The global key trends for 2018 brought about some significant changes in innovation and technology. With the start of 2019, Shailesh Kumar Dave, Vice President, ManageEngine a division of Zoho Corp. and a technology veteran expects technology trends to disrupt, shift and change the way you do business.

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Below are 5 key exponential technology trends to watch out for in 2019.

Digital process automation will accelerate

Enterprise adoption of process automation technologies will continue with the same vigor as the technologies are expected to make the enterprises nimble, data-centric and quick to make decisions across geographies. More importantly, process automation will also help enterprises to go beyond the simple operational and efficiency gains made with basic automation to tap new revenue opportunities.

For example, a bank embracing fintech can use digital process automation to improve real-time visibility into its customers’ data and factor the improved view into real-time risk assessment of the customers.  To elucidate further, a bank could provide its customers with digital tools related to accounting, receivables, payables, and all other back office functions. The customers can give permission to the bank to use selective data to have good visibility on the velocity of their businesses. This could enable the bank to provide financial services at a faster clip to the customer and at lower cost, not only due to automation but also do due to better risk visibility of the customer.

OCR/NLP/Voice/Video/Image processing will aid productivity gains

The main nemesis of process automation is any web form customers, employees, or partners must fill out when an organization wants to capture their data.  Every one dreads screens with forms.

AI/machine learning technologies are mature enough to process voice, video, text, and images reliably. Using these mature technologies, the natural activities of making a phone call, taking a video, or taking a picture could be used to fill out data-enriched forms automatically. Hence both objectives will be met – collecting adequate data and filling out fewer forms – and these technologies will continue their march into the enterprise.

Privacy concerns will hold center stage

With GDPR becoming a reality and hosts of other countries passing similar privacy laws, data usage will be closely monitored. Data will be tagged so that its origin will be known at the point of usage. Tools related to data tagging and master data management will become crucial. Privacy concerns and related legal ramifications could slow down decision making in enterprises. In response, new generation messaging, audio/video web conferencing tools will be used by enterprises to achieve the twin objectives of privacy compliance and rapid decision making.

Data locality will increase diversity

Lots of countries mandate that data needs to reside within geographical boundaries. Enterprises using SAAS or PAAs will end up using country-specific public clouds or even private clouds. As a result, critical data and applications that need to be monitored will be spread across geographies. Monitoring tools and technologies that help consolidate the view of these applications and data will see larger enterprise adoption.

This increase in data locality will also require federated Identity and Access Management [IAM] with Zero Trust security considerations. Single sign-on, multi-factor authentication, and enterprise mobility management will also become common place in the enterprises.

New kinds of hardware in the data center

Data workloads in the data center are increasing, and the demise of Moore’s law is not helping the CPU to keep pace. Newer hardware like GPU, FPGA, ASICs will become commonplace in the data center.  Enterprise IT teams will have to be knowledgable about these technologies and use the right applications and tools to ensure that money is wisely spent on the newer hardware.

About the Author

Shailesh Dave is the Vice President, ManageEngine, a division of Zoho Corp. You can know more about him here.

In an era where advancements around technology have leapfrogged exponentially, the year ahead will see the Indian IT industry charter new frontiers, driven by innovation, speed and accuracy. The IT industry would see enterprises move towards Industry 4.0, the convergence of Internet of Things [IoT], cloud computing among others will enable them to be future-ready.

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Driven by technological advancements and data security at the core, we foresee all sectors in the Indian industry in for exciting times and the Banking, Financial Services, Insurance [BFSI] and Healthcare segments will be no exception. Complexity brews herein, fueled by regulatory challenges, uncertain economic cycles, risks, partnerships and alliances, talent management and above all ever-increasing customer expectations.

With this backdrop, the top technology trends to watch out in 2019 would be

Intelligent Digital Mesh

Intelligent digital mesh, the combination of humans, devices, content, and services is going to emerge as one of the major trends of the year 2019. Businesses have already started adapting this innovative technology to convey advanced results, where technology is embedded in almost every facet.

Artificial Intelligence/Machine Learning

With AI and ML already playing a critical role in the assessment and treatment of business KPIs, the IT operations are further set to undergo transformation. In 2019, there will be continued progress toward the integration of AI, ML and deep learning in business applications. AI and ML will enable working with large swathes of data and help converge isolated or distributed data for more informed decisions. There will be a further push to implement machine learning and artificial intelligence into smart devices.

