As a part of the Corporate Social Responsibility, ESR Tech Chief Information Security Officer Ravi Dhungel delivered the best practices on child online safety to the families of the Little Angels&#39; School. ESR Tech is committed to cybersecurity and privacy to contribute to a safer and better virtual environment for young and old alike. We thank the Little Angels&#39; community for this opportunity. Let&#39;s work together to make the internet a safe place for everyone.

Best Practices on Child Online Safety

Starting with the idea of culture being the software for the brain&#39;s hardware, we looked at several &quot; behavioral rules&quot; one might have to guide behavior. Our cultural norms help us know what to expect in social situations, how to make decisions, and what leads to successful interactions. Cultures are layered and, within those layers, have many dimensions to them. We looked at the tree as a metaphor for culture and discussed several examples of what is considered surface culture, shallow culture, and deep culture. We then looked more closely at six dimensions of deep culture that shape our beliefs and values, which in turn impact our behavior at work.&nbsp;

Please find more information here: <a href="https://storage.googleapis.com/esrweb-blog-image/uploads/2020/12/21/organizational-culture-1.pdf" style="color: blue; text-decoration-line: underline" target="_blank">Organizational Culture</a>.

Organizational Culture: Company's operating system

The ESR Tech team wishes you and your family a wonderful Christmas time and a happy New Year! We hope that a great year is ahead of you and will bring you good health, joy, and prosperity. We are also going to be here for you in 2021. Contact us for our services and we are looking forward to helping you.

Merry Christmas and a Happy New Year!

The solar winds vulnerability exposed in December of 2020 shows the challenges and complexity of securing the software systems. Microsoft acknowledging the fact that their source codes were viewed is even more disturbing. The challenge to manage the supply chain in software systems and secure patches and builds in the applications are common denominators in cyber security. The impact of COVID-19 and the increase in remote learning, the digital data of students are stored in many learning management systems. The omnipresent of digital learning and gaming systems in the post COVID-19 increases the attack surface.&nbsp;Safeguarding the kids&#39; privacy and data security is a daunting task for educators, parents, and technology providers.

Vulnerable to threats 
Children are even more vulnerable to cyber threats. In the post COVID-19 era, kids are spending more time inside the house in mobile devices. Kids are using all types of electronic devices to play games and remote learning. Few strategies and best practices that help keep your kids safe on the internet are described below.

While society moves to consume digital technologies at an unprecedented rate, basic training in cyber security and privacy is needed to all. Parents and guardians should considering providing basic training on computer hygiene, data security, roles and responsibilities, and physical security to their children. The training should be similar to onboarding of new employees and refreshed yearly or bi-yearly. Basics on cyber security should be taught to all the citizens.

Policymakers and legislative bodies need to influence and educate your public policy experts and politicians to bring the new policy for child security on the internet. Engage and educate your public policy experts to bring the new policy for children security on the internet. The United States has policies such as FERPA (family educational rights and privacy act) and COPPA (children online privacy protection Act) to protect the privacy of children and students.

Law enforcement agencies have a vital role to play in strengthening cyber security. This is one of the most challenging jobs. Safeguarding the privacy of the individual under cybercrime investigation is even more challenging. Law enforcement agencies should protect the privacy of children during the investigation of any cybercrime incidents. They should be able to weigh the challenges on national security as there are no rules of engagement in cyber security.

It is the responsibility of the schools and higher education institutes to provide the education and training of cyber security and privacy to the students, parents and educators.

Instructional and educational technologies providers need to ensure that technology providers have all knots and bolts of cyber security controls in the system. It&#39;s the responsibility of software vendors to educate schools administrators and teachers on the cyber security best practices on their applications. Children are easily frightened and impressionable. Certain activities are illegal for children on the internet and real world. Parents can make decisions for children.

Criminal law bars on producing and possession of sexual abuse material. Internet is open, without appropriate technical and administrative controls of the internet. It is very difficult to control the access of the contents in the internet. Regularly educate your kids on internet security, cyber threats, and cyberbullying.

Cyberbullying is the use of electronic communication to bully a person, typically by sending messages of an intimidating or threatening nature. Children may be reluctant to admit to being the victims of cyberbullying. The access of the internet should be scheduled and closely monitored by parents. Allowing the apps that are well vetted on safety, security and usage is important before downloading arbitrary apps from the internet. Internet and online habits have real life consequences. Children need to acknowledge that online actions lead to real-life consequences.

Ask your kids about different sites they visit, listen passionately, pretend you don&#39;t know, and learn from them. Teach your kids the consequences of sharing age, location and other things to strangers on the internet. Educate not to share that information to someone on the internet and publish on the internet.

It is necessary to apply the patches of the software of routers, computers, mobiles and other digital devices. New patches provide security for the devices. Use antivirus software in the computers and maintain cyber hygiene.

Multiple passwords 
Recommend your kids to use multiple passwords for applications. If possible, use multi factor authentications such as SMS, phone calls or 2FA apps. Advise your kids not to use public wifi to browse the internet. The bad guys are waiting in the public space. Phishing is the most common and widely used cyber security challenge. Children should be taught about phishing emails and how they can recognise and avoid those emails.

If you are not using any kids account, close the account permanently. Be permissive on privacy settings that are available on most systems. Don&rsquo;t hesitate to call the software providers for privacy and data security of your kids. Computers are not reliable, so are the internet and network connectivity. Computers may get lost. Malware and ransomware can corrupt the data and ask for ransom. Teach your kids on how to back up the data or files so that kids don&rsquo;t freak out if something gets deleted.

Safeguarding Kids’ Privacy And Cybersecurity

You are trying to buy something important for your loved one on an e-commerce website and suddenly, the server doesn&rsquo;t respond after you click &lsquo;buy&rsquo; icon. You are in the middle of your medical screening and a medical professional cannot access your electronic medical record. Government has critical infrastructures which include power lines and central banks information that the government cannot access due to cyber-attack. Are computer systems inherently unreliable? Do we have cyber security controls in place to ensure the data is confidential, integral and available? Building cyber resilient enterprises continues to be a challenge to industry, government, and military. 
 
Developing cyber resilient enterprises is both art and science. Computer science is in the conundrum of art and science. Securing data in the computer and servers are even more challenging and inherently complex because of the scalability, complexity and interconnectivity of the computer networks. Lately, COVID-19 has led to the creation of plethora of workforces that have never worked from home and have established the new norm of zoom way of doing things all over the world.

Conceptual security model 
CIA (Confidentiality, Integrity and Availability) triad is the well-known conceptual security model for implementing security controls in the digital information system. &rsquo;C&rsquo; in the CIA triad stands for Confidentiality. Confidentiality ensures that data is confidential and people with proper access will have access to confidential data. One way of achieving confidentiality is through encryption. The unreadable format is achieved through encryption. Use of encryption techniques safeguards our data. DES (data encryption standard) and AES (advanced encryption standard) are widely used encryption technologies. Only the person with the encryption key can decrypt and read the data. 
 
&lsquo;I&rsquo; in the CIA triad stands for integrity. The integrity ensures that the content of the message is not altered either maliciously or by accident. Hash function is used to map the data from arbitrary size to fixed size values which is used for data integrity check. The storing of the secrets with hash value and salting ensure that the passwords have integrity. Signing the code provided by the vendors also ensures integrity. &lsquo;A&rsquo; in the CIA triad means availability, which includes network and services, should readily be available for the authorised users. To keep the system running and making sure the network can handle the expected load to ensure the data availability. DOS or DDOS (distributed denial of service) may render a network unavailable as the resources of the network are drained. Securing the system services like DNS (domain name system) is critical to mitigate DDOS attack in any web applications. Building cyber resilient enterprises requires administrative and security controls in the genes of the organisation. Proper data security policies, compliances and processes that consist of the administrative and technical controls are framed on the basis of confidentiality, integrity and availability of the enterprises. 
 
