February 2020 - anteelo

Know Whys and Hows of Stock Trading App Development

Posted on 29/02/202015/06/2021 by Tushar

There was a time when investors had to call up the stock exchange who would then put them on hold as they were connected to a stockbroker who would in return charge money to buy stocks for the investors. The time is now gone. For good. Today, brokerage firms and other investment platforms have brought the whole process of stock buying and selling on mobile. This has given the investors the opportunity to trade in their own time, without any unnecessary guidance, right on the move. In this article, we are going to walk you through the process of how to get started with stock trading application development – giving you the reasons why it should be done and the process of how to make a stock market app.

Understanding the User Demographics of a Stock Trading App

Why Should You Invest in Stock Trading App Development?

Best Share Trading Apps

Features That Make Up For a Successful Stock Trading App

Key Points to Consider When Building a Stock Trading App

FAQs About Online Share Trading App Development

Understanding the User Demographics of a Stock Trading App

There are four categories of users that you will be majorly focusing your design, development, and promotion efforts on –

Young people who are still trying to figure out whether the stock investment game is for them
First-time investors who have very little skills but wish to start their trade journey right away.
Professionals who value their time and want to have a quick in and out experience
Tech-savvy users who want to have all of their information and statistics in one place.

Countries wise interest in best stock investment apps –

Let’s move on to the investors’ age range now.

According to statistics shared by Statista, the online stock trading industry has found a very strong user base in the Millennials age group in 2018.

Now that we have looked into the users’ age group and their geography, let us move on to the next part of the business – The need to invest in stock trading app development.

Why Should You Invest in Stock Trading App Development?

Aside from the obvious factor that there is a massive user base for the app category, across age groups, the ease that they offer is too big to overlook when listing down the benefits of developing the stock trading app.

Stock trading apps make it possible for busy investors to be updated on how their portfolios are moving. And in return for this ease, they easily agree to become the paid members of the app.

All in all, the scope to benefit both in terms of money and fame is high when you think of stock trading app development.

With the reason why you should build a stock trading app like Robinhood and E-Trade now known, let us move on to the next step that you will have to consider when thinking of starting your own stock trading app business – The competitors you will soon be leveling the grounds with.

Best Share Trading Apps

Robinhood Stock Trading App

By offering free stock trades, Robinhood has become one of the best stock trading apps present today. The primary features of the app revolve around tracking the stocks that you own, searching, and trading stocks, etc.

The free version of the application gives you access to stocks, ETFs, and Bitcoin but if you wish to invest in and out of Mutual Funds, you will have to take up the paid version.

The fact that Robinhood offers a wide set of supreme features in its free version has made it a classic reference point for fintech app development companies on how to develop a free stock trading app that sticks.

Stash Stock Trading App

This app, which is also one of the best stock trading apps of 2019 is primarily for newbies who wish to make their own investment decision by playing safe along the way. It lets you invest as little as $5, while constantly educating you on how the investment world moves.

The apps come loaded with a series of tips and articles to make the whole investment journey all the easier.

E-Trade

E-Trade used to be a pioneer in the online investing world. Based out of Silicon Valley, the brokerage started offering online trade with the help of America Online (AOL) and Compuserve. And soon they launched one of the best stock trading apps – the E-Trade app.

The app lets you view investments or enter trades for ETFs, stocks, and mutual funds, etc.

These are only the cream of the stock market business apps that you will be aiming to reach once you enter the space. The actual list of operative apps is much extensive.

Let us now look at the features set of fintech application development that would help you take the journey and reach the stage where the top stock trading apps are at. These features are your answer to how to develop a stock trading app similar to Robinhood and E-Trade.

Features That Make Up For a Successful Stock Trading App

1. The check-in process

The authorization process has to be extremely easy and non-burdening for the users. It is at this stage when you should offer users multiple check-in options – use of pin code, biometrics, etc. This way, you will be able to ensure that their experience is safe.

2. User profile

Users should be given the option to save their personal information and preferences related to notifications or simply the frequency in which they want their account to get debited.

3. Putting trades on stocks

The one obvious feature that should be added to your stock trading app development process is giving the users the functionality to execute orders and monitor their flow of funds.

4. Real-Time portfolios

Irrespective of which fintech application development company you ask, they will unanimously tell you that nothing is deemed more beneficial than real-time updates when your users invest in a stock trading app, through their time and money. Users should be given the ease to view their portfolios in real-time and they should be timely updated to give them a very clear idea of where they stand investment-wise.

5. Deposits

Using this feature investors will be able to see the status of their deposits in real-time with minimal effort.

6. Search

In your stock trading app for investors, your users should be given the option to search for active stocks and their present rate in the market.

7. Analytics

The stock market participants would appreciate the opportunity to look at the statistics and analyze the end result of their trades, transactions, etc.

8. Push Notifications

Another must-have part of your online trading app development process would be to integrate push notifications. You should give your users notification of how their stocks have moved, but they should be timed in a way that they are not bothersome for busy investors.

9. Newsfeed

Although the feature gets the least attention, the newsfeed is one of the most crucial features of a stock trading application. For a new trader who belongs to the amateur category of stock market app development user study, a newsfeed that informs them of recent happenings in the stock industry – the winners and losers, latest M&As, IPO details, etc.

With the feature-sets for trading-based fintech software development services addressed, at this stage, you are all set to take that next move and start planning the technicalities of how your stock trading app would run. Here are some key points to consider which we believe will make you confident to take the step towards stock-centric finance mobile app development.

Key Points to Consider When Building a Stock Trading App

1. Have a plan to secure your application

One of he high-priority considerations in terms of stock trading app development is having control over the process where the app will gather and use sensitive information. Here are some steps that we follow to ensure complete security of your application –

Incorporation of multi-factor authentication system, bank-grade encryption, and next-gen firewalls
Implementation of real-time threat intelligence to remain on top of the threats.
Embracing ‘compliance as code’ for the incorporation of compliance testing and security in the CI/CD timeline.
Safeguarding of application programming interfaces.

