Zero Knowledge Proofs in Healthcare Data Sharing

Srinivasan Sundararajan

Recap of Healthcare Data Sharing

In my previous article (, I had elaborated on the challenges of Patient Master Data Management, Patient 360, and associated Patient Data Sharing. I had also outlined how our Rhodium framework is positioned to address the challenges of Patient Data Management and data sharing using a combination of multi-modal databases and Blockchain.

In this context, I have highlighted our maturity levels and the journey of Patient Data Sharing as follows:

  • Single Hospital
  • Between Hospitals part of HIE (Health Information Exchange)
  • Between Hospitals and Patients
  • Between Hospitals, Patients, and Other External Stakeholders

In each of the stages of the journey, I have highlighted various use cases. For example, in the third level of health data sharing between Hospitals and Patients, the use cases of consent management involving patients as well as monetization of personal data by patients themselves are mentioned.

In the fourth level of the journey, you must’ve read about the use case “Zero Knowledge Proofs”. In this article, I would be elaborating on:

  • What is Zero Knowledge Proof (ZKP)?
  • What is its role and importance in Healthcare Data Sharing?
  • How Blockchain Powered GAVS Rhodium Platform helps address the needs of ZKP?

Introduction to Zero Knowledge Proof

As the name suggests, Zero Knowledge Proof is about proving something without revealing the data behind that proof. Each transaction has a ‘verifier’ and a ‘prover’. In a transaction using ZKPs, the prover attempts to prove something to the verifier without revealing any other details to the verifier.

Zero Knowledge Proofs in Healthcare 

In today’s healthcare industry, a lot of time-consuming due diligence is done based on a lack of trust.

  • Insurance companies are always wary of fraudulent claims (which is anyhow a major issue), hence a lot of documentation and details are obtained and analyzed.
  • Hospitals, at the time of patient admission, need to know more about the patient, their insurance status, payment options, etc., hence they do detailed checks.
  • Pharmacists may have to verify that the Patient is indeed advised to take the medicines and give the same to the patients.
  • Patients most times also want to make sure that the diagnosis and treatment given to them are indeed proper and no wrong diagnosis is done.
  • Patients also want to ensure that doctors have legitimate licenses with no history of malpractice or any other wrongdoing.

In a healthcare scenario, either of the parties, i.e. patient, hospital, pharmacy, insurance companies, can take on the role of a verifier, and typically patients and sometimes hospitals are the provers.

While the ZKP can be applied to any of the transactions involving the above parties, currently the research in the industry is mostly focused on patient privacy rights and ZKP initiatives target more on how much or less of information a patient (prover) can share to a verifier before getting the required service based on the assertion of that proof.

Blockchain & Zero Knowledge Proof

While I am not getting into the fundamentals of Blockchain, but the readers should understand that one of the fundamental backbones of Blockchain is trust within the context of pseudo anonymity. In other words, some of the earlier uses of Blockchain, like cryptocurrency, aim to promote trust between unknown individuals without revealing any of their personal identities, yet allowing participation in a transaction.

Some of the characteristics of the Blockchain transaction that makes it conducive for Zero Knowledge Proofs are as follows:

  • Each transaction is initiated in the form of a smart contract.
  • Smart contract instance (i.e. the particular invocation of that smart contract) has an owner i.e. the public key of the account holder who creates the same, for example, a patient’s medical record can be created and owned by the patient themselves.
  • The other party can trust that transaction as long the other party knows the public key of the initiator.
  • Some of the important aspects of an approval life cycle like validation, approval, rejection, can be delegated to other stakeholders by delegating that task to the respective public key of that stakeholder.
  • For example, if a doctor needs to approve a medical condition of a patient, the same can be delegated to the doctor and only that particular doctor can approve it.
  • The anonymity of a person can be maintained, as everyone will see only the public key and other details can be hidden.
  • Some of the approval documents can be transferred using off-chain means (outside of the blockchain), such that participants of the blockchain will only see the proof of a claim but not the details behind it.
  • Further extending the data transfer with encryption of the sender’s private/public keys can lead to more advanced use cases.

Role of Blockchain Consortium

While Zero Knowledge Proofs can be implemented in any Blockchain platform including totally uncontrolled public blockchain platforms, their usage is best realized in private Blockchain consortiums. Here the identity of all participants is known, and each participant trusts the other, but the due diligence that is needed with the actual submission of proof is avoided.

Organizations that are part of similar domains and business processes form a Blockchain Network to get business benefits of their own processes. Such a Controlled Network among the known and identified organizations is known as a Consortium Blockchain.

Illustrated view of a Consortium Blockchain Involving Multiple Other Organizations, whose access rights differ. Each member controls their own access to Blockchain Network with Cryptographic Keys.

Members typically interact with the Blockchain Network by deploying Smart Contracts (i.e. Creating) as well as accessing the existing contracts.

Current Industry Research on Zero Knowledge Proof

Zero Knowledge Proof is a new but powerful concept in building trust-based networks. While basic Blockchain platform can help to bring the concept in a trust-based manner, a lot of research is being done to come up with a truly algorithmic zero knowledge proof.

A zk-SNARK (“zero-knowledge succinct non-interactive argument of knowledge”) utilizes a concept known as a “zero-knowledge proof”. Developers have already started integrating zk-SNARKs into Ethereum Blockchain platform. Zether, which was built by a group of academics and financial technology researchers including Dan Boneh from Stanford University, uses zero-knowledge proofs.

ZKP In GAVS Rhodium

As mentioned in my previous article about Patient Data Sharing, Rhodium is a futuristic framework that aims to take the Patient Data Sharing as a journey across multiple stages, and at the advanced maturity levels Zero Knowledge Proofs definitely find a place. Healthcare organizations can start experimenting and innovating on this front.

Rhodium Patient Data Sharing Journey

IT Infrastructure Managed Services

Healthcare Industry today is affected by fraud and lack of trust on one side, and on the other side growing privacy concerns of the patient. In this context, the introduction of a Zero Knowledge Proofs as part of healthcare transactions will help the industry to optimize itself and move towards seamless operations.

About the Author –

Srini is the Technology Advisor for GAVS. He is currently focused on Data Management Solutions for new-age enterprises using the combination of Multi Modal databases, Blockchain, and Data Mining. The solutions aim at data sharing within enterprises as well as with external stakeholders.

Healthcare Data Sharing

Srinivasan Sundararajan

Patient Care Redefined

The fight against the novel coronavirus has witnessed transformational changes in the way patient care is defined and managed. Proliferation of telemedicine has enabled consultations across geographies. In the current scenario, access to patients’ medical records has also assumed more importance.

The journey towards a solution also taught us that research on patient data is equally important. More the sample data about the infected patients, the better the vaccine/remedy. However, the growing concern about the privacy of patient data cannot be ignored. Moreover, patients who provide their data for medical research should also benefit from a monetary perspective, for their contributions.

