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OWASP Mobile Top 10 Security Risks-Real-world Cases

Posted on 16/05/202102/06/2021 by Anteelo Master

Carrying an industry record of developing 100% hack proof applications come with a responsibility and a baseline guarantee that none of the digital solutions developed under our name would face security breach. As a way to achieve that, Anteelo’s Quality Assurance team are familiar with all the possible security risks which an app can face. Knowing the risks makes it easy to ignore pitfalls and write secure apps. Helping us be on top of the game when it comes to assuring security is having complete knowledge of OWASP secure coding practices (Open Web Application Security Project). It is an online community of security specialists who have developed free documentation, learning materials, and tools for building secure mobile and web applications.

Along with other things, they have also compiled a list of OWASP Mobile Top 10 security threats in mobile applications.

While the OWASP security practices document is fairly clear, it can sometimes be difficult for businesses to connect it from real-world cases.

In this article, we will give you a basic overview of Top 10 mobile security risks and give examples of the real world disclosed vulnerabilities for each of them. It will give you an insight into what we prepare for at Anteelo when we work on your application.

Before looking into the risks, let us look into statistics.

NowSecure looked into the apps on Google Play store and App store identified that over 85% of apps violate one of the risks.

Of these applications, 50% have had insecure data storage and somewhere the same number of apps were working with insecure communication risk. Here’s a graph showcasing the percentage of occurence of the OWASP Mobile Top 10 risks

List of 10 Most Common Threats to Mobile Applications and the Best Practices to Avoid Them

M1: Improper Platform Usage

The category of OWASP security testing consists of the misuse of a device functionality or the instance of failure when using platform’s security controls. It can include platform permissions, Android intents, misuse of the TouchID, Keychain, etc.

Real-World Case:

Three iOS apps: “Fitness Balance app”, “Heart Rate Monitor”, and “Calories Tracker app” came into light for bypassing Apple’s Touch ID. They were asking users to use their fingerprint to get fitness information, while they were using it to charge money from the App Store.

Best Practice to Avoid:

The developer must not allow Keychain encryptions through server route and keep the keys in one device only, so that it’s impossible to get exploited on other servers or devices.
The developer must secure the app through Keychain to store the app’s secret that has a dedicated access control list.
The developer must take permission to limit which apps are allowed to communicate with their application.
The developer must control the first of OWASP Mobile Top 10 list by defining the explicit intents and thus blocking all other components to access information present in the intent.

M2: Insecure Data Storage

OWASP consider it a threat when someone gets access to a lost/stolen mobile device or when malware or another repackaged app starts acting on the adversary’s behalf and executes action on mobile device.

An insecure data storage vulnerability usually lead to these risks:

Fraud
Identity Theft
Material Loss.
Reputation Damage
External Policy Violation (PCI)

Real-World Case:

Dating apps like Tinder, OKCupid, and Bumble have time and again been scrutinized for their insecure data storage practices. The security lapses present on these apps vary according to feasibility and severity and feasibility, can expose users’ name, login details, message history, and even location, in addition to other personal account activity.

Best Practices to Avoid:

For iOS, OWASP security practices recommends using purposely made vulnerable apps like iGoat to threat model their development framework and apps. This will help the ios app developers understand how APIs deal with the app processes and information assets.
The Android app developers can use the Android Debug Bridge shell for checking the file permissions of targeted app and DBMS to check database encryption. They should also use Memory Analysis Tool and Android Device Monitor to ensure device memory doesn’t have unintended data.

M3: Insecure Communication

When devising a mobile app, data is exchanged in client-server model. So, when the data is transmitted, it should first traverse the device’s carrier network and the internet. The threat agents could exploit vulnerabilities and intercept sensitive data while traveling across wire. Here are the different threat agents who exist:

Adversary who shares your local network – a compromised Wi-Fi
Network or Carrier devices – cell towers, proxy, routers, etc.
Malware on the mobile device.

The interception of sensitive data via communication channel would end up in a privacy violation, which can lead to:

Identity theft
Fraud
Reputational Damage.

Real-World Case:

Rapid7 security company disclosed several vulnerabilities attached with kids’ smartwatches. Those watches were marketed as ones used by parents for tracking their children and sending them messages or making calls on their smartwatch.

The watches were supposed to be contacted by approved contact numbers through the mode of a whitelist, but the company found that the filters were not even working. The watches even accepted configuration commands via text messages. It meant that a hacker could change the watch settings and put children at risk.

“You can identify where the phone or the child is, you can gain access to audio, or make phone calls to children,” said Deral Heiland, the IoT research lead at Rapid7.

Best Practices to Avoid:

Developers should not only look for leakages over traffic communicated between app and server but also device that holds the app and other device or local network.
Applying TLS/SSL for transporting channels is also one of the mobile app security best practices to consider when it comes to transmitting sensitive information and other sensitive data.
Use certificates given by trusted SSL chain verifications.
Do not send sensitive data over alternate channels like MMS, SMS, or push notifications.
Apply separate encryption layer to sensitive data before giving to the SSL channel.

M4: Insecure Authentication

The threat agents who exploit authentication vulnerabilities do so via automated attacks which makes use of custom-built or available tools.

The business impact of M4 can be:

Information Theft
Reputational Damage
Unauthorized Access to Data.

Real-World Case:

In 2019, a US bank was hacked by a cyber attacker who took advantage of the bank’s website flaw and circumvented the two-factor authentication that was implemented for protecting accounts.

The attacker logged into the system through stolen victim credentials and upon reaching the page where PIN or security answer had to be entered, the attacker used a manipulated string in the Web URL, which had set the computer as a recognized one. This enabled him to cross the stage and initiate the wire transfers.

Best Practices to Avoid:

The app security team must study the app authentication and test it through binary attacks in offline mode for determining if it can be exploited.
The OWASP web application testing security protocols must match those of mobile apps.
Use online authentication methods as much as possible, just like that in case of web browser.
Do not enable app data loading until the server has authenticated the user sessions.
The places where local data us eventual, ensure that it is encrypted through encrypted key derived from users login credentials.
The persistent authentication request must also be stored on the server.
The security team should be careful with device-centric authorization tokens in the app, since if the device gets stolen, the app can get vulnerable.
Since the unauthorized physical access of devices is common, the security team must enforce regular user credential authentication from server end.

M5: Insufficient Cryptography Risks

The threat agents in this case are the ones who have the physical access of data which was encrypted wrongly. Or where a malware is acting on the behalf of adversary.

Broken cryptography generally result in these cases:

Information Theft
Intellectual Property Theft
Code Theft
Privacy Violations
Reputational Damage.

Real-World Case:

Sometimes ago an alert from DHS Industrial Control Systems’ Cyber Emergency Response Team and the Philips advisory warned users of a possible vulnerability in the Philips HealthSuite Health Android app.

The issue which was tracked back to inadequate encryption strength, opened the app to hackers who could get access to users’ heart rate activity, blood pressure, sleep state, weight and body composition analysis, etc.

Best Practices to Avoid:

To solve this one of the most commonly occuring OWASP Top 10 Mobile risks, developers must choose modern encryption algorithms for encrypting their apps. The choice of algorithm takes care of the vulnerability to a great extent.
If the developer is not a security expert, they must refrain from creating own encryption codes.

M6: Insecure Authorization Risks

In this case, the threat agents are able to access someone else’s application typically via automated attacks which use custom-built or available tools.

It can lead to following issues:

Information Theft
Reputational Damage
Fraud

Real-World Case:

The Information security specialists at Pen Test Partners hacked Pandora, a smart car alarm system. In theory, the application is used to track a car, cut off the engine if stolen and lock it until police arrive.

On the other side of the coin, a hacker can hijack the account and get access to all the data and the smart alarm functionalities. Additionally, they could:

Track vehicle movements
Enable and disable alarm system
Lock and unlock car doors
Cut the engine
In the case of Pandora, hackers got access to everything that was talked about inside the car through the anti theft system’s microphone.

Best Practices to Avoid:

The QA team must regularly test the user privileges by running low privilege session tokens for the sensitive commands.
The developer must note that the user authorization schemes go wrong in the offline mode.
The best way to prevent this risk is to run authorization checks for permissions and roles of an authenticated user at server, instead of the mobile device.

M7: Poor Code Quality Risks

In these cases, untrusted inputs are passed by entities to method calls made in the mobile code. An effect of this can be technical issues which can lead to degradation of performance, heavy memory usage, and poor working front-end architecture.

Real-World Case:

WhatsApp last year patched a vulnerability that hackers were taking advantage of for installing surveillance malware called Pegasus Spyware on smartphones. All they had to do was place a WhatsApp audio call on the targeted phone numbers.

Within a simple few steps, hackers were able to get in the users’ devices and access it remotely.

Best Practices to Avoid:

According to the OWASP secure coding practices, the code should be rewritten in the mobile device instead of fixing them at the server side. The developers must note that bad coding at the server side is very different than poor coding at client level. Meaning, both weak server side controls and client side controls should be given separate attention.
The developer must use third party tools for static analysis to identify buffer overflows and memory leaks.
The team must create a third-party libraries list and check it for newer versions periodically.
Developers should see all the client input as untrusted and validate them irrespective of whether they come from users or the app.