Finalize APIs that are appropriate for a high-frequency trading software

The development of a stock trading application comes loaded with several technical challenges. The answer to these issues generally lies with the integration of third-party APIs. However, it is very important to know which APIs to use in your app on the ground of security and scalability.

The ones that we generally use are – E*TRADE API, Intrinio, and Marketstack.

2. Create a user-friendly interface

A stock trading app is, by nature, filled with data of multiple nature – text, image, statistics, numbers, etc. It becomes extremely important to not let your application become a case of information overload – one that turns off users who are not as enthused about stock trading as their heavily invested counterparts.

What we recommend is having a UI/UX design that is fit for a quick in and out time (at least on the first few screens) and then keep the detailed pages for after the second or third click.

FAQs About Online Share Trading App Development

Q. Which is the best stock trading mobile app?

There are a number of different options when you are looking to invest in a stock trading app. Depending on your experience level, you can either go with the Robinhood app – if you are an experienced investor or with Stash, if you are a newbie.

Q. How to use stock trading apps?

This is the process that stock trading apps normally work on –

Link your bank account
Set up a one-time transfer or periodic deposits into your Robinhood account
For trading a specific stock or for keeping it in the Watchlist, you will have to click on the Search option.
Once the stock and its current trade come up on the screen, you can choose to buy it which takes you to the page you actually have to buy the stock off of.
The selling option works almost the same as the Buying option.

Tips & Trends to Follow For Mobile App UI Design in 2021

Posted on 28/02/202015/06/2021 by Tushar

UI design has proven to play a crucial role in mobile app success. It has positioned itself as a ladder to reach the hearts and minds of the users and customers by displaying engaging visual content and more.

But, is everyone able to relish its benefits? Do all the designers and entrepreneurs know about the best mobile app UI design tips that work in the customer-centric world?

Sadly, no.

So, with the intention to simplify their journey of figuring out what the UI of future apps look like, we have prepared a list of tips and trends that will be popular in the mobile world in 2021.

But first, let’s take a recap of the benefits of UI design.

Now that we have taken a visual walkthrough of the importance of good user interface design during app development, let’s peep into a few mobile apps that are giving serious UI designing goals to others in the industry.

Best Apps That You Can Get Inspiration From

1. Netflix

Netflix app – the one that has changed the landscape of the movie streaming industry – tops the list with its breathtaking UI design.

The application introduced incredible layout and color options to the mobile domain. It has not just worked on simplifying the navigation process but also ensured that all the reported bugs are solved in real-time. In this way, it has increased the chances of offering a positive experience to their audience.

2. Splitwise

The UI design of the application is simple, sophisticated, and pleasant. The color scheme is chosen in a way that it complements app elements as well as employs the center of the device effectively.

3. Spring

Spring, the popular shopping app, is also a good option to consider while looking for design tips for mobile apps.

The mobile application offers a simple and interactive experience – using icons to give a hint of the functionality of each element. The app uses different font styles and sizes along with a card layout to deliver an enhanced UI experience.

4. Trello

Trello is yet another application you can consider for deciding the type of UI design to create.

This productivity app is easy to use and gives the facility of creating boards for managing their tasks. It comes with a clean and sophisticated look and feels along with its tactics of arranging all the pins in a ‘pipeline’ manner. Also, it offers tons of cool backgrounds and labels colors to amp users’ experience.

5. Shine

Another application that has enhanced its customer experience via the user interface is Shine.

The mobile app uses custom and abstract aesthetics to match the mood of users. It also relies on soft shapes and calm colors to make them experience some peaceful moments.

6. Coursera

Coursera is yet another mobile application whose User interface offers some real goals in the design world.

The app design is simple and smooth, offering the ease to navigate from a well-organized syllabus. It uses different font styles and colors to give users an idea of what they have covered, what they are interacting with, and what’s next.

Now that we have taken inspiration from different mobile applications, let’s turn towards the main part of the article, i.e, best mobile app UI design tips to follow in 2021.

Mobile app UI Design Tips To Follow While Designing Your App

Keep It Simple

The foremost tip for designing a better mobile app is to keep the UI simple.

When you restrict the number of app UI elements, users do not get drifted by unnecessary details. They find it easier to focus on the prime elements of the application, which eventually improves the user retention rate.

Make it Responsive

Concentrating on responsiveness is also one of the proven tips to enhance mobile app design by improving its UI.

This is because when you design elements that fit the screens, regardless of the device users are using, they find ease in performing actions. This, in turn, encourages them to spend more time on your platform and add higher value.

Use Popular Icons

Users, when interacting with various mobile apps on a daily basis, become familiar with certain icons. They can easily relate those icons to particular functionalities without even reading the label.

In such a scenario, using those icons can cut down the hassle of making users understand what an app element is for. This eventually enhances customer engagement and delivers higher ROI. So, introduce popular and similar icons in your UI designing strategy.

Maintain Consistency

Another best practice for app designing that UI mobility experts follow is showing consistency. That implies using the same font style, color, design, and icons throughout the app screens – and that too in the same order.

This simplifies the user journey and helps them make an action without getting a feel of being on some other platform. So, keep it into consideration while planning the app UI design.

Follow Platform-Based Rules

Both Apple and Google have set guidelines for mobile app design for iOS and Android platforms

. Following those guidelines improves the look and feel of your application on the respective platform.

So, do not overlook these Google and Apple UI design guidelines while crafting your app design.

Do not Forget about Loading Speed

Focusing on speed is also one of the best design tips for enhancing user interaction. This is because when UI elements take too much time to load, users get frustrated. They decide to exit the platform soon, because of which all of your efforts could go in vain.

So, think about optimizing your app speed frequently.

Invest in Testing

Many times, the elements you introduce in your app UI design do not work effectively. In such cases, they ruin the user experience instead of adding value to it.