Although the red team and blue teams evolved in the armed forces, security teams across the organisation simulate the red blue environments. Red team exploits and compromises the organisation&#39;s own system to predict the potential attackers&rsquo; pattern. Red team uses security vulnerabilities of access system, computers, credentials, file servers, endpoints, and physical security breach, exploiting directory and email, and using different social engineering techniques. Red team is great way of validating the attack surface and identifying security risks to reduce the attack surface digitally, physically and socially. 
 
The blue team is defense focused and builds security architecture and maintains the protective internal cybersecurity infrastructure. Blue team gathers data, documents of what exactly needs to be protected and carry out the risk assessment. Defensive plan is made by first identifying the key assets. Then, the related threats for each asset are identified to perform the risk assessment. Finally, the action plan is developed to implement based on cost-benefit analysis to lower the impact of the threat by building layered security controls with zero trust. If the blue team identifies that the company&rsquo;s network is vulnerable to DDOS which reduces the availability of network for users, then the team calculates the loss in case if the threat occurs. Consideration of installing the intrusion detection and prevention system is based on the cost-benefit analysis aligning with business objectives. 
 
Phishing is the most widely used tactic to lure the receiver with some financial gains so they click the links that are vulnerable. Building resilient cyber security programmes requires good investment in insider&#39;s threat programmes. Insider&rsquo;s threat has been the challenge to most organisations. In one way, insiders require proper access to data for employees to do their work. In contrast, most data leakage and exfiltration are happening inside the organisation accidentally or deliberately. The concept of principle of least privilege and separation of duties plays an effective role to mitigate the challenges of the insider&rsquo;s threat. Training and awareness is another important function of the good cyber security programmes to mitigate the insider&rsquo;s threat challenges.

Data regulation 
Proper data compliance and regulations enforced by the state or federal government with financial penalty to the enterprises also helps build cyber resilient enterprises. Regulations like HIPAA, FERPA, and GDPR enforce penalty for data leakage and exfiltration. Cyber security continues to be the biggest challenge in developing countries and developed countries alike. President Joe Biden recently emphasised cyber security through the executive order and with public private-partnership. Public private partnership has been emphasised in recent meetings presided by the President as many critical infrastructures are managed by the private corporations in the United States and all over the world.

Google and Microsoft have committed to providing $10 billion and $20 billion to implement cybersecurity initiatives respectively. The AWS committed to provide free multi-factor authentication devices to US customers who spend at least $100 a month on average on Amazon Web Services. Similarly, IBM committed to provide secure backup service and Apple too encouraged enhancing the cybersecurity of supply chain as well as multi-factor authentication and better logging. This shows the securing digital supply chain requires collaboration between the federal government and private enterprises. Developing resilient cyber security programs requires multi-year planning with both internal and external stakeholders executing cyber security programmes in the enterprises.

(Dhungel is a cyber security practitioner and co-founder of esrtech.io and Bastakoti is an electronics engineering student at IOE, Tribhuvan University.)&nbsp;

Source:&nbsp;<a href="https://risingnepaldaily.com/opinion/building-cyber-resilient-enterprises">https://risingnepaldaily.com/opinion/building-cyber-resilient-enterprises</a>

Building Cyber Resilient Enterprises

As the digital transformation continues in scale, information technology is crucial for all industries and not limited to fintech, healthtech, agritech and edtech products. When the world sees the COVID-19 pandemic in the rear view, the revival of travel and tourism is inevitable. The technological advances have even made their way into the travel and tourism industry. We can now book hotel rooms, flights, other activities, and plan our entire trips &ndash; all from a mobile device. Technology has revolutionised the way we travel, making our travel adventures fun. This phenomenal change in the tourism industry is often referred to as traveltech. However, in the context of Nepal, traveltech products and services are still at infancy despite huge opportunities to build traveltech products. 
 
In 2017, the average tourist arrival was 0.94 million which skyrocketed to 1.17 million in 2018, and spiked to 1.19 million in 2019, according to Nepali Sansar, a US-based media house. This number is a very small compared to the customers of any global traveltech products and services. According to strata research, the global travel and tourism market offers 4.6 trillion dollars. Nepal continues to be a fascinating tourism destination and for 2022 Nepal is placed in top 10 best travel destinations by Lonely Planet.

Quality services 
Travel is a resource intensive activity and there is no middle ground whether you travel or not. We have to provide quality services that require good infrastructure to support millions of travelers. What about providing self-services and customised travel tech products? The benefits are trivial to the travelers and service providers. However, with the limited infrastructure, the scaling of tourism products and services are challenging where resources are scarce and technology automation is at the bedrock. Traveltech services can be built on trekking, hiking, mountaineering, expedition, rafting, kayaking, canoeing, peak climbing, mountain biking, bird watching, mountain flights, ultra-light aircraft flights and paragliding, hot air ballooning and Jungle safari. These events can be developed as traveltech products with high degree of customisation of events, time, partners and cost. 
 
Nepal is rich in cultural tourism. The cultural experience, traditions, festivals, lifestyles of ethnic groups, handicraft, painting and rituals can be developed as a knowledge base where the travetech services can act as a digital repository for cultural tourism. These products can easily be managed and provided via a single traveltech product. Temples, gumbas, domes, stupas and museums can be enabled to the wider world using virtual reality and augmented reality. Why not take a five-minute virtual trip to Changunarayan Temple before booking the trip? These are only possible in the traveltech products. 
 
In global traveltech products, it&#39;s very common to have chatbots and Artificial Intelligence (AI) used for automating the reservation systems by providing FAQ answers, payment information, schedules on the basis of user&rsquo;s behaviour and analytics round the clock. Traveltech products like Tripadvisor are considered as the world&rsquo;s largest travel guidance platform, scaling to millions of people. The site and app provides information on what to eat, where to go and stay on the basis of reviews of the people who have already been there before. The company is available in 43 markets and provides end to end travetech services with a click of the mouse. 
 
According to Condor Ferries, 70 per cent of travellers use smartphones for travel research and 33 per cent of them plan their trips with the help of a virtual travel assistant. Around 82 per cent of 2018 travel bookings were made without a travel agent and 66 per cent of all travellers make their bookings online. Some 83 per cent of consumers in the US prefer making their travel bookings online while 80 per cent of travelers rely on reviews on Tripadvisor before making bookings. About 72 per cent of consumers won&rsquo;t make a booking before reading online reviews. This data shows the value of traveltech services and products in the years to come for Nepali market where digital transformation will grow at unprecedented rate. 
 
Technology in travel and tourism services is a must for scaling and providing customised services. Traveltech services can be directly provided to the small tea houses as B2B and local travel specialist as B2C as a digital platform and as a service. There has been much talk about the digital divide in the last decade but with the mobile penetration of more than 100 per cent in the Himalayas, there is a potential that travel tech products can be easily accessible in the country like Nepal. 
 
Traveltech products also help to increase the bottom line on per day expenditure of the travellers by providing quality and customised services. The total expenditure of the travellers per day is very low compared to other countries although expenditure increased to $44 from 2018 to $48 in 2019. Traveltech products and services built as software and service applications can help small businesses and entrepreneurs to scale and optimise their resources thus increasing their profit margins and quality services by providing diversified products. Also travellers can sell their digital contents and experience using their personal blogs.

