Modern day customers are used to getting things fast – fast internet, fast mobile devices, fast transportation etc. This changed their expectations as well. Customers now expect businesses to be expeditious when it comes to delivering products, services, and support. This is why many organizations adopt Agile.

Not all organizations manage to successfully implement and run an Agile ecosystem however. Nevertheless, the ones that are willing to adopt the methodology are granted a plethora of benefits in return that subsequently get the businesses a few steps closer to success.

That said, here are a few of those benefits organizations can get by adopting an Agile approach.

Faster time to market

Project teams are often put under pressure to get deliverables market-ready quickly. This is because the global economy is quite fast-paced not to mention competitive. Faster time to market is crucial for modern enterprises. Agile grants this benefit without compromising quality of the deliverables, provided it’s implemented properly with sufficient planning.

More room to innovate

Some organizations believe that technology is the main influencer on innovation. On the contrary, it’s people or the intellectual capital that influence how innovative an organization can be. A business lacking innovation would soon be outpaced by the competition. A more agile and nimble approach allows the business personnel to collaborate more effectively and bring innovative ideas into fruition without delaying the project.

Improved product quality

Customer experience is an important factor that directly ties into the success of a business. If the business can provide excellent customer experience along with quality products/services, they will gain the loyalty of their customers. Successful organizations often go out of their way to make sure their customers are happy. An agile business will be responsive enough to meet customer needs efficiently and deliver quality products/services to them on time which would impress them even more.

Boost employee morale

Keeping employee morale high should be a priority for business to maintain or even improve productivity. Increased productivity influences a business’ ability to enhance the quality of their deliverables. In an Agile environment, organizations give room for their employees to showcase their skills and innovate. Knowing that their efforts are being noticed and their contributions are being appreciated boosts the morale of employees which in turn boosts their loyalty and productivity.

Increased business efficiency and reduced risks

With Agile methodologies, business will have shorter release cycles and frequent deliveries for their products. This also enables them to ensure that quality of the final product is the best the team can achieve since each iteration of the project will be checked at every stage.

As the stakeholders will also be involved with the project along with a team, the risk of the team spending time on low priority activities is eliminated. In addition, the project will be accessing the market faster allowing the business to start generating revenue while the team keeps on improving the product.

Conclusion

There are even more benefits that an Agile ecosystem can provide an organization with. However, we thought these five required special mention. Agile project management is one great approach with which modern businesses can thrive in highly competitive and dynamic markets.

Agile is how we do our projects here at AOT. Talk to our experts to learn more about AOT’s Agile environment and its role in our punctual deliveries.

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There are risks associated with every kind of IT services including software development. These risks depend on various factors associated with the project – primarily its nature and intended purpose. The risks can be categorized based on their traits as well.

Many development companies adopt Agile methodologies to address or avoid some of these risks. But some risks are still prevalent even in Agile ecosystems due to various reasons that include process failures, unexpected changes, planning mistakes etc.

In this blog, we will explore a few types of software development risks in an Agile environment, starting with:

Budget risks

Budget risks are perhaps the most common as a project can go over budget due to a number of reasons. When developing software in an Agile environment, the team will have to proceed based on certain assumptions at some point till they get new information that disproves their assumptions. Naturally, as the product development progresses, there will be changes in goals or objectives. This approach may cause the project to exceed the budget.

To mitigate budget risks, it’s better to make product decisions when the decision-makers are in the best position to do so and not earlier. They don’t have to make a detailed plan at the beginning of the project either. The progression of the product will provide them with information to make actionable decisions that do not waste time and resources. A budgeting plan that complements this approach would further reduce budget risks.

Employee risks

A company always stands a risk of losing project team members while development is underway. This can potentially delay the project. The company should always be prepared for an absent project team member. A good approach to mitigating this risk is to co-locate the project team as squads. This way the team will be able to plan together, share knowledge, overcome obstacles, and complete code reviews. The development would be seamless without knowledge silos.