So, it is good to invest your efforts into mobile app UI testing. For when you test your app icons and other elements for different conditions, it ultimately helps bring a positive impact on the users.

When talking about app testing, one thing that UI/UX designers must consider is the depth to which they should test their UI screens.

While educational and commercial apps require thorough UI testing across all the devices and OS versions, business apps can skip investing in extensive testing. This is because their audience, in most cases, is trained to employ the application.

In a nutshell, the depth of UI testing depends on the app’s purpose and the market it will target. However, it is a must to test your app UI on at least three different OS versions.

Iterate Regularly

Since user behavior and market trends keep on changing with time, it is again effective to upgrade your app UI design timely. And eventually, gain higher conversions.

As previously mentioned when talking about the latest mobile UI design trends 2021, changing market trends also influence the success of the user interface you design. So, let’s uncover what are the future mobile design trends 2021 to pay attention to.

The State of UI in 2021: Technologies and Trends That Will Dominate the Industry

1. Conversational Interface

Conversational Interface is one of the leading UI design trends for the future.

Just like Apple, Amazon, Google, Facebook, and Microsoft, various startups, and established brands will invest in Chatbot development to deliver the next level of conversational experience to their user base.

2. The Overlapping Effect

In 2021, UI/UX designers for a mobile app will embrace the idea of overlapping different elements, like text, image, and colors in a single screen.

The concept will help in creating a well-organized interface and create an illusion of space. This will eventually enhance the user experience to a great extent.

3. Typography

Just like last year, considering typography in-app UI design will be one of the best mobile app design trends in 2021.

While brands have been applying bold San-Serif fonts and strong typography for some time now, they will now focus more on typography that reflects motion-based and three-dimensional effects.

4. Voice-Powered Interfaces

By 2021, 50% of the search engine queries will be performed via voice. Because of this, voice-governed interfaces will also become one of the popular mobile application design techniques which are poised to deliver higher output.

5. Simple Curves and Geometry

Another UI design trend that will transform our future is the use of simple curves and geometry.

These curves and geometry will lower down confusion that might arise when multiple illustrations, pictures, catches, and animations are present in the design

6. Custom Illustration Interfaces

Illustrations will also be one of the popular mobile application design techniques to follow in the future.

Both brands and designers will turn towards introducing custom illustrations into their application – just like how Uber did.

7. White space

White space will also continue to be one of the core elements of mobile app design strategies.

With white space, designers will be able to deliver an uncomplicated experience to their target user base. They will find ease in making them focus upon the main part of the application over others. And ultimately, add value to their business.

8. Artificial Intelligence (AI)

Another technology that will bring a major impact in the field of UI design is Artificial Intelligence.

AI will not just help designers with creating multiple versions of any particular landing page or screen, but would also introduce personalized elements backed by thousands of studies and visual analysis. This, as a whole, will encourage them to look into how to use AI for better user interface design.

9. Contrasting Font Color/Shapes

Using contrasting font colors/shapes for mobile UI design will increase its popularity in 2021.

Mobility experts will infuse contrasting colors and shapes into their design to break the regular flow and add a tint of surprise into user interactions.

10. Animation

Animation, which was one of the key app UI design trends for 2018 and 2021, will also continue to enjoy the same momentum in the future.

Brands will embrace the technique to introduce micro-interactions in their design process. And, in this way, prompts users to spend more time on their platforms.

11. Opacity

Setting the opacity of different UI elements will be considered among the top key app design trends 2021. The technique will be used to bring more emphasis on certain elements while maintaining smoothness and seamlessness.

12. Augmented Reality (AR)

In 2021, UI/UX design experts will turn towards Augmented Reality (AR) for creating real-world interactions. They will embrace the technology to add immersion effects to their apps and products and help users comprehend the information more efficiently.

Besides, the technology will also be considered for building 3D brand impressions in the coming years.

13. Storytelling

Storytelling, i.e. the art of engaging users by narrating a story, will also be seen as one of the best UI/UX mobile design trends in 2021.

Mobile app designers will put more effort into crafting a story that highlights the purpose of the app and make users feel like a part of it. They will turn towards the best visual storytelling guides, tools, and techniques to make a story that keeps their audience hooked to their platform.

14. 3D Graphics

3D graphics will also land on the list of top UI/UX trends to consider in 2021.

Mobile app designers will incorporate sophisticated textures and 3D images into their designs to add a realistic feel. Also, users will demand more 3D designs and marketing content to enjoy a vivid, fresh, and engaging experience.

15. Placement of Navigational Elements

Another trend that will change the future of the mobile app design world is the placement of navigational elements.

As we have already seen in our blog upon the impact of Phone X’s new design on mobile apps, the absence of a home screen button will influence the navigation process. This will urge mobility UI experts to discover new ways to deliver a seamless navigational experience to their users.

16. Virtual Reality (VR)

Last but not least, the incorporation of Virtual Reality (VR) in UI design will also be in trend in the coming years.

The technology, after redefining the healthcare, marketing, and gaming industry, is expected to boost interaction levels in-app UI design. It is expected to emerge out as the ‘Internet of experiences’ by spilling out the app elements in the real world and prompting users to feel them.

While these were some of the mobile app design tips and trends that are predicted to revolutionize user interface in 2021, many more are hoping

Dimensions of change in the digital workplace

Posted on 26/02/202015/06/2021 by Tushar

Upgrade workplace technology: check. Modernize infrastructure: check. Adjust to new workforce: check. Overcome resistance to new ways of working: check. Adjusting to digital transformation’s impact on the workplace and workers is, well, a lot of work. A lot of change. And it’s essential to understand that workplace transformation will only deliver expected business benefits when organizations develop effective ways to cope with change along many dimensions. These include:

Workforce. For the last few years, we have focused on the generational shift taking place as millennials become the bulk of the workforce. However, there is a second shift that will impact how we operate. Organizations are adopting more gig workers for specific tasks or projects, which puts pressure on IT to streamline gig workers’ experience and optimize processes to maximize gig workers’ productivity. Capitalizing on automation, intelligence, and integration to optimize business flows and processes will become fundamental to IT operations.