Sustainable tourism 
In Nepal, you can see as many temples as houses and as many Gods as people. Building sustainable tourism, scaling the infrastructure, providing the quality services and diversification of traveltech services is required to be globally competitive. We can build the traveltech products to optimise the resources, diversify the travel products and innovate the new products in the traveltech space.

With the massive potential of tourism, from expensive Everest climbing to budget hiking, Nepal offers services to all types of tourists. With the young and talented software engineering workforce and the experienced resources in mountaineering and hiking, Nepal can be a test bed to develop traveltech products for the world. Nepal can lead the world by building traveltech products and become a centre of excellence in travel and tourism.

(Kunwar is a graduate of travel and tourism management and the business analyst of JewelTrek.com. Dhungel is the vice president of platform engineering and cybersecurity of JewelTrek at esrtech.io )&nbsp;

Source:&nbsp;<a href="https://risingnepaldaily.com/opinion/build-traveltech-centre-of-excellence">https://risingnepaldaily.com/opinion/build-traveltech-centre-of-excellence</a>

Build Traveltech Centre Of Excellence

Software systems are inherently complex. The vulnerability of the software systems in critical infrastructure is a national security concern. To build a software application, thousands of lines of code are written by the software developers. Many of the codes are open source - managed by communities and the code and applications are provided free of cost with some licensing requirements. Codes written by private corporations and government entities are proprietary and confidential information. Log4j2 was written by apache foundation and is the open source library for logging used primarily in Java applications. 
 
There are many reasons for the software vulnerability. One of the major reasons is human error or the poor quality in the software development process. If the software is tested rigorously, much vulnerability can be fixed during the development cycle. However, testing the software rigorously is not an easy task and is out of the scope for many reasons - often the application consists of the external libraries that are developed by the external entities and the development team doesn&rsquo;t have experience on building those libraries. Also the cost drives the software testing. Development teams have to rely on third parties to improve the quality of their applications. Writing a new operating system and all the stacks on top of it is very expensive and not feasible. With the microservices architectures, the application has to rely on third parties API&rsquo;s (Application Programming Interface) and software supply chain continues to be critical for data security.

Software vulnerability 
Log4j2 is zero day vulnerability. This is the most severe software vulnerability in a generation. Java is the most widely used programming language on the internet. According to Wikipedia &ldquo;zero-day is a computer-software vulnerability either unknown to those who should be interested in its mitigation or known or a patch has not been developed. Until the vulnerability is mitigated, hackers can exploit it to adversely affect programmes, data, additional computers or a network.&rdquo; The patch has already been developed for log4j. The scope of the log4j2 vulnerability is very high as apache foundation lists at least 43 applications vulnerable to log4j developed by Apache foundation. Apache foundation is one of the most widely used open source community that also develops apache web server - one of the most widely used web applications on the internet that is not written in Java. 
 
The log4j flaw allows bad actors to execute code remotely on a target computer, which could let them steal data, install malware or take command and control. In simple terms, any request made on the internet by your browser is logged in the application server if it is running the Java and log4j2 library. This logging is done by the open source software log4j2 that makes the system vulnerable. Because of the flaw, the attacker can remotely connect to the remote server and steal the data. 
 
Law enforcement agencies like Nepali Army, Nepal Police and Armed Police Force should develop Cyber warriors - the special cyber force that can fix the software vulnerabilities, deploy immediately and also coordinate with international law enforcement agencies to curb the challenges of global and national security of digital infrastructure. Nepal should establish a threat intelligence sharing platform between government entities and private entities. Furthermore, threat Intel can be developed for different types of industry ex FS-ISAC for financial institutions, DB-ISSAC for defence industrial base. E-ISAC for electricity threat Intel sharing like in the United States. 
 
Private organisations should empower themselves with the cyber security engineering workforce. Private organizations should be forthcoming on any cyber security related threats and breaches and report to the law enforcement agencies immediately. As a private citizen, you should be lobbying for better public policy on cyber security and privacy. As secure cyberspace is critical both for kids and adults, it is the responsibility of citizens to educate themselves and the government for the next generation of technologies we will be using and building. 
 
As an individual, it&#39;s very less likely that you will be directly impacted. But it&#39;s very likely that you are already using the software applications written in Java core that uses log4j2 logging libraries. If you know the vendors, they should have already mitigated the vulnerability and published it on their website. If you are curious, just do some research on the applications that you are using.

Software inventory 
The biggest challenge in software security lies in the management of the supply chain process. With hundreds of libraries and microservices being developed inside and outside the organisation, management of libraries becomes a challenge. Log4j2&#39;s biggest challenge is also a supply chain. Most java applications use the log4j2 logging library. While buying a new software or hardware proper supply chain management and vendor risk management process should be developed both in private and public enterprises. More specifically, if the infrastructure is related to critical infrastructure, there should be a provision to make the defence clearance and ensure that the product is of national interest by Nepalese Army. 
 
The importance of software inventory at the national level is critical so that law enforcement agencies proactively deploy their cyber warriors in case of emergency and mitigate the vulnerabilities in the critical infrastructure. Vulnerabilities management process should be a continuous process. Monitoring and scanning the digital environments using static and dynamic scanner should be ingrained in the continuous integration and continuous deployment process of the software development. Sooner or later new vulnerabilities will be found and the organization should have processes in place to patch the vulnerabilities as soon as possible. The organization should develop metrics for monitoring vulnerabilities and decrease the Minimum Time To Patch (MTTP).

(Dhungel is the Chief Information Security Officer at www.esrtech.io. ravi@esrtech.io.)

Source: <a href="https://risingnepaldaily.com/opinion/national-security-and-software-vulnerability">https://risingnepaldaily.com/opinion/national-security-and-software-vulnerability</a>

National Security And Software Vulnerability

A Fintech storm is brewing in Nepal

A few statistics are very compelling for banking revolution in Nepal. More than 65% of the population is below 35 years of age, 45% of the population is not yet banked, cell phone subscription is more than 1.3 times the population of the country and 65% of the population have access to the internet with the government aiming for 100% by 2024.&nbsp;

The amalgamation of technology savvy customers, young and energetic bankers and a new brood of computing and technology graduates in Nepal have primed the banking sector for a facelift. Top it off with the legacy system, lengthy bureaucratic processes and status quo of the prevailing banking system and you get an environment that could not be more conducive for disruption.

According to CB Insights - a leader in fintech survey reports, global fintech investment topped USD 40 billion in 2018. A large portion of the investment has been in developing economies. Simply put fintech adoption is on the rise globally. They are extremely cost effective in reaching the last-mile customers. To paraphrase Jack Ma, adding one million new subscribers could merely mean adding an additional server for digital service providers, while for the brick and mortar service model it requires a building, staff, and multiple bureaucratic regulations to comply at the least.

Fintech solutions come mostly in two flavors. First, they help banks reduce their operational costs by automating and digitizing existing services. Second, they offer (unique) products that can be fully serviced through digital channels. It is always more cost effective for banks to partner and build fintech solutions than building it entirely in house. Bret King in his book Bank 4.0 summarizes it well, &ldquo; Who is going to be faster and cheaper at building new tech for financial services? A company that only focuses on tech, has a smaller more agile structure, works with multiple financial institutions and has to answer to a board full of VC? Or a bank that has to deal with legacy systems, compliance and risk issues, and significant challenges with recruiting the right skills to build these new technologies in the first place?&rdquo;

There is a great enthusiasm in the banking sector in Nepal to embrace new technologies. Artificial Intelligence, analytics, predictive modeling, chat bots, e-banking, digital banking and data based decision making using Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs) are of interest in to C-Level banking executives.&nbsp; Solutions that enhance customer experience vis-a-vis supporting the bottom lines are in high demand.

