Robotic Process Automation (RPA) technology has become increasingly popular in recent years, thanks to its ability to automate repetitive manual tasks across a range of business functions. RPA implementation, however, can be complex and requires a well-defined project management approach to ensure success. Software automation is the new normal in today’s business environment. It reduces time consumption and increases the productivity of enterprises. However, implementing an RPA in an already set organization or even a startup is not easy. Numerous stakeholders are involved, and many aspects need to be considered before diving into it.

A successful RPA implementation undoubtedly depends on the solution. However, it also depends on how the organization manages the changes that accompany the implementation and post-implementation phases. RPA change management involves managing the future of the company with respect to these three elements: process, organization, and people. We must fundamentally be prepared to redefine things in order to ensure synergy between these three. There are strategies and approaches that can be helpful in addressing the problems that arise when managing organizational transformation with RPA. Here are some best practices for managing an RPA project to achieve optimal results:

Have a clear plan

The first step is to define the goals and objectives of the RPA project clearly. These objectives must relate to specific business goals and metrics, such as cost reduction, process efficiency, and increased productivity. The project team should also consider how RPA will impact existing processes, employees, and roles. Defining the RPA roadmap for the organization is one of the most crucial steps. The plan should set short-term and long-term goals.

Create Solution Design Document

In RPA projects, the Solution Design Document (SDD) plays a crucial role by providing a comprehensive blueprint of the automation solution’s architecture and design. This document serves as a communication bridge among team members, ensuring everyone clearly understands the project’s structure and functionality.

The SDD becomes a valuable resource during troubleshooting, helping to pinpoint issues and identify areas for enhancement. As the project evolves, the SDD simplifies maintenance tasks, guiding developers in making updates or modifications to the RPA solution efficiently. In essence, the SDD is a cornerstone for effective collaboration, problem-solving, and project continuity in RPA development.

Assembling the right team

RPA implementation requires a team with cross-functional expertise. Team members must have a deep understanding of automation technology, and business processes, and the ability to collaborate effectively. Include process owners, IT staff, and business users with in-depth knowledge of the processes that will be automated. In order to ensure that it is perceived as a beneficial implementation, it is important to offer structured guidance to everyone who is associated with the project.
Providing appropriate training to all the associated employees helps create a bevy of digital workers in the organization. Ensure that you train everyone, right from the senior, managerial pool, right down to the junior employees. Effectively explain the need for RPA in the company, how and where it will make a difference to their responsibilities, and the potential benefits of implementing RPA.

Use reusable components

Reusable components are an important aspect of building efficient and effective RPA projects. Reusable components are pre-built software modules that can be easily integrated into an existing bot or process, reducing development time and improving overall performance.

Taking advantage of reusable components saves time, increases reusability and decreases maintenance costs. Well-built reusable components lead to increased collaboration, consistency, and standardization across RPA projects.
Examples of reusable components are the following: Log in and logout to the web portals, Data scraping, Sending and receiving emails, etc.

Regular monitoring and reporting

Regular monitoring and reporting of project progress is critical to ensure the project stays on track. To effectively monitor an RPA project, project managers should have a clear understanding of the project’s scope, timelines, and objectives. They should be aware of the specific workflows and processes being automated and the expected benefits of the project. Regular monitoring can involve tracking metrics such as cost savings, productivity gains, and error reduction. This may involve weekly or bi-weekly status updates, progress reports, or more frequent communications during critical project milestones. Reports should be concise, accurate, and easy to understand, providing relevant updates on the project’s progress and any issues or concerns that need attention.

Building an effective communication flow

Effective communication is crucial for the success of RPA projects. It helps everyone involved understand the project’s goals and requirements. Clear communication ensures that challenges are addressed promptly, keeping the project on track. It also allows for adjustments to changes in scope or timelines. Team collaboration is improved, making work more efficient and accountable. Transparent communication about potential risks helps in planning ahead to avoid issues. Reporting and documentation aid in accountability and knowledge transfer. Addressing end-user concerns ensures a smooth adoption of automated processes. Continuous feedback loops encourage ongoing improvements, making RPA initiatives more successful over time. In summary, a strong communication flow is essential for coordinating, managing risks, and improving RPA projects.

Build proper error handling

An efficient flow always contains error handling that makes the process execution trouble-free and easy-going at production and saves the execution from unknown error stoppages. The first step in building error handling in RPA project management is to identify potential errors. Once potential errors have been identified, prioritize them based on their severity and impact on the business process. This will help in determining the level of attention required for each error. Any new errors identified should be incorporated into the error management plan for continuous improvement. All errors and corresponding solutions should be documented for future reference and to avoid similar errors in the future. The RPA project management team can build a robust error-handling mechanism that minimizes the impact of errors on the RPA process and delivers optimal results for the business process.

Testing

Testing is a crucial aspect of RPA project management. The team should conduct extensive testing to ensure the software performs correctly and meets all the project requirements. Testing of RPA projects should include several levels and types of testing, such as unit testing, integration testing, system testing, and acceptance testing. That way we can achieve several benefits like cost effectiveness, improved quality, reduced risk, and faster deployment.

Successful RPA implementation

Implementing an RPA solution is a complicated and costly business. It is necessary to ensure that your business processes are as less affected during the implementation as possible. Proper project management is the key to successful RPA implementation. With the right planning, team, software, and testing, you can ensure that your RPA project delivers the intended benefits.