Human resources. This blended workforce, and the recognition that organizations are already adopting a task or gig-like approach internally, impacts the way we run our Human Resources processes. The line manager might continue as a custodian, but the management chain becomes flatter, tied to activities and projects. The old reporting model breaks by having so many stakeholders and managers. We need to automate and collate information for the relevant project and stakeholder, distill it succinctly, and publish it to those who are invested, as well as archive it as input to the performance review process.

Project management. That information will enable project managers and stakeholders to better manage the individual and the team, optimizing for performance and cost. As they see near-real-time information about productivity and performance (on their specific project), they can flex, coach, and change the team as needed. It is a much more hands-on world, although some of the tasks can be automated. Project resource managers can learn from just-in-time manufacturing techniques, bringing in the right folks at the time they are needed.

Relevant information. In this environment, relevant information — not more information — is the key. Luckily, the platforms citizen developers are experimenting with also provide some of the components needed. They can capture tasks done, documents touched and discussions held, giving us a raw feed of activity. Post-process this information, in the context of each stakeholder, can be used to produce concise, relevant reports grounded in system data, not flawed memories.

Embrace employee-driven innovation. Organizations must become better at matching the pace of change, using techniques like employee-driven innovation to quickly identify new workplace trends and opportunities. Formalizing informal support networks can help manage change more effectively and capture the benefits of disruption. And when companies understand how productivity and morale are boosted by ongoing workplace investments, the cost of change is less daunting and easier to justify.

Connection and collaboration. Companies must continue to develop policies that give workers flexibility in the devices they chose to use. How people connect and collaborate is changing as well; companies will need to foster collaboration on, and set policies for, social media in the enterprise.

Automation. Software agents, bots and intelligent machines will make tasks easier. Companies will need to consider how these new devices and applications can learn and apply user preferences, and how they can use real-time information in context to automate more tasks and decisions.

Enterprises can truly change the way employees work by providing a flexible, expansive workplace with the right technologies and policies. Those who come to grips with the new definition of the workplace and its enabling technologies will be the digital leaders of tomorrow.

Here’s how a digital core enables industry-wide digital transformation

Posted on 25/02/202015/06/2021 by Tushar

Companies in every industry are facing the challenge of evolving digital capabilities given their current operating models, resources, talent and culture. These elements are so intrinsic that any digital transformation not addressing them will ultimately fail because the legacy organization will inevitably exert a gravitational pull back to established practices, while agile competitors forge ahead. Some enterprises may be further along than others, but in most industries there are only a few companies that have made significant progress.

Becoming a digital enterprise is a complex and lengthy journey. It is much more than implementing predictive analytics or intuitive eCommerce experiences. Beyond product/service innovation, the journey demands attitude change in agility, experimentation, openness and transparency. However, for now let us focus on the digital core levers that CIOs and their teams can use to accelerate transformation –and how industries’ different use of digital enablers leads to different routes to digitilization.

Digital core enablers – technologies that realize digital transformation

As I explained in the first blog of this series, a digital core represents a set of loosely coupled cloud-enabled and SaaS business applications integrated with analytics and big data, on top of an elastic, yet resilient, data platform. A digitalized enterprise core enables a scalable, enterprise-wide digital strategy with the intent to accelerate business innovation through insight-based customer, partner and employee engagement. This transparency and automation drives optimization of business process and asset utilization, as well as employee productivity, and allows forays into new business models beyond the industry.

The digital core components accelerate the benefits of digital transformation by:

Enabling creation of engaging and effective customer, employee and partner “experiences,” leading to adaptable, collaborative transactions
Optimizing end-to-end business processes, even extending them beyond the enterprise to improve business efficiency and effectiveness
Innovating current business models that open potential for net-new revenue from products and/or services in unexplored market segments or via cross-industry collaboration and/or digital business platforms.

Digital core demands a hybrid transactional and analytics data platform

So, where should most enterprises start? While the hype about cloud-native, loosely coupled microservice applications is raging, there is a quiet revolution taking place enabling the sensible modernization of a business operational core. SAP, Oracle, Microsoft Dynamics, IBM, Workday, Salesforce and other vendors are increasingly offering “in-process,” hybrid transactional and analytical business applications based on optimized, ACID-compliant, columnar databases sharing one data platform. These merged platforms support data harmonization and application consolidation from a value stream perspective into one data store — with significant impact on TCO. In-process applications leveraging translytical data platforms or hybrid transaction/analytical processing (HTAP) accelerated by in-memory computing are disruptive. Companies can optimize business process execution by meshing many of the digital core enablers like real-time analytics (for example, planning, forecasting, outcome simulations and what-if analysis) in transactional execution, rather than performing them as separate activities after the fact.

Beyond this potential transition route to a digital core by consolidating applications into transanalytical data platforms, big data (Apache Hadoop) repositories can complement the reach of core applications by infusing additional external or sensor-based data to transition from manual to sense-and-respond, event-driven processes. As shown in the graphic below, these digital enablers may even “blur” the boundaries between industries, therefore enabling cross-sector collaboration.

Digital enablers disrupt industries and break down boundaries

Recent disruptive competitive moves by Amazon into transportation and financial services reinforced the importance of establishing a hybrid data platform that drives internal optimization and allows competitive moves into new services and products.

While different industrial sectors have a natural proximity to some of the digital enablers shown below, there is a rising consensus that the transparency and insight provided by richer data in analytical and big data repositories are the “fuel” of automation. Most of the technologies highlighted as disruptive in the graph below revolve around the utilities of artificial intelligence and machine learning.