A collaboration between banks and fintech solution providers is a win win win scenario. Banks do not have to invest a huge amount of resources and manage a team of developers, instead fintech service providers can use their agile and nimble product development processes to reduce development costs, and the windfall of this process is new products and services that enhance customers&rsquo; banking experiences. In the last decade technology adoption has skyrocketed while technology costs have nosedived. Shying away from using technology based solutions and maintaining either the status quo or even wait and see positions are recipes for increasing cost in delivering banking services.&nbsp;

The success of fintech in Europe, the Americas, Asia and everywhere else has been primarily driven by their ability to jump bureaucratic hurdles and avoid unnecessary red tape. One of the key players in the promotion and development of fintech in Nepal will be Nepal Rastra Bank. While the central bank enthusiastically promotes digital banking and envisions a cashless economy it still lags in progressive policies. Fintech developments in Nepal are handicapped by antiquated rules like the &lsquo;wet ink&rsquo; signatures. Similarly the Know Your Customer (KYC) requirement has created more friction between the banks and the customers rather than helping increase the quality of service. Fintech and other digital service solutions will proliferate as antiquated policies sunset.

The policy responsibility however, cannot be fully put on the shoulders of the government or a regulatory body. Banks and Financial Institutions (BFIs) will need to collaborate with the regulators to identify and revise policies. Such revisions shall duly consider customers privacy and data protection issues. Favorable fintech policies can unleash a plethora of innovative banking solutions that support GDP growth aspirations.&nbsp;

Fintech solutions like the e-wallet are already flourishing. Required infrastructures like the Nepal Clearing House Limited (NCHL), Smart Choice Technologies (SCT) and the ill-fated Nepal Electronic Payment Systems (NEPS) have a broad user base. BFIs are offering some services through digital and mobile channels. While the recent hacking highlights the challenges in securing digital systems for banking services, it nevertheless has invigorated new interest and raised awareness on digital strategies for delivering banking services.

Fintechs are here to stay. There will certainly be challenger banks, digital only banks and custom service providers that compete directly with the traditional banking products. In an era where automation and AI is reducing operational costs and opening new avenues for service delivery and product diversification, defending legacy systems and lagging in technology adoption will only hurt the financial institutions.

* An edited version of this article was published on The Rising Nepal on Oct 18, 2019.

Fintech Storm Brewing in Nepal

Data is not the new oil! Data is in fact, bigger than oil. The velocity, variety and volume at which data is generated today is mind boggling. According to a&nbsp;<a href="https://public.dhe.ibm.com/common/ssi/ecm/wr/en/wrl12345usen/watson-customer-engagement-watson-marketing-wr-other-papers-and-reports-wrl12345usen-20170719.pdf" rel="nofollow noopener" target="_blank">report&nbsp;</a>published by IBM in 2017, &quot;Every day, we create 2.5 quintillion bytes of data. To put that into perspective, 90 percent of the data in the world today has been created in the last two years alone &ndash; and with new devices, sensors and technologies emerging, the data growth rate will likely accelerate even more.&quot;

Data is collected in all forms, shapes and sizes. The first thing that comes into mind when we think about data is the ubiquity of smartphones and the applications that run on them. But that is just a tip of the iceberg. We have been generating and storing digital data for a long time . We stop at a traffic light and our vehicle&rsquo;s license plate gets scanned. When we stop at a grocery store and pay with a credit card we generate data on our consumer goods preferences. Places we work or do business have our socio-economic data. Places&nbsp;we go to worship and recreate have our data. Our life is a digital model. Don&rsquo;t be be surprised when one of these days when you happen to be flying on your birthday and the captain wishes you &quot;Happy Birthday!&quot; We generate and share data in ways we don&rsquo;t know.

&ldquo;Data are to this century what oil was to the last one: a driver of growth and change. Flows of data have created new infrastructure, new businesses, new monopolies, new politics and&mdash;crucially&mdash;new economics. Digital information is unlike any previous resource; it is extracted, refined, valued, bought and sold in different ways. It changes the rules for markets and it demands new approaches from regulators. Many battle will be fought over who should own, and benefit from, data&rdquo;, writes&nbsp;<a href="https://www.economist.com/briefing/2017/05/06/data-is-giving-rise-to-a-new-economy" rel="nofollow noopener" target="_blank">The Economist</a>.

The increase in the numbers of devices that are capable of capturing, storing and transmitting data is just one part of the coin propelling the Information Technology industry. The other part is the innovation happening in data processing and analysis. Data Science, Machine Learning, Algorithms and Artificial Intelligence are becoming more common in our daily life. The decline in cost of collecting, storing and processing data has expanded the&nbsp;reach of data based applications. Today data is used to diagnose cancer cells, make art and music, fight crime and manage inventories. Travel, transportation, health care, aerospace, defense, education, policy making, you name it every business and sector today is exploring data based solutions to achieve their missions and goals. Information Technology solutions are changing trade and commerce landscapes in unprecedented ways.

The biggest businesses of our times like the Google, Baidu, Facebook, LinkedIn are all built on data. Low cost of building, testing and deploying data based business solutions, modular development of applications, agile product development and open source revolution has helped Information Technology industry to grow. Data has created a new kind of market and business opportunities. As devices become more and more connected and the cost of of data based solutions drop this technology will penetrate deeper in our personal and professional life.

Digital models will be ubiquitous soon!

Data is bigger than oil!

For the love of data science.

I ended up being a&nbsp;datacrat&nbsp;because I enjoy finding mathematical representations to mundane problems. &ldquo;If you do what you love, you&rsquo;ll never work a day in your life,&rdquo; said Marc&nbsp;Anthony. I believe it is true. My work allows me to do what I love doing. I love making estimates and predictions. Some estimates are right and some estimates are wrong. I do that for a living. I also live to do that in my everyday life. Many of us do it unconsciously. We make estimates and predictions every day. For example, how much water do I use in the shower everyday? What much $ worth of gas I buy every month? How long will it take me to get there from here? We are confronted with questions like this in our life everyday.

US Energy Information Administration (EIA) makes a lot of forecasts about long term and short term oil and energy prices. More often than not these forecasts end up being wrong. I chose the EIA example to highlight the usefulness of models than in their actual predictions.

<blockquote>&ldquo;Essentially, all models are wrong, but some are useful.&rdquo; - George Box.</blockquote>

One can begin to formulate mathematical equations in many ways to answer the question like the ones above. There are many ways to tackle mundane questions using mathematics. If you practice enough you will get it. In Malcolm Gladwell&#39;s words you require 10,000 hours of practicing before you become good at it.

The company I work for was moving from one part of the city to another. The new location will be saving approximately 4 miles each way off my daily commute! I chose miles to represent the change for one good reason. I could have chosen the time saved to express my excitement for the change but I chose miles. For some people four miles takes five minutes, for others it may take 15 minutes and it will be different for many more. But the distance of 4 miles is 4 miles for all. One of the early lessons I learned in my data science career is that choosing the right data helps a lot in data story telling.

It appears that moving a corporate office with about 200 employees requires a lot of planning. Anyways, this corporate office move gave me an opportunity to work from home the whole week.