The above facts basically point to the need for being able to share vital healthcare data efficiently so that patient care is improved, and more lives are saved.

The healthcare industry needs a data-sharing framework, which shares patient data but also provides much-needed controls on data ownership for various stakeholders, including the patients.

Types of Healthcare Data

  • PHR (Personal Health Record): An electronic record of health-related information on an individual that conforms to nationally recognized interoperability standards and that can be drawn from multiple sources while being managed, shared, and controlled by the individual.
  • EMR (Electronic Medical Record): Health-related information on an individual that can be created, gathered, managed, and consulted by authorized clinicians and staff within one healthcare organization. 
  • EHR (Electronic Health Record): Health-related information on an individual that conforms to nationally recognized interoperability standards and that can be created, managed and consulted by authorized clinicians and staff across more than one healthcare organization. 

In the context of large multi-specialty hospitals, EMR could also be specific to one specialist department and EHR could be the combination of information from various specialist departments in a single unified record.

Together these 3 forms of healthcare data provide a comprehensive view of a patient (patient 360), thus resulting in quicker diagnoses and personalized quality care.

Current Challenges in Sharing Healthcare Data

  • Lack of unique identity for patients prevents a single version of truth. Though there are government-issued IDs like SSN, their usage is not consistent across systems.
  • High cost and error-prone integration options with provider controlled EMR/EHR systems. While there is standardization with respect to healthcare interoperability API specifications, the effort needed for integration is high.
  • Conflict of interest in ensuring patient privacy and data integrity, while allowing data sharing. Digital ethics dictate that patient consent management take precedence while sharing their data.
  • Monetary benefits of medical research on patient data are not passed on to patients. As mentioned earlier, in today’s context analyzing existing patient information is critical to finding a cure for diseases, but there are no incentives for these patients.
  • Data stewardship, consent management, compliance needs like HIPAA, GDPR. Let’s assume a hospital specializing in heart-related issues shares a patient record with a hospital that specializes in eye care. How do we decide which portions of the patient information is owned by which hospital and how the governance is managed?
  • Lack of real-time information attributing to data quality issues and causing incorrect diagnoses.

The above list is not comprehensive but points to some of the issues that are plaguing the current healthcare data-sharing initiatives.

Blockchain for Healthcare Data Sharing

Some of the basic attributes of blockchain are mentioned below:

  • Blockchain is a distributed database, whereby each node of the database can be owned by a different stakeholder (say hospital departments) and yet all updates to the database eventually converge resulting in a distributed single version of truth.
  • Blockchain databases utilize a cryptography-based transaction processing mechanism, such that each object stored inside the database (say a patient record) can be distinctly owned by a public/private key pair and the ownership rights carry throughout the life cycle of the object (say from patient admission to discharge).
  • Blockchain transactions are carried out using smart contracts which basically attach the business rules to the underlying data, ensuring that the data is always compliant with the underlying business rules, making it even more reliable than the data available in traditional database systems.

These underlying properties of Blockchain make it a viable technology platform for healthcare data sharing, as well as to ensure data stewardship and patient privacy rights.

GAVS Rhodium Framework for Healthcare Data Sharing

GAVS has developed a framework – ‘Rhodium’, for healthcare data sharing.

This framework combines the best features of multi-modal databases (relational, nosql, graph) along with the viability of data sharing facilitated by Blockchain, to come up with a unified framework for healthcare data sharing.

The following are the high-level components (in a healthcare context) of the Rhodium framework. As you can see, each of the individual components of Rhodium play a role in healthcare information exchange at various levels.

GAVS’ Rhodium Framework for Healthcare

GAVS has also defined a maturity model for healthcare organizations for utilizing the framework towards healthcare data sharing. This model defines 4 stages of healthcare data sharing:

  • Within a Hospital 
  • Across Hospitals
  • Between Hospitals & Patients
  • Between Hospitals, Patients & Other Agencies

The below progression diagram illustrates how the framework can be extended for various stages of the life cycle, and typical use cases that are realized in each phase. Detailed explanations of various components of the Rhodium framework, and how it realizes use cases mentioned in the different stages will be covered in subsequent articles in this space.

Rhodium Patient Date Sharing Journey

Benefits of the GAVS Rhodium Framework for Healthcare Data Sharing

The following are the general foreseeable benefits of using the Rhodium framework for healthcare data sharing.

AIOps Digital Transformation Solutions

Healthcare Industry Trends with Respect to Data Sharing

The following are some of the trends we are seeing in Healthcare Data Sharing:

  • Interoperability will drive privacy and security improvements
  • New privacy regulations will continue to come up, in addition to HIPAA
  • The ethical and legal use of AI will empower healthcare data security and privacy
  • The rest of 2020 and 2021 will be defined by the duality of data security and data integration, and providers’ ability to execute on these priorities. That, in turn, will, in many ways, determine their effectiveness
  • In addition to industry regulations like HIPAA, national data privacy standards including Europe’s GDPR, California’s Consumer Privacy Act, and New York’s SHIELD Act will further increase the impetus for providers to prioritize privacy as a critical component of quality patient care

The below documentation from the HIMSS site talks about maturity levels with respect to healthcare interoperability, which is addressed by the Rhodium framework.


This framework is in its early stages of experimentation and is a prototype of how a Blockchain + Multi-Modal Database powered solution could be utilized for sharing healthcare data, that would be hugely beneficial to patients as well as healthcare providers.

About the Author –

Srini is the Technology Advisor for GAVS. He is currently focused on Data Management Solutions for new-age enterprises using the combination of Multi-Modal databases, Blockchain, and Data Mining. The solutions aim at data sharing within enterprises as well as with external stakeholders.

Observability versus Monitoring

Sri Chaganty

“Observability” has become a key trend in Service Reliability Engineering practice.  One of the recommendations from Gartner’s latest Market Guide for IT Infrastructure Monitoring Tools released in January 2020 says, “Contextualize data that ITIM tools collect from highly modular IT architectures by using AIOps to manage other sources, such as observability metrics from cloud-native monitoring tools.”

Like so many other terms in software engineering, ‘observability’ is a term borrowed from an older physical discipline: in this case, control systems engineering. Let me use the definition of observability from control theory in Wikipedia: “observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs.”

Observability is gaining attention in the software world because of its effectiveness at enabling engineers to deliver excellent customer experiences with software despite the complexity of the modern digital enterprise.

When we blew up the monolith into many services, we lost the ability to step through our code with a debugger: it now hops the network.  Monitoring tools are still coming to grips with this seismic shift.

How is observability different than monitoring?

Monitoring requires you to know what you care about before you know you care about it. Observability allows you to understand your entire system and how it fits together, and then use that information to discover what specifically you should care about when it’s most important.

Monitoring requires you to already know what normal is. Observability allows discovery of different types of ‘normal’ by looking at how the system behaves, over time, in different circumstances.