The Tech world is undergoing constant changes, and at the heart of these changes lie the remarkable works of Artificial Intelligence (AI) and Machine Learning (ML). Their impact on the rapidly evolving tech landscape is undeniable and unforgettable, as it drives innovations and advancements that were once unimaginable. These powerful technologies are shaping a future where possibilities are endless, making the fast-changing tech world a fascinating realm to explore.

AI and ML in Action: Real-World Applications

• Improving Customer Experience: AI and ML are being used to improve customer experience by analyzing customer behavior and preferences. For example, by using AI-powered chatbots, businesses can provide personalized support to customers 24/7. With ML algorithms, businesses can also analyze customer data to understand their behavior and preferences, and use that information to provide a more customized experience.

• Automation: AI and ML are being used to automate tasks and processes, freeing up time for workers to focus on higher-level tasks. For example, AI-powered robots can be used in manufacturing plants to automate repetitive tasks, while ML algorithms can be used to automate decision-making processes in finance and healthcare.

• Predictive Analytics: AI and ML are also being used to improve predictive analytics. With ML algorithms, businesses can analyze large datasets to identify patterns and relationships, and use that information to make predictions about future trends. This can be used in a variety of industries, including finance, healthcare, and retail.

• Personalization: AI and ML are being used to provide personalized experiences in a variety of areas, including e-commerce, advertising, and entertainment. By analyzing customer data, AI algorithms can recommend products and services based on their preferences, and ML algorithms can provide personalized recommendations for movies, music, books and many more.

• Improving Safety: AI and ML are being used to improve safety across industries such as transportation, manufacturing, healthcare etc. For example, AI-powered cameras and sensors can be used to detect potential safety hazards in the workplace, while ML algorithms can be used to predict and prevent medical conditions before they escalate.

AI and ML are revolutionizing the tech landscape. They enhance customer experience, automate tasks, predict trends, personalize content, and boost safety. Their impact is evident across industries, reshaping how we live, work, and engage with technology. As they advance, the future of tech holds even greater possibilities.

Another transformative aspect is task automation. Mundane and repetitive tasks that once consumed valuable time and resources can now be efficiently handled by AI and ML algorithms. This liberation from routine enables human resources to engage in more creative, strategic, and complex endeavors that drive innovation.

Moreover, AI and ML contribute to heightened safety and efficiency standards across industries. In sectors like manufacturing and transportation, AI-driven predictive maintenance ensures that equipment malfunctions are preemptively identified, minimizing downtime and enhancing workplace safety. This amalgamation of AI and ML reshapes not only the operational landscape but also the very fabric of our daily lives.

AI and ML: Shaping Industries, Redefining Future

• Automation and Efficiency: AI and ML are propelling rapid technological changes by driving automation and efficiency. Machine Learning algorithms, empowered by extensive data and master patterns are automating intricate tasks that were once time-consuming and prone to errors. Notably, AI-powered robotics in manufacturing execute precision tasks, accelerating production cycles and enhancing product quality.

• Personalized Experiences: AI and ML foster personalized experiences by analyzing user behavior for tailored content and recommendations. Entertainment platforms recommendations are based on viewing history, and e-commerce suggests products aligned with preferences, enhancing engagement and loyalty.

• Healthcare Revolution: The significance of AI and ML in healthcare is immense. These technologies are reshaping diagnostics and treatment, with ML models accurately detecting diseases from medical images. AI-driven chatbots provide initial medical guidance, while AI simulations aid in drug discovery, potentially revolutionizing treatment development.

• Financial Advancements: In finance, AI and ML fuel progress in fraud detection, algorithmic trading, and risk assessment. ML identifies anomalies in transactions for real-time fraud prevention, while AI-driven algorithmic trading makes rapid investment choices, reshaping finance through efficiency and risk reduction.

AI and ML’s synergy sparks transformative innovation across industries, their evolving impact set to intensify. From automation to healthcare revolution, these technologies drive rapid change. Embracing and staying updated with AI and ML is essential for thriving in this dynamic tech landscape.

Densen Puthussery, the author of this article, has been serving as a Senior Machine Learning engineer at Founding Minds, focusing on developing AI and ML platforms for the past few years.

Robotic Process Automation (RPA)

Robotic Process Automation (RPA) is a technology that automates repetitive, manual tasks using software robots, freeing up human employees to focus on higher value tasks.

RPA Implementation

Robotic process automation implementation allows businesses and organizations to automate different, often menial, mundane, and rule-based tasks across applications and systems that would otherwise fall under the scope of human responsibility. In short, RPA implementations aim to transfer process execution from humans to software bots. RPA implementation technology is a game-changer for businesses looking to improve efficiency and productivity while cutting costs.

By implementing RPA in an organization, you can streamline operations and free up your employees to focus on more important tasks.

Here is a guide to help you implement RPA in an organization:

• Identify the tasks that can be automated: Start by identifying the tasks that are repetitive, rule-based, and time-consuming. These are the tasks that can be automated with RPA. Create a list of these tasks and prioritize them based on their impact on an organization.

• Evaluate the potential benefits of RPA: Analyse the benefits that implementing RPA can bring to your organization, such as reducing processing time, improving accuracy, and freeing up human employees for higher-value tasks. You can also consider the ROI of implementing RPA.