<blockquote>I had one goal in mind - build an artificial neural network from scratch in Python.</blockquote>

I was excited!&nbsp;

<img src="https://media-exp2.licdn.com/dms/image/C5612AQGWP4uJLCCsCQ/article-inline_image-shrink_1000_1488/0/1520238241040?e=1660780800&amp;v=beta&amp;t=tOjFgjIgs4226xV99OmKI0ppOpZrDtPo_yhFrjwirZM" />

A week deep in artificial neural net.

I was interested in building a neural net that can predict with better accuracy than a logistic regression model, decision trees and some boosting methods that I have been using regularly in my work. I have built neural nets in R in the past. I was aware of at least two hyper parameters that I could tune and their effects in stabilizing the graph. The neural net I had built had not amazingly outperformed the logistic regression model for the dataset at that time. I chose logistic regression and quietly forgot about the neural net. One of the big reasons for choosing logistic regression was its simplicity. Data Science is often viewed as a &lsquo;black box.&rsquo; Making complex and intricate models is not the place to begin.

But this time I was quite determined. Over the next six days I worked out of the kitchen island in my house. Armed with a pot of coffee every morning I was ready to start the day at around&nbsp;7:45 AM&nbsp;and working through&nbsp;5:00 PM&nbsp;religiously every day of the week. I ended up spending more than 70 hours in the week that ended up becoming a six day work-week. I was in full force trying to understand and build an artificial neural network to predict credit risk. Although I was working from home I actually spent less time with my family &ndash; cooking/eating dinner &ndash; helping with homework and household chores. I found myself reading about neural nets in all settings.

Internet is the cornucopia of learning resources!

Thanks to the open source ideas and the internet, freely available learning resources can cater to the needs of anyone. Stackoverflow, Stackexchange, Quora, Youtube and MITOpen Courseware all provided a lot of fuel to help me understand and build the artificial neural net. There were numerous other webpages, tutorials and cheat sheets that I cruised through. The online community of Python developers has good documentation on python and the libraries. I ended up spending a lot of time coding in python using Jupyter notebook.&nbsp;I had to use pandas, numpy and tensorflow vigorously. Matplotlib library was very useful in visualizing data in several steps. This exercise required me to revisit partial derivatives, chain rule, slope and tangents and matrix operations among others. There will always be some linear algebra in data science and ANN uses it too. Sigmoid function, randomness and probability estimates are ubiquitous and I found ANN to have more than a heatlhy dose of them.

Casting credit risk problem into image recognition problem.

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Tensorflow is one of the most popular libraries used to build deep neural networks to predict image classes. Tensorflow was tailor designed to solve image classification problems. While the problem I am trying to solve is also a classification problem and it has only two classes it was difficult for me to cast it into a digit recognition problem. If I can however, formulate the credit risk problem in a matrix form then I can use the same matrix operations to minimize the loss and increase the accuracy of the function that is generating the result in image classification. I have less to do with what the function is and more to do with how far off I end up from the expected value. So if I can make a neural net that gets closer and closer to the expected value through the repetitive process then I have found a neural net that will work in my setting. There is a chance I will end up with a better model to predict credit risk than what I have in hand. The models I build are between 55 and 60 percent accurate. It is quite difficult to predict human behavior using socio economic data.

I concluded that if I can build a matrix of my data in accordance with the image recognition Numpy array of tensorflow then I can apply the same concept downstream. I will expect my input data to have more variability in the dimensions. This may make the learning process slower but at the same time I had advantage of using less dimensions. l was leaving that for my 10GB RAM to compute. So if I can formulate my data in a matrix form then I am all set! It took quite a bit of thinking and attempting some matrix calculations before I was able to take my data and cast it into the array as used in the tensorflow.

Data wrangling is art and it requires a lot of patience and healthy dose of creativity!

Most often Data Science boils down to data quality and quantity. Since the data became &lsquo;Big Data&rsquo; we also talk about the Vs (Velocity, Variety, Volume etc.). I started with about 6 GB size of sas7bdat file. The variety in this context was more organic. The data were not collected uniformly, some were &lsquo;a&rsquo; and some were &lsquo;A&rsquo; even when they meant the same thing. They lacked consistency in physical, logical and conceptual data modeling, There were problems associated with UTF-coding and like many data sets that we deal with every day it has a lot of missing data. If it was a dataset of scatter martix probably the volume would have been one-third. In a nutshell I was attempting to build this model from a dataset that was generated by different people, in different states, in different operating systems and for different purposes. The data needed a lot of cleaning and normalization.

The ANN outperformed my best model by 7 points.

I had two things in my mind&nbsp;on Monday&nbsp;morning. I wanted to understand the conceptual idea behind the artificial neural net and also be able to apply it programmatically to solve a credit risk problem. At the end of the 70 hours sprint I was successful in building a neural net that has better accuracy than all the other models I have been testing for credit risk prediction. The accuracy of the neuralnet was 7 percent better than my go-to logistic regression model.

It was a thrilling experience. I still have not exhausted all the possibilities of fine tuning the neural net I built but I certainly have built a better model with the resources at my disposal. There are many dimensions upon which it can be further improved &ndash; one of the easiest being increasing the computing power so that the learning rate of the NN can be reduced further or increasing the number of nodes. There are many ways I think I can work on it to fine tune its hyper parameters. A week was not enough for me to master the neural net but it certainly has reinvigorated my curiosity.

Notes: I wanted to put the codes with explanations on git hub but given that the process and data are both proprietary I am not able to publish it. I will post again if I am able to create a repository for the ANN I have built. Pictures credit to tensorflow.com.

Artificial Neural Network for credit risk modeling.

1. What is the Data Analytics revolution?

&nbsp; &nbsp; &nbsp;&ldquo;The goal is to turn data into information, and information into insight.&quot;

&nbsp; &nbsp; &nbsp; &mdash;&thinsp;Carly Fiorina, Former CEO of HP

Data Analytics&nbsp;is used by Amazon to recommend products and Google uses it to refine its search results. Data Analytics is performed by Facebook to suggest friends and LinkedIn uses it to suggest networks and groups. Target and Walmart use Data Analytics to identify their potential buyers and predict what goods might be in shortage under certain conditions. You have heard of Target sending pregnancy material promotion offers for a teenager in Minneapolis and Walmart stocking on Pop-Tarts&reg; in stores in an event of possible hurricane threats. All of these are great examples of Data Analytics. There is one thing common between all these companies &ndash; they are multibillion dollar industries and they have trillions of bytes worth of data. &nbsp;But does Data Analytics ends there? The answer is&nbsp;NO. Small organizations have equal opportunity to use the data they have collected for strategic planning. The question is who will be the early adopters and who will fall behind.

It is used in&nbsp;supply chain management&nbsp;of all sorts. It is used in&nbsp;health care. It is used everywhere.&nbsp; Search for&nbsp;PASSUR. The company collects and analyzes data every 5 seconds or less to identify time lag between estimated time of arrival (ETA) and actual arrival of planes in airports. This allows airlines to plan the crew and other logistics more effectively.&nbsp; Accurate analysis like this is valued at several hundred million dollars per year, as aircraft diversions are expensive, disruptive and costly operations in airline industry. &nbsp;Client Relationship Management&nbsp;(CRM) software allows companies to collect their operational data which can be leveraged to improve efficiency and reduce cost of operations. Data Analytics opportunities exists for all. It is just a matter of how well an organization is positioned to take on this challenge.

