2) better adherence to compliance and data-residency requirements;  and (3) rapidly growing number of IoT devices, utility drones, etc.

With distributed cloud services, the service providers are moving closer to the users. These cloud services are offered not just as public-cloud-hosted solutions but also on the edge or the on-premise data center. This approach of having a SaaS model with an on-premise application has its own advantages like ease of provisioning new services, ease of management, and cost reductions in the form of greater operational efficiency brought about by streamlined infrastructure management.

Cloud service providers have a deep understanding of both the needs of enterprises and their unique business requirements. They use their expertise to develop solutions that meet these objectives. They are also well known for providing easy accessibility to their services from the internet. This enables fast and convenient access for end-users.

Enterprises may think that by switching over to a distributed cloud computing service they will lose control of their data. However, the cloud service providers enable excellent security and monitoring solutions. They also ensure that users are given the highest level of access to their data. By migrating on-premises software to a cloud service provider, enterprises do not stand to lose the expertise that their employees have built up during their time in the organization.

Google Anthos: A first-mover advantage

Google formally introduced Anthos, as an open platform that lets enterprises run an app anywhere—simply, flexibly, and securely. In a blog post, dated 9 April 2019, Google noted that, embracing open standards, Anthos let enterprises run applications, unmodified, on existing on-prem hardware investments or in the public cloud, and was based on the Cloud Services Platform announced earlier.

The announcement said that Anthos’ hybrid functionality was made generally available both on Google Cloud Platform (GCP) with Google Kubernetes Engine (GKE), and in the enterprise data center with GKE On-Prem.

Consistency, another post said, was the greatest common denominator, with Anthos making multi-cloud easy owing to its foundation of Kubernetes—specifically the Kubernetes-style API. “Using the latest upstream version as a starting point, Anthos can see, orchestrate and manage any workload that talks to the Kubernetes API—the lingua franca of modern application development, and an interface that supports more and more traditional workloads,” the blog post added.

AWS Outposts: Defending its cloud turf

Amazon Web Services (AWS) has been among the first movers. On 3 December 2019, the cloud services major announced the general availability of AWS Outposts, as fully managed and configurable compute and storage racks built with AWS-designed hardware that allow customers to run compute and storage on-premises, while seamlessly connecting to AWS’s broad array of services in the cloud. A pre-announcement for Outposts had come on 28 November 2018 at the re:Invent 2018.

“When we started thinking about offering a truly consistent hybrid experience, what we heard is that customers really wanted it to be the same—the same APIs, the same control plane, the same tools, the same hardware, and the same functionality. It turns out this is hard to do, and that’s the reason why existing options for on-premises solutions haven’t gotten much traction today,” said Matt Garman, Vice President, Compute Services, at AWS. “With AWS Outposts, customers can enjoy a truly consistent cloud environment using the native AWS services or VMware Cloud on AWS to operate a single enterprise IT environment across their on-premises locations and the cloud.”

IBM Cloud Satellite: Late but not left out

IBM has been a bit late to the distributed cloud party. It was only on 1 March 2021 that IBM announced that hybrid cloud services were now generally available in any environment—on any cloud, on premises or at the edge—via IBM Cloud Satellite. The partnership with Lumen Technologies, coupled with IBM’s long-standing deep presence in on-premise enterprise systems, could turn out to be a key differentiator. An IBM press release noted that Lumen Technologies and IBM have integrated IBM Cloud Satellite with the Lumen edge platform to enable clients to harness hybrid cloud services in near real-time and build innovative solutions at the edge.

“IBM is working with clients to leverage advanced technologies like edge computing and AI, enabling them to digitally transform with hybrid cloud while keeping data security at the forefront,” said Howard Boville, Head of IBM Hybrid Cloud Platform. “With IBM Cloud Satellite, clients can securely gain the benefits of cloud services anywhere, from the core of the data center to the farthest reaches of the network.”

