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7 Important Points To Consider Before Developing A Mobile App

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Are you developing an application? Don’t you know what must be considered before starting?

Let’s start with an example – You have an idea to develop an application but you don’t know whether it actually will get good response from users or not. The first step is that your idea should be unique that has never been implemented previously.

Even if you develop an app that has never been developed, what is the guarantee that users will download and use? Even if they download what are the possibilities of using your app in a right way?

Don’t worry, here are the few strategies, if you follow these strategies before starting an app, you will surely succeeded.s01(5)(1)

Let’s take a look on strategies that should be considered:

1. Target
You should know who you are targeting. Suppose you are going to develop an application related to education then you should categorize education levels into different groups based on their ages and education level. So it is easy for the user to select right option in your app based on his/her education level. So know who you are targeting.

2. Speed
Your app should respond as quickly as possible. If it’s showing waiting or loading user will be irritated. No one wants slow apps. Suppose, user wants to check movie tickets availability and app is taking more time to show results, when your results are displayed finally, it shows all tickets are sold; because of time constraints what you will do? Obviously, next time you will go for other alternatives. So, speed should be considered important while developing an app.

3. Number of downloads
Always focus on developing something that can be used by almost everyone. You never want to create an app that has a limited usage to a specific class, rather focus on making it more public and something that is used by all. With that, also make sure you’re your app has that extraordinary feature that compels users to start using it, the moment they download it.

4. Include Social media
Connecting your app with social media has one biggest advantage, which might not be wise to avoid. If you integrate your developed app with social media such as Facebook, Twitter, or LinkedIn, then more social media users will know there is such an app that exists, leading to more downloads.infographic-mobile-app-design-its-the-rule-of-thumbs(1)

5. Competition
Your app should compete with other play store apps. So you should think about, how do you develop an app which is different from others and why users should download this. Suppose if you are developing an ecommerce application, try to automate some features like auto filling data, OTP entering etc. So that it would be easy for users would feel less trouble and will get a good impression of an app.

6. Make it simple and avoid loads of features
If you are planning to load your app with way too many features, then it is not a good idea. You don’t want a unique features that can turn out to be bad. You don’t want users to give feedback that it is “messy”, “too much to do”, “still discovering its features”, “didn’t understand the app completely even after a month of download” etc. Instead go with easy features or user friendly features, which would compel users to use your app.  Surely you want to see good reviews on the review page.

7. Add customizing feature
Users love customizing features. Adding a few customizable features will make your app more appealing in comparison to an app that cannot be customized. Users should be capable of getting everything they choose, even if it’s an app. In fact, a customizable app are more in demand.

Mantra Labs deep dives into latest trends and innovations in the Web, Mobile, Enterprise and Internet of Things space. The insights generated from these studies helps us provide more value for our clients.

Guest Blog by Ravi Teja – our rockstar Android developer.

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Will AI Be the Future’s Definition of Sustainable Manufacturing?

Governments worldwide are implementing strict energy and emission policies to drive sustainability and efficiency in industries:

  • China’s Dual Control Policy (since 2016) enforces strict limits on energy intensity and usage to regulate industrial consumption.
  • The EU’s Fit for 55 Package mandates industries to adopt circular economy practices and cut emissions by at least 55% by 2030.
  • Japan’s Green Growth Strategy incentivizes manufacturers to implement energy-efficient technologies through targeted tax benefits.
  • India’s Perform, Achieve, and Trade (PAT) Scheme encourages energy-intensive industries to improve efficiency, rewarding those who exceed targets with tradable energy-saving certificates.

These policies reflect a global push toward sustainability, urging industries to innovate, reduce carbon footprints, and embrace energy efficiency.

What’s driving the world to impose these mandates in manufacturing?

This is because the manufacturing industry is at a crossroads. With environmental concerns mounting, the sector faces some stark realities. Annually, it generates 9.2 billion tonnes of industrial waste—enough to fill 3.7 million Olympic-sized swimming pools or cover the entire city of Manhattan in a 340-foot layer of waste. Manufacturing also consumes 54% of the world’s energy resources, roughly equal to the total energy usage of India, Japan, and Germany combined. And with the sector contributing around 25% of global greenhouse gas emissions, it outpaces emissions from all passenger vehicles worldwide.