Productivity risks

These type of risks are common in projects with long-term goals and deadlines. The main cause for this risk is employees slacking off due to the lack of immediacy. This risk can be avoided if the Agile environment is centered on sprints to deliver demo versions of the software within a preset timeframe.

The sprints emphasize actionable goals to the team adding a sense of immediacy. Fostering a culture where completing sprints will be considered as a good achievement is also a great approach as it helps maintain development agility.

Time risks

These risks are the result of delays in development due to various factors such as poor planning, poor adaptability, impractical deadlines etc. Lack of flexibility in development processes is one of the more common causes of time risks.

It is up to the project managers to encourage and ensure flexibility in development so the team can adapt to changing requirements better. The team should also assess the project velocity periodically and employ an optimal time management strategy during development.

Conclusion

Software development companies with years of experience in software development are aware of the risks involved, and how they can be avoided without compromising the integrity of product development. Practices like sprints, co-location, sufficient planning etc. can help the team minimize risks considerably.

This blog also explains how AOT handles project risks. We have never failed our clients when it comes to product quality and timely delivery. Feel free to drop us a message to learn more about our skillsets and expertise.

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Are businesses getting to grip with Artificial Intelligence and Machine Learning?

AI and ML have been creating a lot of buzz in the tech realm for the last couple of years. However, many businesses still aren’t clear about the long-term benefits of these technologies.

According to a new report by Microsoft named ‘Maximizing the AI Opportunity’, nearly two-thirds of business leaders lack clarity when it comes to potential returns from artificial intelligence.

The report surveyed 1000 business leaders in the UK. It may seem surprising but there are a lot of companies out there that still consider AI as an unjustifiable expense with more limitations than benefits. Many industry experts point out that AI shows promise but adopting it in now in its present state may lead to unpleasant surprises.

That said, businesses that have invested in AI in return for something did see tangible benefits. Many organizations don’t even realize that they are using AI in some form. As a matter of fact, getting started with AI is rather simple really.

This blog includes a few best practices enterprises can follow to get started with AI in the right manner.

Identify business problems

Before investing in AI, an enterprise should make sure that they have identified and individually assessed each of their business problems. This way it will be easier for them to determine if a specific business problem can be solved efficiently with AI. The problem can be anything from handling a lot of online customer chats to freeing up employees’ time so they can focus on core tasks; AI can solve pretty much all of it.

Assess enterprise readiness to adopt AI/ML

Once the enterprise identifies the problems that they can solve using AI, the next step is to assess the enterprise itself for its readiness to build and manage AI or ML-based systems.

Major cloud service providers like Microsoft Azure and AWS offer on-demand ML services for a number of purposes including image processing and speech recognition. In addition, tools and ML-centric software frameworks are also available for the enterprise itself to build custom ML models or in-house AI-based systems. For any of these systems to work, data play a crucial role.

The main question to ask here is whether the enterprise generates and captures the right kind of data to train predictive ML models to deliver the right results. Even if it collects the right kind of data, there should be copious amounts of them for the AI system to process. Both quantity and quality of data matter when AI-based analytics is involved.

Assess in-house skills to handle AI

Before getting started with AI, enterprises should make sure they have the right talents to manage their AI systems. It’d be a wise approach to assess in-house skills to handle the AI project. This way the enterprise would also be able to identify missing skills that they will need in their mid to long-term run with AI systems.

Microsoft’s report also found that many business leaders are not sure as to how they can provide employees with the skills needed to adapt to and manage the disruption caused by AI. There’s also the fact that employee roles might change once AI starts doing its job. This requires the organization to put considerable effort into training employees when needed and retain sufficient skills for stable functioning of the AI ecosystem.

Experiment with AI

AI’s only started being of use to businesses. As such employees may be hesitant to engage with it. It’s up to the organization to foster a work culture where employees can experiment with the implemented AI systems. The employees can start small, get familiar with the technology, learn how it works, and then tinker with it to get an idea of what it can and can’t do. The company can gather feedback from them and scale up to leverage AI better.

