The DNA of a Good Leader (PART I)

Rajeswari S

In our lives, we would have come across some people with great leadership qualities. They may not be leading a team, or an organization, but they exude an aura. They conduct themselves in a manner that sets them apart from the rest. As the debate rages on whether leaders are born, made, discovered, innovated, invented!? Let’s see what makes a person a true and admirable leader.

Generally, a good leader should be successful, progressive, and positive, must possess good personality traits, communication and delegation skills, charisma, agility, adaptability, and ability to transform the air around them by effecting positive changes.

Some people are able to bring out the best in others and that is the edge they have over others. So, let’s look beyond and list out those qualities that makes a person or YOU a quintessential leader.

  1. Be passionate: Obviously, you would think it is the dedication, commitment for one’s work to up the number of clients, revenue figures, etc. However, it is not just about that. The passion that you have which affects not only your attitude and energy but that of those around you. Your passion should spread like a wildfire and inspire action and positive change among others.

  1. Face obstacles with grace: If any leader knows exactly what a customer or market truly wants from the business, they would be hailed as no less than a God! But alas, life is always full of obstacles, and a true leader knows which battles to fight and how. Effective leaders approach roadblocks with a high level of positivity and maturity. They adopt creative problem-solving techniques that allows them to overcome situations that others might give up on.
  1. Allow honest mistakes, spot talents: An over-protected child learns nothing and cannot sail against the tides. A good leader allows their people to just GO FOR IT! Failure often provides us with some of life’s biggest learning opportunities. As uncertainty and risk are inherent to running a team or business. Some people do commendable jobs under high pressure situations. A good leader spots such resources in their team and makes the best use of their qualities.
  1. Be street smart: It’s hard to find a substitute for old-fashioned street smarts. Knowing how to trust your gut, quickly analyzing situations as well as the people you’re dealing with and knowing how-to spot a bad deal or scammer is an important aspect of leadership. Maturity and experience complement each other, and a perfect combination of this makes a great leader.
  1. Be intuitive and take ownership: Intuition is to art as logic is to math. Leadership is often about following your gut instinct. It can be difficult to let go of logic in some situations but learn to trust yourself. Having said that, if your instinct fails, leadership is also about taking ownership for what happened, learning lessons from it and NEVER TO REPEAT THE SAME MISTAKE.
  1. Understand opportunity cost: Leaders know that many situations and decisions in business involve risk and there is an opportunity cost associated with every decision you make. An opportunity cost is the cost of a missed opportunity. This is usually defined in terms of money, but it may also be considered in terms of time, man-hours, or any other finite resource. Great leaders understand the consequences of their decisions before making them.
  1. Be liked: You can respect a person who talks flamboyantly, has a brilliant mind, impeccable manners, and business skills, but do you LIKE them? A leader should not only be respected but they should also be liked. Liking a person is a not a quantifiable quality, is it? But, it can be achieved in the way a leader captains the team, spreads a positive feeling among them and make the group feel that they belong there.
  1. Laugh: Yes…you read it right. The proven routes to a person’s mind or heart is a healthy sense of humor. It works well in getting the best out of your team. Nobody likes a templated talk or expression, even if it is good news you are trying to convey. Also, effective leaders can laugh at themselves as they understand that they are also humans and can make mistakes like everyone else. Leaders who take themselves too seriously risk alienating people.

Unique brands of Leadership

A quick look at some successful CEOs, new-age entrepreneurs, and their unique leadership mantras:

  1. Satya Nadella, CEO, Microsoft

Leadership mantra: 

  • An avid reader
  • Looks beyond the Horizon
  • Makes the right move at the right time
  • Makes every second count
  • Nurture strong company culture 
  1. Nitin Saluja and Raghav Verma, Founder, Chaayos, fastest growing tea startup of India,

Leadership mantra: Give people wings to fly and they will carve out their own journey.

  1. Mukesh Ambani, Chairman & Managing director, Reliance Industries Ltd

Leadership mantra:

  • Money is not everything but important
  • Have a dream and plan to fulfill it
  • Let your work speak for itself  
  • Trust your instincts
  • Trust all, but depend on none

References:

  • https://briandownard.com,
  • https://economictimes.indiatimes.com

About the Author –

Working in IP, into Content Development with 13 years of Technical, Content and Creative Writing background. Off-work, passionate about singing, music, creative writing; love highway drive, a movie buff.

Post – Pandemic Recruiting Practices

Prabhakar Kumar Mandal

The COVID pandemic has transformed business as we know it. This includes recruitment. Right from the pre-hire activities to the post-hire ones, no hiring practices will be exempt from change we’re witnessing. To maintain a feasible talent acquisition program now and in the coming years, organizations face a persistent need to reimagine the way they do things at every step of the hiring funnel. 

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In my perspicacity, following are the key aspects to look at:

1. Transforming Physical Workspaces

Having employees be physically present at workplace is fraught with challenges now. We envision many companies transitioning into a fully or partially remote workforce to save on costs and give employees more flexibility.

This means companies that maintain a physical headquarter will be paying much closer attention to the purpose those spaces really serve—and so will the candidates. The emphasis now will be on spaces of necessity—meeting areas, spaces for collaborative work, and comfortable, individual spaces for essential workers who need to be onsite. 

2. Traveling for interviews will be an obsolete

It’s going to be a while before non-essential travel assumes its pre-corona importance. In a study of traveler attitudes spanning the U.S., Canada, the U.K., and Australia, the portion of people who said they intended to restrict their travel over the next year increased from 24% in the first half of March to 40% in the second half of March.

Candidates will be less willing than they once were to jump on a plane for an in-person interview when a video conference is a viable alternative. 

3. Demand for workers with cross-trained skills will increase

Skills-based hiring has been on the rise now and will keep increasing as businesses strive to do more with a lesser headcount. We anticipate organizations to increasingly seek out candidates who can wear multiple hats. 