Becoming digital – a maturity and context-based approach per industry

Recently, researchers from the McKinsey Global Institute (MGI) looked at the state of digitization in sectors across the United States and Europe and found significant gaps between many of them. Most digital companies see outsized growth in productivity and profit margins. But what are the key attributes of these digital leaders, and how can companies benchmark themselves against competitors? MGI’s digitization index encompasses (a) digitization of assets, including infrastructure, connected machines, data, and data platforms, (b) digitization of business operations, including processes, payment and business models, customer and supply chain interactions and (c) digitization of the workforce, including worker use of digital tools, digitally skilled workers and new digital jobs and roles.

The industry digitization dashboard below shows the digitization maturity scores. The IT technology sector comes out on top. Media, finance and professional services are right behind. Not surprisingly, these are some of the industries that currently invest in cognitive AI for operations and services, which in many ways demand a rapid modernization of their business operational cores.

No doubt the extent to which companies are digitizing their physical assets and supply chains and enabling their knowledge workers — that is, if they have smart buildings, connected vehicle fleets, big data or IoT systems and information at their employees’ fingertips – determines the performance they get out of equipment, systems, and business networks. However, different states of maturity with such enablers demand a varied approach by industry. For example:

A consumer-products company will benefit from focusing its data and automation efforts on establishing a synchronized supply network able to respond to events from their customers. The fourth recommendation above shows that digitization of the B2B channel through “intelligent shelves” will improve forecast accuracy and trade promotion efficiency and evolve from a make-to-stock model into a make-to-order product flow. That in return will demand a transition from forecasting to response planning and big data repositories that sense, categorize and act upon on-shelf shortages. Product and packaging fragmentation will further demand digitization of the heart of manufacturing.
Asset-intensive industries like utilities can leverage AI to drive improved matching of supply and demand, which needs to be done, literally, in real time. With the addition of smart metering sensors, utilities have been able to progress from forecasted to actual consumption billing, but more importantly, to increase accuracy of their short-term load forecasts in order to adjust supply to meet anticipated demand. This delivers substantial savings, reduces waste and emissions and adds further system resilience via predictive and preventive maintenance.
Service- and labor-intensive industries like retail need to improve their interactions with consumers by improving the omni-channel experience and empowering their employees towards higher productivity via mobile-enabled tools, while collecting and bargaining using the wealth of information on behavior and assortment. Efficient logistics, goods tagging and placement can be automated.

In summary, by understanding their digital maturity vis-à-vis their peers and even related industries, companies can streamline the deployment of a digital core, focusing on business model optimization or innovation while enhancing their business network experience. Easier deployment of digital enablers is one of the benefits of a modernized digital core. Advanced analytics, IoT, AI/ML, robotics, algorithmic operations and blockchain can transform how companies create and manage digital assets, accelerate supply-to-demand, facilitate digital experiences and empower digital workers towards higher productivity.

In my next blog post, I’ll write about how a digital business platform extends an enterprise’s digital core into the broader business network and allows for end-to-end value stream optimization of current operations.

Optimizing Agile delivery when the development team isn’t co-located

Posted on 24/02/202015/06/2021 by Tushar

Co-locating Agile development teams with the customer or business unit is optimal for collaboration and customer intimacy. However, co-location is not always feasible. Development team members could be from multiple geographic locations, the customer could also be spread across multiple locations, and economic considerations might direct some of the development to regions with lower costs.

This requires an effective Distributed Agile/Remote Agile Delivery model. Here are the four key considerations that need to be taken into account for a Distributed Agile Delivery model to ensure successful delivery:

1. Culture. If the teams are spread across multiple countries, cultural differences are bound to arise due to diverse work practices, values, processes, styles of leadership, decision-making, and problem-solving approaches. Not being able to work side-by-side can lead to misunderstandings from unrecognized cultural differences.

To mitigate, it is essential to build trust and establish relationships between the teams early on. Initiation events, where teams meet and work together, and establish common standards and consistent practices, present a great opportunity to establish trust and foster team building. Sending “Ambassadors” from each site to the others on a periodic basis is also an effective way to bridge the cultural gap.

2. Common hours and communications. Cultural and language differences make effective communications hard. Even with web- and video-conferencing, it is challenging to overcome the lack of visual cues and face-to-face interactions. This is further compounded by insufficient time zone overlap.

Teams need to work out an approach to shift some work hours to improve their time zone overlap. Often teams agree on “core hours” during which members at all locations will be simultaneously available. Reliable communication tools, desktop sharing, phone, instant messaging, and virtual rooms can then play a big role in establishing strong communications. Agile coaches and Scrum masters need to step up as effective coordinators. Bi-directional travel by key customer stakeholders and vendor leaders also helps.

3. Collaboration. Distance makes collaboration and frequent communication challenging. Context of discussions is sometimes lost as well. Using a “Proxy Product Owner” at each site can help bridge any gaps in business and domain knowledge. Building a work culture around compulsively using Enterprise Agile Planning Tools (EAPT) and collaboration tools facilitates collaboration among remote teams. The Ambassador program mentioned earlier — rotating some or all of the team between locations — and bringing the teams together on a periodic basis helps.

4. Consistent Infrastructure and Configuration Management. Challenges with Distributed Agile multiply if you do not have standard shared infrastructure and continuous integration. You need to leverage virtualization and provide identical environments for teams at all sites. Other strategies include using a single configuration management system for all teams, deploying DevOps (at least Continuous Integration and Continuous Testing), and insisting on frequent builds.

Ensuring that these four areas are addressed at project onset sets the collaborative tone for your distributed agile delivery. Having a collaborative team mindset from kick-off through delivery is crucial to project success.

Techniques and Tactics concerning Hybrid IT

Posted on 23/02/202015/06/2021 by Tushar

As companies embrace hybrid IT, they must address both technology and the human side of change. There are several key actions to take:

Staff and train differently: As applications move from traditional platforms to the cloud, current IT staff needs to be trained and re-skilled. Companies should recruit developers adept in Agile methodologies. Siloes should be broken down, and the workforce should become more integrated, multifunctional, flexible and agile.