<img alt="" src="https://storage.googleapis.com/esrweb-blog-image/uploads/2022/06/21/analytics.jpg" style="height:765px; width:1100px" />

Every retailer offers promotions. But designing and implementing promotions at the right time for the right duration is a challenge. How will you know with a certain degree of accuracy whether or not certain kinds of promotions do well? Will launching a 20% off store-wide deal in the middle of summer generates more revenue or will it be better launching in November? Do all states across the US do the same during such promotions or are there clusters? Do you have special deal on pizza for Friday night when everybody is looking to a weekend or on Monday night, when people are still reeling with their weekend getaways? Data Analytics helps in answering these kinds of questions.&nbsp;Retail&nbsp;giant Sears, Walmart, Target deploy Big Data analytics to design promotions, which not only allows them to look into the data in much finer details but also cut the time required to design and implement such promotions. The essence of Data Analytics is not just collecting and processing data. &nbsp;It is the efficiency with which analytics are performed. Yes, without grinding your teeth. If you have all the resources and time, you can do it without using state of the art Information Technologies, but scarcity is the fundamental principles in economics. You do not have all the resources and all the time, so use Data Analytics.

2. How do decision makers perceive Data Analytics?

&nbsp; &nbsp; &ldquo;The price of light is less than the cost of darkness.&quot;

&nbsp; &nbsp; &mdash;&thinsp;Arthur C. Nielsen, Market Researcher &amp; Founder of ACNielsen

A very generic answer will be, &ldquo;It offers opportunities but it has challenges too.&rdquo; Yes, of course everything that offers some opportunities brings its&nbsp;challenge friend&nbsp;along. A shrewd manager will evaluate opportunities for Data Analytics, having higher values than the associated cost challenges. Also, depending upon the industry and availability of&nbsp;proprietary data&nbsp;or&nbsp;public data, some organizations may feel more comfortable to cruise in the&nbsp;wait-and-see&nbsp;mode than jump on the band wagon of Data Analytics. If Google had approached innovation opportunities in&nbsp;wait-and-see&nbsp;mode, Bing probably would have been the search engine giant! If Progressive Insurance had spent a long time debating whether or not to use the Snapshot data to revise premium for its members, their annual average growth over the last five years probably would not be nearly 6%, while the industry it belongs to saw a decline of nearly 2%. In a recent interview, Progressive CIO Ray Voelker outlined how the company has been tapping into Data Analytics to make decisions that set it apart from its competitors. Availability of data and the ability to use it in organizational strategic planning is key in fending off competitors and generating revenue, Voelker explained. If Amazon, Facebook, LinkedIn and Twitter have not dug underneath their data to drive business and expand services, their growth would have stagnated like that of Hi5, Altavista and MySpace.

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All right, C-level executives are aware of this. But the question is &ldquo;How exactly are you going to use it in the decisions you make?&rdquo; &nbsp;Do you have a clear vision and quantifiable milestones to evaluate whether or not Data Analytics could help you in expanding your business, or is it just going to become another unmanageable 2 years down the line project as you keep up with your forecasts, opportunities and active pipeline. As I explained in the first question &ndash; resources are scarce and there is always additional data that you could collect to make even better decision, but you have to start somewhere. Gaining&nbsp;access&nbsp;to data,&nbsp;structuring&nbsp;the data streams and beginning the process that you have in hand will lead to converting data into revenue sooner than you expected.&nbsp;

3. How Data Analytics fits into organizational development?

&nbsp; &nbsp; &ldquo;What gets measured, gets managed.&quot;

&nbsp; &nbsp; &nbsp;&mdash;Peter Drucker (founder of modern management)

The evolution of&nbsp;cloud-based services&nbsp;or in a more traditional term, a&nbsp;networked society, has enabled data collection in unprecedented ways. Growth in organizational ability to store data at a relatively small cost, and the low latency in accessing the stored data has helped organizations to accumulate&nbsp;Varieties&nbsp;of data in huge&nbsp;Volumes&nbsp;and at increasing&nbsp;Velocities&nbsp;(3Vs).&nbsp; The digital footprint of any organization today can be measured in multiple dimensions &ndash; social media presence, volume of proprietary data, data management cost, web traffic and ranking and comprehensive IT&nbsp;metrics&nbsp;on performance, availability and capacity of available resources, plus many more.&nbsp; There is operational costs associated with maintaining all these data silos and infrastructure. Data Analytics will allow to justify that cost by innovative ways to increase revenue.

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Organizations scramble to find ways to process and analyze the data they are collecting. The rate at which innovation occurs in Big Data architecture is difficult to understand for managers who have not followed this development over the years. As Davenport and Patil outline in an article for Harvard Business Review, &ldquo;&hellip; intense curiosity &ndash; a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested&rdquo; can come from Data Analytics, and indeed a curious data scientist is needed for that. Innovation in computational frameworks of big data architecture allows processing interactive, batch, real time, streaming and iterative data at an amazing speed. The development of tools like Pig, Hive and Libraries like the Mahout and SparkR allows performing statistical analysis of 3Vs data with surprising levels of details.

There are several paths that an organization can take to tackle or embrace Data Analytics. It can&nbsp;outsource&nbsp;the Data Analysis part and trust in the Business Analyst to identify key performance metrics for the organization and use it for inter- and intra-organizational performance evaluation and benchmarking. On the other hand, it can see this as an opportunity to&nbsp;innovate within&nbsp;and invest resources to make it a dynamic process and use it in decision making regularly. Data Analytics allows organizations to&nbsp;quantify risks. Business managers need to be adept at mathematical reasoning and competent in the interpretation of quantitative data.&nbsp;Outside-the-box&nbsp;thinkers, who are willing to apply analytical reasoning and test hypothesis, can develop metrics to measure organizational health and performance, which are critical for its growth.

Conclusion

&nbsp; &nbsp; &ldquo;Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.&quot;

&nbsp; &nbsp; &mdash;&thinsp;Geoffrey Moore, Author of Crossing the Chasm &amp; Inside the Tornado

The adoption of Data Analytics in decision making process is growing but not uniformly across all businesses. Decision makers need to understand that IT strategy is nearly indistinguishable from the business strategy. Data Analytics not only allows businesses to gain competitive advantages but also help in retaining their loyal customers and understanding their behavioral patterns. &nbsp;Organizations do not need to wait to collect petabytes of data to begin looking at improvement opportunities in operations. Availability of more data increases confidence of analysis but most decisions do not need conformity at four-sigma confidence interval. Innovative product offerings like&nbsp;Database-as-a-Service&nbsp;(DBaaS),&nbsp;Infrastructure-as-a-Service&nbsp;(Iaas),&nbsp;Platform-as-a-Service&nbsp;(PaaS) and&nbsp;Software-as-a-Service&nbsp;(SaaS) and concepts of&nbsp;Unified Computing System&nbsp;(UCS) has significantly lowered the cost of Data Analytics over the past five years. &nbsp;&nbsp;

What are Data Analytics and Why Should I Care?

<h1>My Love for Quantitative Analysis</h1>

Quantitative data really fascinates me. I like exploring data with measures, such as the mean, standard deviation and standard error and I enjoy examining the PDFs and the CDFs of the data distributions. Glamorous Monte Carlo Analysis, Meta-Data Analysis, Big Data Analysis and data characteristics, like relational and 3V, absolutely captivates me. If I ever end up getting into home brewing these will be the name of my beers!