Additionally, as machines take on more jobs that were once reserved for people, we will see even greater demand for uniquely human skills like problem solving and creative thinking. Ravi Kumar, president of Infosys Ltd., summed it up perfectly in an interview with Forbes: “machines will handle problem-solving and humans will focus on problem finding.” 

4. Recruiting events will look a lot different 

It’s unclear when large-scale, in-person gatherings like job fairs will be able to resume, but it will likely be a while. We will likely see most events move to a virtual model, which will not only reduce risk but significantly cut costs for those involved. This may open new opportunities to allocate that budget to improve some of the other pertinent recruiting practices on this list. 

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5. Time to hire may change dramatically

The current approach is likely to change. For example, that most people who took a new job last year were not searching for one: Somebody came and got them. Businesses seek to fill their recruiting funnel with as many candidates as possible, especially ‘passive candidates’, who are not looking to move. Frequently employers advertise jobs that do not exist, hoping to find people who might be useful later or in a different framework. We are always campaigning the importance of minding our recruiting metrics, which can help us not only to hire more competently but identify interruptions in our recruiting process.

Are there steps in the hiring process, like screening or onboarding, that can be accelerated to balance things out? Are there certain recruitment channels that typically yield faster hires than others that can be prioritized? These are important questions to ask as you analyze the pandemic’s impacts to your hiring funnel. 

6. How AI can be leveraged to screen candidates?

AI is helping candidates get matched with the right companies. There are over 100 parameters to assess the candidates. This reduces wastage of time, money, and resources. The candidates are marked on their core strengths. This helps the recruitment manager to place them in the apt role.

The current situation presents the perfect opportunity for companies to adopt new tools. Organizations can reassess their recruitment processes and strategies through HR-aligned technology.

Post-pandemic hiring strategy

This pertains more to the industries most impacted by the pandemic, like businesses in the hospitality sector, outdoor dining, and travel to name a few. Many of the applicants in this domain have chosen to make the shift towards more promising or booming businesses.

However, once the pandemic blows over and restrictions are lifted, you can expect suffering sectors to come back with major recruitment changes and fierce competition over top talent.

Companies that take this time to act by cultivating relationships and connections with promising talent in their sphere, will have the advantage of gathering valuable data from probable candidates.

About the Author –

Prabhakar is a recruiter by profession and cricketer by passion. His focus is on hiring for the infra verticle. He hails from a small town in Bihar was brought up in Pondicherry. Prabhakar has represented Pondicherry in U-19 cricket (National School Games). In his free time he enjoys reading, working on his health and fitness and spending time with his family and friends.

Quantum Computing

Vignesh Ramamurthy

Vignesh Ramamurthy

In the MARVEL multiverse, Ant-Man has one of the coolest superpowers out there. He can shrink himself down as well as blow himself up to any size he desires! He was able to reduce to a subatomic size so that he could enter the Quantum Realm. Some fancy stuff indeed.

Likewise, there is Quantum computing. Quantum computers are more powerful than supercomputers and tech companies like Google, IBM, and Rigetti have them.

Google had achieved Quantum Supremacy with its Quantum computer ‘Sycamore’ in 2019. It claims to perform a calculation in 200 seconds which might take the world’s most powerful supercomputer 10,000 years. Sycamore is a 54-qubit computer. Such computers need to be kept under special conditions with temperature being close to absolute zero.

quantum computing

Quantum Physics

Quantum computing falls under a discipline called Quantum Physics. Quantum computing’s heart and soul resides in what we call as Qubits (Quantum bits) and Superposition. So, what are they?

Let’s take a simple example, imagine you have a coin and you spin it. One cannot know the outcome unless it falls flat on a surface. It can either be a head or a tail. However, while the coin is spinning you can say the coin’s state is both heads and tails at the same time (qubit). This state is called Superposition.

So, how do they work and what does it mean?

We know bits are a combination of 0s and 1s (negative or positive states). Qubits have both at the same time. These qubits, in the end, pass through something called “Grover Operator” which washes away all the possibilities, but one.

Hence, from an enormous set of combinations, a single positive outcome remains, just like how Doctor Strange did in the movie Infinity War. However, what is important is to understand how this technically works.

We shall see 2 explanations which I feel could give an accurate picture on the technical aspect of it.

In Quantum Mechanics, the following is as explained by Scott Aaronson, a Quantum scientist from the University of Texas, Austin.

Amplitude – an amplitude of a positive and a negative state. These could also be considered as an amplitude for being 0, and also an amplitude for being 1. The goal for an amplitude here is to make sure that amplitudes leading to wrong answers cancel each other out. Hence this way, amplitude with the right answer remains the only possible outcome.

Quantum computers function using a process called superconductivity. We have a chip the size of an ordinary computer chip. There are little coils of wire in the chip, nearly big enough to see with the naked eye. There are 2 different quantum states of current flowing through these coils, corresponding to 0 and 1, or the superpositions of them.

These coils interact with each other, nearby ones talk to each other and generate a state called an entangled state which is an essential state in Quantum computing. The way qubits interact are completely programmable, so we can send electrical signals to these qubits, and tweak them according to our requirements. This whole chip is placed in a refrigerator with a temperature close to absolute zero. This way superconductivity occurs which makes it to briefly behave as qubits.

Following is the explanation given according to ‘Kurzgesagt — In a Nutshell’, a YouTube channel.

We know a bit is either a 0 or 1. Now, 4 bits mean 0000 and so on. In a qubit, 4 classical bits can be in one of the 2^4 different configurations at once. That is 16 possible combinations out of which we can use just one. 4 qubits in position can be in all those 16 combinations at once.

This grows exponentially with each extra qubit. 20 qubits can hence store a million values in parallel. As seen, these entangled states interact with each other instantly. Hence while measuring one entangled qubit, we can directly deduce the property of its partners.

A normal logic gate gets a simple set of inputs and produces one definite output. A quantum gate manipulates an input of superpositions, rotates probabilities, and produces another set of superpositions as its output.