Ensure ethical handling of AI

At the end of the day, data-driven AI/ML systems are only as good as the data fed to them. Invalid, biased, or wrong data will drive an ML algorithm to deliver useless results. Many companies make this mistake of feeding flawed data into the system leading to poor results and ROI.

All factors considered, it’s a great practice for a business to use an AI/ML manifesto to ensure that the technology is used ethically and securely. The manifesto should lay out specific guidelines to overseers and everyone else in the company using the AI-system.

Conclusion

AI and ML tech are at their infancy even now and demands diligent human oversight. The technology should be nurtured to deliver unbiased, responsible outcomes that can give businesses a great edge in the market and trigger disruption. If the company is ill-equipped to leverage AI but is willing to invest nevertheless, it’s better to seek service from an established AI expert.

That said, it’d be a pleasure for AOT to provide you with assistance when it comes to new-gen technologies like AI, ML, and IoT. Feel free to dial us up to learn more about AI for businesses.

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A while back, the Internet of Things created a lot of buzz with many technology experts deeming it as a revolutionary technology with massive potential to digitally transform enterprises. The hype encouraged many companies to jump on the IoT bandwagon and invest in the technology for a promising future. However, not all of those companies gained revenue from their IoT projects.

As a matter of fact, a recent Capgemini report revealed that less than 30% of organizations generate service revenue from their IoT projects.

If the organization is simply taking a leap of faith with IoT, chances are that their IoT efforts could end up being a cost center instead of a revenue generator. They will need a great IoT monetization strategy to make sure they are not losing more than they are making with the technology.

Here are a few tips to monetize IoT projects effectively.

IoT devices + value-added software

Instead of creating programmed IoT devices, many companies have started creating reprogrammable devices. The software for these devices can be updated over the air, which means the devices can be potentially programmed to do more things than what they were initially intended to do.

This strategy also makes it easier for the company to generate revenue. The devices can be built so that value-added software can be enabled in the field. The software can be sold or linked to the hardware for a price.

Leverage SaaS

Companies investing in IoT will have to connect their devices to some network using some kind of technology. Choosing what technology to go for in order to connect the devices won’t be easy. Many companies evaluate a number of platforms that can get this job done for various kinds of services including Microsoft Azure for Cloud, Jasper for connectivity etc. Many others take a safer approach of inventing their own combination – whatever works best for them.

But this isn’t always a great idea. Sure it’s a safer approach but this path requires even more investment from the firm. There’s no monetization opportunity here. We simply included this to warn companies not to resort to building tech that already exists in various popular platforms. Instead they should leverage Software-as-a-Service (SaaS) to quickly and consistently deploy and iterate without investing a lot.

Give room for third-party developers

Some companies go a mile further by giving third-party developers access to their ecosystem. Oftentimes this ends up as a great investment. Third-party developers can bring innovation into the mix – things the company’s in-house team may not have thought of, and add value around the company’s core products and services. The key is to make it easy and appealing for developers to innovate on your company’s IoT platform. Innovative platforms tend to competent and easier to monetize.

Join or create a marketplace

All that effort and innovation would be pointless if customers can’t find your company’s IoT products/services. The IoT products a business wants to sell – be it apps or connectivity platforms should be displayed at a marketplace where customers can find them. If they can’t find such marketplaces to join, they can create an automated, integrated and scalable marketplace themselves. This naturally leads to more revenue.

Optimize the monetization of assets

Companies investing in IoT projects normally don’t contemplate monetizing their investments on day one. But the growing IoT market eventually makes them think they should have thought about it in the beginning.

Software is one of the major factors that determine an IoT project’s success. So companies normally opt for a basic business model where they sell the software or give it away as a freemium product. In such cases, billing can be quite costly. Fulfilment and licensing won’t be automated as well. The company won’t be focusing on showcasing or promoting the software.

A better approach would be to move the services and software on to the cloud so customers can purchase and use them on-demand. As the value of the data generated by this software increases, the software itself will start to make more revenue. The company should make sure the billing models deployed are new and that the billing system is future-proofed.