Monitoring asks the same questions over and over again. Is the CPU usage under 80%? Is memory usage under 75% percent? Or, is the latency under 500ms? This is valuable information, but monitoring is useful for known problems.

Observability, on the other side, is about asking different questions almost all the time. You discover new things.

Observability allows the discovery of different types of ‘normal’ by looking at behavior, over time, in different circumstances.

Metrics do not equal observability.

What Questions Can Observability Answer?

Below are sample questions that can be addressed by an effective observability solution:

  • Why is x broken?
  • What services does my service depend on — and what services are dependent on my service?
  • Why has performance degraded over the past quarter?
  • What changed? Why?
  • What logs should we look at right now?
  • What is system performance like for our most important customers?”
  • What SLO should we set?
  • Are we out of SLO?
  • What did my service look like at time point x?
  • What was the relationship between my service and x at time point y?
  • What was the relationship of attributed across the system before we deployed? What’s it like now?
  • What is most likely contributing to latency right now? What is most likely not?
  • Are these performance optimizations on the critical path?

About the Author –

Sri is a Serial Entrepreneur with over 30 years’ experience delivering creative, client-centric, value-driven solutions for bootstrapped and venture-backed startups.

Autonomous Things

Machine learning service provider

Bindu Vijayan

“Autonomous things (AuT), or the Internet of autonomous things (IoAT), is an emerging term for the technological developments that are expected to bring computers into the physical environment as autonomous entities without human direction, freely moving and interacting with humans and other objects…”

To put it simply, Autonomous Things use AI and work unsupervised to complete specific tasks without humans. Devices are enhanced with AI, sensors and analytical capabilities to be able to make informed and appropriate decisions.  They (these devices) work collaboratively between humans and the environment and provide superior performance.  Today AuT work across several environments with various levels of intelligence and capabilities. Some popular examples of these devices are drones, vehicles, smart home devices among others. The components of Autonomous things – software and AI hardware are getting increasingly efficient. With improved technologies (and significantly reducing sensor costs), the variety of tasks and processes that can be automated are increasing, with the advantage of bringing in more data and feedback that can efficiently improve and enhance the benefits of autonomous things.

The technology is used in a wide variety of scenarios – as data collectors from a variety of terrains and environments, as delivery systems (by Amazon, pizza deliveries, etc.), medical supplies to remote areas, etc. Robotics used in the supply chain has proven it reduces/elevates the danger out of the hitherto human tasks in warehouses.  And they probably have the most economic potential currently, followed by autonomous vehicles.  Drones are used to collect data across a wide variety of functions –  for surveillance, security, stock management, weather forecasting, obtaining air data, oceanic data, agricultural planning, etc.

Some fascinating use cases:


Drones are proving to be more and more effective in several ways – they are currently used extensively for surveillance of disaster sites that have biological hazards.  There is no better relevance than the current times when they can actually be used in epidemiology to track disease spread,  and of course for further research and studies.  Drones are facilitating on-demand healthcare by providing medicines to terrains that are difficult to access.  Swoop Aero is one such company that provides medicines via drones.  Drones have brought healthcare into the most remote areas with diagnosis and treatment made available. Remote areas of Africa have their regular medical supplies,  vaccine supplies, lab samples collected, emergency medical equipment made available through Drones. They are also used in telementoring, for perioperative evaluation and so on.  Drones have been very efficient in accessing areas and providing necessary support where ground transport is not reliable or safe or impossible.  Today, most governments have Drones on their national agenda under various sectors. The Delft University of Technology is developing an ambulance drone technology that can be used at disaster sites to increase rescue rates..


In a world where we have virtual assistants do grocery shopping, replenish stocks, and cooking machines making food, when there is a need to go out shopping, shoppers want to have an easy, fast and frictionless process.  Today, customers do not want to wait in queues and go through conventional checkouts, and Retailers know that they might be losing customers due to their checkout process.  And autonomous shops like Amazon Go are giving that experience to customers where they can purchase without the inconvenience of checkout lines.

Providers of checkout-free shopping technology like ‘Grabango’, use sensor vision and ML to actually hold a virtual shopping basket for every person in the store.  The technology is reputed to process a multitude simultaneous checkout transactions. “Grabango’s system uses high-quality sensor hardware and high-precision computer algorithms to acquire the location of every item in the store. This results in a real-time planogram covering the entire retail environment.” They say it results in increased sales and loyalty, streamlined operations and inventory management and out of stock alerts.


Companies like Chicago based, Komatsu American Corp., have autonomous haulage stems that have optimized safety in the mining industry like never before. They “help you continue to meet your bottom line while achieving zero-harm” while their focus has been on developing autonomous mining solutions, they have been doing it for more than three decades now! Their FrontRunner AHS has moved more than two billion tons of surface material so far in driverless operations.  Catepillar would be deploying their fleet of autonomous trucks and blast drills for the iron mine in Western Australia – Rio Tinto Koodaideri.  The industry is thriving with autonomous and semi autonomous equipment, and it is evident that it has brought improvements to productivity, and increased profitability. At the Australian mine “autonomous vehicles operated on average 700 hours longer and with 15 per cent lower unit costs”… Similarly, there are other companies like Intsite, a heavy machinery company; their autonomous crane ÁutoSite 100’ does autonomous operation of heavy machinery.


Most of us think Tesla when we think autonomous vehicles.  Elon Musk’s dream of providing autonomous ride-sharing has Tesla working on getting out one million robotaxis on the road this year. We will have to wait and see how that is going to pan out. Though autonomous vehicles are the most popular, I suppose it might take a little more time before it finds answers to the regulatory challenges, definitely not an easy task.  It gets quite overwhelming when we think of what we are expecting from autonomous vehicles – it assumes correct performance no matter the uncertainties on the roads and the environment, as well as the ability to face any sort of system failures on its own, and AI is a very critical technology when we are talking real-time decision making. Those sort of scenarios call for a strong computing platform in order to do the analysis at the edge for faster decision making.  The new V2X, which is the 5G vehicle-to-everything is expected to make autonomous vehicles mainstream because the vital information would get transmitted as structured data to the vehicle. V2X is expected to have vehicles interfacing with anything, be it pedestrians, roadside infrastructure, cyclists, etc.

Today, technology is also looking at ‘vehicle platooning’ – “Platoons decrease the distances between cars or trucks using electronic, and possibly mechanical, coupling. This capability would allow many cars or trucks to accelerate or brake simultaneously. This system also allows for a closer headway between vehicles by eliminating reacting distance needed for human reaction.” It has a group of self driving vehicles moving at high speed but safely, as the trucks are in constant communication with each other and use this intelligence to make informed decisions like braking, speeds, etc.  And autonomous trucks and cars can automatically join these platoons or leave, this has the advantages of reduced congestion, fewer traffic collisions, better fuel economy, and shorter commutes during peak hours. 