• Choose the right RPA tool: Research and choose an RPA tool that suits your organization’s needs. Look for a tool that is easy to use, scalable, and can integrate with your existing systems.

• Develop a proof of concept: Before implementing RPA on a large scale, it’s best to start with a small project to test the waters. Develop a proof of concept by automating a single task and evaluate the results. This will help you understand the benefits and limitations of RPA and make any necessary adjustments.

• Choose the right team: Implementing RPA requires a team of experts who can design, develop, and deploy the automation. Choose a team with experience in RPA and the skills required to execute the project successfully.

• Train your employees: Once the RPA solution is deployed, it’s important to train your employees on how to use it. This will help them understand the benefits of automation and how it can improve their productivity.

• Develop an RPA strategy: Develop an RPA strategy that outlines the processes to be automated, the timelines for implementation, and the roles and responsibilities of the team members.

• Test and refine the automation: Once the RPA solution is developed, test it thoroughly to ensure that it meets the requirements and is error-free. Refine the solution as needed.

• Roll out the RPA solution: Roll out the RPA solution in a phased manner, starting with a pilot program before scaling up to the entire organization. Provide training to the employees who will be using the RPA solution.

• Monitor and evaluate: Once the RPA solution is in place, it’s important to monitor its performance and evaluate its impact on your organization. This will help you identify areas for improvement and make any necessary adjustments.

• Continuously improve the RPA solution: Keep refining and improving the RPA solution to maximize its benefits and ensure that it continues to meet the organization’s needs.

By following these steps, you can successfully implement RPA in your organization and enjoy its benefits.

• Boost Productivity
• Improve Efficiency to Generate Savings 
• Hit Accuracy Goals 
• Reliable Consistency
• Better Business Data Security 
• Produce Data for Important Analytics 
• Better Customer Service Experience
• Great Scalability

Return on Investment (ROI) is a project’s expected return in percentage terms. ROI is a critical tool for measuring the impact of your RPA investment with real data. With an understanding of your RPA initiative’s ROI, you can: Justify the initial investment to business leaders with data-driven evidence.

An investment in RPA can help companies optimize their processes, improve delivery of information, capture errors, alert users, and improve solutions that drive customer satisfaction.

Return on investment (ROI) in the form of both cost and time savings is expected to boost the RPA .

To calculate ROI: Subtracting the initial value of your investment from the final value of the investment. This is called the net return. You then divide the net return by the cost of the investment and multiply by 100.

Common Challenges in the RPA Implementation Process

Despite the many benefits of RPA, the implementation process can be challenging. It’s important to understand the challenges and prepare adequate strategies for dealing with each one.

Here are some of the key challenges businesses and organizations face during the RPA implementation process:

• Reluctance — Reluctance, or resistance to change, is one of the most common challenges associated with RPA implementation. Your employees might be hesitant to embrace new technologies, fearing that their jobs might be at risk. Therefore, it’s important to communicate the various benefits of RPA implementations to your employees and involve them in the implementation process to help them overcome their reluctance and resistance to change.

• Process Standardization — RPA implementations require the standardization of processes taking place within your organization’s operations to automate effectively. Without standardization, the RPA implementation can be both challenging and time-consuming. So, it’s a good idea to standardize your organization’s operational processes before implementing RPA technology.

• Technical Complexity — Depending on the architecture, the RPA implementation can be technically complex, requiring expertise in areas such as programming, data analysis, and system integration. This can prove challenging for organizations that lack technically proficient staff with the necessary technical skills. If you are worried about the technical complexity of implementation at your organization, it’s best to work with a reputable vendor and establish a Center of Excellence (COE) that can provide technical guidance.

• Change Management — RPA implementations often require and result in significant changes in the organization’s workflows, processes, and systems. This can be challenging for organizations that lack a structured approach to change management. It’s important to develop a change management plan that includes communication, training, and stakeholder engagement.

• Security and Compliance — RPA software bots often require access to sensitive data, which raises security and compliance concerns. To avoid potential legal issues, it’s crucial to establish adequate security protocols to protect the data and ensure compliance with industry standards.

• Scalability — Scalability of RPA implementations can be challenging, especially if your organization has many processes that need to be automated. Choosing an RPA solution that can be easily scaled is crucial, and establishing a process that would prioritize other automated processes is vital.

• Maintenance — RPA requires ongoing maintenance to ensure the technology continues operating efficiently. However, this can be challenging for organizations lacking the necessary resources. That’s why it’s important to establish a maintenance plan and work with a vendor that offers comprehensive maintenance and support.

Addressing these common challenges allows organizations to better prepare for RPA implementation and increase the likelihood of success.

RPA implementation can be challenging and complicated if it is done without proper planning and allocation of tools and resources. In the absence of these, the implementation of RPA can seem daunting and intricate. Therefore, having an RPA automation expert at your disposal can take off the burden from the organization. This also prevents failures and problematic anomalies. Moreover, you can study the RPA implementation examples to derive insight before implementing them.

Posted by Nikhil Jayan and Kathika.S.M

Multi-tasking is seen as a must-have skill in today’s fast-paced environment. In many cases, it has become a necessity rather than a choice. Increasingly though, it is being realized that human beings are incapable of true multitasking and even when we multitask, it is not productive.

Human multitasking

Multi-tasking is defined as the ability to do two or more things at the same time. There is concurrent multitasking, where two or more tasks are done at the same time. Alternatively, context switched multi-tasking involves switching between multiple unfinished tasks. We will talk about the science behind multitasking, the pitfalls and some thoughts on being effective at juggling tasks.