Overhaul change management: The existing governance processes, gates and approval procedures designed for traditional legacy IT environments are no longer appropriate in a cloud environment. Companies need to revamp their change management systems to allow changes to happen quickly and, using automated workflows, to reduce manual intervention.

Integrate cloud operations: As organizations move workloads to the cloud, the IT operations function should adapt to manage both on-premises and cloud-based applications. This new model, called CloudOps, can provide continuous integrated operations in a multi-cloud environment to enable rapid response to events, incidents and requests. Adding DevOps to the mix then utilizes automation, integration and organizational change to enable more frequent enhancements that result in higher quality software.

Automate support: To the extent possible, automate IT support functions. For example, the traditional trouble ticket system can be manually intensive and inefficient. Automation can improve service and free up IT personnel for higher-level activities. Longer term, companies will be able to deploy machine learning and AI to take log data from cloud-based systems and automatically take actions to resolve and even prevent incidents.

Manage “shadow IT”: Business units are often acquiring the cloud services they need because IT moves too slowly. At some point, those services must be integrated back into the traditional IT environment for operational and security reasons through a services governance model that encompasses hybrid IT elements.

In addition, it’s important for CIOs to have a handle on what the enterprise is spending on IT services. The only way to accomplish this is to adopt hybrid IT and demonstrate to business units that IT can support the pace and scale that the business requires.

Most popular questions companies have regarding AI and ML

Posted on 22/02/202015/06/2021 by Tushar

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly evolving to help companies with both digital transformation and innovation. There has been a lot of hype and discussion about these topics, and, in a very short time, we have moved the conversation from “AI is cool” to “AI can drive specific business outcomes.”

Experience has allowed companies to clarify the economics of AI and reduce time to value. In addition, the technology has continually improved, with advancements including:

extracting unstructured data for improved insights and processes
moving from simple chatbots to more sophisticated conversational assistants that are smart, use more natural language interaction (text and/or voice), and enable the initiation of transactions
integrating operational and knowledge management systems

As our clients start to understand more about AI/ML, there are 2 key questions typically asked:

Question 1: “How do AI and Machine Learning differ from traditional programmed systems?”

There are three different capabilities that AI/ML typically extends and enhances into existing applications. One aspect is understanding – enabling systems to understand language, other unstructured data, including pictures, just like humans do. A second aspect is reasoning – enabling systems to grasp underlying concepts, form hypotheses, and infer and extract ideas, similar to humans. The third aspect is focused on learning – improving over time and avoiding repeated mistakes. These capabilities, often referred to as U-R-L (understand, reason, learn), are easily integrated into existing applications as consumable APIs, can reduce time to value.

Question 2: “Where is the value from Artificial Intelligence/Machine Learning?”

As we look across client environments, most clients are very comfortable with structured data that is within their firewall – things like transaction systems, customer records, and even predictive models. Many analysts estimate that 80% of data created today is unstructured, which requires clients to expand their current perspectives in 2 dimensions:

Structured to unstructured, such as documents, transcripts, social media, weather, images, IoT and sensor data, and news
Within the firewall to outside the firewall, including public data, licensed private data, and new types/sources being created every day

From a value perspective, the enticing aspect of AI and machine learning is connecting these structured and unstructured data types within and outside these walls. This enables richer, more, and unexpected insights, new business processes, and improved workflows at dramatically reduced cost levels.

As AI and machine learning mature, three use cases patterns have emerged around customer care, human capital management and the rethinking/reimagining of processes thanks to insights gained from unstructured data and natural language capabilities.

We’ll expand on these use cases and how we are applying AI/ML for our clients in our next blog post.

How DevOps’ is reaping the benefits of microservices!

Posted on 21/02/202015/06/2021 by Tushar

In the world of “one-up” IT, it seems like almost everyone is wanting to understand how to integrate microservices into their solution architecture. And rightly so. The benefits of using microservices are numerous and varied. Let’s examine some of these positives and consider if they can help you solve some of the problems that you are facing today.

Agile scalability

In a traditional Web application, you can author scaling rules such that when a certain request count is reached, additional instances of the entire Web application can be automatically spun up on newly (and dynamically) allocated Web servers. However, you do not have any control over which specific area of that Web application needs to be scaled. Do you need to scale the entire Web app, or just a part of it?

For instance, there could be a queued backup of HTTP requests waiting to post values into a payment system. Perhaps there is a rather extensive validation algorithm that needs to be processed before the payment can be finalized. This small yet often-accessed part of the Web app could thus become a bottleneck. In traditional scaling of a Web app, to scale up new Web servers would be dynamically provisioned, the entire Web app will be loaded onto those servers, and the process will continue.

A more efficient architecture design would be to scale up just the payment service on its own. Not only would that be quicker (since you are not provisioning new versions of the complete Web app), but it uses less resources (since you are only scaling a piece of the solution).

To further save in resources and time, add in a cloud provider to leverage its container technology to host microservices and other cloud services to help with innovation, scalability, provide resource optimization.

Focused development

The goal of “micro” service is to do one thing only but do it very well to meet the needs of the business. This typically means a small team, a finite and very focused development scope, and functionality to design and implement the microservice very well. Services should be “slim” and keenly targeted and no overlapping functionality with other supporting microservices. When this is accomplished, consumers of that service can thus focus on using that service and could care less about its implementation or how the microservice accomplishes its goals.

Keeping development focused at the microservice level gives teams the chance to experiment. It is very very easy for multiple versions of a microservice to co-exist for A/B testing. You can route certain percentages of requests to the different versions, assess /compare the results, and then make design decisions. This can be done multiple times per day if necessary. This ability to experiment is not possible with anything larger than a microservice.

When decomposing the monolith down to microservices, we are now free to implement each microservice in the most effective way. This may mean using a different version of Java or NodeJs than what the other microservices are using. Or you can go all the way in on polyglot development and allow teams to choose the specific technology (e.g. Java, .NET, Go, etc.) they want for their given service.

