Home > Blogs > The Top 3 Jobs FinTechs are Hiring for
The rising customer expectations, increasing e-commerce activity, and aggressive smartphone penetration is revolutionizing the Fintech industry. This has created demand for new talent with multidisciplinary skills across artificial intelligence (AI), machine learning (ML), blockchain- a crucial imperative to enhance operations and address the needs fuelled by digital transformation.
Home > Blogs > Why Industry 4.0 Must Bring University 2.0.
The industrial revolution 4.0 isn’t anything like we’ve seen before. So far, India’s IT sector has progressed, thanks to an abundance of skilled professionals; something that was unique to our country. What we are facing now, however, is obsolescence of the very skillsets that brought us here. The hiring, training, and deploying of systems that worked before is no longer a match for the new-age technologies that are changing the landscape. The industry is battling rapid disruptions while waiting for an unprecedented scale of transformations to catch-up and help solve this workforce crisis.
Source: Manipal ProLearn NextGen White Paper
In what is being termed as ‘India’s largest HR challenge’, the country’s next daunting task is easier said than done: To right-skill 2 million employees within the next 3 years.
Industry 4.0: Opportunities and Evolution
“A crisis not to be wasted!”
The supply gap appears more like a chasm when we see reports of unemployment at massive scale. At the same time, there are thousands of job vacancies requiring candidates skilled in new-age technologies. This is a great paradox.
Pointing fingers at new digital age technologies as the cause of unemployment is pointless. Disruptive technologies are always going to be a result of necessary evolution and not the cause. It is how we educate emerging workforces and retrain existing workforce that decide whether we continue dominating the IT world or perish.
Educating Emerging Workforces
“The solution to Industry 4.0.”
Skill gaps emerge when universities dust their hands off a new batch of graduates and proceed to the next one. How are we to establish an ecosystem of continuous and futuristic learning that paves the path towards the big Indian IT dream, then?
It is no longer a one-time course/degree that can ensure life-long employment, but a continuous endeavor towards upskilling that can achieve it. The responsibility of universities today is to ensure two things. First, their students should possess hard and soft skills to be ready for their jobs. Second, they must have necessary attitude to become a lifelong learner.
Source: Manipal ProLearn NextGen White Paper
The industry, today, is under significant revenue and margin pressure and has slowed down it's hiring (direct employment is expected to reach 4.3 million by 2020). With this 4th revolution bearing down hard, companies only want candidates who are production ready. This means shifting the onus of right-skilling to where it should be - the job seekers. That brings us to University 2.0.
University 2.0: Self-paced, Credit-based, and On-Demand
“Universities of the Future, Now.”
In our globalized economy, technological disruptions have created the need for evolved forms of brick and mortar universities; ones that can enhance the lifelong learning experience of a student. This can be achieved by universities offering a continuous, comprehensive learning system, which, besides offering program to right skill for start of a career, also provides for re-skilling students while they are on the job.
One key step will be to design and develop course content that allows itself to be used across multiple delivery modes. Such content will enable switching between online, blended, or on-campus courses, that can suit various learning styles and learner preferences. These can then be offered as learning credits – be it for award of a degree, or for shorter certifications.
Another important step will be to shift focus from current approach of “learn and do” to “learn by doing”. Students should be asked to work on industry projects, and they should be supported in the same by learning resources – content, courses and faculty as mentors. Modern techniques such as Machine Learning (ML) can be used for granular assessment of student progress and provide valuable insights into a student’s strengths and weaknesses.
Such self-paced, credit-based, and on-demand education will promote a pool of professionals, eager to invest in learning.
This model can create a viable ground for academia-industries partnership. Preparing learners for jobs of the future can become an ‘evolution’, rather than ‘revolution’ when industries and universities collaborate, co-create, and co-invest in programs.
Technology will not stop advancing. And neither should we. India’s re-skilling challenge can be met through an evolved understanding between the three links of this chain: the industry, the jobseekers and the universities. With the right learning environment, professionals in this country will always find themselves equipped enough to handle the jobs of the future.
This article has originally been published in India Today.
Dr. Yogesh Kumar Bhatt
Home > Blogs > Conflict Management at the Workplace
Conflict at workplace often leads to loss in productivity and a confusion among team members. This can further lead to loss of business and reputation. Here are some ways of effective conflict management that you should know.