M8: Code Tampering Risks

Usually, in this case, an attacker exploits code modification via malicious forms of the apps hosted in the third-party app stores. They might also trick users into installing an application through phishing attacks.

Best Practices to Avoid:

The developers must make sure that the app is able to detect code changes at runtime.
The build.prop file must be checked for the presence of unofficial ROM in Android and to find out if the device is rooted.
The developer must use checksums and evaluate the digital signatures to see if file tampering has taken place.
The coder can make sure that the app keys, code, and data are removed once tampering is found.

M9: Reverse Engineering Risk

An attacker typically downloads the targeted app from the app store and analyzes it inside their local environment with a suite of different tools. Following which, they are able to change the code and make the app function different.

Real-World Case:

Pokemon Go recently faced the security breach glances when it was found that users had reverse engineered the app to know the vicinity of the Pokemons and catch them in minutes.

Best Practices to Avoid:

The best way to safeguard an app against the risk, according to OWASP mobile security, is to use the same tools as the hackers would use for reverse engineering.
The developer must also obfuscate the source code so that it gets difficult to read and then reverse engineer.

M10: Extraneous Functionality Risk

Usually, a hacker looks at the extraneous functionality inside a mobile app in order for discovering the hidden functionalities in the backend systems. The attacker would exploit extraneous functionality from their own systems without any end-users involvement.

Real-World Case: The idea of Wifi File Transfer app was to open port on Android and allow connections from the computer. The problem? An absence of authentication such as passwords, meaning, anyone could connect to a device and get its full access.

Dropbox Store and JetPack in Modern Android App Architecture

Posted on 14/05/202103/06/2021 by Anteelo Master

A few days ago, Dropbox acquired an open-source Store library. The aim behind taking the ownership was to modify it to make it more suitable to the prevailing Android developer ecosystem.

Now, Store also includes Google JetPack collection of libraries which poses as a solution for creating current-day Android apps.

Google JetPack makes it possible to create high-quality Android apps while accelerating the development process.

There are two objectives that this library fulfills – It leverages advanced Kotlin features in order to reduce the boilerplate code and offers high-level abstractions besides those found in the Android SDK, i.e., Fragments and [Activities]. These allow the developers to present complex tasks in an easier and simpler way.

Like in case of the traditional mobile app architecture, there are numerous components in Jetpack that developers can use independently and cover four areas – Architecture, Foundation, User Interface, and Behavior.

In fact, Google uploaded its own recommended Android app architecture along with JetPack defining the set of modules that make up an Android app and how they interact. As shown in the image, a well-architecture Android app is fundamentally based on the tenets – model-driven UI, separation of concerns, and one-directional dependencies across several modules.

However, though Jetpack offers most of the components for the creation of an Android app based on the architecture suggested by Google, there is an exception – the Repository layer.

On this matter, Mike Nakhimovich, the creator of Store states-

“Repository currently only has a few code samples and no reusable abstractions that work across different implementations. That’s one of the big reasons why Dropbox is investing in Store–to solve this gap in the architecture model above.”

Store, while relying on a reactive design, aims to support Android app development where data flows in and out of the UI in a seamless manner without forcing the users to navigate back and forth. Mike goes on to say on this matter –

“Reactive front ends led me to think of how we can have declarative data stores with simple APIs that abstract complex features like multi-request throttling and disk caching that are needed in modern mobile applications.”

To explain this in brief – Dropbox Store helps in connecting the app model with an external data source by using a declarative interface centralizing all data-related activities.

Store aims at optimizing network usage in order to keep it at a minimum. This library was rewritten Kotlin backed by Coroutines and Flow, followed by another major change of discarding RxJava for structured concurrency paradigm which is implemented in Kotlin reactive streams.

This switch poses a big impact on ensuring all resources employed in concurrent tasks are freed whenever the task completes, says Mike.

“The big problem with RxJava’s approach to scoping background operations is that it’s too easy for engineers to forget to call dispose. Failing to dispose of active subscriptions directly leads to memory leaks.”

In addition, the Store also supports disk caching, memory caching with TTL and size policies, explicitly skipping the cache to fetch new data from the data source, multi-casting of responses, among many others.

Now, that Dropbox is implementing many changes in the Store for improvement, it has been set on a path of becoming a great source of resources for all Android app development developers.

creating-a-culture-of-design-critique-within-the-team

Posted on 21/11/202014/05/2021 by Anteelo Master

One of my friends and mentor once shared the secret behind his success- I’ll always be grateful for my struggles and the criticism I received because if not for them, I would have never been where I am today.When I asked him what kind of criticism– positive or negative– was most helpful, he replied – “This is where all problems begin. We weigh feedback as positive or negative criticism. Instead, we must think of feedback as one of the ways to accelerate learning and do better next time.”This made me remember a quote from Norman Vincent Peale- “The trouble with most of us is that we would rather be ruined by praise than saved by criticism.”

We all have done that at some point in our life. We want to hear more praises to validate our talent. But we associate criticism with negativity. The moment we hear criticism, we let our guards up.

What we need is a mindset shift that allows us to look at criticism as a tool to improve our work.

Why is critique culture so important?

Short answer– to create better ideas, build better products and become a better designer/developer/leader.

Long answer– The answer lies in C. S. Lewis’s quote that says “Two heads are better than one, not because either is infallible, but because they are unlikely to go wrong in the same direction.”

Consider this example- while designing a healthcare application, a designer oversees the usage of colors and letter casing in designs. Another designer, who has past experience in working on healthcare apps shares why letter casing is important to consider during design decisions.

This is just one of the many examples. I’m sure you can think of one from your own experience where, upon receiving feedback, you were happily surprised- “Wow! That’s a great suggestion. Why didn’t I think of that?”

What should critique givers keep in mind?

Critique-givers have a defining role in the success of a product.

Pixar co-founder Ed Catmull credits the success of Toy Story to the honest and candid feedback that everyone in the team shared when they saw the first screening of the movie. He admits that “Early on, all of our movies suck.” and goes on to say that it’s the critique that brings out the best in their movies.

What should critique-seekers keep in mind?

Theodore Roosevelt once said- “It is not the critic who counts; not the man who points out how the strong man stumbles, or where the doer of deeds could have done them better. The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again, because there is no effort without error and shortcoming.”

If you’re a critique receiver, one thing to keep in mind is that criticism is not for you, but for your work. So, even if there are any harsh words, take them in your stride.

How to run critique sessions?

For critique seekers

Before beginning the critique sessions, set the context for everyone who is going to share their feedback. Send an email to your team with the time and location details of the session. Mention the subject of the critique and include a short summary of the design you will be presenting.

For example- always tell your team about the user personas for whom you’ve designed the application. It helps them understand the rationale behind your decisions.

During the session, listen to everyone’s feedback with an intent to improve your designs. Explain everything that must be explained. Remember, you’re the only person in the room who has the entire picture in your mind. Everyone else is seeing the project for the first time, so it’s okay if they question your choices (By the way, they won’t if you share the context beforehand.)

Be present in the discussion. Listen with utmost attention. Capture everything; even the harsh feedback. You can always decide later which ones you wish to implement. And when the session ends, thank everyone for their time and feedback. You really must do that.

Most importantly, avoid contradicting the critique by getting into an argument with critique-giver. Getting defensive or angry or taking criticism personally (even if it’s hurled at you in your face) means that you are not ready to hear the truth about your work.

After the session, take time to reflect upon every feedback. Not everything would be worthy of action. So don’t fret over implementing every single feedback. In case you need any clarification, reach out to the person who gave you feedback. Don’t stop before you implement, showcase, iterate on the feedback and present a better solution than before.

For critique givers

Before the critique sessions, understand every detail about the project you’re going to see. If it’s not already provided, ask for related information about the project’s goals, the user personas, their pain points, so that you’re in a better position to suggest improvements.

During the critique session, make sure that you are criticizing the work, not the person. Put aside all biases and prejudices and focus on solving the problem. Empathize with the end user (not the designer), and keep your target audience in mind. Ask genuine and thoughtful questions that help you uncover the intent and rationale of the designs. The designer has worked hard to design the project, they deserve your patience and respect.

If you like something, praise lavishly. If you don’t like something, be critical. But avoid being harsh or rude. Offer constructive feedback, something that can inspire the designer to think in a different way. Listen attentively to what others have to say and provide inputs in case you want to add something to it.

After the critique session, follow-up with the designer to check if he/she needs further help. If the person comes back to you with iterations, share your candid feedback (once again!) without shit-sandwiching it.

When two people discuss and take feedback from each other, they build on each others’ suggestions and make the product twice better. When more people get involved, it takes an exponential form where each member builds on others’ opinion, or suggestion. This is why critique sessions, as a cultural practice, are far more effective than peer-to-peer feedback.

Another reason to create a culture of design critique is that it creates an atmosphere of psychological safety in the team where everyone knows they’ll get honest, candid feedback from their peers and leaders. In such teams, learning and growth happens organically, not forcefully. Passion to do more, be more, drives people, rather than appreciation or promotions. And when that happens, people don’t feel an iota of hesitation in sharing their thoughts. They openly talk about what’s on their minds. They share ideas, opinions, and criticize when things don’t go right.