Hence a quantum computer sets up some qubits, applies quantum gates to entangle them, and manipulates probabilities. Now it finally measures the outcome, collapsing superpositions to an actual sequence of 0s and 1s. This is how we get the entire set of calculations performed at the same time.

What is a Grover Operator?

We now know that while taking one entangled qubit, it is possible to easily deduce properties for all the partners. Grover algorithm works because of these quantum particles being entangled. Since one entangled qubit is able to vouch for the partners, it iterates until it finds the solution with higher degrees of confidence.

What can they do?

As of now, quantum computing hasn’t been implemented in real-life situations just because the world right now doesn’t have such an infrastructure.

Assuming they are efficient and ready to be used. We can make use of it in the following ways: 1) Self-driving cars are picking up pace. Quantum computers can be used on these cars by calculating all possible outcomes on the road. Apart from sensors to reduce accidents, roads consist of traffic signals. A Quantum computer will be able to go through all the possibilities of how traffic signals

function, the time interval, traffic, everything, and feed these self-driving cars with the single best outcome accordingly. Hence, what would result is nothing but a seamless commute with no hassles whatsoever. It’ll be the future as we see in movies.

2) If AI is able to construct a circuit board after having tried everything in the design architecture, this could result in promising AI-related applications.

Disadvantages

RSA encryption is the one that underpins the entire internet. It could breach it and hackers might steal top confidential information related to Health, Defence, personal information, and other sensitive data. At the same time, it could be helpful to achieve the most secure encryption, by identifying the best one amongst every possible encryption. This can be made by finding out the most secure wall to break all the viruses that could infect the internet. If such security is made, it would take a completely new virus to break it. But the chances are very minuscule.

Quantum computing has its share of benefits. However, this would take years to be put to use. Infrastructure and the amount of investment to make is humongous. After all, it could only be used when there are very reliable real-time use cases. It needs to be tested for many things. There is no doubt that Quantum Computing will play a big role in the future. However, with more sophisticated technology, comes more complex problems. The world will take years to be prepared for it.

References:

About the Author –

Vignesh is part of the GAVel team at GAVS. He is deeply passionate about technology and is a movie buff.

Reduce Test Times and Increase Coverage with AI & ML

Kevin Surace

Chairman & CTO, Appvance.ai

With the need for frequent builds—often many times in a day—QEs can only keep pace through AI-led testing. It is the modern approach that allows quality engineers to create scripts and run tests autonomously to find bugs and provide diagnostic data to get to the root cause.

AI-driven testing means different things to different QA engineers. Some see it as using AI for identifying objects or helping create script-less testing; some consider it as autonomous generation of scripts while others would think in terms of leveraging system data to create scripts which mimic real user activity.

Our research shows that teams who are able to implement what they can in scripts and manual testing have, on average, less than 15% code, page, action, and likely user flow coverage. In essence, even if you have 100% code coverage, you are likely testing less than 15% of what users will do. That in itself is a serious issue.

Starting in 2012, Appvance set out to rethink the concept of QA automation. Today our AIQ Technology combines tens of thousands of hours of test automation machine learning with the deep domain knowledge, the essential business rules, each QE specialist knows about their application. We create an autonomous expert system that spawns multiple instances of itself that swarm over the application testing at the UX and at the API-levels. Along the way these Intelligences write the scripts, hundreds, and thousands of them, that describes their individual journeys through the application.

And why would we need to generate so many tests fully autonomously. Because applications today are 10X the size they were just ten years ago. But your QE team doesn’t have 10X the number of test automation engineers. And because you have 10X less time to do the work than 10 years ago. Just to keep pace with the dev team requires each quality engineer to be 100X more productive than they were 10 years ago.

Something had to change; that something is AI.

AI-testing in two steps

We leveraged AI and witnessed over 90% reduction in human effort to find the same bugs. So how does this work?

It’s really a two-stage process.

First, leveraging key AI capabilities in TestDesigner, Appvance’s codeless test creation system, we make it possible to write scripts faster, identify more resilient accessors, and substantially reduce maintenance of scripts.

With AI alongside you as you implement an automated test case, you get a technology that suggests the most stable accessors and constantly improves and refines them. It also creates “fallback accessors” when tests run and hit an accessor change enabling the script to continue even though changes have been made to the application. And finally, the AI can self-heal scripts which must and update them with new accessors without human assistance. These AI-based, built-in technologies give you the most stable scripts every time with the most robust accessor methodologies and self-healing. Nothing else comes close.

The final two points above deal with autonomous generation of tests. To beat the queue and crush it, you have to get a heavy lift for finding bugs. And as we have learnt, go far beyond the use cases that a business analyst listed. Job one is to find bugs and prioritize them, leveraging AI to generate tests autonomously.

Appvance’s patented AI engine has already been trained with millions of actions. You will teach it the business rules of your application (machine learning). It will then create real user flows, take every possible action, discover every page, fill out every form, get to every state, and validate the most critical outcomes just as you trained it to do. It does all this without writing or recording a single script. We call this is ‘blueprinting’ an application. We do this at every new build. Multiple instances of the AI will spin up, each selecting a unique path through the application, typically finding 1000s or more flows in a matter of minutes. When complete, the AI hands you the results including bugs, all the diagnostic data to help find the root cause, and the reusable test-scripts to repeat the bug. A further turn of the crank can refine these scripts into exact replicas of what production users are doing and apply them to the new build. Any modern approach to continuous testing needs to leverage AI in both helping QA engineers create scripts as well as autonomously create tests so that both parts work together to find bugs and provide data to get to the root cause. That AI driven future is available today from Appvance.

