Archives for September 2017

September 26, 2017 - No Comments!

Top 10 Predictions for HR Tech in 2018

- Rajiv Jayaraman, Founder CEO, KNOLSKAPE

As we enter the last quarter of the calendar year, it is useful to start thinking about the major trends that we are likely to witness in the HR Tech space in 2018. Here are the top 10 predictions.

1. AI will be positioned more as an "&" strategy

AI will make the HR function efficient in a variety of areas including hiring, development and assessments. HR teams will provide the situational context for AI systems to make the right impact for the organization. The combination of human + AI will produce dramatic results.

2. New-age collaborative platforms will become more prevalent

Social, collaborative platforms like Slack, FB @ Work will penetrate deeply into many organizations unleashing the platform + app model for HR. In this model, the platform enables seamless communication and collaboration across levels within the company and there will be plethora of apps that cater to specific needs across performance management, feedback, learning, assessments, engagement etc.

3. Mobile + Videos will become the norm for learning, on-boarding, engagement

With high speed internet connections becoming a reality and smart phones in the hands of all the employees, videos will be the norm for learning, on-boarding and talent engagement.

4. New Leadership Models will evolve for the digital age

Traditional leadership model anchored around the industrial age will get replaced by more modern leadership theories for the digital age. HR Tech companies will play a big role in helping leaders learn new skills better and stay relevant through on-going learning.

5. HR tech will start to solve issues for the extended enterprise

With organizations becoming increasingly boundary-less, it will become imperative for the HR teams to focus on cascading culture, values and engagement not just within the organization but also across the extended enterprise. HR tech will respond to this need and develop platforms that create communities around the extended enterprise.

6. HR analytics will come of age

Decisions in many HR domains are currently being taken without the use of data and analytics. HR Tech will provide analytics solutions across the employee life cycle from talent acquisition to exit.

7. Performance Management will become more agile

Today, anything with the prefix "annual" is seen as anachronistic. With the annual bell curve based performance appraisal process going out of fashion, there is a need for real-time, instant feedback on performance. HR Tech will provide the ability for employees to track their performance on a more frequent basis with real-time feedback from different stakeholders.

8. HR tech will find interesting ways to gamify HR

Gamification has found great acceptance when it comes to on-boarding and learning. There are plenty of other areas within HR that can still benefit from gamification - knowledge management, coaching, rewards and recognition to name a few.

9. Neuro assessments will start to gain traction

We will start to see employees getting assessed using head gears that measure neural activity while performing various tasks or while learning. The data from these tools will be used in the assessment process.

10. Wellness Tech will find a lot of acceptance

With increasing stress and anxiety in the workplace, wellness will become a key employee proposition offered by organizations. We will witness growth in platforms that offer comprehensive wellness solutions to employees.

September 20, 2017 - No Comments!

3 things you can do to become a “Super Predictor”

by Rajiv Jayaraman, Founder - CEO, KNOLSKAPE

In today's VUCA context, it is becoming increasingly important to be able to anticipate changes ahead of time and develop a response with great agility. Honing our prediction skills, then, can become an incredible strength and a source of great competitive advantage.

Let's do a quick quiz. Can you identify the leaders who made the following predictions?

  1. The phonograph is of no commercial value
  2. I think there is a world market for about 5 computers
  3. 640K ought to be enough for anybody
  4. There is no reason for any individual to have a computer in their homes
  5. Computers in the future may not weigh more than 1.5 tons

Before I give you the answers, let me assure you that these are people of incredible repute who were at the top of their game when they made these predictions. We now know that these predictions are way off the mark. Some of them are ludicrously off. If this can happen to the best amongst us, is there any respite for the rest of us? Let's find out.

Why are we so outrageously bad at forecasting the future and what can we do about it?

One of Yogi Berra's famous quotes goes like this: "It is tough to make predictions, especially about the future". Let's face it, most of us are outrageously bad at forecasting the future. Let's understand why and what can we do about it.

1. Over-confidence effect

According to Philip Tetlock, a professor at the University of Pennsylvania and the author of “Superforecasting: The Art and Science of Prediction,” experts are only about as effective at predicting the future as dart-throwing chimpanzees.

This can be attributed to the overconfidence effect. Wikipedia summarizes this aptly. "The overconfidence effect is a well-established bias in which a person's subjective confidence in his or her judgments is reliably greater than the objective accuracy of those judgments, especially when confidence is relatively high."