Isn’t that enough reason to create a culture of criticism?

How Can AI Be Used to Improve User Experience in Mobile Apps?

Posted on 30/10/202012/06/2021 by Tushar

Imagining Artificial Intelligence in situations and use cases where there are a massive number of data in picture makes perfect sense. But what happens when the situation is entirely based on human discretion? Will an artificial intelligence user experience design would also be able to do what AI did to several other industry verticals?

Designing, almost in all its different forms is driven by keeping the human part of process at a much higher ground than the analytical and data driven side. While there are some domains like CAD design or Product Design that leaves some space open for machine learning to enter, when the design form in question is mobile app design, the gap seems to become negligible.

However, Artificial Intelligence, like a number of other industries have found a place in the Mobile App Design vertical as well, giving birth to the concept of artificial intelligence user interface design. A concept that is ought to bring a new level to the relationship between artificial intelligence and customer experience.

While, the answer to whether machine would replace designers is next to impossible, there are ways that the designer community has started taking AI user experience together in their journey to designing memorable mobile apps in multiple ways, like –

Getting time-taking manual works like image resizing automated
Making designs localized by taking help of AI based translation
Bring system consistency between users and products
Give insights into which elements are users interacting with, which needs attention

This participation that the deisgning industry is witnessing coming in from the AI driven UI domain is something that is showing to have a huge impact on the industry’s present, while paving the way to a world where AI and the future of design is much better linked.

Now that we have seen the impact that AI carries on Mobile app Design and how it is soon becoming one of the proven tips to enhance mobile app design, the next step is to look at the principles that guide their unison in the domain of designing AI experiences

The Guiding Principles that Combine Mobile App Design with Machine Learning

Develop a Shared Language

Elements like user experience review, product vision, and business goals are something that needs to be understood and shared by the complete team. You would only be able to create a meaningful and truly intelligent user experience if the mobile app design and machine learning development methods complement each other through shared concepts and common language. The machine learning experts and user experience designers should come together to develop a common blueprint which includes data pipelines and user interfaces, with the aim to set a blueprint that grounds the team’s product planning with the users’ reality.

Focus on Use Case

The important thing when developing a consumer facing app, as the top software designers would tell you, is not the technology that backs it but the business goal and the user experience that you plan on achieving. And so, it is extremely important that you crystallize the use case. With a separate focus on the use case, you can then put your intricate attention on the user flow, which then allows the team to identify the main points where machine learning can be added to enhance the experience.

A clear understanding of the use case also enable teams of the mobile app design company to determine the right KPI for the development of user experience program, which in turn is aligned with machine learning metrics.

Mix Quantitative and Qualitative Data

In order to understand the true impact of combining the machine learning solution and user experience design, it is important that both qualitative and quantitative data is considered. You should make use of qualitative research methods like questionnaires, interviews, etc to measure how the users are experiencing your app.

The reason why we are emphasizing on using a combination of quantitative and qualitative data is because when designing a new app, it is possible that you meet unexpected factors that affect machine learning developmant and user experience. Factors like: Effectiveness of feedback loop, ability of data point capturing intention and user behaviour, which are must to know parts of Artificial Intelligence app design can best be answered only after a deep consideration of both the data types.

Bring Your Combined Data to Real Life Setting

How do you make sure that machine learning is actually used to develop comprehensible and fluent user experience? By setting up an end to end solution that shows how machine learning and user experience fit together in real world. An MVP that includes the working data pipeline along with the machine learning models makes it easy to iterate the AI assisted design together and helps in getting a direct feedback from the users via beta or user testing.

When both UX designers and Machine Learning experts of your partnered AI app development company share the understanding of product design issues, iteration is productive and fast. While on the other hand, user experience designers become aware of possibilities that surrounds machine learning: when it can be used to improve the user experience and how.

Be Transparent About Collecting Data

Designing for AI and with it, needs a constant effort and for it to be absolutely on point, it is important that you give a special focus to the data you have collected. It is very important to consider the end user side in this cycle of collect data – convert data into information – iterate design. Tell users that their data is being used to feed the AI and give them the option to alter the collected information in a way that the best context comes through. In addition to giving users the option to change what data is collected by the AI, you should also give them the option to change what the AI learns – to ensure that the predictions are what the users desire.

While these principles that we just saw help in giving some clarity into how the combined AI and UX design should function, let us look at how some of the famous designing and editing tools that are backed by the developers community across the globe are using the technology to offer better mobile app user experience.

Tools That Use Artificial Intelligence for Design

Tailor Brands

The Tailor Brands logo maker is a famous product used by businesses to get professional logo in a small budget. The AI designs are built upon with your input coming in form of information that would be entered in logo.

Adobe Photoshop

The Select Subject functionality that Photoshop offers make use of AI for memorizing the shape, and then shifting, changing, and editing them with much ease. The tool works on an internal AI system known as Sensei that enables changing backgroungds by recognizing the different subjects in the image.

Prisma and Deepart

Both the famous image editing tools/AI design software make use of artificial intelligence for identify the different aspects of your video and photo and transforming them in a style of your choosing. They give you the option to work around filters and colours among other things.

Let’s Enhance

One of the most frequently arising issues in the designing industry is low quality images. Let’s enhance, powered by AI improves the quality of images using three filters. Anti-JPEF filter converts image to high quality PNG while Boring filter scales up image to around 4 times without any compromise on the image quality. Magic, the third filter allows you to add detailing inside the image. Making Artificial Intelligence a primary part of the Mobile App Design process is something that comes packaged with several add on factors that have to be considered to ensure that that User Interface and User Experience is intact.

And this in turn is not an easy process.

Packaging your app’s user experience with Artificial Intelligence in a way that the whole process gets translated into Artificial Intelligence design patterns calls for a lot of homework, which in itself is heavily dependent on the information that the users provide with consent.

If you are just starting with making your designs smarter, there are some UI patterns that would help you start on the intelligent journey.

A. Criteria Sliders

A number of apps use machine learning algorithms to predict an outcome or pass recommendations. A criteria slider comes in handy here for it helps userss adjust and then fine tune recommendations on the basis of criteria that is meaningful to them. Here, you will have to ensure that the criteria that the users are manipulating with is mapped correctly to data which the machine is using in algorithms.

B. Like and Dislike Button

A simple like and dislike button help better the user experience that someone shares inside the application. Wwhen you ask users to feed in their experience even through a simple like and dislike button, you give them the option to not just build upon the recommendation system but also give feedback on what they don’t like and why.

C. Confidence Inducing Tips

More often than not, users not just not know how the whole prediction and artificial system works, but also they don’t know how much confidence they can place in the system. When you ask users to feed in their data or answer questions in return of something – better matched clothes choice, next show to follow option, etc. The confidence quotient increases even more when you give users the result and let them approve or disapprove it. Doing this makes your users in charge of the charge – something that automatically instills confidence in the app.

D. Give them an In and Out Option

Not all users would want to feed in data for you to fetch and feed in the artificial intelligent system or even want to take the smart route. So, give them the option to opt in and out of the smart options as and when it suits them. Doing this, they would not just have a more positive outlook towards your app but also, knowing that they have an out option, they will be more willing to add in their data in the future.

Now that you have seen the ways AI powered UX is impacting the app design industry, the guiding principles of designing for AI, tools that are already using AI, and the UI patterns that you should add in your design manifesto to make your users open to the idea of AI, there is only one last thing left to do.

And that last thing is to make AI an active part of your mobile app design process. Let our team of UI/UX designers help you with that.

Without Downtime, Here Are Five Ways To Deal With Digital Transformation

Posted on 16/07/202008/06/2021 by Anteelo Master

Advanced technologies are significantly impacting and transforming the way people communicate and collaborate. How are businesses tackling this evolving corporate landscape?

From an option to a necessity – the trek of the digital transformation journey has always been full of obstacles and problems. When advanced technologies started having a significant impact and transforming the way people communicate, interact, and collaborate with a business, the majority of CEOs realized that it’s a matter of survival in the ever-evolving corporate landscape.

A survey conducted by Tech Pro Research Center in 2018 revealed several interesting facts. Out of all the respondents, 70% admitted that their business heads are either working on a digital transformation or already have one in place. Moreover, the survey also revealed that the budgets for IT transformation have been increased in the past couple of years by senior-level executives.

With the acceptance of C-LEVEL executives, every businessman knows that digital solutions are crucial for the success of an enterprise. However, the percentage of businesses that invested in a digital transformation strategy is surprisingly less. What’s the major contribution to such a low adoption rate? What’s hindering you from adopting digital transformation solutions?

The last ten years of information technology have been about changing the way people work. The next ten years will be about transforming your business!

A lot of CEOs are afraid that they’ll have to stop their business process while they undergo digital transformation. However, with proper planning and monitoring, you can easily conduct digital transformation in your company while keeping your business running.