Studies show that Autonomous things are fast moving to ‘swarm’ or a bunch of intelligent devices, where multiple devices will function together collaboratively, as against the previously isolated intelligent components/ things. They are going to be intelligently networked among themselves and with the environment, and the wider that becomes within every industry, they are going to show phenomenal capabilities. But let’s not forget there is a whole other side to AI, given how unpredictable things are in life, AI would sooner or later have to respond to things that it never saw in training… we still are the smarter ones…


Smart Spaces Tech Trends for 2020

data center as a service providers in usa

Priyanka Pandey

These are unprecedented times. The world hadn’t witnessed such a disruption in recent history. It is times like these test the strength and resilience of our community. While we’ve been advised to maintain social distancing to flatten to curve, we must keep the wheels of the economy rolling.

In my previous article, I covered the ‘People-Centric’ Tech Trends of the year, i.e., Hyper automation, Multiexperience, Democratization, Human Augmentation and Transparency and Traceability. All of those hold more importance now in the light of current events. Per Gartner, Smart Spaces enable people to interact with people-centric technologies. Hence, the next Tech Trends in the list are about creating ‘Smart Spaces’ around us.

Smart spaces, in simple words, are interactive physical environments decked out with technology, that act as a bridge between humans and the digital world. The most common example of a smart space is a smart home, also called as a connected home. Other environments that could be a smart space are offices and communal workspaces; hotels, malls, hospitals, public places such as libraries and schools, and transportation portals such as airports and train stations. Listed below are the 5 Smart Spaces Technology Trends which, per Gartner, have great potential for disruption.

Trend 6: Empowered Edge

Edge computing is a distributed computing topology in which information processing and data storage are located closer to the sources, repositories and consumers of this information. Empowered Edge is about moving towards a smarter, faster and more flexible edge by using more adaptive processes, fog/mesh architectures, dynamic network topology and distributed cloud. This trend will be introduced across a spectrum of endpoint devices which includes simple embedded devices (e.g., appliances, industrial devices), input/output devices (e.g., speakers, screens), computing devices (e.g., smartphones, PCs) and complex embedded devices (e.g., automobiles, power generators). Per Gartner predictions, by 2022, more than 50% of enterprise-generated data will be created and processed outside the data center or cloud. This trend also includes the next-generation cellular standard after 4G Long Term Evolution (LTE), i.e., 5G. The concept of edge also percolates to the digital-twin models.

Trend 7: Distributed Cloud

Gartner defines a distributed cloud as “distribution of public cloud services to different locations outside the cloud providers’ data centers, while the originating public cloud provider assumes responsibility for the operation, governance, maintenance and updates.” Cloud computing has always been viewed as a centralized service, although, private and hybrid cloud options compliments this model. Implementing private cloud is not an easy task and hybrid cloud breaks many important cloud computing principles such as shifting the responsibility to cloud providers, exploiting the economics of cloud elasticity and using the top-class services of large cloud service providers. A distributed cloud provides services in a location which meets organization’s requirements without compromising on the features of a public cloud. This trend is still in the early stages of development and is expected to build in three phases:

Phase 1: Services will be provided from a micro-cloud which will have a subset of services from its centralized cloud.

Phase 2: An extension to phase 1, where service provider will team up with a third-party to deliver subset of services from the centralized cloud.

Phase 3: Distributed cloud substations will be setup which could be shared by different organizations. This will improve the economics associated as the installation cost can be split among the companies.

Trend 8: Autonomous Things

Autonomous can be defined as being able to control oneself. Similarly, Autonomous Things are devices which can operate by themselves without human intervention using AI to automate all their functions. The most common among these devices are robots, drones, and aircrafts. These devices can operate across different environments and will interact more naturally with their surroundings and people. While exploring use cases of this technology, understanding the different spaces the device will interact to, is very important like the people, terrain obstacles or other autonomous things. Another aspect to consider would be the level of autonomy which can be applied. The different levels are: No automation, Human-assisted automation, Partial automation, Conditional automation, High automation and Full automation. With the proliferation of this trend, a shift is expected from stand-alone intelligent things to collaborative intelligent things in which multiple devices work together to deliver the final output. The U.S. Defense Advanced Research Projects Agency (DARPA) is studying the use of drone swarms to defend or attack military targets.

Trend 9: Practical Blockchain

Most of us have heard about Blockchain technology. It is a tamper-proof, decentralized, distributed database that stores blocks of records linked together using cryptography. It holds the power to take industries to another level by enabling trust, providing transparency, reducing transaction settlement times and improving cash flow. Blockchain also makes it easy to trail assets back to its origin, reducing the chances of substituting it with counterfeit products. Smart contracts are used as part of the blockchain which can trigger actions on encountering any change in the blockchain; such as releasing payment when goods are received. New developments are being introduced in public blockchains but over time these will be integrated with permissioned blockchains which supports membership, governance and operating model requirements. Some of the use cases of this trend that Gartner has identified are: Asset Tracking, Identity Management/Know Your Client (KYC), Internal Record Keeping, Shared Record Keeping, Smart Cities/the IoT, Trading, Blockchain-based voting, Cryptocurrency payments and remittance services. Per the 2019 Gartner CIO Survey, in the next three years 60% of CIOs expect blockchain deployment in some way.

Trend 10: AI Security

Per Gartner, over the next five years AI-based decision-making will be applied across a wide set of use cases which will result in a tremendous increase of potential attack surfaces. Gartner provides three key perspectives on how AI impacts security: protecting AI-powered systems, leveraging AI to enhance security defense and anticipating negative use of AI by attackers. ML pipelines have different phases and at each of these phases there are various kinds of risks associated. AI-based security tools can be very powerful extension to toolkits with use cases such as security monitoring, malware detection, etc. On the other hand, there are many AI-related attack techniques which include training data poisoning, adversarial inputs and model theft and per Gartner predictions, through 2022, 30% of all AI cyberattacks will leverage these attacking techniques. Every innovation in AI can be exploited by attackers for finding new vulnerabilities. Few of the AI attacks that security professionals must explore are phishing, identity theft and DeepExploit.

One of the most important things to note here is that the trends listed above cannot exist in isolation. IT leaders must analyse what combination of these trends will drive the most innovation and strategy fitting it into their business models. Soon we will have smart spaces around us in forms of factories, offices and cities with increasingly insightful digital services everywhere for an ambient experience.


About the Author:

Priyanka is an ardent feminist and a dog-lover. She spends her free time cooking, reading poetry and exploring new ways to conserve the environment.

People-Centric Technology Trends for 2020

Priyanka Pandey

“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change.”  

– Charles Darwin, 1809

Most of us know about ‘Darwinism’ or the theory of biological evolution by Charles Darwin. It talks about natural selection and inheriting variations by organisms to increase its ability to compete and survive. Over the years, there have been many examples that prove this theory applies not only to biological evolution, but also to the technological evolution. With technologies advancing with ever-increasing velocity, it becomes a necessity for Technology Innovation Leaders to adapt to these changes with least friction. What can come handy is the annual analysis report released by Gartner, which galvanizes different technology trends together.