Home > Blogs > Future of Leadership Development Training 4 Important Characteristics
Traditional approach to leadership development is passé as modern day leadership challenges calls for a new approach. Are you investing the right training to breed new-age leaders? Here are 4 important characteristics of developing an effective leadership development training.
Home > Blogs > 5 ways we can fix India's unemployment crisis
Jobs -- or the lack thereof -- has been a sticking point that not only dominated politically charged debates in the recently held general election but also continues to impact the lives of youth on a daily basis.
In its publication South Asia Economic Focus, Spring 2018: Jobless Growth, the World Bank asserted that India has been creating 7,50,000 new jobs corresponding to every one per cent rise in its gross domestic product (GDP) over long term.
However, if the country is registering an average growth of 7 per cent, it should at least be creating a minimum of 5.25 million jobs.
These figures are reflective of how wide the supply-gap chasm is when it comes to jobs.
However, the underlying problem in India’s mounting unemployment crisis is that the debate is always focussed on aggregated number whereas, in fact, we should be looking at sector-wise figures and the influence of emerging information technology (IT) trends on changing profiles of jobs across industry verticals.
The problem lies in an abundance of workforce with unresolved employability issues. Sample this: the expected supply of people to the IT-BPM (Business process management industry) rests at more than 7 million.
Of these, 1.3 million come from tech backgrounds, with qualifications ranging from diplomas, graduate and post-graduate degree, and PhDs.
Yet, a large pool of this aspiring work force lacks the relevant skills and training to be employable in this sector. As per a survey carried out by the World Bank and FICCI, 64 per cent of employers in this sector are either somewhat or not at all satisfied by the quality of skills possessed by engineering graduates.
The up and coming roles such as Mobile Developers, Data Engineers, UX/UI, Cloud Computing, Software Architects and Data Scientist are also hard to fill.
So, on the one hand, you have millions of qualified youngsters struggling to find employment avenues, and on the other, futuristic job openings are vacant with no suitable candidates to fill them.
That’s why embracing the new and emerging digital economy may well be India’s only hope for solving its unemployment crisis. Here’s how:
1. Re-skill for digital interventions
The first and foremost step towards effectively combating the rising unemployment would be to acknowledge the impact of artificial intelligence (AI) and automation on job growth.
India can no longer afford to brush aside the need for upgrading skills in sync with the market demands.
We are in the midst of a digital revolution and coming out on the other side of it in a prosperous manner would require re-skilling nearly 40 to 45 million workers and creating over 20 million tech-enabled jobs.
Adapting to an inevitable digital intervention is India’s only hope at beating a long-standing job crisis. To do so, focus on quality education and better skill development is fundamental.
A lot of education and training providers are filling in this space by offering future-ready curriculum and training students and professional across campuses, corporate and online platforms. Several online professional learning platforms are emphasizing on fields such as data science, cloud computing, IT, AI, Internet of Things and machine learning now.
2. Seek opportunities in automation
For over two decades, industry growth directly resulted in creation of new jobs. However, technological changes and advent of automation has nearly reversed that trend.
The net job addition in the IT sector alone has dropped substantially over the past five years – nearly 1.05 lakh jobs were created in 2017-18 as compared to 3.01 lakh in 2013-14.
The effects of digital transformation are not limited to the IT sector alone. Almost every sector, be it finance, healthcare, manufacturing or public, can be seen undergoing a paradigm shift to embrace the trends of industry 4.0.
Empowering the existing and upcoming work force with tools such as data analytics, cloud computing, Internet of Things and more can unravel a gold mine of opportunities.
A recent government report on digital opportunity in India predicts the creation of $1 trillion digital economy with 65 million jobs by 2025.
For that to happen, not only will the government have to focus on improving digital infrastructure and policy but also implement radical education reforms. The long-term solution for job growth hinges on harnessing of quality talent in the country.
3. Upgrade and Upscale
Today, there is a sea change in technologies and workings of the IT industry.
Old skills are fast becoming obsolete and a new crop of professionals is being called upon to strengthen the workforce.
This calls for a desperate need to revamp the fresh talent chain. For this, higher education institutions will have to go back to the drawing board and overhaul their curriculum, and companies need to encourage a culture of self-learning.
Incorporating new specifications for certification standards can help create a workforce capable of staying relevant and productive.
This, in turn, would save the employer thousands of crores spent on fresher training and onboarding. The same resources can then be re-allocated for re-skilling and up-skilling existing employees.