About the Author –

Kevin Surace is a highly lauded entrepreneur and innovator. He’s been awarded 93 worldwide patents, and was Inc. Magazine Entrepreneur of the Year, CNBC Innovator of the Decade, a Davos World Economic Forum Tech Pioneer, and inducted into the RIT Innovation Hall of Fame. Kevin has held leadership roles with Serious Energy, Perfect Commerce, CommerceNet and General Magic and is credited with pioneering work on AI virtual assistants, smartphones, QuietRock and the Empire State Building windows energy retrofit.

Enabling Success through Servant Leadership

Vasu

Vasudevan Gopalan

Servant Leadership – does it seem like a dichotomy? Well, it is not so. In this new age of Agile and Digital Transformation, this is a much sought-after trait in Leaders by their Organizations.

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The goal of Servant Leadership is to Serve. It involves the leader supporting and empowering their teams and thus enabling Success. The paradigm shift in the thought process here is that – instead of the people working to serve the leader, the leader exists to serve the team. And do remember that a Servant Leader is a Servant first, Leader next – not the other way around 😊

In today’s Agile world of Software Delivery, the Scrum Master needs to be a Servant Leader.

So, what are the characteristics of a Servant Leader?

  • Self-aware
  • Humble
  • Integrity
  • Result-oriented
  • Has foresight
  • Listener
  • Doesn’t abuse authority
  • Intellectual authority
  • Collaborative
  • Trusting
  • Coach
  • Resolves conflict

As you can see here, it is all about achieving results through people empowerment. When people realize that their Leader helps every team member build a deep sense of community and belonging in the workplace, there is a higher degree of accountability and responsibility carried out in their work.

Ultimately, a Servant Leader wants to help others thrive, and is happy to put the team’s needs before their own. They care about people and understand that the best results are produced not through top-down delegation but by building people up. People need psychological safety and autonomy to be creative and innovative.

As Patrick Lencioni describes, Humility is one of the 3 main pillars for ideal team players. Humility is “the feeling or attitude that you have no special importance that makes you better than others”.

Behaviors of Humble Agile Servant Leaders

  • Deep listening and observing
  • Openness towards new ideas from team members
  • Appreciating strengths and contributions of team members
  • Seek contributions of team members to overcome challenges and limitations together
  • Be coachable coaches – i.e. Coach others, and simultaneously be easy to be coached by others

Humility’s foe – Arrogance

In Robert Hogan’s terms, arrogance makes “the most destructive leaders” and “is the critical factor driving flawed decision-makers” who “create the slippery slope to organizational failure”.

Humility in Practice

A study on the personality of CEOs of some of the top Fortune 1000 Companies shows that what makes these companies successful as they are is the CEOs’ humility. These CEOs share two sets of qualities seemingly contradictory but always back each other up strongly:

  • They are “self-effacing, quiet, reserved, even shy”. They are modest. And they admit mistakes.
  • At the same time, behind this reserved exterior, they are “fiercely ambitious, tremendously competitive, tenacious”. They have strong self-confidence and self-esteem. And they’re willing to listen to feedback and solicit input from knowledgeable subordinates.

According to Dr. Robert Hogan (2018), these characteristics of humility create “an environment of continuous improvement”.

What are the benefits of being a humble Servant Leader?

  • Increase inclusiveness – the foundation of trust
  • Strengthen the bond with peers – the basis of well-being
  • Deepen awareness
  • Improve empathy
  • Increase staff engagement

So, what do you think would be the outcomes for organizations that have practicing Servant Leaders?

Source:

https://www.bridge-global.com/blog/5-excellent-tips-to-become-a-supercharged-agile-leader/

About the Author –

Vasu heads the Engineering function for A&P. He is a Digital Transformation leader with ~20 years of IT industry experience spanning across Product Engineering, Portfolio Delivery, Large Program Management, etc. Vasu has designed and delivered Open Systems, Core Banking, Web / Mobile Applications, etc. Outside of his professional role, Vasu enjoys playing badminton and is a fitness enthusiast.

Mentoring – a Win-Win Situation

Rama Vani Periasamy

“If I have seen further it is by standing on the shoulders of giants.” — Isaac Newton

Did you know the English word ‘Mentor’ actually originated from the Greek epic ‘The Odyssey’?

When Odysseus had to leave his kingdom to lead his army in the Trojan war, his son Telemachus was left under the guidance of a friend ‘Mentor’. Mentor was supposed to guide and groom Telemachus during his developmental years and make him independent. The word ‘Mentor’ was thus incorporated in the English language. We use the word in the same context that existed in Greek Mythology – to guide a person, make him/her an independent thinker, and a doer.

In the age of technology, there may be tools and enormous amounts of data to get a competitive advantage, but they’re no match for a mentor. The business hall of fame is adorned with the names of people who discovered that finding a mentor made all the difference.

A lot of people have been able to achieve greater heights than they imagined because they were able to tap into their potential and that is the energy mentoring brings in.

In today’s world, a lot of corporate offices offer mentoring programs that cut across age groups (called the cross-gens), backgrounds, and experiences that benefit everyone. But sometimes the mechanisms and expectations of a mentoring program are not clear which makes the practice unsuccessful. Today’s young generation think they have the internet to quench the thirst of their knowledge. They do not see mentors as guiding beacons to success but only help them meet their learning needs. Citing it with an example, mentoring is equivalent to teaching a man to not just fish, but also share the experiences, tricks, and tips, so that he becomes an independent fisher.  More often, our current generation fails to understand that even geniuses like Aristotle and Bill Gates needed a mentor in their lives.

When mentoring is so powerful, why don’t we nurture the relationship? What stops us? Is time a factor? Not really. Any relationship needs some amount of time to be invested and so is the case with mentoring. Putting aside a few hours a month is an easily doable task, especially for something that is inspiring and energizing. Schedules can always be shuffled for priorities.

Now that we know that we have the time, why is it always hard to find a mentor? To begin with, how do you find a mentor? Well, it is not as difficult as we think. When you start looking for them, you will eventually find one. They are everywhere but may not necessarily be in your workplace.

We have the time, we have a mentor, so what are the guidelines in the mentoring relationship?