As per a recent industry report, AI will boost India’s annual growth rate by 1.3% by 2035. Some of the major growth drivers of AI/ML in 2019 would be – specialized chip optimized for speeding up the execution of AI-enabled applications and Industrial IoT, making it the biggest driver of artificial intelligence in any enterprise.

Internet of Things [IOT]

IoT is no longer viewed as a wonder but an enabler. The year 2019 will see incremental use cases of IoT in the Insurance space. Telematics, wearables, voice assistants and home control devices will mature further and will be increasingly adopted. There will be a continued rise in the demand for wearable devices and IoT.

The convergence of IoT and AI will create new opportunities for insurers and better and more customized premiums for the insured. It will enhance process transparency and service delivery.

Robotic Process Automation

The Robotic Process Automation [RPA] is seeing traction in the IT industry. The robots have been modernizing our way of administering business processes, IT support, workflow, remote infrastructure and back-office work.

In the upcoming year, the improvised RPA models will show some dramatic progress in accuracy, cycle-time and increased productivity in transaction processing. RPA will be efficient enough in providing answers to the queries in a natural language which will be a superior way to conserve resources for large call centres and for customer interactions. We will see the further adoption of tools like chatbots, straight through processing and robotic process automation for routine repetitive processes. Chabot will be integral to websites and mobile apps.

Big data and analytics

Data and analytics have become daily aspects of organisations today across industries, which improvises business processes and optimizes operations. Presently, it is estimated to be $2.71 billion annually in revenues, which is growing at a healthy rate of 33.5% CAGR in India, as per a recent report. However, 2019 will bring a modern version of big data analytics which has evolved through adopting modern and breakthrough technologies. Speed and efficiency are the major benefits that big data analytics will bring to the industry.

Data and data value management is something that is going to dominate our industries over the next few decades at least. Estimates peg that the analytics, data science and big data industry in India is expected to reach $20 billion, by 2025. Prescriptive analytics driving proactive decision making, cognitive technologies reiterating businesses, increasing adoption of cloud-based platforms for big data analytics by major enterprise and start-ups are some of the future trends that we can look forward to, in 2019.

Blockchain

In 2019, blockchain will bring some enterprise applications into the main stream. The most innovative corporations will start using blockchain to improve collaboration. Blockchain will also see itself out of cryptocurrency transactions and will become an integral part of the business platform. Blockchain enables transactional transparency across a variety of business functions. Blockchain will also be present at the core of business innovation in many industries.

According to a recent report, an approximate of 56% of Indian businesses will be making the blockchain technology a part of their core business. Blockchain adoption will depend on regulatory concerns being addressed. The government and the regulators should take an active role in making this happen. In certain countries, we are already seeing action in this space, whereas most are yet to take their step forward.

About the Author

Mr. Padmanabhan Iyer is the Managing Director & Global CEO, 3i Infotech. You can find more about him here.

An efficient and effective hiring process is one of the main pillars of a successful company. The recruitment team has a difficult job on their hands as they’re responsible for sourcing the future employees of a company. If this process is flawed and they take too much time to find the right candidates, it can incur a substantial cost to the company. You might also lose out on good candidates while your competitors might end up hiring them.

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Qualified candidates are always in demand and research has found that they’re usually available for 10 days only. So, your hiring process needs to be quick and effective.

Here are some awesome strategies that will help you speed up your time-to-hire in the best possible ways.

Create a Structured Hiring Process

Not having a structured hiring process can lead to mismanagement and confusion. Candidates won’t get to know what the next step in the hiring process is. This will result in a poor candidate experience which can drive away many qualified candidates.

A documented and streamlined hiring process will help you minimize your time-to-hire as you will know what to do next. Your hiring team needs to be knowledgeable and experienced enough to set up an efficient recruiting process.

Build a Strong Employer Brand

Passive candidates are those who aren’t actively searching for other opportunities but wouldn’t mind considering suitable opportunities if they come up.

Building a strong employer brand can help you attract these passive candidates who constitute 85% of the workforce. This can help you tap into a wider pool of experienced and knowledgeable candidates.

Candidates are likely to be impressed and apply for positions at your company when you have a strong employer brand. You can build a strong employer brand by regularly responding to your online reviews and sharing updates about your work environment and culture.