The Gartner report for this year – ‘Gartner Top 10 Strategic Technology Trends for 2020’ is structured around the idea of “people-centric smart spaces”. It examines how certain technologies can create numerous opportunities and can drive disruptions in a way that will change how we, humans, will live in the coming years. This report makes it very clear that Artificial Intelligence (AI) plays a bottom-line role in providing a good ambient experience. It also talks about how important it is to have governing principles, policies, best practices and technology architectures to increase transparency and trust in AI.

At Gartner 2019 IT Symposium/Xpo™ in Orlando, Florida, Brian Burke, Gartner Research VP, said “These trends have a profound impact on the people and the spaces they inhabit. Rather than building a technology stack and then exploring the potential applications, organizations must consider the business and human context first.”

Workplaces are becoming more people-centric, putting people at the centre of any technology strategy. Organisations are now making significant investments in user experience to meet growing expectations. Listed below are the 5 People-centric Technology Trends which, per Gartner, have great potential for disruption.

Trend 1: Hyperautomation

Automation can broadly be defined as employing technology to perform routine tasks thus reducing the human involvement. Hyperautomation is the next step. This trend is about providing an end-to-end automation solution using a wide array of machine learning algorithms, packaged software and automation tools. Almost every forward-looking company is now looking at processes it can automate and are also aware of the potential of Robotic process automation (RPA) and Intelligent Business Process Management Suite (iBPMS) in achieving this. Since it involves automating every process of an entire organization like operations model and business process model, it often results in the creation of a dynamic, virtual representation of that organization, also called Digital Twin of Organization (DTO). DTO helps align employees with the organization’s goals and operations and evaluates the impact of changes in a constrained environment.

Trend 2: Multiexperience

Multiexperience is about changing the way people interact with the digital world by providing them with a multi-modal user interface that will utilize multisensory and multitouchpoints. It will use all human senses along with advanced technological senses (like heat, humidity, radar) to connect across different devices including traditional computing devices, wearables, automobiles, environmental sensors, and consumer appliances. These widened sensory channels will support varied capabilities, such as emotion recognition through facial expression analysis or using accelerometers to identify abnormal movements that may indicate a health condition. Both Google and Amazon are already working on providing multi experience by adding screens and cameras to their smart speakers.

Per Gartner, “By 2023, more than 25% of the mobile apps, progressive web apps, and conversational apps at large enterprises will be built and/or run through a multiexperience development platform.” A multiexperience development platform (MXDP) is a suite that offers both front-end and back-end services for the development of an ambient experience that can be integrated across a range of devices. Although predictions state that privacy concerns can impact the level of adoption in many organizations, but it is still expected to evolve through 2024.

Trend 3: Democratization

Democratization is about empowering everyone through access to technical and business level expertise without extensive and costly training. The target of this trend could be anyone from customers, business partners to professional application developers and assembly line workers. Democratization has four key aspects: Democratization of Application Development, Democratization of Data and Analytics, Democratization of Design and Democratization of Knowledge.

It also talks about dealing with “Shadow AI”. Shadow AI is a natural outcome of democratization where people without formal training can use tools to develop their own AI-powered solutions and provide peer-to-peer support to others. Low-code or No-code application development has seen an increase due to the rising demand for rapid application development platforms. Per Gartner, by 2024, more than 65% of application development will be based on low-code development and 75% of large enterprises will be using at least four such tools for both IT application development and citizen development initiatives.

Trend 4: Human Augmentation

Human Augmentation (or “Human 2.0”) aims at enhancing human capabilities through technology. It may seem to be a new trend, but it started even before the computers were introduced. It goes back to the time when the usage of typewriter, copy machine and printing press started, which gave humans the ability to create, copy and publish text. This trend includes combining different innovations to deliver cognitive and physical improvements as part of human experience. Physical augmentation has several aspects like Sensory Augmentation, Brain Augmentation, Genetic Augmentation and, Appendage and Biological Function Augmentation. Since human augmentation will affect human lives to a very great extent, organizations must consider five major areas before adapting to it: Security, Privacy, Compliance, Health impact, Ethics. All types of enterprises are now examining ways of implementing human augmentation in different business use cases.

Trend 5: Transparency and Traceability

As consumers are becoming more aware, they want a guarantee of the products they consume and demand control over their personal information. With increasing AI-based decision making, the concern of digital ethics and privacy needs are rising, and transparency and traceability are critical in supporting it. This trend focuses on six pillars of trust: Ethics, Integrity, Openness, Accountability, Competence and Consistency. This is the age of surveillance capitalism. There are billions of endpoints collecting information of each one of us through which it is not difficult to identify who you are, where you are, what you’re doing and even what you’re thinking! Many jurisdictions, including Europe, South Africa, South Korea and China, have the ‘Right to be forgotten’ (RTBF) legislation in place. Gartner predicts that by 2023, over 75% of large organizations will employ AI experts in behaviour forensic, privacy, and customer trust to reduce brand and reputation risk and by 2025, 30% of government and large enterprise contracts for purchase of digital products and services using AI will require the use of explainable and ethical AI.

One of the most important things to note here is that the trends listed above cannot exist in isolation. For people-centric technologies to provide digital services, people need an environment where they can interact with digital spaces as a natural part of their everyday life. This brings in the concept of Smart Spaces. The next 5 trends in the Gartner report explores the technologies around Smart Spaces. IT leaders will have to analyse what combination of the above-mentioned trends along with smart space technologies, will drive the most innovation and strategy fitting it into their business models.

To Be Continued…         


About the Author:

Priyanka is an ardent feminist and a dog-lover. She spends her free time cooking, reading poetry and exploring new ways to conserve the environment.

Evolutionary Transitions and the Move to The Next Age™

Kerrie Hoffman

We are living in amazing times! It’s a time of transition and great transformation. As business continues to accelerate, all companies have a choice to either keep up with the transformation or experience an increased level of friction in their quest to serve the customer. Choosing the path of transformation will ignite the move into the Digital Flow of Business – and there’s a lot less friction in the Digital Flow.

History of the Ages

I mentioned we are living in a time of transition and great transformation. Looking back at human history, we find descriptions of eras, ages, and revolutions. Here are some interesting points about this History. Everyone is familiar with the Hunting and Gathering Era which started almost 2M years ago1; the Agricultural Age which started in 10,000 BC2, and the Industrial Age which started in the mid to late 1700s3. But have you thought about the impetus for the start of each age?

In my research, I have found the impetus for moving between the ages is a trigger of some sort, followed by a significant change in the way business is conducted:

•      The move into the agricultural age is when we moved from hunting and gathering to stationary farming with primitive irrigation. Stationary farming with irrigation was the trigger. This was a big change where people started to settle in villages and cities and sell their goods and services. A completely new way of living and working.