The guidelines can be extracted very much in the word ‘MENTOR’.

M=Mission: Any engagement works only if you have something to work on. Both the mentor and mentee must agree on the goals and share their mission statement. Creating a vision and a purpose for the mentoring relationship adds value to both sides and this keeps you going. Articulating the mission statement would be the first activity, to begin with in a mentor-mentee relationship.

 E=Engage: Agree on ways to engage that works with your personalities and schedules. Set ground rules on the modes of communications. Is that going to be a one-one conversation periodically or remote calls? Find out the level of flexibility. Is an impromptu meeting fine? Can Emails or text messages be sent? Decide on the communication medium and time.

 N=Network: Expanding your network with that of your mentor or mentee and cultivating productive relationships will be the key to success. While expanding your network will be productive, remember to tread carefully. Seek permissions, respect, and even ask for an introduction before you reach out to the other person’s contacts.

 T=Trust: Build and maintain trust with your mentoring partner by telling the truth, staying connected, and being dependable. And as the mentorship grows, clear communication and honesty will deepen the relationship. Building trust takes time so always keep the lines of communication open.

O=Opportunity: Create opportunities for your mentee or mentor to grow. Being in a mentor-mentee relationship is like a two-way lane, where you can come across opportunities from both sides, which may not be open for non-mentors/mentees. Bringing in such opportunities will only help the other person achieving his/her goal or the mission statement that was set at the beginning.

R=Review and Renew: Schedule a regular time to review progress and renew your mentoring partnership. This will help you keep your progress on track and it will also help you look for short goals to achieve. Reviewing is also going to help retrospect if a different strategy is to be laid out to achieve your goals.

Mentoring may sound irrelevant and unnecessary while we are surviving a pandemic and going through bouts of intense emotions. But I feel it is even more necessary during this most unusual situation we’re facing. Mentoring could be one of the ways to combat anxiety and depression caused by isolation and the inability to meet people face-to-face.

Mentoring can be done virtually through video calls, by setting up a time to track the progress of your goals and discuss challenges/accomplishments.  Mentoring also proves to be the place to ask difficult questions because it is a “No Judging” relationship and the absolute safe place to deal with work-related anxiety and fear. I still recall my early days as a campus graduate where I was assigned a ‘Buddy’, the go-to person. With them, I’d discussed a lot of my ‘what’, ‘why’ and ‘how’ questions of the work and the corporate world, which I had resisted opening up to my supervisors.

Mentoring takes time. Remember the first day you struggled to balance on your bicycle and may have fallen down hurting your knees? But once you learned to ride, you would have loved your time on the saddle. The same applies to mentoring. Investing the time and effort in mentoring will energize you even better than a few hours of Netflix or scrolling on Instagram. Let us create a culture that shares knowledge, guides & encourages nonstop, like how Socrates taught Plato, Plato taught Aristotle and Aristotle held the beacon for many. There is an adage that goes “when you are ready to become a teacher, the student appears”.

“A mentor is someone who allows you to see the hope inside yourself.” — Oprah Winfrey

The article is based on the book “One Minute Mentoring” by Ken Blanchard & Claire Diaz Ortiz.

About the Author –

Rama is that everyday woman you see who juggles between family and a 9 hours work life. She loves reading history, fiction, attempting half marathons, and traveling.
To break the monotony of life and to share her interest in books & travel, she blogs and curates at www.kindleandkompass.com

Significance of CI CD Process in DevOps

Muraleedharan Vijayakumar

Developing and releasing software can be a complicated process, especially as applications, teams, and deployment infrastructure grow in complexity themselves. Often, challenges become more pronounced as projects grow. To develop, test, and release software quickly and consistently, developers and organizations have created distinct strategies to manage and automate these processes.

Did you know?  Amazon releases a new production code once every 11.6 seconds.

Why CI/CD/CD?

The era of digital transformations demands faster deployments into production. Faster deployments do not warrant defective releases, the solution – ‘DevOps’. The development team, operations team, and IT services team have to work in tandem and the magic circle that brings all of them together is DevOps.

To adopt a DevOps culture, implementing the right DevOps tools with the right DevOps process is essential. Continuous integration/continuous delivery/continuous deployment (CI/CD/CD) help us developers and testers ship the software faster and safer in a structured environment.

The biggest obstacle that needs to be overcome in constructing a DevOps environment is scalability. There are no definite measures on the scalability of an application or product development, but DevOps environment should be ready to scale to meet business and technology needs. It lays a strong foundation for building an agile DevOps for the business.

Continuous Integration and Deployment has seen many benefits in the software delivery process. Initiating automated code builds once checks are completed, running automated test suites, flagging errors and breaking builds if not adhered to compliance have eased the way of deploying a stable release into staging or production environment and eliminating manual errors and human bias.

How is CI/CD/CD Set Up?

Version control tools play an important role in the success of our DevOps pipeline. And designing a good source stage is pivotal to our CI/CD success. It ensures that we can version code, digital assets, and binary files (and more) all in one spot. This enables teams to communicate and collaborate better — and deploy faster.

Our code branching strategy determines how and when developers branch and merge. When deciding on a strategy it is important to evaluate what makes sense for our team and product. Most version control systems will let you adopt and customize standard strategies like mainline, trunk-based, task/feature branching, etc.,

Typical Branching Model Followed

A basic workflow starts with code being checked out. When the work in the branch is committed, CI processes are triggered. This can be done with a merge or pull request. Then the CI/CD pipeline kicks into high gear.

The goal of CI/CD is to continuously integrate changes to find errors earlier in the process, as known as ‘Shift Left’.  The ultimate goal of having an automated CI/CD process in place to identify errors or flag non-compliance at an early stage of the development process. This increases the project’s velocity by avoiding late-stage defects and delays. It creates an environment where code is always ready for a release. With the right branching strategy, teams are equipped to deliver success.