Here’s a list of stats that’ll help you decide by yourself:

A report by Adobe & E-consultancy stated that companies with a digital-first approach are 64% more likely to achieve their business goals than their competitors.
According to a case study conducted by Deloitte, 45% of companies tell people that digital transformation has a positive impact on their business and reported higher net revenue growth.
A published article by PwC stated that 52% of the companies plan to cut their defer investment amid the rise of COVID-19, while only 9% are likely to do the same with digital transformation’s budget.

As the statistics suggest, businesses that have adopted digital transformation strategy not only have an edge over their competitors but also allow them to get a higher revenue growth. In this article, you’ll know about five assured ways to tackle digital transformation without downtime. However, before we start, let’s get back to the basics and understand the correct meaning of digital transformation.

The Main Issues of Downtime

For most digital transformation services company owners, downtime is the single biggest reason behind the loss of production time. According to research by Vanson Bourne Research Study, 82% of companies have experienced unplanned downtime at least once over the past three years. Aberdeen’s Research further includes the cost of a company that can go as much as $250,000 an hour. Not just the production, but companies are also facing issues related to productivity, IT, and customer service due to the downtime.

The study by Vanson Bourne also revealed high levels of asset estate ignorance across organizations, wherein 70% of companies lack full awareness due to equipment maintenance, upgradation, or replacement.

The same study also reveals another issue that occurs due to unplanned downtime is that the unplanned downtime results in loss of customer trust and productivity. This loss resulted in a 37% loss in production time and 29% inability to support equipment for production.

When unplanned downtime occurs, no value is generated but the cost of digital transformation grows constantly specifically around overhead operations , which in parallel impacts a company’s bottom line.

The unplanned downtime is the real issue that is pervasive and finding a solution for this downtime gap is a primary step in an organization’s digital maturity and an essential role for a transformative journey.

Road Towards Zero Downtime

As organizations create and invest in their digital transformation business strategy, we are soon entering a time where zero tolerance and zero unplanned downtime will turn into a norm. The key to this is an understanding of and interest in field service management and asset performance management.

As indicated by Vanson Bourne, eight out of ten organizations have effectively perceived that digital tools can improve the visibility of assets and eliminate unplanned downtime. Around half of the organizations confirmed their intent to invest in field service and asset management in the following three years, while 72% claim that zero unplanned downtime is presently the focus of priority.

One of the significant barriers to digital modernization is the challenge to replace systems while maintaining business continuity. To build a strong customer base, and empower employees with modern technical skills, there is a strong need to increase the uptime and follow digital transformation maintenance to bring digital and IT transformation strategy in the business. Let’s look at the ways businesses are overcoming digital transformation challenges and adopting digital business transformation strategy.

5 Ways To Conduct Digital Transformation Without Missing Business

Digital transformation is a sure-shot way for large and successful organizations to stay ahead of their digital-only competitors. That’s why these projects are usually large in ambition and scope, but there are always some chances of risk. With that said, let us take a look at some of the handiest tips that allow you to undergo digital transformation without any downtime

1. Phase-wise Approach

Instead of following the traditional “rip and replace” methodology, you need to approach transformation in a more efficient way to prevent the risk of downtimes. Consider taking a phased approach to reduce the risk in your transformation. You can release a minimum viable product (MVP) into production early to get realistic structural and operational criticism. This phased approach lets you focus on each stage to make changes and develop a customer centric product.

To tackle the digital downtime, the first phase should always be to create and deploy a front-end proxy. The proxy will provide the data. Only after getting the data, you should move to now comes the time for the second phase which includes the replacement of the old stack.

2. Identify Problems Earlier

As downtime can be caused by a native problem, for example, a software glitch in a workstation, remote server, a major event, or any other reason. Thus, for a major transformation phase, you need to build an early warning system to validate and test things in each phase, so that not much time is wasted in detecting the issue and then resolving it.

Identifying problems earlier also helps in having a solution right there, so when the problem occurs then it is easier to correct it without affecting any productivity. With a little bit of testing, iterating, and assessing, you can easily manage traffic to the new system and identify any potential problems earlier.

3. Plan For Accuracy and Reliability

While undergoing a digital transformation, you must visualize, collect, and alert on in-depth operational metrics. It’s better to have a dynamic plan to ensure functional accuracy and operational reliability to minimize the chances of errors and move towards the next step. The plan can involve the right management. Then comes the skill development to streamline standard operations, decrease downtime, allow quick decision-making, enable employees to attain the skill effectively, and improve brand reliability.

The accuracy provides a convenient digital strategy framework to identify important components within the system and reliability helps in decision-making which is meant to upgrade the system availability or reduce the mean duration of system downtime.

4. Establish A Multi-Layered Fallback Mechanism

Multi-Layered Fallback Mechanism helps to reduce the use of the old system while decreasing the impact and elegantly degrading in case of problems. The mechanism helps in a way that the issues arising in one service do not harm overall operations.

During the transformation, you need to make sure that your team gets familiar with the use of new systems to prevent the product or service quality from degrading. That’s why it’s always a good idea to plan for multiple layers of fallback to keep your back covered.

5. Keep Everyone Involved in the Plan

One of the major issues is the skill gap in what needs to be transformed and what is there in the workforce. Thus, to make everyone in your organization understand the process, recognize the process, and agree that it will be worth the efforts, it is important to involve everyone in the plan. Involving the team in a plan helps to track the progress that is being made towards the goal. It helps build trust within the team and provide employees a chance to come up with approaches that they think will work in a way. Also this helps in getting out-of-box ideas from different members, preparing business transformation strategies, and there are chances of not wasting much time in finding a solution or explanation.

The After-Transformation Effect

Although DT is filled with numerous revolutionary technologies, the top ones are the internet of things, cloud computing, artificial intelligence, and big data. However, it’s more than just the use of technology – transforming corporate culture and business processes are also an integral part of the digital transformation process.

While it’s easier to manage the disruption created by technology to your business, you also need to make sure that your people can cope up with the changes – and it’s more than just technical skills. It’s more about embracing the change and being resilient and resourceful enough to make decisions faster and better.

If you have any business transformation challenges in your organization, you can partner with a digital transformation agency like Anteelo to take care of the migration and adoption needs. We are a well known brand that builds digital products and processes to help teams get acquainted with changes through the shortest learnability curve. We have served digital transformation companies across the globe including digital transformation companies in USA and parts of the globe.

Business changing powerful entities: AI and IoT

Posted on 10/07/202008/06/2021 by Anteelo Master

Before autonomous drones and machine learning came into foray, James Cameron enthralled the world with his dream project The Terminator in 1984 where he introduced ‘Skynet’, a futuristic artificial superintelligence network that wants to replace humans with machines. Much has been debated about the film franchise ever since as scientists passed it off as a fan service action series, yet the seed of technological brilliance was sown. Whether Artificial Intelligence will take over the world or not, it certainly has given businesses a means of revolution and to readers/debaters like us, food for thought.

Another important piece of disruptive technology that is equally changing lives is IoT which expands to the Internet of Things. Like AI, the IoT has come of age. Its utilities include not just making smart homes but also wearable devices, smart vehicles and smart cities. The role of Artificial Intelligence and IoT in business is currently at its epitome.

AI and IoT are redefining the way businesses used to perform. On one hand, AI with its powerful subset of machine learning, has paved the way for smarter task execution with real-time analysis and greater interaction between humans and machines; IoT, on the other, has upped the scale of communication between devices and humans via effective intelligent technology. The confluence of the Internet of Things and Artificial Intelligence makes each other’s applications more varied and powerful.

The merger: How AI and IoT joined forces

IoT accumulates large amounts of data through device connectivity via the internet and AI, especially through its powerful mechanism, Machine Learning helps in assimilating and evaluating this data. Machine learning in IoT devices helps to identify patterns and detect any faults in data collection through extremely advanced sensors. Intrinsic things such as stimulation to air, temperature, humidity, pollution, sound, vibrations, lights, etc. are derived with this technology over a period of time. Unlike traditional technology, IoT and machine learning make operational forecasts 20x faster with heightened accuracy. This is the reason why businesses that use AI technology sees a growth in their revenue numbers – a validation of which can be seen in the graph below

Revenues generated by businesses using AI from 2018 to 2025 (estimated)

AI’s role in IoT’s revolution has helped in a massive revenue boost which also means in the sale of more connected devices.

Below is a graph that shows how many IoT-powered devices were there in 2025 and the estimated curve predicts a huge nerve till 2025.

The demand for IoT is certainly going uphill. IoT, along with AI, are currently on demand by every business, whether it’s a Fortune 500 or a startup. Since there is no limit to either’s abilities, companies wish to use them to their full potential and unbridle their potentiality to the world. The following image draws a comparison among different technologies and shows which ones are the most trending.

As IoT keeps collecting data, AI takes the onus of converting it into meaningful and creative actions. Data exchange happens through sensors and in the process, a few of the following things happen:

Data insights are more accurately obtained, monitored and evaluated
The entire process becomes faster and more efficient
Surveillance against cyber-attacks is more defined and stronger

Advantages of AI and IoT in business

Together AI and IoT are unstoppable forces of technology. There are a lot of advantages which the two provide. The following elaborates the same:

Data collection, sharing and formulating user perceptions

Data collection is extremely vital for a business’ growth and development. A business with an IoT strategy knows how technology can transform data compulsion by offering greater access to consumer information. AI makes it easier to handle that information. IoT devices have this unique mechanism to track, record and observe patterns in a user and his/her interaction with the device(s). Businesses use the acquired data to devise better means to enhance consumer experiences.