“With the Lumen platform’s broad reach, we are giving our enterprise customers access to IBM Cloud Satellite to help them drive innovation more rapidly at the edge,” said Paul Savill, SVP Enterprise Product Management and Services at Lumen. “Our enterprise customers can now extend IBM Cloud services across Lumen’s robust global network, enabling them to deploy data-heavy edge applications that demand high security and ultra-low latency. By bringing secure and open hybrid cloud capabilities to the edge, our customers can propel their businesses forward and take advantage of the emerging applications of the 4th Industrial Revolution.”

Microsoft Azure Arc: General availability awaited

Julia White Corporate Vice President, Microsoft Azure, in a blog post, dated 4 November 2019, announced Azure Arc, as a set of technologies that unlocks new hybrid scenarios for customers by bringing Azure services and management to any infrastructure. “Azure Arc is available in preview starting today,” she said.

However, the general availability of Azure Arc was not to be announced anytime soon. Six months after the ‘preview’ announcement, Jeremy Winter Partner Director, Azure Management, published a blog post on 20 May 2020, noting that the company was delivering ‘Azure Arc enabled Kubernetes’ in preview to its customers. “With this, anyone can use Azure Arc to connect and configure any Kubernetes cluster across customer datacenters, edge locations, and multi-cloud,” he said.

“In addition, we are also announcing our first set of Azure Arc integration partners, including Red Hat OpenShift, Canonical Kubernetes, and Rancher Labs to ensure Azure Arc works great for all the key platforms our customers are using today,” the post added.

The announcement followed Azure Stack launch two years earlier, to enable a consistent cloud model, deployable on-premises. Meanwhile, Azure was extended to provide DevOps for any environment and any cloud. Microsoft also enabled cloud-powered security threat protection for any infrastructure, and unlocked the ability to run Microsoft Azure Cognitive Services AI models anywhere. Azure Arc was a significant leap forward to enable customers to move from just hybrid cloud to truly deliver innovation anywhere with Azure, the post added.

Looking ahead

A distributed cloud presents an incredible opportunity for businesses that are looking to improve their bottom line while also increasing their agility and versatility.

A distributed cloud is essentially a distributed version of public cloud computing which offers the capability to manage nearly everything from a single computer to thousands of computers. The cloud promises the benefits of a global network without having to worry about hardware, software, management, and monitoring issues. The distributed cloud goes a step further and also brings the assurance on fronts such as latency, compliance, and on-premise application modernization.

MORE FROM BETTER WORLD

AI tools can drive big efficiencies in oil and gas

AI tools can drive big efficiencies in oil and gas

The role of artificial intelligence (AI) is evolving, especially in industrial organizations such as oil and gas, where data acts as a critical enabler to provide a competitive advantage. Industrial organizations operating in the fields of mining, oil, and gas; and marine, are going through a radical transformation and seeking innovative ways to optimize performance with minimized risk.

The volatile and ever-competitive nature of the industrial companies demands them to identify new and innovative sustainable models to stay profitable, grow and unlock efficiencies. The situation has become more challenging in the wake of the coronavirus pandemic. According to a Capgemini research, over 50% of the European manufacturers, 30% in Japan, 28% in the USA, and 25% in South Korea implement AI solutions.

Enterprises operating in Oil and Gas, Marine, and Oil use traditional machinery which may not be easily replaceable because of the huge costs associated with it. Hence, they need advanced technologies to optimize their operations. They are the ones where data could act as a critical enabler to provide them a competitive advantage if managed with the right combination and tools. (See: How will AI impact enterprise ecosystems in 2021?)

Intelligent machines, optimized production

An estimate from the Robotic Industry Association says the cost of one minute of production-line downtime for a company like General Motors could be around $20,000. That’s enormous!

AI for industrial organizations has become essential for driving operational efficiencies of their assets and processes. With AI and ML advancements, industrial enterprises can make their machines smarter, predict maintenance schedules, minimize downtime and let the devices identify problems sooner, and even rectify them automatically in some instances.