The Science of multitasking

Prefrontal Cortex is the task manager of the human brain. It is split into two hemispheres. Studies have shown that when human beings are dealing with one activity, the entire prefrontal cortex is dedicated to managing this task. When you add a second task, the prefrontal cortex dedicates one hemisphere to each task. Each hemisphere is now theoretically able to handle a task independent of the other. Add a third task and the brain starts to swap things around to accommodate the third task. Humans are imperfect machines and we start forgetting things as we switch between tasks, which leads to a significant increase in errors. (Multitasking splits the brain)

It would seem that with adequate training we could do two tasks effectively at the same time. This would be true if we had no other stimulus around us but these two tasks. In reality, though, there is a constant barrage of things ready to distract us from our two tasks. A door slamming, notification of a new email coming in are all stimuli that will need the attention of our brain to process consciously or subconsciously.

If we cannot do true multitasking, then we are left with the possibility of doing context switched multi-tasking. When we switch tasks, it puts a significant drain on one’s brain to catch up and to get refocused. This can be a few minutes for tactical tasks to over a half an hour for creative or strategic activities. It seems reasonable that humans can handle two or more tactical or repetitive tasks simultaneously, but it’s best to focus on one strategic activity at a time. It is ironic then that it is managers and leaders who have a more strategic focus that get called on to multitask more than staff members who typically are doing one assigned task!!!

Multitasking hurts

It is widely accepted that multitasking leads to lower productivity overall. This is not limited to slowing your activities, thereby reducing overall productivity. Studies have shown that your IQ drops when you multi-task significantly. You go through the motions of a task without thinking it through leading to lower quality outcomes.

There are health impacts as well. A study by the University of Sussex found that heavy multi-taskers have smaller gray matter density. This brain damage can have long lasting implications.

Multi-tasking also lowers your emotional intelligence. Social awareness, empathy, self-esteem etc. drop when you become more machine than a human trying to juggle multiple tasks without emotionally connecting with the activities. It also impacts the way you engage with people affecting relationships.

How to manage tasks more effectively

I would like to share a strategy I use to manage my work. I use a variation of the Eisenhower Matrix to organize my tasks.

I keep assigning tasks as they come into these quadrants. You can use any tool of your choice to model these.

Daily Planner

Every day in the morning, I pull down items from this list into my daily ToDo. I choose one or two tasks that are strategic and important, as well as several tasks that are tactical and urgent. I allocate time slots for the strategic items in my calendar, so I am not disturbed. During the day, I make several passes through the list ticking the tactical-important things off. These sometimes serve as a break for more heavy-lifting strategic activities and I get some satisfaction from striking off these lists. I limit any multitasking to tactical tasks.

There are any number of distractions to take you away from your task but there are some which I consider self inflicted. It is an easy escape when I get stuck or bored. This is especially true at the start of a heavy long activity and my brain needs to be forced to focus. For me, it is checking the news feed to catch up on recent world events. I do this without thinking and before I know it, I have lost time and focus. These can be habit forming and very hard to break.

When it is time to focus on my strategic tasks, I close the door to my office and I give my full attention to the task at hand. It takes time to get my juices flowing, but when it does, my productivity and creativity are at its peak. Often I am surprised by how quickly I am able to get a large task done when I am focused solely on it.

End of the day, I throw out my ToDo to start all over again the next day. It gives me both a sense of achievement and closure. Starting fresh has a more positive impact on me than incrementing the list for the next day. I use a physical spiral binder for my daily ToDo list and keep striking off items when done. At the end of the day, I tear and throw the daily ToDo in the bin.

I hope this gets you thinking about your own task management practices and helps you improve them. All of the above works within a framework of long term planning so you have your strategic and important items prioritized. I will talk about this more in a future blog.

Author: Regi Roy

With over twenty years of experience bringing innovative products to market, Regi Roy, as CEO, provides leadership to all activities at Founding Minds. Regi brings a wealth of expertise, having led large teams developing WordPerfect Suite at Corel, bootstrapping his medical imaging company and recently helping grow TITUS into a Deloitte Fast 500 company.

Agile project management has been all the rage lately because it’s super flexible and adaptable compared to old-school methods like Waterfall. The best part about Agile is how it puts customer satisfaction and value delivery front and center. Here at Founding Minds, we believe that Agile project management metrics are crucial – they help teams make sure they’re actually delivering value to customers and stakeholders while achieving success.

Agile KPIs vs. Traditional KPIs

Agile project management is gaining popularity due to its flexible and adaptable nature compared to traditional methods like Waterfall. Agile puts customer satisfaction and value delivery at the forefront, making Agile project management metrics crucial. These metrics ensure that teams are delivering value to customers and stakeholders while achieving their goals.

Traditional KPIs measure output, such as the number of tasks completed, while Agile KPIs measure outcomes like customer satisfaction and value delivery. Relying solely on output metrics can lead to poor decision-making and sacrificing quality for quantity.

Cycle and Lead Time

In Agile project management, there are these two KPIs that come from Lean process management called cycle time and lead time. Cycle time means the time it takes to finish one piece of work, from start to finish. On the other hand, lead time is how long it takes for a work item to go through the whole process, from the moment it enters the system until it’s finished. These metrics are pretty important because they can help teams figure out where there might be hold-ups in the process, predict how things will go in the future, and make decisions based on data.