Elimination of downtime

Oil and gas manufacturing organizations use heavy machinery which can suffer unseen/unplanned breakdowns. This causes downtime that can incur huge losses. Having an AI-enabled IoT platform makes it possible for predictive maintenance. It helps in anticipating machinery failures and breakdowns in advance by utilizing the analytics so that you can plan a course of action beforehand and not let your operations get affected. A study by Deloitte led to the following conclusions-

20-50% reduction in time taken for maintenance planning
5-10% cutback in maintenance costs
10-20% increment in equipment availability and uptime

Strengthening security measures

With the current rise in data breaches and theft of confidential information, security and safety are the most concerning factors for a business. IoT powered by AI provides militant support to your private information and doesn’t allow third parties to intrude. Machine-to-machine communication is being facilitated by various organizations to detect incoming threats and give out automated responses to hackers. A common example could be in the banking sector where illicit activities in ATMs are picked up by IoT sensors and conveyed immediately to law enforcement bodies.

Automated operational efficiency

IoT deployment streamlines your business and helps in making accurate predictions, all of which are extremely crucial for improving the efficiency of the business. Placing your money on the Internet of Things investment is very necessary in today’s time as the technology also helps in giving you insights into redundant activities and the ones which are consuming a lot of time. A good example will be Google’s reduction in expenditure in cooling their data centres which they could do with AI and IoT. Like Google, you too can find out which of your operational activities need some fine-tuning so that efficiency is not neglected.

Helps in processing business analysis

There needs to be a fine balance between demand and supply. AI helps in improving inventory management and letting go of the pressure on the stock as it will help you to know in advance when you need to restock. This provides an important aid to retailers as they at times hoard too many products to find out later on that all of them cannot be sold. This proves how accurate it is than manual methods. There are IoT applications which help them in gathering the data and analytics for the maintenance of stock.

Better at Risk Management

Earlier we mentioned how AI and IoT help in maintaining cybersecurity. When it comes to risk management, which includes handling financial loss, personnel safety and cyber threats, the pair effortlessly deal with situations and give out prompt responses so that such situations do not arise. For example, Fujitsu, a Japanese IT equipment and service provider makes certain worker safety is maintained through data collected from wearable devices with the help of AI.

Scope for new and improved products and services

The Natural Language Processing (NLP) technology which aims to improve communication via speech, text or gestures has augmented the transmission of information between humans and devices. AI-powered drones and robots give a whole new meaning to monitoring and inspection which never existed previously. It helps to fetch data that a human may never be able to do physically. This proves how strong the IoT and AI future is. For commercial vehicles, it helps in fleet management by monitoring every measurable information. Rolls Royce is a great example of AI-powered IoT use cases. Plans to use AI technology to implement IoT-enabled aeroplane engine maintenance needs. This will help in creating perceptual patterns and help explore in-depth insights.

Examples where AI and IoT are showing brilliance

Now that you’re aware of how AI and IoT solutions help in leveraging business opportunities, let us mention a few examples from real-life instances to prove how the role of artificial intelligence and IoT is helping to create new business models and provide better user experiences. Many of these examples also make up for the most cutting-edge and futuristic trends to watch out for.

Wearables

By now you must have heard how wearables play a key role in the current IoT scenario. Fitness trackers, smartwatches, wearable panic buttons, remote monitoring systems, GPS trackers and music systems are some of the most popular examples of wearables which take up a large part in the IoT ecosystem. You need to simply download IoT applications in your smart devices to get the most precise information.

Robotics

The manufacturing industry was in dire need of adopting AI-focused IoT solutions. This helps in facial recognition, deep learning, big data analytics and especially robotics. Robots and robotics have always been the frontrunners of technology for decades and now, with the passage of time, they have become smarter, more reliable and more efficient. Through implanted sensors meticulous communication is facilitated. Using the fusion of AI and IoT, robots can learn and adapt to newer environments with precision. This makes the manufacturing process linear and saves time and money.

Smart Homes

The smart home ecosystem is growing and is currently valued at $91 million. It’s one of the most pleasing activities of technology where you do not have to get and go to a particular appliance and operate it. The AI-powered IoT technology enables the controlling of your light, fans, television, thermostat, ACs, etc. through your phone. Not just inside but even if you’re travelling outside, say to an outstation and you need to check whether an appliance has been wrongly set on, you can do it with a simple command. Or if you’re returning home after a tiresome day at work and need a bath, you can set the temperature of the water say 10 minutes before you reach home.

Self-driven vehicles

The thought of autonomous cars and vehicles seems exciting and thrilling at the same time. With powerful sensors, installed cameras and robust hardware and software integration, a car gathers monumental information roads, traffic, additional routes, navigation, weather conditions, consumer behaviour and whatnot. Self-driven cars are the perfect examples that will highlight the role of artificial intelligence in future technology. One major concerning factor is safety. Many will face apprehensions over their initial journeys in driverless cars, but that’s what the whole game is about. It has mindblowing learning abilities and high-powered AI mechanisms that will give priority to the passenger’s life at all costs.

Amazon Go

This is truly a masterstroke in AI technology use. To support its retail outlets, Amazon uses IoT to make the shopping experience more convenient for the user. With no cashier or even cash counters, the sensors present will optimise the entire process. For example, sensors are used to determine your activities. Like a supermarket or retail outlet, items are arranged and when you pick up any product, it automatically adds it to your cart and the moment you keep it back, it’s removed from your cart. It connects to your payment mode(s) so when you leave the store with the items, the total amount is debited from your account or online wallet. Just like self-driven cars, they used computer vision, deep learning algorithms and sensor fusion, procreating the ‘Just Walk Out’ technology.

Healthcare

This is currently the need of the hour. With the Coronavirus pandemic, everyone has become extra cautious with their health and technologies like AI and IoT are leveraging the entire healthcare system. The IoT applications and deployments powered by AI help in collecting data to provide preventive measures for a person/patient, early detection and providing drug administration. It draws data from internet-powered medical devices, medical records, fitness trackers, healthcare mobile apps, etc. Many healthcare companies around the globe are making IoT investments so that people stay safe under such hazardous conditions.

Smart Cities

This is the biggest example to show the prowess of the AI and IoT pair. If it is able to maintain civic decorum, then it speaks volumes about technology’s success. Things like smart traffic management, smart parking, smart waste management, smart policing, smart governance and many other factors are the components which constitute a smart city. The Internet of Things for smart cities changes the way cities operate and delivers amenities to the public which includes transportation, healthcare, lighting, etc. Smart cities are arguably a futuristic concept and have a lot of ground to cover. The above video explains how three cities have successfully implemented it.

There are many IoT application development company who have done a tremendous job of integrating the technology into various business types and creating something unconventional out of the banal scheme of things. AI is truly reinventing IoT along with other modern-day techs, and businesses that are vigorously using this technological emergence only have good things to say. No second thoughts need to be spared to explain — The future of IoT is AI and will remain so.

Blockchain Projects Ruling the Decentralized Economy- Guide

Posted on 24/06/202007/06/2021 by Anteelo Master

Blockchain has come a long way since it was described by Stuat Haber and W Scott Stornetta back in 1991. The technology has become one of the biggest innovations of the century and has given rise to various new possibilities in different sectors and industries. Say it fintech, retail, healthcare, enterprises, real estate, or supply chain.

A clear evidence of which is that today, almost every entrepreneur, digital marketer, and even blockchain development firm is showing an interest in learning the basics of blockchain technology and looking ahead to entering the space. And eventually, getting a slice of the market which is anticipated to be valued USD 39.7 Bn by the year 2025.

They have also begun looking into the latest blockchain trends and the best business models top players are working with.

However, most of them are missing one main point.

With the growing popularity of the technology, different ways to embrace it for business transformation are coming into the limelight and so, the kinds of blockchain projects; making everyone intrigued to know which of these types is destined to aid them in leading the digital environments in 2020. Something that you will come to know by the time you reach the end of this article.

So, shall we begin?

[Just in case you want to take a recap of the role of blockchain on the industries, check our blog on ‘the impact of blockchain on the economy’.]

Explained: The 5 Categories of Blockchain Projects

1. ‘Fear of Missing Out’ Blockchain Solutions

The first kind of blockchain solutions that are getting developed these days is FOMO (Fear of Missing Out).

As depicted from the name, this type of projects are brought into life just to ensure that companies do not remain behind in the market. They have not held any meeting and discussed its role into their traditional business model and the possible outcomes they would derive from it in a particular time span. Or even looked into whether investing in blockchain app development is beneficial for them.

Rather, they have just taken this step just to show that they are innovative and work with the latest technology trends impacting the business world.

These kinds of projects, as you might have guessed so far, do not create much value for the business and remain a marketing act for the company. It just increases the chances of your target audience giving a second look to your business products/services or competitors fear of missing out and take the same step.