Conclusion

If the company realizes the true value of their IoT project, they should be able to successfully and consistently create that value from the technology. But monetizing that value requires diligence and leadership in order to align the company’s goals with the service or product and their sales strategy. So either they are going to need highly qualified IoT veterans in-house at the top to successfully monetize projects or they need to team up with IoT experts.

If you’d like to explore the opportunities and benefits of an IoT partnership or develop an IoT mobile app, contact the experts at AOT today.

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The evolution of mobile phones into a must-have gadget in people’s day-to-day lives also established the dominance of mobile apps and the significance of data. With millions of mobile devices and mobile apps in circulation, massive amounts of data will be generated.

Determining useful data sets from data silos, and mining those data can help businesses uncover invaluable insights that would help them understand and serve customers better, and improve their decision-making. The same strategy is being used today to build cutting-edge mobile apps that are better than their predecessors.

Seems all too fine, doesn’t it? Here’s the catch.

The booming app market gives customers practically uncountable number of choices for apps that can perform a specific single task. This results in a great many apps running out of steam in the market and disappearing simply because they were outpaced by their competition.

To thrive in such harsh conditions, mobile app developers will need to leverage every advantage they can when building apps. It’s data that can give them such advantages. But where to start when you have an immense data pool?

This is where big data comes into the picture.

Investing in big data

With the right kind of tools and analytics strategy, big data can help developers build robust apps that serve customers better while offering a great user experience. Such apps most certainly score high in the market.

Still however the question persists whether big data is actually a big deal that it claims to be. This question is one of the reasons why some organizations are hesitant when it comes to investing in big data.

But the answer is quite obvious when you observe the matter with mobile apps.

For businesses, mobile apps serve as a powerful tool to connect with their customers via their personal mobile devices from anywhere. For the app to become successful, it should first satisfy its userbase in terms of features, functionality and experience. An app can achieve this in the best way possible with the insights hidden in the app’s user data. This user data will have intricate details on users’ behavior in the app.

Studying user behavior would in turn make it possible for businesses to understand user expectations, the problems they encounter when using the app etc. Rectifying the pain points will make an app seem a great option to the users, leading to them recommending the app to other users. This subsequently increases app downloads and the likelihood of success for the app.

Long story short, it is big data that can give businesses such game-changing insights. Here are a few other facts that make big data a big deal when it comes to mobile apps.

Big data helps with marketing apps

The app needs to turn some heads when it launches. So marketing is fundamental. Big data analytics can help app makers categorize market segments based on the market potential, identify audience expectations, and devise app marketing strategies accordingly.

Big data helps enhance user experience

User experience is a critical aspect that businesses should prioritize when developing mobile apps. Even if the app’s fully functional and efficiently serves its purpose, sporting an annoying UI could simply frustrate its users to a point where they will actively seek a replacement with a better UI and UX.

Big data analytics in real-time combined with powerful machine learning algorithms can give app makers a comprehensive overview of user behavior highlighting common usage patterns. This allows developers to determine what their next course of action should be in order to improve the app’s user experience and add more value to it.

Big data helps scale up app revenue

Even if the app scores high on all fronts including UX, interface, features, and functionality, it may not generate expected revenue if it lacks a proper engagement strategy. The app makers should know how to engage their target audience and keep them engaged while enticing them to make purchases.

With a pool of big data about user behavior which includes their likes, dislikes, location, expectations, purchase history etc. app makers can determine what type of push notifications should be sent to a specific set of users for conversion. This also helps them devise a good engagement strategy which can subsequently scale up the revenue generated by the app.

Conclusion

Everything points to the fact that big data will have a crucial role in the future of digital technology; particularly mobile app development. Big data, at present, is being widely used by app makers to increase app visibility, traffic, and revenue. Organizations across the globe preparing to adopt big data emphasizes the fact that big data really is a worthy investment when it comes to mobile app development.

The experts here at AOT can help your business use an app that wields big data technology effectively to dominate your target market. Contact us today to for a clearer overview of big data and its benefits.

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