Industrial organizations have an enormous amount of data from their different manufacturing processes. However, the lack of talent and necessary tools prevent them from leveraging the same for deriving meaningful insights.

By monitoring and analyzing data carefully, industrial organizations can anticipate the gaps in the output and receive automated warnings to stop the machine when there is an issue. This helps save cost and time, assisting companies to better their efficiencies. For instance, by leveraging AI-based predictive tools in oil and gas, companies can identify the machine and pipeline deterioration signs and raise alarms to pipeline operators. The use of voice-enabled AI chatbots can also help in oil and gas and mining areas, whereby operators can engage in meaningful automated conversations around the processes, focusing solely on production-related activities.

The supply chain is another crucial process gaining substantial benefits from the AI and ML-driven applications, ensuring industrial companies create equipment buffers as per the real-time market demand. Besides, AI capabilities are also being used extensively for manufacturing and industrial companies to reduce energy consumption, minimize assembly lead times, and increase asset utilization.

Key challenges

The challenge, however, for the industrial organization is a widening gap in the knowledge and competencies of various enterprises’ internal IT departments. The shortage of internal talent to deploy and scale AI in production and integrate with existing standardized solutions.

The successful predictive maintenance strategy is heavily dependent upon the data to integrate necessary engineering in the machinery. Data can not bring efficient results in case they are working in seclusion.

The industry needs strong foundations and collaboration models to create new enterprise-specific applications to analyze data and automate critical processes. Another major challenge that many enterprises need to deal with is managing the people and cultural change. It becomes necessary for organizations implementing AI solutions to conduct essential workshops and focus group discussions on understanding the pain points and queries of their employees.

As we move forward in 2021, AI for industrial organizations will see greater demand as they focus on reducing time to impact and balance their supply chains according to the real-time demand. The industry is likely to witness a steep rise of several integrated solutions from emerging solutions providers and specialized companies to help Industrial companies drive further innovations.

Star-Disney India ropes in Tirthankar Dutta as CISO

Star-Disney India ropes in Tirthankar Dutta as CISO

Tirthankar Dutta, CISO, Star-Disney India

Tirthankar Dutta, CISO, Star-Disney.

Tirthankar Dutta has joined as the Vice President (VP) and CISO of Indian media conglomerate Star-Disney India, a Walt Disney subsidiary in India.

In his new role at Star-Disney, Dutta will spearhead the company’s security transformation initiatives and provide the necessary direction and guidance to the CTO/CFO and key Disney-Star business leadership members.

Besides, Tirthankar Dutta will also manage information security governance processes, chair the information security advisory committee, and lead information security programs and project priorities at Star-Disney. He will be internally assessing and providing necessary recommendations around security controls to the Disney leadership in India. Dutta’s responsibility also includes establishing an inclusive and comprehensive security program for Disney and developing essential support for internal information systems and technology research capability.

As an IT professional with over 14 years of experience, Dutta has led several IT and IT security projects in top financial services, travel shopping, and IT services companies such as Religare, Expedia, HCL, TCS, and IBM.

Dutta has established and implemented large information security programs, including deploying a patent-pending fraud detection solution that protected thousands of clients from phishing attacks. He has been credited with performing evaluation and selection of IT security tools and successfully implemented IT security systems to protect availability, integrity, and confidentiality of critical business information and information systems.

Before moving to Star-Disney, Dutta was the Sr VP and Head of Information Security at Infoedge India, a pure-play internet classified company. At Infoedge, he led the information security program and built cohesive security and compliance programs to address state and Country statutory and regulatory requirements effectively.

About Star India

Owned by the Walt Disney Company, Star-Disney India is an Indian media conglomerate with its headquarters in Maharashtra. The media company offers content in eight languages through its 60 channels. Its network reaches approximately 790 million viewers a month across India and globally.

For other recent C-Track movements, click here.