When you build a strong employer brand, you might become an employer of choice for many applicants. This is likely to bring a steady source of quality candidates to your job openings.

Building consistent and loyal employee is also a great way to attract new talent which enhances the sound work culture in the organization. Time to hire will speed up automatically and you will get what you want for work.

Audit Existing Talent

You need to keep yourself updated about the status of existing candidates in your recruitment database. Internal auditing will save you time and can help you keep better track of candidates who might be looking for jobs. You can even fill out some of your vacant job positions by carefully auditing this talent pool.

If you want to learn more about how can you reduce your time-to-hire, check out the infographic given below

Infographic Source

About the Author

Ray O’Donnell is the Founder & CEO of TotalRewards Software, Inc. and Candidate Rewards. He has been helping companies to find, retain, and engage top talent by bridging the gap between the two. TotalRewards Software, Inc. is available on on LinkedIn, Twitter, and YouTube.

According to a recent Indian jobs study, data science is one of the topmost and fastest growing field in India and its relevance is increasing in almost every sector. Reports from NASSCOM suggests that India’s data industry would reach $16 billion by 2025 from the present level of $2 billion. At the core of it, data science is the science of examining raw data and applying statistical techniques for the purpose of drawing business related conclusions and predicting business outcomes. In every organization, there are opportunities to implement data science and transform the way business is carried out.

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Leading analysts like Gartner and Forrester have quoted 2018 as a milestone year for organizations, with over 70% of them expected to leverage data science for Business Optimization.  It is one of the most talked about topics in the CxO community.

In today’s era, all small and large corporates are sitting on a gold mine of data, however, the biggest challenge they are facing is to use these data to get business insights which they can implement to make effective business decisions and optimize their business. In the Indian context, below are the industries adapting data science to gain the competitive advantage

  • Financial institutions are optimizing price, improving customer satisfactions, predicting risk of defaults, optimizing underwriting process
  • Hospitals are increasing diagnoses accuracy, providing physicians with accurate sickness’s causes for individual patients, preventing patient readmissions, predicting risk of infections
  • Retail chains are increasing occasional and loyal customer satisfaction, optimizing campaigns, offering the right price for products, preventing inventory shortage
  • Manufacturing organizations are predicting machine failures, providing predictive safety alerts, building accurate pro-active maintenance plan

However, applying traditional data science methods to real-world business problems is time-consuming, resource-intensive, and challenging. It also requires experts in the several disciplines, including data scientists.

Enterprises leveraging Automated Data Science to achieve efficiencies

Automated data Science represents a fundamental shift in the way organizations of all sizes approach machine learning and data science. Automated data science platforms are bringing the advanced AI techniques into reach for the mainstream. Organizations are finding that with automated data science they can make progress in AI without hiring new data scientists or embarking on expensive, time-consuming training for their employees. Instead, almost anyone with domain experience and a familiarity with data can build predictive models without writing a single line of code or having deep knowledge of machine learning algorithms.

With automated data science, AI innovation is not just exclusively in the realm of the data scientists, but can now be shared with those that best understand the business needs. The main obstacle to AI success is no longer capability, but rather a refusal to embrace new methods and new approaches. Automated data science platforms removes many of these obstacles, and with a sound data science strategy will accelerate your success.

Automated data science saves up to 80% of time in model building, cuts 90% of the learning curve time, delivers 20~40% more accurate and stable models and lastly zero preparation time for production deployment of models, thereby giving the utmost advantage to organizations to adapt data science.

The world is being disrupted by visionaries. Combining the power of AI and automated data science with a sound strategy is helping build a future that is smarter, more efficient, and fairer for everyone. The companies that take advantage of automated data science will succeed and prosper. Those that don’t will be left behind.

About the Author

Srinivasan Rengarajan is the VP & Global Head – Data Science and Analytics at 3i Infotech. You can know more about him here.

In today’s globalized world, disease outbreaks do not stop at national borders. A health threat anywhere is a health threat everywhere. Efforts taken by the United Nations [UN], World Health Organization [WHO] and Centre for Disease Control and Prevention [CDC] in conjunction with the healthcare efforts taken up by various governments, NGOs, Research Institutions, Branded Pharma Companies etc. have managed to reduce the impact of Communicable Diseases and as per 2016 WHO data, Lower Respiratory Tract Infection is the only Communicable Disease that features in the list of Top 10 Diseases Causing Death. Globally. And hence, in today’s world, it’s not enough to only focus on vaccination and cure but it’s equally important to do effective reporting to control the cross border movement.