•      In the industrial revolution, we moved from small groups working with their hands to large organized departments working with Machines. Automation of manual work with machines was the trigger. This is where Corporations were eventually born. Another significant transformation in the way we live and work.

•      And in The Next Age™, we are fundamentally changing everything about the way we are used to working in the Industrial Age. The Next Age™ started around the year 2000 when early-adopting technology companies started developing platforms with Next Age architected technology. The year exponential technology became mainstream and the move accelerated was 2007.

The Year 2007

 Here’s an interesting side note on the year 2007. Many people are familiar with the book The World is Flat, by Thomas Friedman. He also wrote the book Thank You for Being Late. Chapter 2 is titled “What the Hell Happened in 2007”. I recommend reading the entire chapter/book, but here’s a sneak peek at some of the things conceived and launched in 2007: the iPhone, Hadoop, GitHub, Android, Twitter, and Facebook take off, Kindle, ATT software-defined network, Airbnb was conceived, internet users crossed the 1b mark, Watson began to be built, Intel created new materials, it was the beginning of clean power industry, the cost of DNA sequencing began to shift dramatically, and more!

Signs of the Move to The Next Age™

Moving from one age to the next requires a trigger followed by transformation. Transformation in this context is defined as a substantial and dramatic change in operations, processes, and structures to run a business.

Another sign we are in transition to The Next Age™ is the speed of business. Business is accelerating, we all feel this daily. Have you ever stopped to wonder why? This acceleration is largely due to rapid development of new technologies. In fact, technology is now being released at an exponential rate. Exponential growth in technology is the trigger for the move to The Next Age™. The challenge is, the adoption of these new technologies is lagging.

Early on in Thomas Friedman’s book Thank You for Being Late, he shows a chart by Eric Teller. The chart shows that technology is already on the exponential part of its curve, however human adaptability is not, in fact, it has fallen behind and caused a gap.

The impact this has on our businesses is profound. Do you have things in your business which used to work really well, and now not so much?  Why is this the case?

The Time to Transform is Now
It’s important we move now into adopting the transformation needed to keep our businesses relevant and growing strong. Interestingly, small business is moving somewhat organically into the next age partly out of necessity and partly because small businesses are comprised of small, nimble teams.

To fill the gap between exponential technology growth and human adaptability, it’s important to change the way we work. The reality is companies need to exit the Industrial Age and enter The Next Age™. Here are some of the key ways to change the way you work in The Next Age™:

  • Practice Extreme Customer Centricity
  • Work in small, end to end knowledgeable teams focused on customer micro-segments
  • Adopt a Digitally Expanded Mindset
  • Master the Digital Flow Framework

No matter the size of your business, companies in The Next Age™ work in small end-to-end knowledgeable teams with an extreme focus on the customer. For large companies and enterprises, this is a huge change requiring the breakdown of traditional siloed departments and micro-segmentation of the customer base. Extreme Customer Centricity means everyone understands the customer at a very deep level with strategy and process in place to solve customers’ issues, even when not part of the traditional product and service offerings of your company.

The opportunity is immense. Since small businesses naturally operate this way, there is an opportunity for mid and large size companies to learn from and be serviced by small companies. Of course, this may require a mindset change in large enterprises. Beyond the mindset change required for businesses of all sizes to work together, is the need to adopt a Digitally Expanded Mindset. 

There are 5 aspects to a Digitally Expanded Mindset:

  1. Behaviors and attitudes that see possibility in the digital era
  2. A belief in the power of technology
  3. An abundance mentality
  4. Comfort with ambiguity
  5. A growth outlook

You can read more about the 5 aspects of a Digitally Expanded Mindset in the article: Digital Mindset: 5 Aspects that Drive Digital Transformation4 published in the August 2019 edition of enGAge.

The transformation from one age to the next is no small feat. The best way to approach the transformation is to think of it as a journey where you break down the changes into several steps. There are 3 areas that need to be addressed: Talent, Operations, and Technology. The Digital Flow Framework™ breaks these areas down in detail. You can read more in the Forbes Article: Business Transformation Part 1: The Journey from Traditional Business to Digital Business.5

Lessons from History
There is a lot to learn from the transition we made to the Industrial Revolution starting centuries ago. The industrial revolution was a term popularized by the English economic historian Arnold Toynbee in the second half of the 1800s. He coined the term to describe Britain’s economic development starting in 1760 – so it was named the Industrial Revolution nearly 100 years after it started6. This first Industrial Revolution was dominated by Britain that innovated first and adapted faster.  Many other countries fell significantly behind from an economic standpoint. Britain’s vast economic development of the time created wealth and global significance. The second and third industrial

About the Author:

Kerrie is passionate about business transformation and getting as many companies as possible on their journey to The Next Age™. Kerrie is a #1 Bestselling Business Author and CEO of Hoffman Digital, an ecosystem of companies “Igniting the Human Experience at Work”. This includes Strategic Advisor at GAVS, Partner at Get Digital Velocity, and Digital Advisor at FocalPoint Business Coaching.

Essentials of a great place

Padmavathy Ravichanran

While flexible hours, gym time and vacation days are perks, a great place is achieved by doing a few practices that instil trust authentically and consistently.

In today’s digital landscape, leaders are inward, outward and forward-looking.

A great workplace is a place where every team member thinks and behaves like a leader, and where you achieve your organizational objectives with people who give their personal best and work together as a team, all in an environment of trust! As Satya Nadella says, “I know-it-all” to “I will learn-it-all”. Learning from inside and outside the organization are both profound.

Mindfulness and reflection facilitate sharper focus and better sensing. Through self – awareness we can address critical questions of, “What could I change to evolve better” and “how can I add more value” by interpreting cognitions, emotions, and reactions.

Here are a few practices to transform one’s workgroup into a great place.


Proactively solicit suggestions to encourage and incorporate creativity. To develop a personal, connect with team members.

Listening is essential to building trust. Listening to your team members enables you to discover their strengths and challenges, and continuous listening helps build authenticity.

GAVS believes in Respect for individuals, along with instilling trust, through channels of creating Empathy. To make this happen, GAVS has built sustainable tools and forums that encourage listening in the work environment.

As a culture, GAVS follows the open-door policy, and not hierarchy-driven when it comes to reaching out to the right people for the right answers. Each one of us is empowered to share perspectives, facts and solicit feedback that impact them. From GAVS voice to HR forums, from pulse checks to quarterly town halls, from ideation wall to helpdesks, listening is a crucial practice at GAVS.


A great place cultivates a “climate of appreciation” by sincerely recognizing good work and extra effort frequently and in unexpected ways. To ensure every person is appreciated and recognized for even the smallest contribution to ease someone’s work. Self-esteem plays a vital role in performance-oriented organization culture and it is a key driving force that motivates in the longer run. GAVS as an organization has imbibed the importance of this and made appreciation/recognition as part of its core cultural practice instilling a sense of purpose in everyone; one of the core beliefs at GAVS.