Five key steps to a successful RPA implementation

Five key steps to a successful RPA implementation

The Robotic Process Automation (RPA) adoption in India has picked up pace as enterprises focus on developing automated intelligent process automation bots to support their users and employees round the clock. (See: RPA-led tools helping enterprises sail safely through a storm). Despite the benefits RPA offers, many companies struggle to maximize the value of their RPA implementations. Let’s delve deeper into some of the critical steps to a successful RPA implementation for enterprises.

These steps can also ensure there is no gap between reality and expectations from an RPA initiative.

#1. Define your objectives 

RPA is a game-changing digital transformation initiative, automating several traditional mainframe applications by leveraging AI/ML-based software robots. At the backdrop of the pandemic triggered economic slowdown, businesses are increasingly exploring intelligent automation and RPA for refining quality while controlling costs.

According to McKinsey, RPA can deliver up to 200% ROI in the first year of deployment and 20-25% cost savings. Additionally, it also enables organizations to enhance compliance, become risk-averse and strengthen the customer experience. The mundane and time taking processes turn fast, and users get an opportunity to switch to higher-value work.

However, like every strategic technology investment, RPA investments need to be evaluated based on their potential utility to a particular enterprise or a process.

There is no one size fit all solution! As a first RPA implementation step, the process you select for RPA should be carefully mapped against your end-goals. Before you assign the process execution from your employees to bots, you need to set clear goals around what you want to accomplish from a specific RPA implementation and the financial aspects of the deployment.

#2. Select your processes intelligently

An overarching strategy for process selection and implementation should be in place before you move to RPA. The most critical goal that drives RPA adoption is achieving enterprise efficiency for highly repetitive tasks. RPA tools imitate a human being’s actions by following a rule-based structured approach to accomplishing specific routine tasks, helping employees retrieve a significant proportion of their time.

Hence, as a key step for a successful RPA implementation, the process you select for RPA should be mature, predictable, and stable, high-volume, involve a considerable amount of repetitive human efforts, based on pre-defined data patterns, and evaluated on measurable savings. For instance, data validation, extracting data from PDFs, and employment history verification.

#3. Build an execution team

It is paramount for any automated process that a group of team members is assigned to keep a closer look at all the change-related developments and flag any inconsistencies. This team is often called as Center of Excellence (CoE) team for RPA projects.

Enterprises that do not have the right capabilities and resources or deploy the RPA model for the first time can also support specialized external consultants to facilitate RPA implementations effectively.

#4. Develop a robust change management plan

The success of any RPA initiative is dependent mainly upon how internal employees perceive the change.  Similar to any other digital transformation initiative, RPA is also bound to cause apprehension among impacted employees.

While some team members may follow a cautious approach for any recent change, others may like to debate the relevance of change. Moreover, there could be a fear of job losses, change of roles, the transition to a new team, anxiety around lack of training to supervise any new tool, and more.

A robust change management plan includes addressing these fears and anxieties, upskilling and reskilling impacted teams, setting up a robust governance framework, providing the necessary knowledge to groups about the positive impact that RPA will bring for the business. The technology heads and project leads should encourage people to ask relevant questions and engage them through focus group discussions or one-on-one interactions to understand the objectives behind the RPA implementations.

#5. Make sure to conduct the pilots

Any automation process is a long-term journey and needs sustained efforts for success. Do not expect to gain immediate benefits by deploying software robots. It’s a continuous process and needs several pilots before you ultimately obliterate any process-related obstacles or iron out flaws for a smooth run. It is advisable to have a multiple-phase rollout if the process spans several business operations geographies and impacts people from across teams.

Planning for pilots is one of the essential steps to any successful RPA implementation. Pilot implementations of RPA provide an excellent operating overview of the control frameworks, governance structure, and training to ensure that objectives align with expectations; remove reserves, if any;  and get buy-in from key stakeholders.