<h1>My Experience with Quantitative Analysis</h1>

I have two years of experience working for two small, but rapidly growing companies. It is really interesting to see how people shy away from using quantitative data in strategic planning. It is not surprising that people are concerned with forecasting, but what is surprising is that they are not interested in the factors actually contributing to the rosy forecast. Everybody talks about quarterly reports and active pipeline. Yet, not enough thought seems to be given to figuring out what factors actually contributed to the last quarter trend. There is no scenario analysis and there is no uncertainty analysis for such forecasts. The economy is growing and unemployment is falling, and that is where most organizations risk management stops. Risk analysis is very subjective and &ldquo;calculated risk&rdquo; is an abused phrase. People holding leadership roles often want to play it safe &ndash; &ldquo;if it ain&rsquo;t broke don&rsquo;t fix it&rdquo; is the attitude. No matter how much effort is put to eradicate the status quo, the mentality of &ldquo;we have always done it this way&rdquo; prevails. &lsquo;Smart Creatives&#39; aren&#39;t recognized as often as they should be.

<h1>Business Use of Quantitative Analysis</h1>

A lot of companies are using Customer Relationship Management (CRM) applications for business operations, but it looks like very few utilize CRM applications in strategic planning. Some organizations do not have the resources despite interest and many more of them simply do not understand the value of information. Also, a majority of those who have deployed analytics are either at the mercy of consultants and/or the software they have adopted. Organizations are dynamic: the number of employees and social demographics change, financials change, leadership changes, markets and products change and many other things in between. Using static models or organizational architecture analysis, built at an instance of time cannot capture the changes that have taken place. Such analytics or models need to be continuously updated and upgraded to take advantage of Bayesian inferences. Business Analytics is not a one-time analysis, it is a continuous process.

<h1>The Full Spectrum of Quantitative Analysis</h1>

Predictive analytics has been there for a long time but it has taken large strides in the last ten years, as a result of ubiquitous computing. I believe it is going to grow at an unprecedented rate over the next decade as Internet of Things (IoT) penetrates into our lives.

The unprecedented growth of structured and unstructured data introduces raw metrics for any organization to leverage the value of data for risk management and financial forecasting using predictive analytics. As the enterprise architecture starts to become complex and evolves with time, IT and organizational leaders find it difficult to comprehend the benefits of data analytics for many reasons. Enterprise architecture is evolving as a support tool, not a strategic tool. Data and process management challenge spans across all the echelons of organizational hierarchy. Understanding the business processes, the state of information infrastructure, data, domain knowledge and analytical tools are crucial in information analytics.&nbsp;

My understanding of uncertainty analysis, meta-data analysis and inferential statistics is quite good. What I have observed among current predictive analysts, or the ones who design these analytics applications, is that a lot of them gravitate towards the normality assumption. I rarely run into anybody who talks about when and why to use Beta distribution and where to employ the Exponential Distribution, unless I talk to friends from graduate school, and that does not happen very frequently as I would like. Also, many analysts do not consider nonparametric analysis or exploration using machine learning algorithms. &nbsp;A lot of physical theories really aren&rsquo;t used in business strategic planning.

<h1>Concluding Remarks on Quantitative Analysis</h1>

Organization management is a long way from using predictive analysis to drive the business. Not to mention the elite few e-commerce behemoths who have taken Big Data to heart and have sailed far ahead into the ocean.

Why You Should Use Quantitative Analysis for Organizational Growth

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How technology is enabling travel and tourism like never before.

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<img src="https://lh3.googleusercontent.com/ahLbT5Lm48j1_bkCuhVuf3diZ5inpL6N69N640eiwNqrdPX1LViB7WvMbGhkXxQXFZyozaX-exNq2n-_IC_YeDmz24SbUDxjJrNN32AovDsjF1N551H1o4h4q9HCYu8QYVT_mkjEbEJsxAa2Yw" style="height:536px; width:668px" />

<h1 style="text-align:justify">Have Tech Will Travel</h1>

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<img src="https://lh6.googleusercontent.com/9xOFcWwkPj3Kjl8OxxnJmJEqwFIDgRFkelu1kwvRw58XcUmqOg-SN6pvqiuuqqwyO_FByYfGS5puz6l2PZ4vjl4VypOJii8E59pIaygnOin_DhP9EfsIIMhNnaRYjhpnMz1aesBsvvQN5Z5tew" style="height:220px; width:331px" />

Travel technology is the application of information technology (IT) in the travel and tourism industries. &nbsp;The goal of travel tech is to automate travel and related processes to save customers time, reduce costs, and create a more seamless experience. It allows consumers to book their travel without the aid of a travel agent, but it&#39;s so much more than that.&nbsp;

 
Travel tech has moved way beyond just hotels, flights and rental cars now. VR and AR are being used in everything from a virtual tour of the Louvre to try-before-you-buy hotel rooms. There are self guided tours, navigation, AI and virtual assistant, chatbots, all-in-one services for search, booking, reviews, and guides like TripAdvisor, and more. Travel tech isn&#39;t just B2C though. Technology-driven companies and startups are helping every corner of the travel and &nbsp;tourism industries to implement travel technology. Companies are using big data for product development, marketing and improving services. There&rsquo;s also software, IT, UX/UI, cloud services, cybersecurity, and API integrations that are part of the travel tech sector.

 
The driving forces behind the travel tech sector are numerous but two of the biggest ones in today&#39;s world are smartphones and the covid-19 pandemic.

 
The world of travel tech was blown wide open with the evolution of the modern smartphone. Smartphones changed everything about the way people consume and interact with media, marketing, and services online. Today the potential for travel tech is almost unlimited (at least until the physicists finally give us actual teleportation) and travel tech companies and startups are racing to build software and products that utilize the advanced capabilities of today&rsquo;s digital devices.

 
Factor number 2 is this post Covid world we live in. There was a sudden and ubiquitous need to minimize person to person contact in our society, travel and tourism sectors included. QR codes replaced menus, tickets and tour guides, and are even used to prove our testing and vaccination status. Contactless hotel and flight check-ins ramped up in a hurry and the trend is continuing and even expanding. Facial recognition is being tested for use at airport security and other checkpoints to increase ease and efficiency for travelers.

 
There are certainly some internationally known companies in the travel tech game but there&rsquo;s also tons of small startups out there making great products and services as well. Here are some examples of current travel tech, big and small, in action;

 
-&nbsp; TripAdvisor. As I mentioned above, TripAdvisor is a one stop shop web service and app where consumers can explore destinations, services, and accommodations as well as book online and read reviews. It&#39;s been reported that 80% of travelers rely on reviews on Trip Advisor before making bookings and 72% of consumers won&#39;t make a booking before reading online reviews. (hotelmize.com) 
-&nbsp; Jewel Trek. This is a new service by ESR Tech, that arranges guided trekking experiences in the vast and rugged Himalayas of Nepal. Jewel Trek disrupts the status quo by connecting trekkers directly with the service providers, cutting the foreign-owned big outfitters out of the deal altogether. This travel tech&nbsp; service allows users to customize their trip and save money but at the same time puts more money in the pockets of the local guides and porters who lead the trekkers on their adventure. 
-&nbsp; Expedia. Expedia Group Inc. owns sites and services that serve as metasearch engines and travel fare aggregators. Its websites include expedia.com, orbitz, travelocity, vrbo, trivago, and hotels.com, among others, that consumers can use to shop for their travel, compare rates, and book online. 
-&nbsp; Amadeus. This company provides B2B services for companies in the travel industry. The company has two services at its core; its global distribution system (GDS), which provides real time pricing, booking, ticketing and more to its clients, and computer software that automates many of the back office processes.