Continuous Integration: Integrating newly developed code with the central repository is continuous integration. Automated CI results in automated builds that are triggered to merge the newly developed codes into the repository. As part of this process, plugins can be added to perform static code analysis, security compliance checks, etc., to identify if the newly added code would have any impact on the application. If there are compliance issues, the automated build breaks, and the same is reflected to the developer with insights. Automated CI helps in increasing the productivity of the developers and the team.

Continuous Delivery: At the end of a successful CI, Continuous Delivery is triggered. CD ensures to automate the software delivery process and commits to deliver the integrated code into the production stage without any bugs or delays. CD helps in merging the newly developed code into the main branch of the software so that a ready to production product is available with all the checks in place.CD also checks the quality of the code and performs tests to check whether it can release the functional build to the production environment.

Continuous Deployment: The final and most critical part of DevOps is Continuous Deployment. After the successful merging of certified code, the pipelines are triggered to deploy the code into the production environment. These pipelines are also triggered automatically. The pipelines are constructed to handle the target environment be it jar or container deployments. The most important aspect of this pipeline is to tag the releases that are also done in the production environment. If there are rollbacks these tags help the team to roll back to the right version of the build.

CI/CD/CD is an art that needs to be crafted in the right and most efficient way that will help the software development team achieve their success at a faster pace.

Different Stages & Complete DevOps Setup

What is the CI/CD/CD  Outcome?

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About the Author –

Murleedharan is a senior technical manager and has managed, developed, and launched cutting edge business intelligence and analytics platforms using big data technologies. He has experience in hosting the platform in Microsoft Azure by leveraging the MS PaaS. He is a product manager for zDesk – A Virtual Desktop offering from GAVS.
His passion is to get a friction-less DevOps operational in an environment to bring down the deployment time to a few seconds.

Design-led Organization: Creative Thinking as a Practice!

Gogul R G

This is the first article in the series of ‘Design-led organization’ writing about creative thinking as a practice in GAVS. It is the first step for the readers to explore the world of design and creativity. So, let’s get started!

First let’s see what is design thinking is all about

There is a common misconception that design thinking is new. But when you look back, people have applied a human-centric creative process to build meaningful and effective solutions. Design has been practiced for ages to build monuments, bridges, automobiles, subway systems, etc. Design is not only limited to aesthetics, it is more of a mindset to think of a solution. Design thinking is a mindset to iteratively think about a complex problem and come up with a viable solution

Thinking outside of the box can provide an innovative solution to a sticky problem. However, thinking outside of the box can be a real challenge as we naturally develop patterns of thinking that are based on the repetitive activities and commonly accessed knowledge surround ourselves. It takes something to detach away from a situation where we’re too closely involved to be able to find better possibilities.

To illustrate how a fresh way of thinking can create unexpectedly good solutions, let’s look at a famous incident. Some years ago, an incident occurred where a truck driver had tried to pass under a low bridge. But, he failed, and the truck became firmly lodged under the bridge.

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The driver was unable to continue driving through or reverse out. The struck truck caused massive traffic problems, which resulted in emergency personnel, engineers, firefighters, and truck drivers gathering to negotiate various solutions to dislodge the truck.

Emergency workers were debating whether to dismantle parts of the truck or chip away at parts of the bridge. Each of one were looking for a solution with their respective level of expertise. A boy walking by and witnessing the intense debate looked at the truck, at the bridge, then looked at the road and said, “Why not just let the air out of the tires?” to the absolute amazement of all the specialists and experts trying to resolve the issue.

When the solution was tested, the truck could drive with ease, having suffered only the damage caused by its initial attempt to pass underneath the bridge. It symbolizes the struggles we face where often the most obvious solutions are the ones hardest to come by because of the self-imposed constraints we work within.  

“Challenging our assumptions and everyday knowledge is often difficult for us humans, as we rely on building patterns of thinking in order not to have to learn everything from scratch every time.

Let’s come back to our topic “What is Design thinking?” Tim Brown, Executive Chairman of IDEO – an international design and consulting firm quoted design thinking as below.

“Design thinking is a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.

Now let’s think about our truck example. A boy with his fresh mindset provides a simple solution to address a complex problem. Yeah! this is the sweet spot. Everyone is creative and capable of thinking like a designer, and out of the box, to come up with a solution. This way of inculcating design as a mindset for a solution is known as Design thinking.

Yes, you read it right, everyone is creative…

We forget that back in kindergarten, we were all creative. We all played and experimented with weird things without fear or shame. We didn’t know enough not to. The fear of social rejection is something we learned as we got older. And that’s why it’s possible to regain our creative abilities, even decades later. In the field of design and user experience, there are individuals to stick with a methodology a while, they will end up doing amazing things. They come up with break through ideas or suggestions and work creatively with a team to develop something truly innovative. They surprise themselves with the realization that they are a lot more creative than they had thought. That early success shakes up how they see themselves and makes them eager to do more.

We just need to rediscover what we already have: the capacity to imagine, or build upon, new to the world ideas.  But the real value of creativity doesn’t emerge until you are brave enough to act on those ideas.

Geshe Thupten Jinpa, who has been the Dalai Lama’s chief English translator for more than twenty years, shared an insight about the nature of creativity. Jinpa pointed out that there’s no word in the Tibetan language for ‘creativity’ or ‘being creative’. The closest translation is ‘natural’. In other words, if you want to be more creative, you should be more natural! So…be natural!

At your workplace, the complex problems can be easily sorted out when you find a solution using creativity with the mindset of design thinking. Creativity can be improved by following the below steps.