The growing web of digital payment frauds

The growing web of digital payment frauds

The rapid maturing of digital technologies and contactless payments have made lives of businesses and consumers easier. During the pandemic-stricken, confined ecosystem, enterprises quickly moved to digital and incorporated new digital payment and supply chain models. Consumers were also quick to shift to new behavior patterns and replaced in-store shopping with online shopping. Along with merchants and consumers, cybercriminals switched to new ways as well to expand their malevolent and fraud activities.

The upsurge in the online ecosystem is likely to create a brand new generation of digital customers in 2021. As digital experiences continue to become mainstream, cybercriminals are sensing an unprecedented opportunity to use new tricks and technologies to weave a deep fraud web around the gullible people and vulnerable IT networks.

Pandemic fueling fraud surge

By leveraging the latest technologies and network vulnerabilities, fraudsters explore new ways to target individuals and enterprises who lack adequate knowledge or cybersecurity tools to defend themselves.

Consider some statistics to understand the gravity of the situation: India witnessed over 2.9 lakhs cybersecurity incidents related to digital banking in 2020 (Source: CERT-In); a few months back, grocery delivery major Bigbasket faced a data breach, revealing data of 2 crores of its registered users; according to various industry reports, data breaches cost Indian firms Rs 15 crores yearly on average; FICO, a US analytics company revealed that four in five Asian banks are losing money to fraud as real-time payments rise.

The above data is just the tip of the iceberg. With the pandemic as a backdrop, digital payment frauds can upsurge even further.

Unified Payment Interface (UPI) emerged as one of the easiest ways to transfer money through Google Pay, Paytm, PhonePe, Freecharge, and others. This trend, however, also gave birth to various frauds associated with UPI payments.

The situation’s enormity can be fathomable as fraudsters didn’t even spare the Delhi chief minister’s daughter, as reported by various media outlets recently. She recently fell victim to an online payments scam while selling a piece of old furniture on an e-commerce platform. Last year, an Indian Air Force officer too fell prey to one such scam. The UPI-related frauds are even more concerning as India target massive uptake of digital transactions in the next few years, up from the current 46 billion.

There are also instances where users have fallen victim to fake shopping websites and transferring money by relying on unauthorized payment links received through SMS.

In one of the advisories issued in 2019, the Reserve Bank of India had warned all banks to take robust measures to prevent digital banking frauds that can wipe out the entire balance of a customer using UPI technology. With the more users connected to the mobile and the internet, such incidents are ordained to increase.

AI, ML, and user awareness

It is reasonable that most new customers moving to digital payments lack the knowledge and can be tricked by fraudsters to make security mistakes or provide sensitive information about their accounts. It becomes essential for enterprises and banks to take the necessary steps to combat digital payment frauds in such a scenario. (See: AI in banking now geared for a takeoff)

Enterprises and banks overhauling their payment and customer interface mechanisms by integrating digital pieces need to embed technologies such as machine learning and artificial intelligence to provide a secure and frictionless payment experience to customers.

By leveraging AI and ML algorithms’ competencies, the network can flag anomalies and derive a risk pattern, approving or declining a payment. In the year ahead, AI-enabled virtual chatbots will also play a pivotal role in enhancing user awareness and answer all payment-related queries. Enterprises are also testing predictive and prescriptive analysis to identify fraud in digital payment transactions.

There is a strong need for the industry to come together and make appropriate investments in next-generation security frameworks, real-time fraud monitoring solutions, and knowledge sharing programs to outsmart cybercriminals and strengthen consumers’ confidence in digital payments.

Digital transformation deals put IT sector back on track

Digital transformation deals put IT sector back on track

Buoyed by a rapid acceleration in digital transformation service deals, the Indian IT industry is back on the growth track, leaving behind the pandemic’s impact. In its strategic review 2021, titled ‘New World: The Future is Virtual,’ Nasscom estimated the IT industry to clock revenue of $194 billion in FY21, up from $190 billion a year back, registering a growth rate of 2.3% year-on-year. While the numbers may still be well-short of pre-pandemic 6-7% growth levels, Nasscom projections are really encouraging for one of the major industries in India.