These regulations are ambitious and necessary. But here’s the question: Can industries meet these demands without sacrificing profitability?

Yes, sustainability initiatives are not a recent phenomenon. They have traditionally been driven by the emergence of smart technologies like the Internet of Things (IoT), which laid the groundwork for more efficient and responsible manufacturing practices.

Today, most enterprises are turning to AI in manufacturing to further drive efficiencies, lower costs while staying compliant with regulations. Here’s how AI-driven manufacturing is enhancing energy efficiency, waste reduction, and sustainable supply chain practices across the manufacturing landscape.

How Does AI Help in Building a Sustainable Future for Manufacturing?

1. Energy Efficiency

Energy consumption is a major contributor to manufacturing emissions. AI-powered systems help optimize energy usage by analyzing production data, monitoring equipment performance, and identifying inefficiencies.

  • Siemens has implemented AI in its manufacturing facilities to optimize energy usage in real-time. By analyzing historical data and predicting energy demand, Siemens reduced energy consumption by 10% across its plants. 
  • In China, manufacturers are leveraging AI-driven energy management platforms to comply with the Dual Control Policy. These systems forecast energy consumption patterns and recommend adjustments to stay within mandated limits.

Impact: AI-driven energy management systems not only reduce costs but also ensure compliance with stringent energy caps, proving that sustainability and profitability can go hand in hand.

2. Waste Reduction

Manufacturing waste is a double-edged sword—it pollutes the environment and represents inefficiencies in production. AI helps manufacturers minimize waste by enhancing production accuracy and enabling circular practices like recycling and reuse.

  • Procter & Gamble (P&G) uses AI-powered vision systems to detect defects in manufacturing lines, reducing waste caused by faulty products. This not only ensures higher quality but also significantly reduces raw material usage.
  • The European Union‘s circular economy mandates have inspired manufacturers in the steel and cement industries to adopt AI-driven waste recovery systems. For example, AI algorithms are used to identify recyclable materials from production waste streams, enabling closed-loop systems. 

Impact: AI helps companies cut down on waste while complying with mandates like the EU’s Fit for 55 package, making sustainability an operational advantage.

3. Sustainable Supply Chains

Supply chains in manufacturing are vast and complex, often contributing significantly to carbon footprints. AI-powered analytics enable manufacturers to monitor and optimize supply chain operations, from sourcing raw materials to final delivery.

  • Unilever uses AI to track and reduce the carbon emissions of its suppliers. By analyzing data across the supply chain, the company ensures that partners comply with sustainability standards, reducing overall emissions.
  • In Japan, automotive manufacturers are leveraging AI for supply chain optimization. AI algorithms optimize delivery routes and load capacities, cutting fuel usage and emissions while benefiting from tax incentives under Japan’s Green Growth Strategy.

Impact: By making supply chains more efficient, AI not only reduces emissions but also builds resilience, helping manufacturers adapt to global disruptions while staying sustainable.

4. Predictive Maintenance

Industrial machinery is a significant source of emissions and waste when it operates inefficiently or breaks down. AI-driven predictive maintenance ensures that equipment is operating at peak performance, reducing energy consumption and downtime.

  • General Electric (GE) uses AI-powered sensors to monitor the health of manufacturing equipment. These systems predict failures before they happen, allowing timely maintenance and reducing energy waste.
  • AI-enabled predictive tools are also being adopted under India’s PAT scheme, where energy-intensive industries leverage real-time equipment monitoring to enhance efficiency. (Source)

Impact: Predictive maintenance not only extends the lifespan of machinery but also ensures that energy-intensive equipment operates within sustainable parameters.

The Road Ahead

AI is no longer just a tool—it’s a critical partner in achieving sustainability. By addressing challenges in energy usage, waste management, and supply chain optimization, AI helps manufacturers not just comply with global mandates but thrive in a world increasingly focused on sustainability.

As countries continue to tighten regulations and push for decarbonization, manufacturers that embrace AI stand to gain a competitive edge while contributing to a cleaner, greener future.

Mantra Labs helps manufacturers achieve sustainable outcomes—driving efficiencies across the shop floor to operational excellence, lowering costs, and enabling them to hit ESG targets. By integrating AI-driven solutions, manufacturers can turn sustainability challenges into opportunities for innovation and growth, building a more resilient and responsible industry for the future.

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