  1. Go for a walk.
  2. Play your favorite games.
  3. Move your eyes.
  4. Take a break and enjoy yourself.
  5. Congratulate yourself each time you do something well.
  6. Estimate time, distance, and money.
  7. Take a route you never have taken before.
  8. Look for images in mosaics, patterns, textures, clouds, stars…
  9. Try something you have never done before.
  10. Do a creative exercise.
  11. Start a collection (stamps, coins, art, stationery, anything you wish to collect)
  12. Watch Sci-Fi or fantasy films.
  13. Change the way you do things – there are no routine tasks, only routine way of doing things.
  14. Wear a color you do not like.
  15. Think about how they invented equipment or objects you use daily.
  16. Make a list of 10 things you think are impossible to do and then imagine how you could make each one possible.
  17. For every bad thing that happens to you, remember at least 3 good things that happened.
  18. Read something you have not read yet.
  19. Make friends with people on the other side of the world.
  20. When you have an idea, make a note of it, and later check to see if it happened.
  21. Connect a sport with your work.
  22. Try food you never tried before.
  23. Talk to grandparents and relatives and listen to their stories.
  24. Give an incorrect answer to a question.
  25. Find links between people, things, ideas, or facts.
  26. Ask children how to do something and observe their creativity.

Start doing the above-mentioned steps to inculcate a creative mindset and apply it in your day-to-day work. Companies like GE health care, Procter & Gamble, UBER practiced design thinking and implemented in their new product launches and for solving complex problems in their organizations. Be natural to be more creative! When you are more creative, you can apply design thinking for seeking any solution for a complex problem in your work.

This is the first article in the series of Design led Organization in GAVS. Keep watching this space for more articles on design and keep exploring the world of design-thinking!

References:

About the Author –

Gogul is a passionate UX designer with 8+ years of experience into designing experiences for digital channels like Enterprise apps, B2C, B2B apps, Mobile apps, Kiosk, Point of Sale, Endless aisle, telecom products. He is passionate about transforming complex problems into actionable solutions using design.

Artificial Intelligence in Healthcare

Dr. Ramjan Shaik

Scientific progress is about many small advancements and occasional big leaps. Medicine is no exception. In a time of rapid healthcare transformation, health organizations must quickly adapt to evolving technologies, regulations, and consumer demands. Since the inception of electronic health record (EHR) systems, volumes of patient data have been collected, creating an atmosphere suitable for translating data into actionable intelligence. The growing field of artificial intelligence (AI) has created new technology that can handle large data sets, solving complex problems that previously required human intelligence. AI integrates these data sources to develop new insights on individual health and public health.

Highly valuable information can sometimes get lost amongst trillions of data points, costing the industry around $100 billion a year. Providers must ensure that patient privacy is protected, and consider ways to find a balance between costs and potential benefits. The continued emphasis on cost, quality, and care outcomes will perpetuate the advancement of AI technology to realize additional adoption and value across healthcare. Although most organizations utilize structured data for analysis, valuable patient information is often “trapped” in an unstructured format. This type of data includes physician and patient notes, e-mails, and audio voice dictations. Unstructured data is frequently richer and more multifaceted. It may be more difficult to navigate, but unstructured data can lead to a plethora of new insights. Using AI to convert unstructured data to structured data enables healthcare providers to leverage automation and technology to enhance processes, reduce the staff required to monitor patients while filling gaps in healthcare labor shortages, lower operational costs, improve patient care, and monitor the AI system for challenges.

AI is playing a significant role in medical imaging and clinical practice. Providers and healthcare organizations have recognized the importance of AI and are tapping into intelligence tools. Growth in the AI health market is expected to reach $6.6 billion by 2021 and to exceed $10 billion by 2024.  AI offers the industry incredible potential to learn from past encounters and make better decisions in the future. Algorithms could standardize tests, prescriptions, and even procedures across the healthcare system, being kept up-to-date with the latest guidelines in the same way a phone’s operating system updates itself from time to time.

There are three main areas where AI efforts are being invested in the healthcare sector.

  • Engagement – This involves improvising on how patients interact with healthcare providers and systems.
  • Digitization – AI and other digital tools are expected to make operations more seamless and cost-effective.
  • Diagnostics – By using products and services that use AI algorithms diagnosis and patient care can be improved.

AI will be most beneficial in three other areas namely physician’s clinical judgment and diagnosis, AI-assisted robotic surgery, and virtual nursing assistants.

Following are some of the scenarios where AI makes a significant impact in healthcare:

  • AI can be utilized to provide personalized and interactive healthcare, including anytime face-to-face appointments with doctors. AI-powered chatbots can be powered with technology to review the patient symptoms and recommend whether a virtual consultation or a face-to-face visit with a healthcare professional is necessary.
  • AI can enhance the efficiency of hospitals and clinics in managing patient data, clinical history, and payment information by using predictive analytics. Hospitals are using AI to gather information on trillions of administrative and health record data points to streamline the patient experience. This collaboration of AI and data helps hospitals/clinics to personalize healthcare plans on an individual basis.
  • A taskforce augmented with artificial intelligence can quickly prioritize hospital activity for the benefit of all patients. Such projects can improve hospital admission and discharge procedures, bringing about enhanced patient experience.
  • Companies can use algorithms to scrutinize huge clinical and molecular data to personalize healthcare treatments by developing AI tools that collect and analyze data from genetic sequencing to image recognition empowering physicians in improved patient care. AI-powered image analysis helps in connecting data points that support cancer discovery and treatment.
  • Big data and artificial intelligence can be used in combination to predict clinical, financial, and operational risks by taking data from all the existing sources. AI analyzes data throughout a healthcare system to mine, automate, and predict processes. It can be used to predict ICU transfers, improve clinical workflows, and even pinpoint a patient’s risk of hospital-acquired infections. Using artificial intelligence to mine health data, hospitals can predict and detect sepsis, which ultimately reduces death rates.
  • AI helps healthcare professionals harness their data to optimize hospital efficiency, better engage with patients, and improve treatment. AI can notify doctors when a patient’s health deteriorates and can even help in the diagnosis of ailments by combing its massive dataset for comparable symptoms. By collecting symptoms of a patient and inputting them into the AI platform, doctors can diagnose quickly and more effectively.   
  • Robot-assisted surgeries ranging from minimally-invasive procedures to open-heart surgeries enables doctors to perform procedures with precision, flexibility, and control that goes beyond human capabilities, leading to fewer surgery-related complications, less pain, and a quicker recovery time. Robots can be developed to improve endoscopies by employing the latest AI techniques which helps doctors get a clearer view of a patient’s illness from both a physical and data perspective.