In a way, this can be interpreted as, the more confident you are about a particular topic, the more prone to prediction errors you can get making you as vulnerable as a novice if not more.

What can we do about this?

Start recording your predictions, make them public, gather data post the event and do careful analysis of your win / loss ratio. Calibrate yourself accordingly.

2. Under-estimating exponential impact

Human minds are not really well wired for grasping exponential impacts. There's a famous legend about the inventor of the game of chess. When he showed the game to his emperor, the emperor was so thrilled by the new invention, that he offered to grant any wish the inventor had.

The inventor said, "Give me one grain of rice for the first square of the chessboard, two grains for the next square, four for the next, eight for the next and so on for all 64 squares, with each square having double the number of grains as the square before."

The emperor agreed to this request readily. It didn't seem like much after all. After some time, his minister informed him that there is not enough rice in the entire kingdom to satisfy the inventor's request. With each square in the chess board, the number of grains of rice was growing exponentially.

In the business and technology world, we consistently get caught off-guard by the sudden growth or development of exponential systems.

What can we do about this?

86% of the predictions made by Ray Kurzweil have supposed to have come true. Ray is what Tetlock would call a 'super predictor'. BigThink says "In fact, of the 147 predictions that Kurzweil has made since the 1990's, fully 115 of them have turned out to be correct, and another 12 have turned out to be "essentially correct" (off by a year or two), giving his predictions a stunning 86% accuracy rate."

The reason he gets his predictions right is that he has understood the underlying laws that govern the systems that he is making a prediction on.

The key takeaway is that it is important for us to be systems thinkers to get better at making predictions.

3. Lack of accountability / feedback loops

Better forecasting doesn't just entail making better predictions but also having the diligence to gather data afterward and being honest to oneself about which predictions were right and wrong. Weather men and stock traders typically have a tight feedback loop that helps them figure out if their prediction was sound or not. But there are many other systems where the feedback loop is not straight forward. Sometimes the timelines for the prediction are long drawn out or the prediction itself is ill-defined.

What can we do about this?

Gather data post the event, take accountability for the right / wrong predictions. Attach a material consequence to getting predictions wrong. This is bound to make us grounded.

In closing, I'd like to add that our learning systems should equip us to think clearly about the future. That's where we'll all end up after all. Simulations and scenario planning exercises can help us appreciate, understand and apply the power of probabilities.

Here are the answers to the questions above:

  1. Thomas Edison
  2. Tom Watson (IBM)
  3. Bill Gates (MSFT)
  4. Ken Olsen (DEC)
  5. Popular Mechanics magazine, 1949

September 16, 2017 - Comments Off on IS IT REALLY AI VS HR?


- Sethu M, SVP - Growth, KNOLSKAPE

Showcasing immersive tech based learning capabilities was bound to throw up some interesting conversations, here’s one such conversation I had with a visitor to our stall at TechHR2017. Read more

September 15, 2017 - No Comments!

Human response to AI : 3 Possible Scenario

by Rajiv Jayaraman, Founder - CEO, KNOLSKAPE

With advancements in AI reaching dizzying heights, the narrative around AI taking control away from humans is reaching fever pitch. What used to be thought of as uniquely human endeavors, such as writing poems, driving cars, composing music etc., are now being done by robots and in ways that are, in many instances, far superior to human performance. So as an intelligent species that has evolved over many thousands of years, how would humans, most likely, respond and adapt to this situation?

Scenario 1: Humans lose the plot and cede control completely to AI, leading to a disastrous outcome

Elon Musk has been vocal about the dangers of AI. He goes to the extent of saying that AI could be the likely cause of World War III, as countries ramp up their investments in AI. Musk says that war may be initiated not by the country leaders, but one of the AIs, if it decides that a preemptive strike is most probable path to victory.

Scenario 2: Humans find smart ways to collaborate with AI and emerge stronger

Garry Kasparov, the chess grand master, makes a fervent plea to all of us to stop fearing intelligent machines and start working closely with them. In his scintillating TED talk(one of my all-time favorite talks), he demonstrates how the human + machine combination is able to systematically beat the machine in the game of chess.