On-time appreciation and recognition happen at various stages and varying degrees starting from a simple pat on the back to a prestigious Star Performer award during the Town Hall, depending on the magnitude of the achievement and contribution.

The simplest yet effective mode of recognition is an instant appreciation a team member receives from his colleagues/manager in a daily huddle meet, thus promoting a sense of pride and respect. From thank you letter to families to an ice-cream treat for a perfect CSAT, from team lunch and dinners to gift vouchers and GPoints, from Wall of Appreciation/Wall of Fame to spot recognition, from Thank you notes from CXOs to long service awards, GAVS believes that – Appreciation is a wonderful thing. It makes what is excellent in others belong to us as well.


Empathy is one of the core values which GAVS very firmly believes and stands by. As much as we celebrate the success of GAVSians we share the pain of our colleagues during a personal crisis. At GAVS employee well-being is by embracing the individual, in totality. Whether it’s providing a sumptuous lunch, so we don’t have to worry about meal planning or a workstation yoga for our promoting health at work.through essential learning hours or training channels to learning best practices from one other.

From wellness programs like meditation sessions to team lunch and dinner, from a wellness lounge to providing healthy snacks, from health awareness camps to winding off playing table tennis to carom, from health coverage to bringing kids to work, we care for one another. We never miss asking the colleague who is back from a sick day off on how we could help him. A healthier, more motivated workforce is a happier, more productive workforce.


A great place doesn’t have complicated frameworks and models to drive employee experience. The employee experience is an aggregate of the thousands of short, transient interactions that each employee, experiences every week between themselves, the processes they follow, the technology they use, and the interaction with the peers and managers.

We are part of an industry where skillsets get outdated fast. To have a competitive edge in such an environment we must have the right people with the right mindset, and the right skillset. A learning culture is the one that nurtures talent and fosters competent and skilled resources to excel and pursue organizational strategic goals and the endeavors of customers.

Skills and competencies do contribute to the career progression, but a major part of success is the “how” and the “how well” of what one does in terms of performance and results. From onboarding right to providing learning interventions through a learning journey – either through essential learning hours or training channels to learning best practices from one other.

A great place doesn’t have complicated frameworks and models to drive employee experience. The employee experience is an aggregate of the thousands of short, transient interactions that each employee, experiences every week between themselves, the processes they follow, the technology they use, and the interaction with the peers and managers.

Each of us can contribute to a great place by

  • Having a high level of self-awareness
  • Learning, growing and seizing opportunities
  • Actively seeking feedback and respond positively to it
  • Having pride in our contribution to the mission
  • Collaborating with our colleagues
  • Integrating the practice of listening, thanking, caring and developing to instill more trust
  • Managing your personal brand

As a member of a great place, it is everyone’s responsibility to focus on the full circle and not the pieces alone as every situation may be unique, but a focused and purposeful employee holds the key to competitive advantage for the organization.

About the Author:

Padma’s Clifton Strength Finder Top 5 Signature Themes are Consistency, Discipline, Developer, Empathy, and Harmony. She is part of the HR team, and enjoys listening to her audio books, journaling, and practicing yoga.

Evolution of speech recognition

Naveen KT

Speaking with inanimate objects and getting work done through them has transitioned from being a figment of our imagination to a reality. Case in point, personal assistant devices like Alexa can recognize our words, interpret the meaning and carry out commands.

The journey of speech recognition technology has been nothing short of a rollercoaster ride. Let us look at the developments that enabled commercialization of ASR and what these systems could accomplish, long before any of us had heard of Siri or Google Assistant.

The speech recognition field was propelled by both the application of different approaches and the advancement of technology. Over a decade, researchers would conceive of myriad ways to dissect language: by sounds, by structure and with statistics.

Early Days

Even though human interest in recognizing and synthesizing speech goes back centuries, it was only in the last century that something recognizable as ASR was built. The ‘digit recognizer’ named Audrey, by Bell Laboratories was among the first projects. It could identify spoken numbers by looking for audio fingerprints called formants, the distilled essences of sounds.

Even though human interest in recognizing and synthesizing speech goes back centuries, it was only in the last century that something recognizable as ASR was built. The ‘digit recognizer’ named Audrey, by Bell Laboratories was among the first projects. It could identify spoken numbers by looking for audio fingerprints called formants, the distilled essences of sounds.

Next came the Shoebox in the 1960s. Developed by IBM, the Shoebox could recognize numbers and arithmetic commands (like ‘plus’ and ‘total’). Shoebox could also pass on the math problem to an adding machine, to calculate and print the answer.

Half way across the world, in Japan, hardware was being built that could recognize the constituent parts of speech like vowels. Systems were also being built to evaluate the structure of speech to figure out where a word might end.

A team at University College in England had devised a system that could recognize 4 vowels and 9 consonants by analysing phonemes, the discrete sounds of a language.

However, these were all disjointed efforts and were lacking direction.

In a surprising turn of events, the funding for ASR programs in Bell Laboratories were stopped in 1969. The reasons cited were “lack of scientific rigor” in the field and “too much wild experimentation”. It was reinstated in 1971.

In the early 1970s, the U.S. Department of Defence’s ARPA (the agency now known as DARPA) funded a five-year program called Speech Understanding Research. Several ASR systems were created and the most successful one Harpy (by Carnegie Mellon University), could recognize over 1000 words. Efforts to commercialize the technology had also picked up speed. IBM was working on speech transcription in the context of office correspondence, and Bell Laboratories on ‘command and control’ scenarios.

The key turning point was the popularization of Hidden Markov Models (HMMs). These models used a statistical approach that translated to a leap forward in accuracy. Soon, ASR field began coalescing around a set of tests that provided a benchmark to compare to. This was further encouraged by the release of shared data sets that researchers could use to train and test their models on.

ASR as we know it today, was introduced in the 1990s. Dragon Dictate launched in 1990 for a staggering $9,000, with a dictionary of 80,000 words and features like natural language processing.

These tools were time-consuming and it required that users speak in a tilted manner; Dragon could initially recognize only 30–40 words a minute; people typically talk around four times faster than that. By 1997, they introduced Dragon NaturallySpeaking, which could capture words at a more fluid pace and at a much lower price tag of $150.

Current Landscape

Voice has been touted as the future. Tech giants are investing in it and placing voice-enabled devices at the core of their business strategy.

Machine learning has been behind major breakthroughs in the field of speech recognition. Google’s efforts in this field culminated in the introduction of Google Voice Search app in 2008. They further refined this technology, with the help of huge volumes of training data and finally launched the Google Assistant.

Digital assistants like Google Assistant, Siri, Alexa and others, are changing the way people interact with their devices. Digital assistants are intended to assist individuals with performing or completing fundamental assignments and react to enquiries.