Work In Progress (WIP)

Work in Progress (WIP) tells you how many tasks are in progress, and the goal is to keep that number low so that work gets done as fast as possible. Having too many unfinished tasks means wasted time and can lead to multitasking, which isn’t as effective. To keep things moving smoothly, Agile teams often use Kanban boards to visualize their WIP.

Throughput

Throughput is another Agile KPI that gives insight into the team’s capabilities, allowing teams to plan how much work can be delivered within a period of time. It is important to measure throughput regularly to ensure that the team is delivering value to customers and stakeholders consistently.

Visualizing These Metrics with a Cumulative Flow Diagram

The Cumulative Flow Diagram (CFD) is a graph that shows how stuff is flowing through a Kanban system. It’s really helpful for teams to see what’s going on with their Work in Progress (WIP), figure out what’s working well, and what needs to be improved. With the CFD, teams can see how many work items are coming in and going out over time, which helps them spot bottlenecks, predict how things will go in the future, and make smart decisions based on data.

Measuring Success in Agile Projects

Agile project management metrics are very important for measuring success in Agile projects. Instead of just counting how much stuff is done, Agile teams focus on making sure they’re delivering the most value to customers and stakeholders. It’s key to come up with fun and creative ways to track success using all the above indicators to set up projects for success. Check out these items to consider:

1. Quality over Quantity: Agile projects are often very fast and can be error-prone when rushing new features to production. Having a strict process and automation helps the team to keep on track. Project success should be measured by the quality of products, not the number of work items done. Founding Minds ensures that your products are measured by the quality of the application and the not quantity of products done in a specific time frame.
2. Time to market (TTM): How quickly can the project pivot to changing market conditions and customer needs? How soon are new features or fixes being released for production? Every step of the way, the metrics must be continuously evaluated as everything changes.
3. Customer/User happiness: Conduct regular feedback sessions or retrospectives with the team and clients. Make granular improvements in each sprint so everything is preserved along the way and the end product reflects a holistic process.
4. Value Additions: Is new value being added to the product over time? Ultimately, the qualities of a project and the client’s experience determine a project’s success. If, at every stage, opportunities for adding value are taken, the end product holds all the proof of excellence, which will be undeniable to the client.

Agile project management metrics are essential to ensuring that teams are delivering value to customers and stakeholders and achieving success. Agile KPIs focus on outcomes, which helps teams to avoid making poor decisions in project management.

At Founding Minds, we believe that agile project management metrics are the key to effective customer management and value creation. Our approach focuses on consistent monitoring of agile project management metrics as we develop products designed especially for your company’s needs.

Software development is constantly evolving in response to shifting customer demands. There is a need to have polished, easy-to-use, and well-rounded solutions rather than stereotypical business solutions that work but are hard to work with.

For software development teams, the product mindset has become an essential factor in recent years to achieve these goals. It involves taking a holistic, iterative approach to the product, looking beyond individual tasks and siloed working arrangements, in order to maximize its value and continuously enhance outcomes.

The Product-Oriented Mindset Explained

The product mindset is a way of thinking that focuses on creating products rather than project outputs. A product-oriented approach to software development prioritizes business needs, targets, and outcomes over timelines and estimates, such as those typically associated with a project-oriented approach. It also emphasizes the importance of looking at the product from a customer’s perspective, allowing teams to create products that truly meet their needs.
It encourages collaboration and communication between team members to identify opportunities for improvement, create products with greater value, and make changes that are beneficial to the product as a whole.

A CIO survey reveals that a whopping 95% of CIOs understand that their roles now extend beyond typical IT requirements, with customer experience at the forefront of their priorities. A product-friendly approach allows teams to similarly shift their focus to create a product meant to enhance the customer experience.

The Project-Oriented Mindset Explained

The project-oriented mindset focuses on individual tasks and working in silos. This approach can lead to inefficiencies and suboptimal results due to a lack of collaboration and communication between team members.

In the context of software development, the traditional project-oriented approach has the primary goal of developing software on time and within budget and scope. It usually follows the waterfall project management approach with well-defined project specifications and deliverables. Unfortunately, this approach can lead to business objectives and user needs being neglected in favor of meeting the budget, scope, and timeline.

Why a Product-Oriented Mindset Is Better

According to Gartner, a staggering 85% of organizations have embraced, or plan to embrace, the product-centric application delivery model due to its ability to enable fast delivery, digital business transformation, and the utilization of agile methods. Companies such as Slack, Apple, and Google are among the biggest advocates of this mindset, and they have reaped the benefits in the form of increased customer satisfaction and loyalty.

A product-oriented mindset focuses on creating value for customers by understanding their needs and delivering solutions that meet those needs effectively. According to Accenture, this mindset is achieved through a continuous process of collecting feedback and making improvements to the product, a process known as iterative feedback loops. Adopting this approach leads to a more agile product development process and significantly enhances the customer experience.

When it comes to building value, a product mindset is an approach that can deliver results multiple folds from the same effort. This is in contrast to a project mindset, which is focused on completing a specific task within a set timeframe. A product mindset is an ongoing concern with a visionary and long-term approach rather than being time-bound and tactical.