Scenario 3: Humans upgrade themselves and acquire superhuman capabilities

Yuval Noah Harari, the author of Sapiens and Homo Deus : A Brief History of Tomorrow says, “Every day millions of people decide to grant their smartphone a bit more control over their lives or try a new and more effective antidepressant drug. In pursuit of health, happiness and power, humans will gradually change first one of their features and then another, and another, until they will no longer be human.”

Just recently, MIT Technology Review reported that baby genome sequencing is available in China for $1500. This provides parents the possibility of producing designer babies that have reduced risk of diseases. With potential advancements in this domain, it is eminently conceivable that humans will slowly upgrade their "features" and become superhuman. Humans v 2.0 might acquire skills that are far superior to that of robots.

Of course, these are not mutually exclusive scenarios and they are by no means collectively exhaustive. I am sure there are plenty of other scenarios that might emerge as we wrap our heads around this. What do you think are some other possible scenarios?

September 14, 2017 - No Comments!

8 Lessons about Innovation from leaders at leading Global Innovation Centers in India

by Rajiv Jayaraman, Founder - CEO, KNOLSKAPE

I had the opportunity to moderate a panel discussion hosted by AXA business services yesterday in Bangalore, India. The theme was "The Innovation Paradigm- Making it by design". Here are some key insights from the panelists and other guests at the event.

8 Lessons About Innovation

1. "Innovate or perish"

This refrain has never been so pressing and apt as it is today. Every conference you walk into these days leaves you with punchlines that go something like: "If you are not Uberized, you will be Kodak'd" or "It is not the big fish that eats the small fish, it is the fast fish that eats the slow fish". Innovation is imperative for staying relevant and ahead of the game.

2. "Be a nowist" - Joi Ito.

Marie-Louise, the CEO of AXA Business Services, observed that all that one needs to do is stay aware and observe because innovation is all around us. An alert mind seizes the opportunity that's available now.

3. "Innovation is about impact"

While invention is all about creating something new, innovation is about making it useful for a large set of people and creating value in the process.

4. "Electric bulb was not invented by continuous improvement of the candle"

Mr. SriKrishnan from Bosch made a wonderful point about the need to pursue disruptive innovation and doing so in an agile, lean fashion.

5. "There is no such thing as failure. Only learning"

Solomon Devaraj, Dy. CEO of AXA Business Services, spoke about how it is important to reward failures as well. Without this, the culture of innovation doesn't take roots within an organization. It is important to include everyone in the innovation process.

6. "Balancing the now with the next"

Rathnaprabha, Head of Innovation and IT transformation at Societe Generale, spoke about the need to find frugal ways to fund the new in order to balance the now with the next.

7. "Empathy is key"

Dipankar Khasnabis from Infosys Business Consulting spoke about how empathy is key while solving real world problems. This is the essential building block of design thinking.

8. "Innovation is an investment"

Joy-Rajarshi from ABB spoke about how it is important to view innovation as an investment. It is important to establish an ecosystem within an organization for innovation to thrive with senior leadership playing an important role in sponsoring new ideas.


September 13, 2017 - No Comments!

Future of Banks: IaaS, PaaS, SaaS?

by Rajiv Jayaraman, Founder - CEO, KNOLSKAPE

KNOLSKAPE has been working closely with senior leadership teams at large banks in India and APAC to build digital leadership capabilities across critical levels of the organization. As part of our research and eventual large roll-outs, we have been learning some crucial insights on the future of banking.

Here are some nuggets:

  • To say that banking is undergoing massive transformation because of digital would be stating the obvious. In the next 2-3 years, we are likely to witness a fundamentally different industry structure.
  • The banking industry stack may start to look more like the software industry stack, with some players becoming Infra as a Service (IAAS) players, some becoming Platform as a Service (PAAS) players and others becoming Software as a Service (SAAS) players. There will be behemoths who will try to do all three at the same time, the way Amazon does it in the retail / cloud space.
  • Banking is moving towards an open, API based system. Some upcoming regulations will require banks to open their data to third party fintech companies, based on customer consent. This may eventually lead to the "Uberization" of the banking industry.
  • Traditionally, banks have looked at processes from the following 3 lenses : Risk / Compliance, Customers and Profitability, with Risk and Profitability being the dominant lenses and the customer lens taking the back seat. That can't work anymore in the digital age where customers are spoiled for choice. Banks need to find a way to put customers first without breaking the risk and profitability lenses.
  • "GAFA" might soon become the new competitor set for banks. GAFA = Google, Apple, Facebook, Amazon.