DevOps Integration

With all these independent teams developing non-overlapping and focused microservices, how to we integrate this all together into a viable solution? The DevOps model can serve as a facilitator. Both microservices and DevOps offer an agile model that is a key component of the microservices model. Well-designed microservices follow this model to assist in development, speed, and agility – yielding smaller and more frequent releases. Continuous Integration (CI) is all about integrating frequent releases and thus is a perfect platform for a microservices release model. This model encompasses shorter build, test, and deployment cycles that fuel the ability to quickly roll out new versions of a service.

Microservices bring additional productivity to DevOps by embracing a shared toolset, which can be used for both development and operations. That common toolset establishes shared terminology, as well as processes for requirements, dependencies, and problems. This encourages development and operations teams to work better with one another, allowing those entities to work jointly on a problem to successfully fix a build configuration or a build script.

DevOps and microservices work better when applied together. This is especially true when DevOps automation is added to the equation, ensuring you get the same process followed exactly each time through the CI/CD pipeline. Automation also cuts down significantly on the time to process the new code/build/test/deploy cycle.

Standardized Communication

Microservices communicate using common mechanisms, such as RPC (such as REST or SOAP), or messaging. This promotes easy interaction with them. With RPC, a service makes a synchronous request to another service, then waits for that called service to respond back. While it is a simpler programming model due to the logic of the caller continuing immediately upon return from the RPC call, it can also have blocking/waiting issues while calls are waiting to complete.

If asynchronous communication is required to avoid blocking calls, then messaging can be used. Here a message is “published” into a message broker. That broker takes the message and forwards it on towards “subscriber” receivers who have registered to be notified if this message is published. The publisher (calling code) can then return immediately after publishing the message to the broker and does not have to wait for the message to process.

Evolutionary Architecture

One of the big architectural benefits of microservices is how well microservices support the ability to implement an “evolutionary” architecture. This allows you to continually innovate and incrementally change without incurring any significant cost, risk and change to those services that are running on it.

The advantages of microservices

These are the primary positives of microservices. Together they form a very efficient and streamlined agile model for development. However, microservices are not a technology to blindly make everything better. There is overhead in developing them, and it is a more complex model in certain ways than a monolithic architecture. Due to this complexity, we must use the Agile development method, and DevOps automation.

AI and ML Advancement leading to new Application Emergement

Posted on 20/02/202017/06/2021 by Tushar

With most innovative technologies, at some point in the solution evolution there’s a tipping point from “this is cool” to “there are real business outcomes to gain.” We are now seeing that shift with artificial intelligence (AI) and machine learning (ML), especially in three major use case patterns:

1. Customer care

When it comes to customer care, many companies face a similar set of challenges: Customer service representatives (CSRs) typically need to view multiple windows on multiple screens to find answers to a caller’s questions. This results in calls taking a long time to handle, frustrated customers, lower CSR productivity and overall poor customer satisfaction.

AI and ML can help change these outcomes. One insurance customer implemented AI and ML to transform its contact center, which responds to approximately 5 million voice calls per year. It also introduced an intelligent voice agent to respond directly to 50-70% of all customer inquiries. The power of AI and ML extended and enhanced the customer experience and the productivity of CSRs, who are now able to deliver more accurate and consistent answers, at lower cost and greater speed. As a result, we have also seen reduced attrition, as the CSRs are happier in their roles and require less training time to become self-sufficient. Overall, by using AI and ML, the contact center is able to provide a high level of customer service, enhanced customer satisfaction and more efficient engagement.

In another example, a customer service center handling 60M service requests per year is implementing AI “smart chat” to transform customer service, drive better quality, improve consistency and lower costs.

The transformation of an operation as complex as a customer call center is a multi-step journey:

Organizing and visualizing the data required to support typical workflows is a critical early step and can include authenticating/validating the caller, providing easy access to the data from different back end systems, initiating transactions and closing out the call.
A second step adds natural language processing (NLP) to allow the CSR to ask more complex questions. NLP uses a trained ML model to determine the most likely answers from a collection of large, unstructured documents.
A third step includes self-service for external callers, using voice and natural language to respond directly to client inquiries without requiring interaction with a CSR.

While the steps themselves remain the same, the sequencing may vary to align to the specific outcomes the organization desires.

2. Human capital management

By applying cognitive capabilities to human resources, companies are able to transform their human capital management (HCM) processes.

One valuable use case improves the employee experience by leveraging intelligent natural language conversation services to integrate data in operational HR data systems, such as Workday, and in knowledge management systems that explain policies, procedures and guidelines. Benefits include improved employee engagement, higher productivity and lower costs.

Other potential HCM use cases that are ripe for AI and ML include recruiting, selection and on-boarding of candidates. AI and ML models are already being used to help analyze and match job descriptions and candidate resumes, and to recommend potential jobs for existing employees.

3. Process rethinking/reimagination

There are also multiple examples of leveraging AI and ML for rethinking and reimagining processes.

In one example, an insurance company reduced claim settlement time and costs by incorporating AI and ML to improve First Notice of Loss (FNOL) initiation and data collection, as well as claim classification/assignment processes.

Companies can improve the speed and accuracy of FNOL by enabling claimant self-service using natural language voice/chat to initiate a claim. They can integrate external data sources such as weather and employ a fraud scoring model to facilitate claim classification and corresponding assignment to the correct processing alternative. Processing alternatives can include:

Straight-through processing without human involvement
Sending appropriate claims to the legal department for potential early intervention to reduce lawsuits
Rejecting claims because the deductible is higher than the claim
Assigning claims to a human analyst/adjustor

Predictive modeling to triage injured worker claims has been developed and applied to help determine “return to work” outcomes, along with typical treatment plans for various types of injuries (NOT replacing doctors) and estimated treatment costs. This technique optimizes case manager resource assignment and helps injured workers get back to work, improving service quality and lowering costs.

Applying an ML model to extract information from unstructured documents and forms helps to provide insights from previously unanalyzed sources. This capability works by accelerating processing of information buried in those large unstructured documents and drives new insights, lowers costs and improves processing efficiency.