Image Source – BlockChain

This is a perfect use case for Blockchain!

Using blockchain technology to record infected person’s information on a distributed ledger can allow stakeholders in different countries, conditional access to a single source of truth.  A patient’s health data can be recorded on a ledger as a transaction with a time stamped audit trail. This makes Communicable Disease information more secure [patient data is encrypted], can take out the inefficiencies with current reporting practices of sending emails or some other form of non-trusted way of reporting data and real time distribution of data to research centres, quarantine facilities, Points of Entries [POEs] etc.

A centralized system to upload infection and infected party related data is the fastest and the most efficient way of reporting them, within and across border. But security is a major concern for any Healthcare data, especially when it’s about an individual, who is infected by a Communicable Disease. Any mistake therein, can prove really expensive. Hence any system used for this purpose need to be highly secure. Not all record sharing system, using the internet, will be secure. The system might be able to share data real time but the quality of data may be questioned. They might become the hackers’ target.

Blockchain Technology, with its built-in security will be able to address these concerns. Each relevant party can be a node in the chain, and on-boarding a node can also be monitored and approved by an International Organization, like WHO, in this particular case, given the required confidentiality. Blockchain Technology has the underlying trust infrastructure built in. It doesn’t require validation by a centralized authority. Hence it’s faster and real time. Furthermore, Blockchain also removes the need for any intermediary, thereby reducing the cost of operations.

In fact, Blockchain has been garnering substantial attention across industries, with VC’s investing over USD 1.4 billion in the technology in the past 3 years. The World Economic Forum estimates 10% of the global GDP to be stored using Blockchain by 2027.

The top five advantages of Blockchain technology are:

  1. Greater transparency
  2. Enhanced security
  3. Improved traceability
  4. Increased efficiency and speed
  5. Reduced cost

Aren’t they all supremely important for reporting cross-border Communicable Disease cases, a challenge the whole world is trying to grapple with?

About the author

Mohua Sengupta is the EVP & Global Head at Services at 3i Infotech Ltd. More details about her can be found here

Subscription box services are a huge trend in e-commerce. Whether the contents are carefully selected by the customer [Blue Apron, Dollar Shave Club] or come in the form of a mystery box [Ipsy, Bark Box], people love this business model.

Image Source – Subscription Box Business

Buyers love the personalized surprise every month, while sellers love the predictable income due to recurring fees. It’s also satisfying to source specialty items and cater to a specific niche of discerning customers.

Why It’s a Blockbuster Idea to Start a Subscription Service

The subscription e-commerce market has jumped 100 percent annually for the past five years. According to a recent Forbes article, e-commerce subscribers are in the sweet 25 to 44-year-old demographic and bring home $50,000 to $100,000 a year. Although many current subscribers live in urban environments of the northeastern U.S., the market is growing exponentially. In fact, about 15 percent of online shoppers have one or more subscriptions to get products via monthly box services.

Women make up 60 percent of subscribers, but men are the ones most likely to have at least three active subscriptions to avoid trips to the store. Let’s look at the types of box services currently available in the market.

Three Types of Subscription Box Services

The different box types appeal to the core reasons people love getting them. Some subscribers want a monthly surprise, while others want to pick out each item for an uber-customized package.

  1. Build-A-Box – Customers choose each item from a list. Food and meal plan businesses often work off this model to provide variety and flexibility to clients.
  2. Mystery Box – Subscribers don’t know what they’ll get each month. The box includes regularly available merchandise as well as limited edition products. It provides a rewarding customer experience that increases profits and moves inventory quickly.
  3. Membership Model – This subscription resembles a Costco membership for a monthly fee. It grants access and purchase ability at the store. Membership models build customer loyalty and up-sell capabilities.

How to Build a Subscription Box Business in Eight Steps

Let’s look at each stage of building a subscription box business.