What’s more, the poorly planned blockchain projects might overburden the existing business ecosystem and demand additional costs. This can make leaders conclude that they ‘tried and failed’ blockchain or doubt on its future. Whereas, the only problem is that they kept on focusing and investing on the wrong use case of the technology.

2. Opportunistic Solutions

The second category in which blockchain projects fall is Opportunistic solutions.

These types of blockchain solutions are devised to solve any known problem, especially related to record-keeping. They add value to the business, even when not being operational for a longer period of time.

The only problem associated with this project type is that one might lose control over data and contracts later.

When looking into the real-life examples of Opportunistic blockchain projects, the blockchain solution developed by the Depository Trust and Clearing Corporation (DTCC) to regulate records from credit-default swaps is the right one to consider.

3. Trojan Horse Projects

Trojan horse projects also landed into the list of type of blockchain business ideas gaining momentum this year.

These projects, just like trojan horses, are attractive, backed by respected brands and address the usual and wide-reaching problem in a particular industry. But, they demand users to share their sensitive information and transfer some control in such a way that results in market consolidation for the prime blockchain owner. So, it is required to invite different groups of people/ecosystems to participate in its processing.

A potential example of a trojan horse blockchain project is a food-tracking blockchain system. This system run by blockchain, unlike the traditional centralized ones, take comparatively less time and effort to determine the point at which the food items were adulterated/replaced, the people responsible for the same, and prevent it further. It enables users to access the records in real-time and prevent dozens of people from falling sick or suffer in other ways. But only when the participants are ready to share their personal information on the network.

These kinds of projects are quite effective. However, there’s a risk involved with considering these projects. They become reliant on the owner’s technology and locked in to the contract terms. But, with the passing time, they gain more control over the market because of having heaps of user data.

Also, the business currencies involved in the ecosystem where Trojan horse blockchain projects exist usually trade at a much higher risk level for the participating users.

4. Evolutionary Blockchain Projects

Another type that business leaders focus upon is the evolutionary blockchain project.

As the name suggests, these projects evolve with time. They are designed to improve over time so as to employ tokens with decentralized governance.

One example of such kind of blockchain software/applications comes from UEFA – the central committee for European football. UEFA works with two Swiss technology companies, TIXnGO and SecuTix, to create an evolutionary blockchain platform that drives a more equitable and safer market for the sales of football tickets.

The blockchain-powered platform encourages ticket buyers to download the SecuTix and TIXnGO applications. Here, the tickets are tokenized so as to keep a real-time record of the ticket purchase and connect it to the ownership details.

In case someone wishes to give away their ticket to a friend or colleague, they can do it through the application, which then stores the record of the transfer in the blockchain ecosystem. And if they wish to send it to anyone in the open market, the SecuTix platform can help them by defining that markup resellers are empowered to charge. This, as a whole, ensures that no unreasonable pricing is being asked or illegal brokers come into play.

Besides, the secondary market for tokenized tickets could mature into a decentralized sales network with time, such that it brings all the second ticket sellers at the same place.

When compared to trojan horse blockchain projects, the business currencies in this type can trade at a comparatively low risk level for the participants.

5. Blockchain-Native Solutions

Last but not least, blockchain native solutions are also among the type of projects business leaders consider in 2020.

Designed by startups or extended teams of existing organizations, these projects are meant to bring forth a new market of opportunities or disrupt an existing ecosystem. They might begin with different perspectives and facilities, but are supposed to move in the direction of tokenization or decentralized governance with time.

When talking about blockchain-native project types, the two industries that come to the limelight are Education and Sports.

In the Education sector, these projects emerged as a non-profit digital education society where students and teachers from different parts of the world could come together and relish the perks of higher education without worrying about learning exchanges or payments. The best example of which is Woolf University, the one founded by a group of scholars from Cambridge and Oxford and known as the ‘decentralized Airbnb for degree courses’.

Likewise in the gaming sector, these projects enable users to create their own tokens to support their favorite games and players. A perfect example of which is Enjinn.

The Blockchain native solutions introduces new business approaches into the market but comes with major currency risks. Because of this, they are preferred only by those who wish to manage their own data and experiment with the concept of decentralization independently.

Now while the definition and approaches of the different kinds of blockchain projects might have helped you with understanding which one is the right pick for your business, you can reach our blockchain consultants to know further. Our team has years of experience in helping startups as well as established brands from different industries to determine the right way of integrating blockchain into their traditional system and reap higher benefits. And that too, without worrying about the hidden business and tech-based challenges.

Failure of On-Demand Platforms- Reason & Solution

Posted on 23/06/202007/06/2021 by Anteelo Master

The glaring success of the on demand era has given birth to a school of thought among the tech community. They have started believing that following the uber business model and entering the on demand industry will be the only move that is keeping them from reaching complete success.

While it has worked for a number of businesses like GrubHub or Airbnb, the number of businesses that have failed are also extremely huge. In fact, if you sit down to make an excel sheet comparing the on demand services fail vs success ratio, you will find that the number of businesses that struggled to survive were more than those which didn’t.

But does this mean that you should give up hope on your on demand platforms’ business success and give up? Of course not. What it implies is that when you plan to succeed in the crowded on demand market, you should also factor in the reasons behind the application’s failure.

The intent of this article is to help with just that.

Table Of Content

Understanding Uber’s Success in the on demand sector
The List of on demand Brands That Failed Miserably
Reasons Behind on demand Business Failure
How Can on demand Businesses Save Themselves From Shutting Down Prematurely?
Conclusion

Understanding Uber’s Success in the on demand Sector

When you dissect the on demand economy, you will find that it is mainly built on three building blocks: delivery immediacy, consumption passivity, and a fixed cost. Uber did not just ticked all the three boxes of the on demand business model, but also aced some other factors that helped it build a seamless ride booking user experience.

Here are the two factors which added to the brand’s success, making it one of the most successful on-demand companies:

The company operates in populated urban cities where there’s enough liquidity for making the marketplace work.
The customer base were already very familiar with trusting a stranger to take them places. Thus, creating a trust in the market was never a problem.

The Uber model doesn’t care about the transaction’s intimacy aspect nor about the disintermediation challenges. Imagine once you on demand home service app users find a person they like for cleaning their house or planning their kids, how would you stop them from contacting those service providers directly, without going through your application? This disintermediation when continued can lead to greater burn, churn, and in some cases extinction of the business.

Since the Uber model didn’t include the need to care about intimacy, they could survive and grow on a much greater speed. But not every Uber-like story has a happy ending. There are a number of once top in the game on-demand platforms that have fallen owing to the on-demand challenges.

The List of on demand Brands That Failed Miserably

1. Happy Home Company

Happy Home Company was a twist in the otherwise traditional home service market. The idea behind the brand was to offer users home maintenance plans which included recurring things that had to be kept in top working conditions. Inspite of bagging $7 million from investors, Happy Home’s founder wrote a shutdown letter which stated, “Ultimately we weren’t able to make the transition from a scrappy startup to self-sustaining company.”

2. Pronto

The business was set out for helping people get healthy meals faster. The UK based service had the work with the intent of connecting the users with chefs while enabling food delivery in under 20 minutes. It had every element to make it one of the most flourishing on demand delivery apps. Even though the idea sounded good to investors and adopters, the company couldn’t keep up with the promotion budgets of Uber and Deliveroo – one of the very commonly occurring on demand challenges.

3. Workers On Call

AI has changed the face of work, this is something that has been established over time. The Workers On Call services used AI systems for streamlining matching of employers with freelancers who needed jobs. The application that boasted of freelancers getting matched and started to work in under 30 minutes, although backed by a powerful vision, was a little ahead of its time. The brand even after raising $30K funding, signed off with a tersely message saying, “Bye Bye. Sorry Workers On Call is closed.”

4. Homejoy

One of the textbook examples of failed the businesses is Homejoy. Started with $20,000 seed funding in 2000, the business became a big name in 2013 when it raised $38 Millions – making it one of the most successful on demand startups. But soon the customers started failing to convert past their first booking. In fact, only 15-20% people re-booked in a month. The numbers were simply not enough for the brand to survive. Add to this the legal battles against classification of workers a s independent contractors led to the business’s death in 2015.

[Further Read: Why Did HomeJoy Failed]

The truth of the hour that still remains is that even after these on demand platforms failure instances, the fact how the internet has trained consumers to get services in real-time is not stopping budding entrepreneurs from entering the on demand economy. But how can businesses ensure that they are not destined to become yet another name in the list?

While one way to get some satisfaction would be to partner with an on demand software development company that has worked with the inception of popular on demand businesses, it would also help to know the on demand services failure reasons that can lead to their failure.

Reasons Behind on demand Business Failure

1. High Competition

The upsurge of hyperlocal service demand has led to a rise in demand of on demand services attending to the complete needs of their customers. One way entrepreneurs are competing in the market is by lowering their service costs. This, in addition to the high operational costs of transportation, infrastructure, and labour has been keeping on demand startups from flourishing.

2. Reluctance among Venture Capitalists

With on demand failure stories shooting off the roof, investors have started becoming wary of where to put in their money. As it is, getting funded on your application has been a difficult process and when you add in the unsureties that the sector now comes with, the probability of raising money lowers even further.