In a fourth example, Anteelo is automating the underwriting process for home inspection to lower costs and improve scalability and overall quality. This use case applies visual recognition to highlight details in home inspection photos and use those details to consult the underwriting guidelines and then augment the underwriting decision.

As you can see from these use cases, the ability to improve the customer experience and gain operational efficiencies through AI and ML are real and very achievable. What other use cases can you think of for your industry? I’d love to hear your thoughts!

Techniques of making Cloud Application Migrations simpler

Posted on 19/02/202015/06/2021 by Tushar

Many system integrators and cloud hosting providers claim to have their own unique process for cloud migrations. The reality is everyone’s migration process is just about the same, but that doesn’t mean they’re all created equal. What really matters is in the details of how the work gets done. Application transformation and migration requires skilled people, an understanding of your business and applications, deep experience in performing migrations, automated processes and specialized tools. Each of these capabilities can directly impact costs, timelines and ultimately the success of the migrations. Here are four ways to help ensure a fast and uneventful move:

1: Create a solid readiness roadmap.

The cloud readiness stage is often referred to as the business case and/or involve a total cost of ownership assessment, rapid discovery, advisory services, and more. However, most of these approaches fall short of the up-front analysis really needed to decide which applications to move, refactor or replace. When you embark on a migration to cloud, job one is to ensure you are ready to go. Diving right into a migration without a roadmap is typically a recipe for failure. If you don’t know what the business case is to migrate, then stop right there. You should come out of the readiness phase with a high-level plan and an initial set of migration sprints and a detailed roadmap on how to address the subsequent sprints.

2: Design a detailed migration plan.

This phase, also referred to as deep discovery, will help keep migration activities on schedule. All too often, lack of proper analysis and design leads to surprises in the migration phase that can have a domino effect across multiple applications. This phase should include a detailed analysis of the scope of applications and workloads to be migrated, sprint by sprint. This agile process shortens migration time and ensures faster time to value in the cloud. All unknowns are uncovered, and changes are incorporated in the roadmap to ensure anticipated business objectives will be achieved.

3: Set a strict cadence — and stick to it.

Often, most of the planning effort focuses on getting past that first migration sprint. This phase requires a great deal of planning and preparation across multiple stakeholders to keep the project on time and within budget. Scheduling all of the resources and tracking the tasks that lead up to D-day is no simple job. These activities must follow a standard cadence of planning steps to ensure effective and efficient migrations.

4: Automate as much of the migration as possible.

The way your organization performs the migration can also impact the project. In most cases, tools that automate the application transformation process, as well as the migration to cloud, can mean a huge savings in time and money. Unfortunately, there’s no off-the-shelf automation tool to ensure success. The migration phase requires people experienced in a range of tools and how to orchestrate the work.

One could argue that a fifth way to ease migration headaches is optimizing applications during the process. However, there are different schools of thought on whether to optimize applications and workloads before, during or after migration. I can’t say there is a definitive right or wrong answer, but most organizations prefer to optimize after migration. This allows for continuous tuning and optimization of the application moving forward.

It is important to note that steps in the migration process are not one-and-done activities. The best migration and transformation services are iterative and continuous.

You can’t determine readiness only once. The readiness plan needs to be reviewed on an ongoing basis. Don’t analyze and design migrations just once. Do it sprint by sprint, and plan each migration activity. Make sure you continuously collect and refresh data, refine and prioritize the backlog, and look for key lessons learned to ensure continuous improvement through the lifecycle of entire migration. Experience and planning can go a long way toward easing your next application migration.

Understanding the User Demographics of a Stock Trading App

Let’s move on to the investors’ age range now.

Why Should You Invest in Stock Trading App Development?

Best Share Trading Apps

Robinhood Stock Trading App

Stash Stock Trading App

E-Trade

Features That Make Up For a Successful Stock Trading App

1. The check-in process

2. User profile

3. Putting trades on stocks

4. Real-Time portfolios

5. Deposits

6. Search

7. Analytics

8. Push Notifications

9. Newsfeed

Key Points to Consider When Building a Stock Trading App

1. Have a plan to secure your application

2. Create a user-friendly interface

FAQs About Online Share Trading App Development

Q. Which is the best stock trading mobile app?

Q. How to use stock trading apps?

Best Apps That You Can Get Inspiration From

1. Netflix

2. Splitwise

3. Spring

4. Trello

5. Shine

6. Coursera

Mobile app UI Design Tips To Follow While Designing Your App

Keep It Simple

Make it Responsive

Use Popular Icons

Maintain Consistency

Follow Platform-Based Rules

Do not Forget about Loading Speed

Invest in Testing

Iterate Regularly

The State of UI in 2021: Technologies and Trends That Will Dominate the Industry

1. Conversational Interface

2. The Overlapping Effect

3. Typography

4. Voice-Powered Interfaces

5. Simple Curves and Geometry

6. Custom Illustration Interfaces

7. White space

8. Artificial Intelligence (AI)

9. Contrasting Font Color/Shapes

10. Animation

11. Opacity

12. Augmented Reality (AR)

13. Storytelling

14. 3D Graphics

15. Placement of Navigational Elements

16. Virtual Reality (VR)

Digital core enablers – technologies that realize digital transformation

Digital core demands a hybrid transactional and analytics data platform

Digital enablers disrupt industries and break down boundaries

Becoming digital – a maturity and context-based approach per industry

Question 1: “How do AI and Machine Learning differ from traditional programmed systems?”

Question 2: “Where is the value from Artificial Intelligence/Machine Learning?”

Agile scalability

Focused development

DevOps Integration

Standardized Communication

Evolutionary Architecture

The advantages of microservices

1. Customer care

2. Human capital management

3. Process rethinking/reimagination

1: Create a solid readiness roadmap.

2: Design a detailed migration plan.

3: Set a strict cadence — and stick to it.

4: Automate as much of the migration as possible.

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