 
Looking Forward 
It&#39;s a very diverse sector and the limits of technology are ever-expanding. The 2022 CES in Las Vegas premiered some dazzling possibilities for the near future. Companies presented flying taxis, un-lose-able luggage, AR on your windshield, real-time metaverse meets AR, a personal instant breathalyzer for flu and covid, and a palm-sized portable modem that works in over 100 countries. (thrillist) It&#39;s true what they say, the one constant is change. 
Leave us a comment below and let us know what&rsquo;s got you excited in travel tech today.

Travel Tech in 2022

How Today&rsquo;s Entrepreneurs are Finding Their Path to Success

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<img src="https://lh4.googleusercontent.com/ZVEv3lvGpeC9WgCuzfWLHxiLxjpR50SdUdbFo6vXmMoOTAQ69sxEk52bu7MkWTZMULa6pwXvRRwnTD-oM7reXEYPQ_3J8Su02Gjoz0Wh37ZcRTPqNQvUHS18cf_h7BTAvoCAtMKuPO8O_n2y3Q" style="height:528.3697581933466; margin-top:-72px; width:353px" />

Outsourcing 
Outsourcing is a business practice in which a company hires a third-party to perform tasks, handle operations or provide services for the company.

 
What it&rsquo;s not: Outsourcing doesn&#39;t necessarily mean off-shoring. With today&#39;s connected world your small business can follow the talent whether it&rsquo;s in another continent or country, or right in your own community. It also doesn&rsquo;t have to be with a large firm or on a permanent basis, it can be as simple as having a logo designed or a limited series of emails and social media posts for a campaign.

Below are some statistics compiled by fortunly.com about small business and outsourcing

&ldquo;Freeing up resources to focus on core business is the most widely cited reason for outsourcing IT functions, at 49%. Saving money is secondary, but still a top priority. About 45% of companies outsourcing IT say that their information technology outsource projects are meant to save money. About 46% say outsourcing lets them access skillsets that aren&rsquo;t available in-house.&rdquo;

&ldquo;Small businesses usually turn to outsourcing when it comes to accounting and IT because those tasks require proficiency and skills that they might not possess internally. That&rsquo;s why small business outsourcing stats show that 37% of all accounting and IT tasks get outsourced. Digital marketing tasks follow at 34%, with development and human resources at 28%.&rdquo;

&ldquo;Small business owners care about efficiency above all. Compared to larger companies, these businesses usually cannot afford or simply do not have access to the necessary resources to build a team from scratch. 
United States outsourcing statistics show that another common reason (18%) that a small business turns to outsourcing is to increase available expertise and seek expert assistance. The latest research has also shown that 52% of small businesses will continue to outsource, especially non-core functions even in the post COVID economy.&rdquo;

There is a widely held belief in the small business world, especially among first time entrepreneurs and recently launched ventures. Tonya Thomas, president of The Small Office Assistant, puts it this way in an article in Entrepreneur, &ldquo;I felt like I was the only one who could do the work efficiently; I wanted control over everything.&rdquo; &nbsp;Thomas went on to add that she had to learn to &ldquo;let go&rdquo; and in the first year she started outsourcing some of her workload, her company&rsquo;s revenue doubled. Adding to that, David Walsh, an entrepreneur and author of Source Control, notes that &ldquo;Many owners take pride in having the world on their shoulders and their entire organization buried in their mind. Knowing your business is critical, but keeping yourself indispensable is reckless and un-scalable.&rdquo;

Lets address the elephant in the room here, you might be saying &ldquo;My margins are razor thin, I simply can&rsquo;t afford to hire out this task or that process.&rdquo; Now let&rsquo;s look at that claim through a couple different examples. Two of the top challenges of growing a business are retaining existing customers and keeping a positive cash flow.(Crowdsource)

Retaining existing customers. All your marketing efforts and your great product or service turned into customer acquisition. Investment in retaining those customers is literally money in your pocket as it is up to 25 times more expensive to get a new customer than to retain one. Except now you have to spend more time to make more of your great product so there&#39;s less time for marketing. In other words you have to focus on your core business to make sure it&rsquo;s quality stays top shelf. You don&#39;t have time to keep pounding the pavement of social media and google ads.

Cash flow problems are one of the most common reasons that small businesses fail. Yes, businesses need to spend money to make money but that can be a slippery slope, especially if your strengths are in building custom furniture instead of bookkeeping. &nbsp;Simply hiring an auditor to analyze your cash flow and find holes in your efficiency is a form of outsourcing and could make the difference between growth and going under.

Are we seeing a pattern here? Another one of those top challenges to growing a small business was knowing when to delegate. It&rsquo;s inevitable, at some point your one or two-man team is not going to cut the mustard anymore. Either you expand your capacity or your business will start its downhill slide.

Of course your team will grow over time, you will want to acquire and retain highly qualified team members. However, the costs of hiring and retaining employees add up very quickly and it will soon be time to take a hard look at which tasks are core to your business and which are a part of every well-run small business.

 
Reasons why small businesses are choosing outsourcing 
More and more businesses every day are making that calculation and coming up with the answer that hiring out some business functions makes the most sense for their bottom line in one way or another.&nbsp;

Here are 5 reasons that large and small businesses are choosing outsourcing as a part of their business model;&nbsp;

1) The access to talent and skills is unprecedented. Today&#39;s connected world removes geographical barriers. Just like Silicon Valley became known as a tech center, new places all over the world are popping up as hubs for IT services and software development. Many regions around the globe have a combination of low labor costs and high education levels, with many skilled developers and computer engineers. Places that would&rsquo;ve been unthinkable as tech hubs 20 years ago, like Warsaw and Prague are now major players. Similarly, developing countries like India and Nepal have a very low labor cost but a highly educated young population. You may find a team that does HR management in Bulgaria and a team of developers in Kathmandu that suit your needs and your budget.&nbsp;

2) The detrimental effects of multitasking. The dreaded M word. Lots of studies have shown that multitasking is bad for our brains and actually decreases efficiency.That&rsquo;s because it takes lots of mental energy to focus and our supply is finite at any one time. Even if we CAN focus on multiple things at once it&#39;s not long before something slips. On the other hand, deep focus or concentration is actually good for our brains and for our work. Focusing on a single task is not only good for our skills of concentration but makes us happier and more satisfied in our work. It&rsquo;s also more conducive to new ideas and innovation. If your own mind or those of your staff are overburdened with multitasking that opens the door to more mistakes and more stress all around, when what you want is every mind humming along at peak performance.

3) Which leads to the third reason that more small businesses are turning to outsourcing, it allows your staff to concentrate on the core business and make a better product. Handing off a task to the experts is one reason for outsourcing but the other branch of this tree is freeing up time for your staff to do what they do best. You wouldn&#39;t want to have your sales people also keeping track of shipping for instance, or your product development head trying to update the website.

4) Reduction of costs and risk management. Outsourcing can lower costs by reducing those associated with onboarding additional employees, including the candidate search, interview process and training, not to mention healthcare, payroll taxes and increased time and tasks for HR. Outsourcing manages risks and quality control as well. When you hand over a project or responsibility to a contractor they are then responsible for the quality of the product and the costs of maintaining their staff. There&#39;s also savings to be found in equipment costs and not having to office more employees.

5) The capacity expansion potential with outsourcing is endless. Maybe you have an idea for the next big app in college sports, you just need a team to build it. Or maybe you are a gifted artist but only your friends and patrons of your local gallery have viewed your art because you lack the skills of an entrepreneur and marketer. There&#39;s everything from contracting on a permanent basis for your IT security to hiring a free-lancer for a single logo design. Outsourcing is no longer just for customer service and factory labor.

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Every small business owner has a lot to carry on their shoulders. The successful ones have realized which loads they should continue to shoulder and which ones they can set down.

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