VCs are now becoming all the more cynical about the startup’s longevity. Businesses that are promising a strong long-term vision with a cash flow picture backing it have become the only answer to the types of apps investors will be backing in 2020.

3. Product Incompetence

If there is one event that follows every successful startup, it would be the fact that competitors are soon to follow. The value that your business once offered starts getting challenged and bettered by the competitors. This, in turn, is leading to the product becoming incompetent in the market, irrespective of the efforts that went behind on demand app development services.

Brands that are failing to keep up with the changes with timely pivots are soon finding themselves crawling out of the on demand space.

4. Inefficient Resource Set

The lack of an experienced set of people can most often than not result in the failure of on demand companies. The same applies for the on demand industry. Irrespective of which on demand domain you pick, you will find that the ones that survived were known for their skilled workforce. A lacking on this front can lead to on demand business losing their worth in the industry and thus get closer to their demise.

5. Not Being Able to Solve Real Problems

A number of on demand companies that fail deal with band-aid type of problems in place of emergency room type problems that make the solution extremely non attractive to the end users. Example: For example, imagine an on demand car wash service. Just how frequently would users demand the service? But the expenses a business will have to make to keep it afloat would be huge. In short, the business neither ends up being cost-efficient nor effective.

6. Under or Over Valuing Demand and Supply

The last in our list of reasons that tend to lead directly to business failure is under or over valuation of demand and supply that your on demand business would garner. Businesses, more often than not undervalue the demand that they would attract and thus plan low on supply. Likewise, they at times think too much of demand and end up with an underutilized supply of resources.

Now that we have enlisted the most common reasons behind an the app business failure, let us dive into the way outs – how can on demand businesses prevent this fate.

How Can On demand Businesses Save Themselves From Shutting Down Prematurely?

Market Expansion

One of the biggest issues with today’s top-on-demand businesses is that they don’t expand from their existing markets. The entrepreneurs who are very new to the industry end up being limited to a pool of loyal customers and don’t think of expansion opportunities. The problem with this is that the moment a new competitor with deep pockets enters the market, the probability of them getting out of business increases.

Here’s a look into the expansion roadmap that we generally share with our clients when we assist them with on demand app development.

Make Your Customer Needs Your Bible

In the fight between what you can offer and what your users need, your offerings should always prevail. Although it can be a sweet attraction to invest in tomorrow’s big need, it can be extremely unwise to let go of your customers’ present day needs.

The truth is that you will get a multitude of opportunities and time to pivot your startup. But what you won’t get is the current time and your users present day needs. Getting insights into this information is what a sound on demand mobile app development company can help you with.

Think of Being Monetarily Prepared First

The matter of the modern day fact is that it is very difficult to get funding on an application. No matter how well propositioned your application is or how green your cash flow statement looks, there is zero guarantee of you getting funded.

The solution on this front can only be to look into alternate financing options and not remain limited to VCs.

Conclusion

The growing cases of on demand industry failures have led to the sector getting the image of being a house of card. The only way for entrepreneurs to enter and succeed in the domain would be to do extensive user research. One way we suggest to achieve this effortlessly can be through the mode of product design and development sprint – one of the key practices that on demand app developers follow.

Business Benefits and Services of Blockchain

Posted on 23/06/202007/06/2021 by Anteelo Master

The real-world applications of blockchain are expanding by the minute. But the resources and skill sets needed for developing blockchain applications and hosting them are neither cost effective nor popularly available. Is blockchain as a service for business the answer of how to make blockchain technology accessible to an audience?

In this article, we are going to look into the BaaS solution for business works, the benefits of blockchain as a service, and how to choose the best BaaS providers operative in the market today.

Table of Content

What is Blockchain as a Service?
How Does Blockchain as a Service Business Model Works?
How Blockchain as a Service is Shaping Businesses?
The Region Wise Adoption of Blockchain as a Service?
The Top Blockchain as a Service Providers
A Look Into Self-hosting Blockchain Applications

What is Blockchain as a Service?

For offering the benefits of blockchain based services to a wider audience, the technology has started being offered in the cloud as a service business model. On the operational front, it is more or less similar to the SaaS, PaaS, and IaaS models which enables using cloud-based apps and storage.

It allows businesses of all types and sizes to access blockchain based technologies without investing in the in-house development. The BaaS model enables companies to access the blockchain provider’s service wherein they can develop blockchain applications at minimal cost. This benefit is what has made it a key part of the blockchain technology trends.

The only limitation of the BaaS solution for business is that it asks for a certain level of centralization since the transactions have to be funneled through the host’s blockchain services. And because the answer to how blockchain is used in business lies at the center of decentralization, companies tend to be wary of its adoption.

Key takeaways:

Blockchain-as-a-Service is third party cloud infrastructure and management that businesses use for developing and managing blockchain applications.
It operates as a web host which runs an app’s backend.
BaaS acts as a catalyst which leads to widespread adoption of blockchain technology.

How Does Blockchain as a Service Business Model Works?

Blockchain as a service business model describes the process through which third parties install, host, and maintain a blockchain network on the behalf of organizations. The service provider offers setting up of blockchain infrastructure and technology in return for fees.

In many ways, the role of blockchain as a service for business is similar to that of a web hosting provider. It enables customers to make use of the cloud based solutions for developing and hosting blockchain applications and smart contracts in the ecosystem managed by the provider.

Here is a visual showcasing the working of Hyperledger Cello Blockchain-as-a-Service, which is a BaaS-like blockchain module utility system and toolkit under the Hyperledger project.

The BaaS integration in traditional business provides support around allocation of resources, bandwidth management, data security features, and hosting requirements. The biggest impact of BaaS on business is that the enterprises can concentrate on their main business without thinking of the complexities around blockchain operation.

How Blockchain as a Service is Shaping Businesses

Businesses and consumers are willing to adapt blockchain technology. But the operational overhead cost related to development, configuration, operation, and maintenance of infrastructure along with the technical issues act as a barrier. The advantages of blockchain for SMEs, no matter how massive, are very resource intensive and energy consuming – thus preventing the technology’s mass adoption.

Renting a blockchain infrastructure in BaaS allows businesses to acquire the skillset needed for operating the blockchain infrastructure. Additionally, the investment needed for entering the technology segment is also lowered, since the service agreement can be easily scaled up or even terminated within short notice.

It offers a way for businesses to stay at the edge of technology without any unnecessary risks.

BaaS for startups

The opportunities of BaaS for businesses, especially small businesses, is deemed ideal for organizations which outsource the technological aspects, and are not very hands-down involved with the blockchain’s working mechanism. It enables these firms to get the understanding of the technology without having to develop their proprietary blockchain.

The integration of BaaS solutions is being used by a number of industries for things like identity management, supply chain management, and payments. Blockchain development services are emerging as the ideal solution for a number of SME challenges like elimination of middlemen, lack of transparency, etc.

Use cases of Blockchain as a Service for business

Document tracking – Blockchain technology offers a distributed, immutable document tracking system. By keeping the documents on blockchain, all the participants are given equal access to the information. Additionally, blockchain technology is immutable, thus ensuring that the documents are secured.
Data storage – With the data stored in the decentralised blockchain, the amount of data loss risk is reduced by manifold. The regulated industries like healthcare, real estate, etc benefit a lot from this immutable, secure facility of data storage on blockchain.
Contract execution – Under the smart contracts service of blockchain, a platform is provided for the contract execution which promises high transparency levels. Its distributed nature implies that all the parties should be equally informed.

The benefits of Blockchain as a Service lies in the unraveling of the several use cases that are yet to be emerged. It offers enterprises an opportunity to work on those use cases without making any large term commitments. All they would have to do is partner with a blockchain service company and then fully embrace Blockchain’s capabilities.

Now that we have looked into how is blockchain as a service valuable for SMEs and enterprises, let us look into its regional adoption.

The Region Wise Adoption of Blockchain as a Service?

The impact of BaaS on business has led to a huge demand for the service – a sign of which can be seen in the fact how the BaaS market growth is poised to be USD 24.94 Bn by 2027.

The worldwide market of BaaS is big around the US, Mexico and Canada. One prime reason behind this is the presence of SMEs and large businesses operating in the US location along with a willingness to combine the technology with the public utilities services.

Europe has also been seen as the leading BaaS market. One of the major drivers of blockchain and BaaS adoption has been the government support from different countries.

The Asia Pacific (APAC) region is the third-most biggest market for the BaaS integration. Driven by the BaaS integration in traditional businesses and growing investment in Japan, China, and South Korea, the technology is poised to grow in the region.

To take the adoption of blockchain as a service for business further, a number of tech companies have emerged as BaaS providers. Here are a few of them:

The Top Blockchain as a Service Providers

A Look Into the Alternative – Self-hosted Blockchain

Up until this point, we have looked in the BaaS ecosystem and how Blockchain as a Service is influencing the small business, in addition to the list of top providers. While it all suggests that it is a good option to go with this approach, businesses can in fact lose out on the essence of decentralization – the foundation of blockchain fundamentals.

So what is the alternative? The answer is Self-Hosted Blockchain.