How the Product-Oriented Mindset Is Achieved

By keeping a product-oriented mindset at the forefront of the software development process, organizations can create products that are more valuable to customers and position them to succeed in a rapidly changing business environment. However, significant effort is required behind the scenes to make the product mindset rise above the service-oriented mindset or project-oriented mindset. Here are some key elements that help achieve the product-oriented mindset.

User First

If every action you take in the product build process is user-centric, you start to lay the foundations of a product-oriented approach to developing software. Notable questions a product-oriented team will ask are “How will the user use this?”, “Will the use be able to use this intuitively?”, “Will it take too long for the user to do an activity?”. The goal is to make the user happy while using the product, not just to meet the business requirement.

Everyone Has a Part

A product-oriented mindset has to be ingrained into every member of the team. It does not matter if you are a junior tester or a senior architect, everyone needs to think of the activities as leading to a product that human users will use and need to feel happy about. This drives a very different thinking process in terms of polish, intuitiveness, responsiveness, and accuracy. Regi Roy, the CEO of Founding Minds, says,

“A question I ask our teams occasionally is, If this feature were a part of GMail, how would the feature behave ?”.

That is the thought process teams need to have to achieve product outcomes.

Relentless Optimism

One key aspect of a product mindset is relentless optimism. Nothing is set in stone except for the quest for a viable product. This means that the team should always be testing their ideas, learning from them, and modifying or even pivoting them if necessary. A great example of this is Twitter, which started off as a podcast-accessing platform but eventually pivoted to become the leader in microblogging.

Evolve As You Go

A product mindset requires a willingness to take risks and readiness to fail. It is a long-term journey that involves experimenting and pivoting along the way. Building a product requires taking small steps and validating the thinking at every step rather than trying to tackle everything at once.

The Customer Is Not Always King(or Queen)

It is important to remember that the customer is not always king or queen. In many cases, customers do not necessarily know what the true problem is, let alone the right solution. A product builder or team must be bold enough to see opportunities beyond what the customer is talking about and envision a new future.

Believe In Your Instincts but Validate Them

When building a product, it is important to believe in your instincts but also validate them. Not all products have a market gap or problem statement; some create a market. A razor-sharp focus is key, building only to identify problems and just enough to solve them. The development team must avoid generalizing to the point that the problem cannot be solved and not expand into adjacent problems before the core problem is addressed.

Don’t Ask, Show

When approaching a new idea, it is better to show rather than ask. Customers are poor at articulating what they want, even when they are correct. When the team is able to show them something, the customers can provide them with valuable feedback. For this reason, the development team should try to capture mockups that bring the product to life, as this will increase the chances of getting useful feedback.

Be Practical

Finally, it is important to be practical. Software development teams should keep in mind that they are trying to build a product with the least amount of money to create market success. They should not be wasting resources on unnecessary complexity. Even when there is complexity, the goal should be to hide it away and give the customer a chance to use the product and see a benefit very quickly without having to configure and set up a lot of things.

Final Words

The product-oriented mindset has become a key differentiator for software development teams to consider in today’s highly competitive business environment. By incentivizing collaboration, communication, and innovation, this approach puts the customer at the center of the decision-making process. As a result, organizations can create products of greater value that are more differentiated from their competitors and have a greater chance of success.

Partnering with a software product development specialist is key to delivering good quality software products, and many traditional software services firms come up short. They are schooled in requirement analysis, estimation, and planning and delivery but miss the essence of creating products that thousands or millions will use. Founding Minds has helped incubate several new ventures since its inception in 2008. Over the years, we have built a culture of product mindset within our organization. Unlike traditional software service companies, we take time to understand the business our client is in and help build their products. It is a long-term journey, and we become partners, collaborators, and friends along the way.

If you have a product idea and are looking for a software development company to realize your dream, we at Founding Minds would love to hear from you. We offer a comprehensive package to help you build your software products. To learn more, read more about our Incubator-In-A-Box.

Leadership and management are two critical functions that help organizations achieve their goals. Although the two terms are often used interchangeably, they are very distinct. While leaders have people following them, managers have people working for them. At Founding Minds, we believe that anyone can be a leader and encourage our employees to step up. In this article, we’ll look at how a leadership culture can create better outcomes for customers, employees, and the organization.

Leadership and Management

Leadership is the ability to inspire and motivate people toward a common goal. Leaders possess a vision that they communicate to their followers and encourage them to work towards achieving it. They use their charisma, communication skills, and emotional intelligence to inspire and engage their team members. Leaders build and develop the culture which sets the guidelines for managers and the overall team.

On the other hand, management is the process of planning, organizing, and controlling resources to achieve a specific objective. Managers are responsible for setting goals, developing strategies, allocating resources, and ensuring that tasks are completed efficiently and effectively. They focus on the day-to-day operations of the organization and ensure that everything runs smoothly while looking to leadership to set the vision and nurture the movements.

Indicators of a Strong Leader

A strong leader has several indicators that distinguish them from others. They possess a clear vision of what they want to achieve and have the ability to communicate it effectively to their followers. They inspire and motivate their team members to work towards achieving the vision, and they lead by example. Regi Roy, CEO of Founding Minds, adds, “The company and its leadership must create the right circumstances for leaders to emerge. This requires an environment of openness and respect, a willingness to let people experiment without fear. Employees need to know they will be supported.”

Communication skills are also an essential quality of a strong leader. They are excellent communicators and can effectively convey their message to their team members. They are also good listeners and take feedback from their team members seriously.