The Indian IT industry is also likely to add over 138,000 new hires during the FY2020-21, taking the total employee base to 4.47 million. Much of this new workforce is expected to support the new-age technologies such as artificial intelligence, the internet of things, cloud analytics, automation, DevOps among others.

According to the Nasscom review, the indigenous domestic market, driven by hardware-led demand, continued to show resilience, growing at 3.4% in the year.

“As we look at 2021, while there are positives on the vaccination front and accelerated digitization across verticals, the technology industry in India is well geared to build on these trends and continue its transformation journey in this re-defined techad,” said Debjani Ghosh, President, NASSCOM.

The Indian IT industry is benefitting from the strong demand for digital transformation technology deals from Europe and Asia-Pacific (APAC). Sectors such as BFSI and healthcare are likely to continue to invest significantly in digital transformational technologies in the year ahead. (See: TCS finds its new growth mojo in DX)

A quantum leap for DX initiatives

Nasscom’s assessment is not surprising since the Indian IT industry has shown remarkable resilience in the last year and played a pivotal role in accelerating economic growth, enabling businesses to overcome supply and demand disruptions through digital transformation.

The disruption caused by the pandemic was terrifying for many enterprises as they were inexperienced in managing an upheaval of such magnitude. The crisis left them no option but to fast-track their digital transformation (DX) plans to meet the evolving market needs, interact with customers and employees. The immediate focus was to deploy technology solutions to enable the remote working for their workforce and increase business resiliency.

Indian IT services majors are also making continuous efforts to build new digital transformation capabilities in India and enhancing their focus on delivering more thoughtful, practical solutions to construct agile, integrated, simplified, and customized environments for their customers. This trend is likely to create further opportunities for IT firms to accelerate digital transformation deals in India and beyond through strategic mergers and acquisitions. Notably, in 2020 alone, the industry witnessed 146 M&A deals, 90% of which were digitally focused.

“Digital transformation is the topmost priority for global corporations, and in a highly connected world that will remain largely contactless for an extended period, there are shifts in business models, customer experience, operations, and employee experience. Our CEO survey for 2021 indicates that almost 70% of companies expect investment in global technology higher than the previous year. In this hyper-digital economy, trust with the four cornerstones of competence, reliability, integrity, and empathy will be the single-most-important currency, leading the industry growth towards a better normal,” says UB Pravin Rao, Chairman, NASSCOM in a media and analyst release.

Long-term impact

The impact of the crisis is going to be experienced for a long time. While the rapid vaccination program might pacify the COVID-19 effect by the end of 2021, the enterprise tech leaders in India will continue to rely on the cloud and AI-based contactless technologies to open their physical offices cautiously. (See: CIOs’ digital transformation focus accelerates recovery for IT firms)

Digital transformation in India and the global market will continue to see a significant focus in the year ahead as companies look to accelerate growth, innovate and compete at pre-Covid levels.

AI and ML adoption transforming recruitment workflows

AI and ML adoption transforming recruitment workflows

Megha Talpade (name changed), the talent acquisition leader of a leading organized retailer, is in a state of a quandary these days. Just like many other retailers, her company also faced hardships due to the pandemic that caused the shutdown of malls and shops for several months last year. However, as things are getting back to normal, Talpade has been assigned by the leadership to formulate a recruitment plan to expand the operations and sales team. As we continue through 2021, talent acquisition leaders like Talpade have no other option but to explore transforming the recruitment process through technologies such as AI and Blockchain to source the best talent in a cost-efficient way

What could have been a routine hiring exercise before the pandemic has suddenly looked like running a marathon! With the need for social distancing and safety likely to remain the top priority even in the waning pandemic scenario, shortlisting candidates through heaps of data and onboarding hundreds of new employees through traditional processes look like an inconceivable approach for talent heads. (See: How will AI impact enterprise ecosystems in 2021?)