Having understood the advancements of AI in various facets of healthcare, it is to be realized that AI is not yet ready to fully interpret a patient’s nuanced response to a question, nor is it ready to replace examining patients – but it is efficient in making differential diagnoses from clinical results. It is to be understood very clearly that the role of AI in healthcare is to supplement and enhance human judgment, not to replace physicians and staff.

We at GAVS Technologies are fully equipped with cutting edge AI technology, skills, facilities, and manpower to make a difference in healthcare.

Following are the ongoing and in-pipeline projects that we are working on in healthcare:

ONGOING PROJECT:

AI Devops Automation Service Tools

PROJECTS IN PIPELINE:

AIOps Artificial Intelligence for IT Operations
AIOps Digital Transformation Solutions
Best AI Auto Discovery Tools
Best AIOps Platforms Software

Following are the projects that are being planned:

  • Controlling Alcohol Abuse
  • Management of Opioid Addiction
  • Pharmacy Support – drug monitoring and interactions
  • Reducing medication errors in hospitals
  • Patient Risk Scorecard
  • Patient Wellness – Chronic Disease management and monitoring

In conclusion, it is evident that the Advent of AI in the healthcare domain has shown a tremendous impact on patient treatment and care. For more information on how our AI-led solutions and services can help your healthcare enterprise, please reach out to us here.

About the Author –

Dr. Ramjan is a Data Analyst at GAVS. He has a Doctorate degree in the field of Pharmacy. He is passionate about drawing insights out of raw data and considers himself to be a ‘Data Person’.

He loves what he does and tries to make the most of his work. He is always learning something new from programming, data analytics, data visualization to ML, AI, and more.

Center of Excellence – Big Data

The Big Data CoE is a team of experts that experiments and builds various cutting-edge solutions by leveraging the latest technologies, like Hadoop, Spark, Tensor-flow, and emerging open-source technologies, to deliver robust business results. A CoE is where organizations identify new technologies, learn new skills, and develop appropriate processes that are then deployed into the business to accelerate adoption.

Leveraging data to drive competitive advantage has shifted from being an option to a requirement for hyper competitive business landscape. One of the main objectives of the CoE is deciding on the right strategy for the organization to become data-driven and benefit from a world of Big Data, Analytics, Machine Learning and the Internet of Things (IoT).

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Triple Constraints of Projects

“According to Chaos Report, 52% of the projects are either delivered late or run over the allocated. The average across all companies is 189% of the original cost estimate. The average cost overrun is 178% for large companies, 182% for medium companies, and 214% for small companies. The average overrun is 222% of the original time estimate. For large companies, the average is 230%; for medium companies, the average is 202%; and for small companies, the average is 239%.”

Big Data CoE plays a vital role in bringing down the cost and reducing the response time to ensure project is delivered on time by helping the organization to build the skillful resources.

Big Data’s Role

Helping the organization to build quality big data applications on their own by maximizing their ability to leverage data. Data engineers are committed to helping ensure the data:

  • define your strategic data assets and data audience
  • gather the required data and put in place new collection methods
  • get the most from predictive analytics and machine learning
  • have the right technology, data infrastructure, and key data competencies
  • ensure you have an effective security and governance system in place to avoid huge financial, legal, and reputational problems.
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Data Analytics Stages

Architecture optimized building blocks covering all data analytics stages: data acquisition from a data source, preprocessing, transformation, data mining, modeling, validation, and decision making.

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Focus areas

Algorithms support the following computation modes:

  • Batch processing
  • Online processing
  • Distributed processing
  • Stream processing

The Big Data analytics lifecycle can be divided into the following nine stages:

  • Business Case Evaluation
  • Data Identification
  • Data Acquisition & Filtering
  • Data Extraction
  • Data Validation & Cleansing
  • Data Aggregation & Representation
  • Data Analysis
  • Data Visualization
  • Utilization of Analysis Results

A key focus of Big-data CoE is to establish a data-driven organization by developing proof of concept with the latest technologies with Big Data and Machine learning models. As of part of CoE initiatives, we are involved in developing the AI widgets to various market places, such as Azure, AWS, Magento and others. We are also actively involved in engaging and motivating the team to learn cutting edge technologies and tools like Apache Spark and Scala. We encourage the team to approach each problem in a pragmatic way by making them understand the latest architectural patterns over the traditional MVC methods.

It has been established that business-critical decisions supported by data-driven insights have been more successful. We aim to take our organization forward by unleashing the true potential of data!

If you have any questions about the CoE, you may reach out to them at SME_BIGDATA@gavstech.com

CoE Team Members

  • Abdul Fayaz
  • Adithyan CR
  • Aditya Narayan Patra
  • Ajay Viswanath V
  • Balakrishnan M
  • Bargunan Somasundaram
  • Bavya V
  • Bipin V
  • Champa N
  • Dharmeswaran P
  • Diamond Das
  • Inthazamuddin K
  • Kadhambari Manoharan
  • Kalpana Ashokan
  • Karthikeyan K
  • Mahaboobhee Mohamedfarook
  • Manju Vellaichamy
  • Manojkumar Rajendran
  • Masthan Rao Yenikapati
  • Nagarajan A
  • Neelagandan K
  • Nithil Raj Tharammal Paramb
  • Radhika M
  • Ramesh Jayachandar
  • Ramesh Natarajan
  • Ruban Salamon
  • Senthil Amarnath
  • T Mohammed Anas Aadil
  • Thulasi Ram G
  • Vijay Anand Shanmughadass
  • Vimalraj Subash