  1. Start with a great idea – Think of products and services that would appeal to a specific market. Common themes are makeup, fitness, or food. When figuring out your niche, get as specific as you can. For example, the categories above can be segmented further into glamour makeup, martial arts equipment, and workout snacks.
  2. Research potential customers – The more honed-in each box is, the easier it is to sell to a specific group of customers. This lets you optimize retention and customer experience.
  3. Develop a prototype box – Try out prototypes in sample markets to get feedback on each component. The idea is to develop a product your target customer will be delighted to receive every month.
  4. Pre-launch by building a community that can get the word out – Use online content, contests, and other strategies to generate buzz and collect email addresses.
  5. Pre-sales phase – This is where you convert test markets and leads to your first paying subscribers.
  6. Show me the money – Presales revenue lets you build and ship the first month’s boxes.
  7. Build – Grow your target demographic to achieve predictable monthly revenue. Use smart tools to manage your inventory and figure out the right quantities to buy. There are free economic order quantity [EOQ] calculators online that can help.
  8. Encourage word of mouth, shares and referrals. If your product is great, people will come back, but it’s equally important to get new customers in the early stages.

Two Manufacturing and Supplier Tips

The production of items for your boxes is a major consideration. Will you outsource this or handle it in-house?

  1. Negotiate – One of the most difficult things to negotiate is what percentage of the subscriber fee the supplier gets. Consider a per unit, per click, or per minute model that’s appropriate for your industry.
  2. Do it yourself – In the subscription business model, the more you can do yourself, the better. In-house sourcing is streamlined and gives an entrepreneur more control over quality and productivity. It comes down to cost and efficiency, but if you have the wherewithal to do so, this is the preferred sourcing.

Two Important Lessons from Successful Subscription Businesses

  1. Price it right – Establishing a price point involves how much you offer and how often, which lets you predict costs. it takes some research to stay competitive and set a realistic margin expectation based on the local market.
  2. Focus on both growth and retention – Customer retention is vital once you establish a steady subscriber base. Business owners must watch competitors and gather feedback from current subscribers. Product development and services should embrace new technology to enhances both the brand image and bottom line. Take Netflix for example. The subscription-based business constantly adapts to ensure growth.

Conclusion

Ultimately, you need to convince your customers that your products or services are worth paying a monthly charge. The way to do this involves maintaining the speed, quality and customer service your subscribers deserve. Then, it’s a no-brainer, and you’re on your way to becoming a sought-after brand with no problem turning a one-time interaction into a continuing relationship.

References1, 2, 3, 4 & 5

About the Author

Laura Gayle is a full-time blogger at BussinessWomanGuide. She regularly writes on business, entrepreneurship, & e-commerce. You can contact Laura here.

In today’s era all small and large corporate are sitting on a gold mine of data, however, the biggest challenge they are facing to use these data to get business insights which they can to take effective business decisions and optimize their business.

Image Source – Business Optimization

‘Data Science’ is one of the most talked about topics in the CXO community and even leading analysts like Gartner and Forrester have quoted 2018 as a milestone year for organizations, with over 70% of them expected to leverage Data Science for Business Optimization.

Data Science is an automated method to analyze massive amount of data from various sources and extracting insights from them. Data science starts with examining raw data followed by applying statistical techniques for the purpose of drawing business related conclusions about the information and for modelling and predicting business outcomes.

According to recent industry reports, by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet. Hence, unraveling insights from this enormous amount of information will require the seamless adoption of big data technologies, stronger data security, and integration of AI, machine learning and cognitive technologies applications with business operations.

In 2018, the following trends around Data science and Big Data would likely surface. Trends which include – Prescriptive analytics is poised to drive proactive decision-making, which would impact HR processes; Demand for data scientist will substantially increase, while finding data scientists will be an equally arduous task; Cognitive technologies and Artificial Intelligence [AI] will help reshape business processes; Machine learning [ML] is fast becoming the fulcrum of big data platforms and analytics; Enterprises will increasingly adopt a cloud-first strategy and cloud-based platforms for big data analytics.

Use Cases – Key Success factor for any Data Science Program
There are 2 key success factors when it comes to a Data Science program. First one is the identification of the right business use case and the second one is the availability of underlying data. While many organizations are in the process of preparing their systems to be able to apply Data Science and reap its true benefits, the true challenge is with nailing down the right business cases. Business use cases always needs to start with expected outcome and has to be a combination Business Benefits, Organizational Readiness and Technical Complexity.