With the capacity to retrieve data from a wide variety of sources, these robots help take care of issues progressively, upgrading the UX and human productivity.

Popular Voice assistants include:

  • Amazon’s Alexa
  • Apple’s Siri
  • Google’s Google Assistant
  • Microsoft’s Cortana

Application of Speech Recognition Technology

Speech recognition technology and the use of digital has moved rapidly from our phones to our homes, and its application in ventures, for example, business, banking, advertising, and health care is rapidly becoming obvious.

In Workplace: Speech recognition technology in the work environment has been a push to increase productivity and efficiency. Examples of office tasks digital assistants are, or will be, able to perform:

  • Search for documents or reports on computer
  • Create tables or graphs using data
  • Answer queries
  • On-request document printing
  • Record minutes
  • Perform other routine tasks like scheduling meetings and making travel arrangements

In Banking: Theaim of Speech Recognition, in Banking

  • Financial industries is to reduce friction for the customer. Voice-enacted banking could diminish the requirement for human client assistance and lower employee costs. A customized financial partner could consequently help consumer loyalty and satisfaction.

How speech recognition can improve banking:

  • Request financial information
  • Make payments
  • Receive information about your transaction history

In Marketing: Voice-search can and will cause shifts in consumer behaviour. It is essential to understand such shifts and tweak the marketing activities to keep up with the times.

  • With speech recognition, there will be another type of information accessible for advertisers to examine. People’s accents, speech patterns, and vocabulary can be utilized to translate a purchaser’s area, age, and other data with respect to their socioeconomics, for example, their social alliance.
  • Speaking allows for longer, more conversational searches. Advertisers and optimisers may need to concentrate on long-tail keywords and on creating conversational substances to remain in front of these patterns.

In HealthCare: In a situation where seconds are critical and clean working conditions are essential, hands-free, prompt access to data can have a positive effect on medical efficiency.

Benefits include:

  • Quick looking up of information from medical records
  • Less paperwork
  • Reduced time on inputting data
  • Improved workflow

This is just scratching the surface of the applications of this technology. The future of speech recognition technology holds a lot of promise across various industries.



About the Author:

Naveen is a software developer at GAVS. He teaches underprivileged children and is interested in giving back to society in as many ways as he can. He is also interested in dancing, painting, playing keyboard and is a district-level handball player.

Mental Health at the Workplace – A call to action to make sure we “show up” wherever we go.

Vidyarth Venkateswaran

The world focused on a complex, yet socially hyper-relevant subject in “Suicide Prevention” on World Mental Health Day last month. As with any global social issue today, organizations such as WHO or WEF showcased their support in addressing it through efforts centered around awareness creation as well as well-thought-out programs that are implementable.

For the uninitiated – let’s look at some broad numbers to start with.

  • As per the WHO, suicide takes a life every 40 seconds, making it the principal cause of death among people fifteen to twenty-nine years old.
  • An estimated 275 million people suffer from anxiety disorders and depression today. That’s around 4% of the global population. Around

62% of those suffering from anxiety are female

(170 million), compared with 105 million male sufferers.

  • An estimated 26% of Americans aged 18 and older – about 1 in 4 adults – suffer from a diagnosable mental disorder each year.
  • Approximately 9.5% of American adults aged

18 and over, will suffer from a depressive illness (major depression, bipolar disorder, or dysthymia) each year.

  • In low- and middle-income countries, between 76% and 85% of people with mental disorders receive no treatment for their disorder. In high-income countries, between 35% and 50% of people with mental disorders are in the same situation.

While one might be forgiven if these issues do not “show up” at the workplace or do not negatively impact business and productivity, a look under the carpet reveals even more startling numbers:

  • A recent study revealed that 48% of British workers have experienced a mental health problem in their current job.
  • In India, nearly 42.5% of employees in the private sector suffer from depression or anxiety disorder, per the results of a study conducted by Assocham.
  • Per the National Mental Health Survey of India (2015-16), nearly 15% of Indian adults need active interventions for one or more mental health issues.
  • The UK loses an estimated 70 million man-days of effort due to conditions related to poor mental health – the resultant cost being in the range of £100 billion. On the flip side, the costs from ‘Presentism’ are double that number.

Not all is gloom and doom though. Many studies have shown that companies of all shapes and sizes increasingly understand the importance of good mental health. Today’s leaders are aware of the negative impact that poor mental health has on business and productivity. Firms are experimenting with and implementing proactive practices such as employee friendly policies to manage working hours, Fun@ Work programs, Employee Assistance programs etc. to promote mental well-being in their employees.

The aim here is not to establish that this subject is important and needs attention. It is however – a call to action. It is an attempt at emphasizing that while the initiatives at a strategic level are perhaps the norm, there is an increasing need for the effort to become even more individualized at the grass roots. Safeguarding staff well-being, addressing problems before they become severe, enabling those suffering with counseling when issues do emerge, need more headspace in discussions. To put things in perspective, here are some interesting practices that came to light as part of a recent study:

  • Leaders were encouraged to conduct a formal / informal review of employee mental health metrics along with quarterly financial results
  • Mental Health and Awareness sessions/events are being conducted periodically
  • Accountability is being established and Mental Health agenda is being driven through Wellness officers at senior leadership levels across all teams
  • Improving mental well-being as a driver to improving business productivity is taking an increasingly important role
  • Line Managers are being trained to enhance mental well-being in their teams.
  • Companies are beginning to include Mental

Wellness under “Return to Work” programs and other benefits packages

  • Enabling anonymous communication channels to encourage open communication and initiatives that work towards reducing the taboo that accompanies poor mental health
  • Enforcing practices through an Employee Wellness policy
  • Introducing “Power Down” hours where employees are encouraged to step away from their laptops and engage in non-work related interactions with their colleagues

At GAVS, we are proud to say that the topic of Mental Well-being of employees is very important to everyone across the board. For over a year now, employee initiatives under the #WELLNESS and Wellness Wednesdays umbrella have taken shape and are driving this agenda across the board. From guided meditation sessions focusing on self-awareness by some of our certified colleagues, Workstation Yoga, to targeted interventions through talks / sessions by experts, dedicated leadership to enhanced employee experience from Hire to Rehire, dedicated millennium bays where leaders and employees alike are encouraged to unwind, GAVS proactively does its bit in enabling and ensuring each GAVSian is given the opportunity to address his / her mental well-being. Flexible work arrangements and an open-door policy to the organization’s leadership are examples of other initiatives that focus on the broader employee well-being agenda as well.

Regarded as one of the greatest artists of her generation, Glenn Close said it with grace – “What mental health needs is more sunlight, more candor, and more unashamed conversation.” It is time, that asprofessionals and leaders, we embrace what it means to drive growth for our clients and our business and do it while also embracing ‘being human’.

References: suicide mental-disorders