4. Leverage opportunities offered by start-ups
Changing mindsets about what constitute lucrative job opportunities can also play a decisive role in streamlining employment avenues.
It is important to acknowledge that the key to employment growth no longer lies with big corporations with thousands of employees but medium and small-scale units.
The enterprises to jobs ratio is the highest in these organisations. Start-ups today are emerging as a bright indicator of growth in India, next only to prosperous economies like the US and China in terms of attracting investments.
These mushrooming companies offer new avenues for employment, especially in the IT and IT-enabled sectors.
Start-ups have also heralded the beginning of a ‘gig economy’, where people are taking up contractual and freelance projects or online assignments, as opposed to the traditional office-based jobs.
India must nurture its own version of the German Mittelstand, if it hopes to someday overcome the job deficit.
5. Market reforms
We are also in dire need of market reforms that go beyond band-aid fixes such as the recent modifications to the Apprentices Act brought about to make hiring young workers more attractive for employers.
It requires a robust information system capable of capturing and disseminating emerging demands for skills swiftly.
This, in turn, can be supported by necessary certification and training programs that cater to these changing demands.
A responsive public-private partnership model that can channelize investments for skill-building to create a demand-supply balance can be an effective way to achieve this.
If India wants to lend real impetus to its job growth initiative, it needs to start by slicing and analysing sector-wise data to under where economic growth has not be matched by an increase in job creation, and why.
A dynamic, nuanced approach to up-skill, reform and embrace industry 4.0 is the only way out of this limbo.
This article has originally been published in Rediff.com.
Dr. Yogesh Kumar Bhatt
Home > Blogs > 4 Ways to Prepare for Digital Marketing 4.0
Home > Blogs > 4 Reasons to Consider a Work Integrated Learning Program
Emerging technologies such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) are fueling a dramatic shift in the job market across industries. According to the Organization for Economic Cooperation and Development (OECD), nearly half of all workers will need to significantly adapt to the new work environment. This shift impacts both employers and employees equally as the jobs of the future will be more hybrid in nature, requiring a combination of hard and soft skills. Employers will need to make massive investments in upskilling employees in addition to hiring employees with relevant skill sets. Professionals, on the other hand, have the unique opportunity to boost their career growth or script a complete career makeover.
One way for employers to upskill workers and employees to capitalize on the opportunity is to tap into a Work Integrated learning (WIL) program - a program that integrates academic learning of a discipline with its practical application in the workplace. Here’s how.
Upskilling without career break
Building a future-ready workforce is a top competitive priority for organizations across industries today. The WIL model of training helps business leaders upskill employees without disrupting their current work engagement. In the IT sector, many organizations like Samsung, SAP Labs and Wipro are embracing WIL programs. Every year Samsung sponsors 35 of its employees to pursue M-Tech in software systems. IT leaders like Wipro are also extending their WIL program to students to launch their careers in IT.
The banking industry is another sector slated for a complete overhaul by 2022. According to FICCI-NASSCOM and EY- Future of Jobs- report, 15%-20% of Indian workforce in the BFSI sector will be deployed in new jobs related to big data, business intelligence, and analytics in the next five years. Creating access to a relevant WILP can help banks future-proof their workforce. Given that many employees cannot afford to break away from work to venture into full time skill upgradation, WILP allows employers to upgrade their workforce’s skills while still keeping their day jobs.
Relevant learning content and networking with industry experts
One advantage of the WIL program is that it taps into the clarity that learners have about their career roadmap. This clarity helps in creating focused learning interventions aligned to the roadmap of the participant. In short, it helps participants immerse themselves in relevant content as well as experiences required for career development such as networking and forging industry connections. WIL sessions are a great way for employees to connect with professionals as instruction is often jointly imparted by the academic subject coordinator as well as an industry supervisor. A LinkedIn global survey points out that 80% of professionals consider ‘networking’ to be an important tool for career advancement.
Experiential learning through application of theoretical concepts
Often, full-time classroom learners do not have an opportunity to apply the knowledge they have acquired in a real world setting. In the case of WIL programs, by virtue of being able to continue with their job, learners can continuously practice the theoretical concepts in real-world scenarios - making knowledge acquisition more experiential. This integration of theory with professional practice leads to better learning outcomes for both employers and employees.
For instance, the intended outcome of the WIL program offered by Samsung is to offer its employees an opportunity to synergize theory with practice on a sustained basis. The curriculum of the course is aligned with Samsung’s focus on research and skill-development in niche areas such as Machine Learning (ML), cloud computing, data mining, data structure and algorithms design, and Artificial Intelligence (AI).