When we talk about the Self-Hosted Blockchain app cost, the ownership amount tends to be a lot higher because of the startup costs, retirement costs, and operational costs. Moreover, the amount of developing and deploying a smart contract under this model can amount to up to hundred thousand dollars or more.

In contrast, a blockchain app hosted on cloud as a BaaS offering can be around $0.29 per allocated CPU hour. This means, businesses would only have to pay as they go and only for the service units used.

The costs of the BaaS model vary on factors such as number of concurrent transactions, transaction rate, and the payload size on transactions, etc.

Blockchain vs. Traditional Database: Make a Startup’s Choice

Posted on 21/06/202007/06/2021 by Anteelo Master

Blockchain Technology has witnessed phenomenal growth in the last few years and appears to stay on track in gaining enterprise adoption. But while it has covered an appreciable curve of general acceptance, it continues to baffle people conceptually.

Striking similarities between Blockchain and databases makes people wonder “is Blockchain just a database?” Yes, Blockchain is a database that comes with several distinguishable traits. These traits are what lead to the debate of Blockchains versus traditional databases.

Therefore, in this post, we would systematically approach the definitions, similarities, and differences between the two to enable a better understanding of the subject for entrepreneurs and startups looking to explore blockchain.

Table Of Content

What is a Traditional Database?
What is Blockchain?
Defining Blockchain & Traditional Database
Management of Traditional & Blockchain Database
Reasons to Use a Traditional Database
Reasons to Use Blockchain Technology
Closing Thoughts

What is a Traditional Database?

Data structures are defined as a storage format for efficient management of data. A traditional database is nothing but a data structure, that helps in storing and working with data. Each organization, from a startup to a Government entity, uses databases depending upon the scale and size of their operations. The aspect that makes databases utilitarian, is they allow users to fetch the data. In technical terms, this is referred to as requesting or querying data that is achieved by Structured Query Language, SQL.

The first-ever architecture of databases was based on a hierarchical style that made it possible to collect and store data. But that was just about it. As technology caught on with time, dragging the tide of businesses with it, data became complex. Likewise, analysts wanted databases to interoperate so they could draw better business conclusions. Thus, the database design shifted to a relational model. Today, all you need for an end-to-end data optimizing process is a Database Management System (DBMS).

Databases are no rocket science, in that they are simple tables. Tables are fields (columns) that contain the details regarding the nature of data. Rows are called records.

What is Blockchain?

Blockchain is a decentral database that acts as a storage for chunks of bundled information called blocks. The reason the blocks are referred to as chains is that each block carries the hashed data of the block added to the ledger before it. This goes back to Genesis, the first-ever block that was mined for bitcoin. A hash is a code that encrypts the transactions in a given block. This code is, essentially, a pointer, a name of sorts, that uniquely identifies a block.

The bitcoin protocol makes it mandatory for every new block to contain the hash of the previous block plus the hash of the block that contains information for newly processed transactions.

But as any blockchain service providers would tell you, finding this new hash isn’t easy. Blockchain technology underpinning bitcoin adjusts hashing difficulty by calculating the total computing power of the network. The more miners there are, the harder it is to find a hash and vice versa. In return for validating blocks and helping run the Blockchain, miners are rewarded with bitcoin.

A. Defining Blockchain & Traditional Database

Defining the Traditional Database Architecture

Traditional databases are based on client-server architecture. Clients are end-users of the service that request access to a particular set of data. This request goes through a server that hosts the database. Open database connectivity is used to establish a communication line between clients and the database.

This line is further secured by the client software that is authenticated up ahead for access. In private databases, access is granted to only those who have valid login credentials and a password. An example could be confidential health records of a hospital. If a database is public and open for all, then a user account is not needed and the data can be accessed from a website. This, in turn, has played a huge role in Blockchain transforming the closed healthcare system.

Defining the Blockchain Architecture

Blockchain Technology has come off age and offers multiple architectural models such as permissioned, private, or hybrid blockchain.

Network nodes are the lifeline of Blockchain technology and they operate on a Peer-to-Peer, P2P, model. Each peer/node can correspond with a second node. There is no superiority or bias between 2 nodes in terms of responsibilities but yes, there could be a difference in total computing resources they possess. Peers of a network ensure the veracity of the Blockchain.

For the transactions to be manipulated either a 51% attack would need to happen (as mentioned above) or multiple peers would have to collude and accept blocks with falsified data. By architecture, Blockchain database technology protocols accept the longest-running, active chain. Therefore, its decentralized administration makes it safe and secure to be trusted and earns it extra points in the matchup of Blockchain vs distributed database.

B. Management of Traditional & Blockchain Database

Managing Traditional Database

Databases support CRUD operations i.e. you can create, read, update, and delete records. Database management is centralized and under the control of an administrator. This individual has the power to modify the database, potentially at will. Their key responsibility is to up the performance and lower database redundancy. As the database expands, so do the daily audits and the corresponding checklist of maintenance tasks.

To aid in this process, a primary administrator can divide his/her tasks and distribute work between multiple users, each assigned a minor task. This could be anything from data entry to modification.

Databases require backup storage as anything could go wrong. Data can be corrupt, servers could crash, and critical information could be lost. In such cases, the files are retrieved from backups. Backing up also allows archiving multiple versions of a database. As an example, consider an address change. Whereas you might contact relevant Government bodies to update “records” and issue you an ID reflecting the same, they will still save a copy of the last address, for record-keeping.

Managing Blockchain

Blockchain technology decouples administration and divides it amongst all the nodes of the network that ensure it runs with their computing power. Each of the nodes stores a copy of the complete Blockchain. In wanting to change the contents of a block, its hash would have to be changed. Since Blockchain technology automatically revises the difficulty level for hashing a block, a tremendous amount of computing power would be required to change the hash of all the blocks. The only situation where that would be possible is a 51% attack, wherein the rogue actor has more computing power than the majority of the network.

As a result, Blockchain technology is proven to be immutable. Since records can’t be changed, this adds transparency to the architecture. They are also remarkably fault-tolerant as even when a few nodes (computers) are down, the rest of the nodes will ensure a 24/7 uptime.

Since no authoritarian permissions are needed to transact on a Blockchain, this makes them permissionless. Therefore, you can use Blockchain as a database but with the extra convenience of these features.

Reasons to Use a Traditional Database

1. They are customizable

In the Blockchain vs database debate, the latter wins hands down in terms of customizable options. Since traditional databases are administered centrally, permissions, privileges, and set-up requirements can be optimized. The relational architecture and backup practices pave the way for a database to be relocated anywhere. Developers can add plugins to the database and improve the front end for customer-centricity.

2. They are Stable

Traditional databases can tolerate high volumes of transactions per second as permissions are centralized and the controls to update data are in the hands of a few. Client-server architecture reduces the dependency on nodes that are substituted by standalone server centers.

Database administrators revert to sharding and shrinking to optimize the speed of the network. In the event of a power outage, downtime, or any other technical glitch resulting in data loss, the backup acts as a default option to reset the last version.

3. They Deliver Speed

The traditional database design has undergone a lot of upgrades over the years to suit faster delivery times and high-end analytical operations. Big data analytics is a case in point.

Where Does the Traditional Database Lags – Issues That Blockchain can Solve

1. Ethical Issues

The same centralization of power that provides for the above-mentioned advantages could also be the straw that breaks the camels’ back. Critics of the system suggest moral issues with handing over the data into the hands of a single administrator. There is an ongoing war to monetize data in every which way possible.

An open market for selling data to third-party vendors already thrives. The Cambridge Analytica scandal was an eye-washing experience that brings to light what a centralized database with a single administrator, Facebook, could do.

2. Contingencies

Considering the case of a single administrator on top of everyone else. What happens if this individual switches to another employer? Knowledge transfers take their jolly good time not to mention the confidentiality agreements. Resetting of passwords, and appointing new administrators is a task in itself. This recruitment is a huge pain in the neck for project stakeholders.

3. IT issues

Every organization needs a database of some kind or the other. The fact that a company stores information in a database doesn’t signify that the database is safe. The entire IT infrastructure needs to be standardized. A single loophole, given the sophistication of hackers, could sabotage enterprise operations. Security analysts must install and operate effective layers to secure traditional databases.

Reasons to Use Blockchain Technology

1. They are Fault Tolerant

When debating Blockchain vs database, the former wins comfortably in the department of system preservation. Blockchain technology is highly fault-tolerant. Its uptime is not reliant on a few server centers but hundreds and thousands of nodes that offer processing input to run the system.

In the scenario that a few nodes are turned off, the overall efficiency of the network would remain unchallenged.

2. They are Secure

Blockchain technology is one of the most secure infrastructural investments you can make today, especially when it comes to securing mobile apps using blockchain. Each node on the network is supposed to download a copy of the blockchain for validating new blocks. To change even a single block requires each node to update its copy which in turn requires a self-defeating amount of processing prowess for an adversarial power.

3. They Offer Transparency

Provided the Blockchain is public, you can view all the transactions that have ever been recorded on it by simply downloading a copy of the ledger. Unlike a bank, where all the transfers are hidden, Blockchain technology opens the door for critics to fact-check and follow the trail of money in dubious cases.