Integrity and honesty are also critical qualities of a strong leader. They set high ethical standards for themselves and their team members and demonstrate transparency and fairness in their actions.

Indicators of a Strong Manager

A strong manager is someone who can effectively manage processes and resources to achieve a specific objective. Strong execution of a vision is another essential quality of a strong manager. They can take the vision set by the leader and turn it into actionable plans that can be implemented by the team members.

The ability to direct and anticipate needs is also critical for a manager. Leadership will set the expectations and create an ideal environment for communication and clarity, so managers can focus on providing the team with what they need to get the desired results.

Growing your leadership team

While leadership and management are two distinct functions, decision-makers need to combine the best of both worlds to achieve success. A strong leader needs to have a clear vision, communicate it effectively to their team members, and inspire and motivate them towards achieving it. A strong manager, on the other hand, needs to have excellent process management skills, execute the vision set by the leader, and provide the necessary resources to get the job done. One does not have to be a manager to become a leader. At Founding Minds, we believe that leadership culture has to be ingrained in the culture from the top management.

Roy adds here,

“It flows from the top. The CEO and top leadership should nurture the culture which produces strong leadership and great management.”

Creating a strong leadership culture requires a conscious effort. It has to flow from the top. The grounds are set by the leader of the organization so everyone knows it is ok to step up and they will be supported. It is critical to recognize even the simplest achievements. Regi adds, “It is relatively easy to build a habit of recognizing achievements. It is much harder to not ruin initiative by highlighting shortcomings”. Human nature is to undervalue achievements and overstate failures. We need to flip this on its head to create leaders and to be a good leader yourself.

Final Word

Leadership and management are both essential functions that help organizations achieve their goals. While the two are often used interchangeably, they have distinct differences. Leaders inspire and motivate their team members toward achieving a vision, while managers focus on the day-to-day operations of the organization. Combining the best of both worlds requires decision-makers to find a balance between these two functions.

“A leader should be transparent with their team members. Managers/Leaders at Founding Minds are willing to admit when things do not go according to plan and also take accountability, boosting the team’s morale. Here managers trust their team members to perform their duties effectively and delegate tasks accordingly. Clear guidance is provided while empowering team members to make decisions.”

– Sneha Pillai, Technical Lead

At Founding Minds, we encourage our people to find their balance in being leaders. Over the years, we have built a culture of continuously improving and working as individuals and teams within our organization. We encourage our team members to take the initiative and step into leadership roles by providing the environment to experiment with fear. We inculcate openness, respect and a non-hierarchical learning style that enables our members to become leaders.

Building modern web applications can be a tough job! It’s important to use a mix of different tools and frameworks to create something strong and scalable. Angular and ASP.NET Core are two powerful tools that lots of developers use to create cool web apps. At Founding Minds, we’ve used both of these tools in different projects and seen some amazing results! In this article, we’ll talk about the benefits of using Angular with ASP.NET Core and how this awesome combo can help developers create top-notch web applications.

Angular for Frontend

Angular is an awesome open-source JavaScript framework that is ideal for building powerful web applications with excellent performance. With Angular, developers have everything they need to build mobile and desktop applications quickly and efficiently. Angular has many great features, like two-way data binding, dependency injection, and modular architecture, making it easy to create scalable and maintainable code.

One of the coolest things about Angular is that it’s easy to learn, so developers can start building applications fast. Plus, Angular offers extensive documentation and tutorials to help developers get started quickly.

ASP.NET Core for Backend

ASP.NET Core is a web framework developed by Microsoft that lets developers create modern and cloud-based applications. This framework is perfect for building scalable and robust web applications that can handle a ton of requests. ASP.NET Core has a modular design, which means you can easily customize and extend it based on your project’s requirements.

One of the best things about using ASP.NET Core is that it’s open-source, which means it has a huge community of developers who contribute to its development. This makes it super easy to get help and support from others when you need it. Plus, ASP.NET Core offers simple upgrades and quick development release cycles, so you can stay up-to-date with the latest technologies without breaking a sweat.

Benefits of Combining Angular with ASP.NET Core

When it comes to building modern web applications, combining Angular with ASP.NET Core offers several benefits, including:

1. Faster Development: By combining these two powerful tools, developers can create applications quickly and easily. There are plenty of templates and open-source or paid libraries available for both frameworks that can help accelerate development.
2. Cost-effective Deployment: Deploying an application built using Angular and ASP.NET Core is cost-effective compared to other solutions. These tools offer easy deployment options that can help reduce costs associated with hosting and managing an application.
3. Easily Scalable: Both Angular and ASP.NET Core are designed to be scalable. This means that as your application grows, you can easily scale it to handle more requests without having to rewrite large portions of your code.

Example Use Cases

There are several example use cases for combining Angular with ASP.NET Core. Here are a few:

• E-commerce Websites: E-commerce websites require a lot of functionality, including user authentication, payment processing, and inventory management. By using Angular for the front-end and ASP.NET Core for the back-end, developers can create a powerful e-commerce website that can handle a large number of requests.

• Enterprise Applications: Enterprise applications require a lot of functionality and are often used by a large number of users. By combining Angular with ASP.NET Core, developers can create a scalable application that can handle a large number of requests and users.
• Social Networking Applications: Social networking applications require a lot of functionality, including user authentication, user-generated content, and real-time messaging. By using Angular for the front-end and ASP.NET Core for the back-end, developers can create a powerful social networking application that can handle a large number of requests.