Superior learning outcomes with work-related insights and vice versa
Organizations can fuel their next level of growth with the upgraded skills employees acquire through WIL program. At Samsung, for example, employees following their WIL skill building have been deployed on the company’s futuristic mobile and consumer electronics projects. At the same time, participating in a WIL program creates visibility into two different worlds for the learner – the world of business as well as the realm of skill acquisition. Such insights can be used in identifying skills that have maximum demand and thereby optimize learning outcomes. As per a survey by Clover Infotech, 94% of professionals feel there is a lack of integration between work related insights and learning. A WIL program clearly offsets this.
Given its potential, many consider WIL programs the ‘disruptor’ in the learning industry. Learning is a major focus area for today’s talent, especially millennials. They look for organizations that sponsor their ‘back to school’ trips in meaningful ways. Companies that offer access to WIL programs will be better positioned to meet this growing demand, and in turn, attract the right-fit talent.
Home > Blogs > How Data Analytics Can Help You Become a Better Entrepreneur?
While operating in diverse industry verticals, every entrepreneur shares a common goal – transforming ideas into an operational business proposition. Through the collaboration of multiple business concepts, entrepreneurs move towards achieving success bit by bit. However, the path towards accomplishing this goal is divided, one with influential data insights and the other with presumption.
The entrepreneurial path followed by Amazon, Apple, and Google was not an assumption-based accidental success route. Through the years, these companies have incorporated data-based insights into their processes and operational functioning.
An information-driven business strategy with tangible objectives inspire measurable results and redefine decision-making. Pairing definite objectives with valuable data delivers indispensable information regarding consumer patterns, future prospects, and competitor’s position.
Better Up-selling and Cross-Selling
Research says that data analytics demand has increased by 4X and data visualisation by as much as 25X.
Both data analytics and business intelligence allow entrepreneurs to use patterns related to customers. Identifying these unique patterns linked to separate customer segments offers a peek into up-selling and cross-selling business opportunities.
Listen to Consumers
When selling products and services to a wide range of customers spread across different business verticals, reviewing brand sentiment is necessary. BI and data analytics allow understanding of these emotions exhibited by customers for a particular product or service. Knowing these driving factors that bring customers to the business offers an understanding of how to improve customer experience, cross-sell, and up-sell.
The cross-selling and up-selling thus, created include collaborating different product sections as ‘Purchase Together’ items or offering suggestions which can be purchased on a click. The non-e-commerce entrepreneurs can speak to the customer about the special, valuable additions to the package.
Understand Customer Behaviour
A bird’s eye view of customers’ purchase history and an insight into what they are not purchasing.
Combining this data analytics information with user surveys helps in finding the focus point required to sell the right product. Entrepreneurs can eliminate distractions and reduce noise related to services and products not desired by the customers – focusing only on what is important and helps in solving customer issues.
Further, analysing customer patterns across several touch-points offers a deep knowledge of the why of customer behaviour:
•Which promotions are performing the best? Which promotions are converting?
•What parameters improve the performance of marketing efforts? How this can improve future opportunities?
•What are the issues faced by customers at different touch-points? How can these bottlenecks be removed?
•What concern is stopping the customer from the purchase? Is it the price, the complexity of the website, or the marketing copy?
Entrepreneurs who are just stepping into the industry and starting a new journey lack resources. Data analytics and business intelligence eliminate the lack of resources through competitor analysis. Knowing the performance, patterns, and business propositions of industry leaders, competitors, and other entrepreneurs help in analysing the impact parameters.
The ability to figure out impact parameters and factors allow for the setting of accurate objectives and pathways to reach these objectives. Additionally, the data-based information enhances brainstorming sessions and out-of-the-box thinking to make the service or product better.
Apple didn’t reach where it is now through assumption-based thinking and unsubstantiated arguments. This was achieved with thorough data insights and market information. Similarly, entrepreneurs don’t have to gamble with the business strategy.
Data analytics helps in analysing the key influences of business, market verticals, and customer impact. Based on which, it is possible to accomplish data-based future predictions and decisions. With clear insights into market trends and industry positions, entrepreneurs can become future-ready, always knowing their next move.