Reimagining hiring experience through AI

AI is fast emerging as a top technology to transform the future of recruitment. AI-based screening tools empower companies to validate a specific number of criteria before sending the hiring managers’ selected profiles. Since the applications for a job have increased multifold after the pandemic triggered slowdown, it is no longer possible for companies to take the conventional route to shortlist candidates without a resume analysis tool.

Many companies are now looking forward to using AI to transform their recruitment processes and meet their hiring goals.

For instance, Vodafone started using AI to recruit call-center and sales staff in 2017 and has been pleased with the results. Similarly, Cathay Pacific, one of the world’s leading airlines, utilized AI-based platforms to reduce the hiring time for customer service and flight attendant roles from 3 months to 2-3 weeks.

By integrating AI-based analytical tools, talent acquisition teams can focus on the best candidates that match their core profile requirements. The algorithmic process can also scan candidates’ online behaviors by screening their publicly available comments and social media profiles and list the candidates as the top choice, recommended and not recommended at all.

AI tools can also analyze candidates’ facial movements, body language, and verbal skills through real-time AI scanning programs.

According to the 2019 State of Artificial Intelligence in Talent Acquisition report by Oracle, About 73% of organizations expect AI to increase recruitment speed, and 53% expect it to boost the overall productivity of the recruitment function. By 2022, the percentage is likely to go even higher.

In addition to screen the candidates, AI-based tools are also effective for conducting remote interviews through conversational chatbots or robots. Interactive chatbots can help businesses resolve candidates’ queries promptly and guide them with the onboarding and re-boarding process.

Credential verification through Blockchain

Blockchain technology enables hiring managers to access the complete and accurate employment history of a potential candidate. Leveraging its digital recordkeeping capability, Blockchain validates the CV of the jobseeker and removes any possibility of the candidate hiding an undesirable history. 

This means applicants cannot hide their professional historical data and credentials. It will give employers a better insight into their candidates’ natural strengths and weaknesses and assess them better for a given role.

The future will see a massive role of technology in recruitment cycles. Most of these technologies are governed by business logic, making it possible for enterprises to structure the patterns per specific inputs and solve many critical leadership hiring problems. While still at a nascent stage, 2021 is expected to see new use cases of Blockchain and likely play a key role to transform the recruitment processes.

Accelerating skills evaluation by leveraging AR and VR

These immersive technologies that were earlier restricted to the gaming industry can deliver substantial value in the new age recruitment process. By leveraging the advantage of AR and VR, companies can evaluate a candidate in an actual set-up, showcase their brand effectively and test the ability of a candidate to manage complex situations and analyze their resilience levels.

AR and VR can also make the entire recruitment cycle more engaging and exciting. For instance, Siemens was one of the first companies that started using AR and VR for driving recruitment almost a decade back. In 2011, the company had launched Plantville, an online gaming platform that simulates the experience of being a plant manager. Potential hires were given the challenge of maintaining a plant’s operation while strengthening the productivity, efficiency, sustainability, and overall facility health.

Since its launch, the game has helped Siemens build brand awareness, engage thousands of customers, and recruit several engineers.

While all these technologies hold great potential and are expected to play a pivotal role in mechanizing the top talent search and transforming the HR practices, they are yet to overcome obstacles like bias fully to make it wholly reliable. For instance, about three years ago, Amazon removed a secret AI recruiting tool from its hiring process that started to display prejudice against women candidates. For an enterprise looking at transforming its HR and recruitment practices, the best way is to identify your actual needs and partner with the right technology partner to harness the technology and increase the scope of hiring.

In adopting technologies like AI and Blockchain for talent acquisition, Talpade seems to have certainly taken note of this!

0 Comments

Submit a Comment

Your email address will not be published. Required fields are marked *