Final Words

Combining Angular with ASP.NET Core offers a powerful solution for building modern web applications. With Angular’s rich set of features and ASP.NET Core’s scalable and modular architecture, developers can create robust and scalable web applications quickly and easily. If you’re looking to build a feature-rich web application, then consider Angular with ASP.NET Core.

“ASP Core and Angular have been invaluable tools for developing our financial applications. The seamless integration between the two technologies has allowed us to create a user-friendly and efficient system that meets the needs of our clients. With ASP Core’s robust back-end and Angular’s dynamic front-end, we have the power to deliver top-notch financial solutions to our customers. It’s truly exciting to see how these technologies are transforming the industry, and I feel privileged to be a part of it.”

– Jayan Mathew, Technical Lead, Founding Minds Software

At Founding Minds, we believe that the combination of Angular and ASP.NET core underscores the most effective way to design web applications. We are reliable and experienced product development partners for your cloud, mobile, web and enterprise applications. Our products cater to a variety of industries including financial, hospitality, mobile technology, financial intelligence, healthcare and so on.

When you’re thinking about managing a project, it can be tough to figure out whether to use the agile or waterfall methodology. At Founding Minds, we always make a decision based on the team makeup, expertise, and cultural fit of the project. There’s no one-size-fits-all solution – a project manager needs to understand the best use cases for each methodology and compare every aspect of the project before choosing the right approach.

Waterfall Methodology

Waterfall methodology is a linear and sequential approach to project management. It follows a structured process that includes planning, design, implementation, testing, and maintenance, and each phase must be completed before moving on to the next. This method works well for large-scale projects with well-defined requirements and stable teams, but if risk tolerance is low, it might be the way to go.

Agile Methodology

On the other hand, Agile methodology is an iterative and flexible approach that emphasizes collaboration, adaptability, and continuous feedback. It’s often used for complex projects that require innovation and collaboration, and it’s a good fit if the customer has subject matter expertise and time to spend with the team.

Strategic Understanding of Waterfall and Agile

Choosing between Agile and Waterfall depends on the specific needs of your project. Project managers must weigh each methodology against the team makeup, expertise, and culture of the project. Agile and Waterfall both have their own advantages and disadvantages, so it’s crucial to carefully consider each strategy before making a decision.

At Founding Minds, we know how important it is to create a leadership culture that reflects effective consideration of all stakeholders and how a Waterfall or Agile approach will shape the engagement and the end goals.

Here are some key points to compare Agile and Waterfall:

• Approach to Delivering Projects: 
  • Agile adopts an iterative methodology that involves short cycles of planning, execution, and review. It focuses on delivering smaller portions of the project incrementally, incorporating feedback from stakeholders and customers throughout the development process.
  • Waterfall follows a more linear and sequential approach, with each phase of the project completed in a specific order, emphasizing upfront planning and finalizing each phase before moving on to the next one.
• Flexibility and Adaptability:
  • Agile methodology allows development teams to adjust to changing requirements and circumstances. It focuses on continuous improvement, collaboration, and communication between team members.
  • Waterfall is less flexible and adaptable, making it more suitable for projects with well-defined requirements and predictable outcomes. This is because once a phase is completed, it is difficult and costly to revisit it.
• Customer/Stakeholder Feedback:
  • Agile methodology places a strong emphasis on incorporating feedback throughout the development process. This is achieved by delivering smaller, incremental pieces of the project, allowing development teams to make adjustments based on feedback received. The result is a more customer-centric approach to development that is likely to lead to higher levels of satisfaction.
  • Waterfall methodology does not prioritize feedback until the end of the project, which may result in customers feeling dissatisfied with the final outcome.

• Project Planning:
  • Agile methodology takes an iterative approach, with each cycle focusing on the next set of deliverables. While requirements and timelines are determined at the start of the project, they are subject to change throughout based on feedback from the customer and team input.
  • Waterfall methodology plans everything upfront, including all requirements, timelines, and budgets. Any changes to the plan are discouraged, and deviations may result in delays or cost overruns.
• Risk Management:
  • Agile methodology identifies and addresses risks continuously throughout the project, with contingency plans adjusted based on feedback and results from each iteration.
  • Waterfall risk management is done upfront during the planning phase, with all potential risks identified and contingency plans developed. Changes to the plan are discouraged, and deviations from the plan can result in delays or cost overruns.

Agile and Waterfall are two distinct project management methodologies that have their own strengths and weaknesses. Ultimately, choosing the right methodology depends on the specific needs of the project, and project managers should carefully evaluate the pros and cons of each approach before making a decision.

At Founding Minds, we understand that gaining a clear understanding of the project and available resources is essential before determining the best methodology to use. Rushing into decisions during the initial stages of a project can lead to failure. Praveen Ravi, Director at Founding Minds Software, states,

“An Agile mindset and a startup mindset are essential for creating successful products that satisfy customers. Agile enables teams to respond quickly to customer feedback and changing market needs, while a startup mindset fosters innovation and risk-taking to create unique products that exceed customer expectations and generate market success.”

A skilled project manager takes an informed approach to choosing the most suitable methodology. It’s crucial to recognize that a one-size-fits-all approach doesn’t always work, and the project manager needs to evaluate the information available to determine the most effective approach.