Data Analytics for Improved Efficiency
Advanced BI and data analytics help gather valuable information and automate the processing of several data-sets. Drilling down the data insights, achieving correlations, and industry trends drive business success; and understanding the business through its every vertical leads to faster decisions and shorter turnaround time. Undoubtedly, valuable insights reduce work latency and improve the decision-making process.This article has originally been published in Entrepreneur.
Dr. Yogesh Kumar Bhatt
Home > Blogs > How to Make Decisions That Work: Three Things L&D Teams Need to Know about Machine Learning
Automation of mundane processes in departments such as Human Resources and Learning & Development, is old news. However, as companies allocate larger budgets, and assign a seat at the table to L&D departments as strategic partner, it is time for a technology upgrade. Machine Learning has shown a lot of promise with respect to the role it can play in L&D. For instance, it can be used to boost employee engagement, create custom learning content, measure effectiveness of learning programs and determine ROI.
Nevertheless, for a department that has traditionally leaned on human acumen to assess employees and their needs, embracing data driven technologies like Machine Learning (ML) can be perplexing. As a technological disruption that caters to the requirements of the present and the foreseeable future, transitioning to Machine Learning is imperative for L&D. In fact, a recent study indicated that 76% of decision makers believed AI to be a crucial component to overall strategy.
So, how should L&D teams equip themselves to effectively leverage ML technology?
Knowledge about the machine learning process
A survey conducted among professionals across Europe and UAE, indicated skepticism among the workforce towards AI adoption. Less than 20% of them were comfortable with accepting an AI based decision, over one made after human judgement. Moreover, 66% of the respondents believed their organization was unprepared to adopt AI based technology. These findings point to the need for L&D teams to have an extensive understanding of the Machine Learning technology that their organization’s use.
An in-depth understanding about the intricacies of ML can help L&D professionals leverage the technology to devise efficient and creative solutions. Furthermore, L&D teams can use this knowledge to address the apprehensions of the workforce regarding the technology, and encourage them to adopt and engage with the new platform.
Understanding the different algorithms
Analyzing copious amounts of data may be cumbersome for humans, but Machine Learning platforms thrive on large volumes of clean data. It is thereby essential for L&D departments to choose the optimal algorithm that can furnish actionable insights, while minimizing burden on the teams.
One of the more commonly used ML algorithms is ‘supervised learning’ which involves human intervention. Here the platform is supplied with data, and is trained to search for, and recognize particular patterns. The performance of the algorithm is then adjusted until it delivers accurate results. This type is often used to forecast future trends based on historic data. On the other hand in ‘unsupervised machine learning’ the application sifts through all the data, instead of being fed select information. With this type of algorithm, the ML platform has the potential to discover latent data trends and other significant information. However, both the algorithms require human intervention to decipher the results.
Supervised learning is a better option for those that want to evaluate the efficacy of the algorithm since the desired outcome is predefined. However, the effectiveness of unsupervised learning algorithm is more difficult to comprehend, since the value of the outcomes could vary.
Drawing insights from data
Usually, L&D teams collect and sift through a barrage of data generated from HR tools and learning and management systems (LMS). However, the real challenge is in analyzing the data and gaining insights that foster a more efficient and productive L&D program. Machine Learning platforms enable organizations to gain a deeper understanding of learners, facilitating the creation of personalized training modules with adaptive learning capabilities.
In upskilling, ML led programs help L&D teams build augmented content that drives better engagement. For instance, by studying the pattern of pausing, skipping and stopping of video content in particular sections, teams can understand effectiveness, identify the types of information that the learner seeks, as well as determine the optimal format.
Moreover, current learning platforms leverage Machine Learning to obtain predictive analytics driven insights that forecast outcomes based on past data. L&D teams can build detailed reports based on these results, to gauge efficacy and assess return on investment (ROI). They can also use these reports to ascertain individual training needs, and leverage their understanding of trends to avert issues in time. Furthermore, L&D teams can derive useful metrics that help quantify success, and recommend training paths.
When it comes to Learning & Development in organizations, the culture of continuous learning and upskilling is becoming part of the company culture. So it’s essential for L&D teams to meet the demand through optimal channels. Studies show that the completion rate of MOOC course is only 10-15%. Equipped with in-depth understanding of Machine Learning, L&D teams can have better success by designing custom programs with relevant content that are disseminated in the right channels at the right time.
Home > Blogs > Re-Skilling for 5G Success
From enabling businesses with a major technology boost to creation of millions of jobs, 5G can help the business ecosystem grow. Here are 4 key skills sets and how they will grow with the onset of 5G