Business use cases are often specific to the industry and it is important to select the right use case for your data science program based on your industry.  Let’s look at the top practical use cases by each Industry.

Conclusion

Unlike traditional analytics, Data Science programs are focused on a more specific optimization area but yield multi-fold business value. The key lies in the selection of the apt business use case and program execution – right from the data understanding to model deployment. Most of the successful data science program are executed in an iterative manner to refine the scope of the business case to achieve the desired outcome.

About the author

Srinivasan Rengarajan is the VP & Global Head of Data Science and Analytics at 3i Infotech Ltd. More details about him can be found here

The General Data Protection Regulation [GDPR], adopted in April 2016 after four years of deliberations, is now in force. The regulation made headlines around the globe with its stricter data protection standards, substantial fines, and most of all, extensive reach. The GDPR affects any organization that holds an EU citizen’s personal data, no matter the size or location. A company based in Asia is as accountable as a multinational enterprise with offices across Europe – as long as it collects and processes the data of EU citizens.

Image Source – GDPR

The regulation also delineated the data protection obligations of affected organizations – from adopting state-of-the-art security methods to providing people more access to and control of their data. Recognizing the sweeping changes required for compliance, the EU authorities granted member states and organizations two years to get ready and prepare. And today, the transition stage is over – the GDPR will now be enforced.

What happens now ?

Enforcement means that organizations should already be processing personal data in accordance with the GDPR – including provisions for data subject rights. Data Protection Authorities [DPAs] of EU member states will also already be able to penalize organizations that are not compliant. Depending on the member state, it is possible that regulators will immediately take action to address any noncompliance. Some regulatory bodies, however, plan on being more lenient with businesses and organizations that have started but not yet completed their compliance efforts.

What is the worst-case scenario? An organization is liable for damages caused by noncompliance and is subject to corresponding administrative fines. The heftiest fine is 20,000,000 euros or up to 4 percent of annual turnover, whichever is higher.

What is the best-case scenario? If an organization is fully compliant with the GDPR, or uses the regulation as a starting-off point and goes beyond the minimum standards, then there are significant advantages. Some benefits would be – secured valuable information, more efficient operations with proper archiving and data management, and increased trust from customers and users.

While the GDPR applies to personal data of EU citizens, the GDPR has sparked a change in privacy regulations across the world. The 2018 enforcement allowed several countries to make their own legislative improvements – the U.K. and Australia are just two of a number of regions that have also updated their data protection laws. This only indicates that GDPR compliance is a good opportunity – not just for multinational enterprises but smaller organizations as well – to keep up with global advances in data privacy and state-of-the-art security.

What should organizations be doing ?

Ideally, all the groundwork for compliance should have been finished by now, and items on the compliance checklist should have been ticked. Organizations should already be able to provide products or services that address their customers’ rights as outlined in the GDPR. Those using third-party applications or suppliers should watch for updates concerning issues like the ‘right to be forgotten’ and stricter user consent standards and make sure they are working properly. Several laws as well as software changes are also expected to be in effect starting today or in the coming months, and organizations should be ready for any necessary changes.

For those not yet fully compliant, some member state DPAs have reassured companies ‘acting in good faith’ or on the way to compliance that they will initially be treated with consideration. It’s crucial to document steps being taken as well as to prioritize addressing potential security risks.

Ready or not, the road to GDPR compliance does not end on enforcement day – assessments and audits should be regular moving forward.

Building better data protection

The GDPR was enforced to set a new standard for data privacy and protection. One key element to this is building in privacy measures from the first stages of development – not patching up problems after they occur. As organizations create new products and applications post-implementation day, privacy by design must be kept in mind.

Through its new rules and standards, the GDPR encourages organizations to rethink existing data management policies and invest in state-of-the-art security for data protection. To reiterate, compliance efforts should be constant after GDPR implementation day; staying up to date with cybersecurity developments plays a major part.

We created an infographic to demonstrate the path well-protected personal data takes – leaving the data subject’s hands and on to an organization for secure processing. It also shows what happens if something goes wrong and what happens if everything goes right.

The Journey of Safe and Secure Personal Data Charting GDPR Compliance

About the Author

Nilesh Jain is the Vice President, South East Asia and India at Trend Micro. For more information, you can visit his profile here.