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Automated Monitoring of Foreign Exchange Rates using RPA

How to get real value from RPA using Microsoft Process Automation RPA Post Series This is the first in a series of posts summarizing case studies on Robotic Process Automation (RPA). These posts describe a growing number of Innovatix projects done recently to solve client problems as well as several to automate internal processes within our company. These are real-life case studies of RPA, the automation apps we have built and tested are now working as intended or are ready to move into production. We are doing this post series to show the varied nature of RPA apps, from ultra-simple to highly complex over a broad range of business processes. We hope readers will find parallels in their own business processes.  In writing these posts we are attempting to highlight 3 aspects of RPA. First, RPA apps are really critical in leading companies to full digital transformation; second, we want to show how easy and straightforward it is to build and implement RPA apps for many use cases; and third, we want to show how even simple business processes are worthy of automation if they consume a lot of repetitive employee time and especially if they can save employees from mundane tasks.  Robots are of course faster and more accurate than humans at data tasks. When robots do repetitive work then people have more time to do higher-value tasks that are more fulfilling and generate more business value. RPA is software that is programmed to mimic the work that people do. RPA automates rules-based tasks. A robot can log into apps, scrape data from websites or databases, almost any source of information, and can then process and assemble this data to create useful information. Robots can perform monotonous tasks like processing invoices all on their own (unattended). Other times, robots and humans can work together (attended). For example, robots can loop in a human counterpart to handle an exception or make a non-standard decision. Robots can squeeze hours of work into minutes. You can use robots to run reports at the end of a busy week where there are lots of clicking, copying, and pasting data to make it happen. Robots are also more accurate; this makes the compliance department happier too. Stated simply, our view is companies should be seeking out all such processes and building RPA apps to do that work. Gartner defines this view as hyper-automation, namely “the idea that anything that can be automated in an organization should be automated”. We hope this series of RPA case study posts will stimulate further interest among readers to move their companies in that direction. We are here to help. Case Study 1 This first case study involves automating a simple task done by the Finance team at Innovatix Technology Partner. The RPA app monitors and alerts our Finance Department of significant foreign exchange rate fluctuations between the US dollar and Indian and Pakistani rupees. This is important to Innovatix as we make regular funds transfers to our offshore development facilities in Pakistan and India, and we are always looking for the best short-term exchange rates for converting US dollars to either Indian rupees or Pakistani rupees. We automated this process using Microsoft Power Automate, our go-to automation tool[1]. The automation runs every 2 hours and checks current exchange rates and compares them with prior exchange rates[2], and if the current exchange rate is higher by a pre-set amount then the system automatically generates and sends an e-mail notification to a designated person in the Finance org. This automation helps saves human time several times each day looking up exchange rates and deciding if a rate jump meets the threshold. For this application, one of our data engineers (Talha Khan, lead author on this paper) at our international development facility in Pakistan built this exchange rate alerting tool using Microsoft Power Automate. Granted this is a very simple application, but the point we want to make here is using Microsoft Power Automate made it a very simple exercise indeed. Below we describe the steps Talha used to build and test this app and then to put it in production for use by our Finance Department. The entire process took less than a week of Talha’s time, and honestly if he was trying to just build this app, and not at the same time trying to absorb and learn as many other Power Automate capabilities as he can, he could have built this in less than a few days. Of course, this is a very simple process, and others of our case study posts describe much more complicated processes. But simple does not make it irrelevant, in fact it often means it is an obvious use case for automation. And as noted earlier we now hold the conviction that we need to automate anything and everything we can within our company or within our partner companies. The time is now, the technologies are ready. Steps in Building this App This application was built using Power Automate Desktop. There are six basic steps to the app. as follows: Power Automate Microsoft Power Automate is Innovatix’s go-to RPA implementation technology. Essentially all apps we have built to date have been built using Microsoft Power Automate. Power Automate is well rated by technology rating companies such as Gartner, and it is clear to us this platform will continue to advance quickly to the forefront of the field. Moreover, it is easy to use, and generally much cheaper than its competitors, especially for companies that are already Microsoft. We have a second series of papers coming on our website describing the major functions and capabilities of Microsoft Power Automate and how each comes into play in our RPA professional services practice. We hope by writing these posts, we can better communicate with our clients and potential clients how well equipped and ‘ready for action’ Power Automate is in allowing us and them to quickly, easily, and at low cost build a whole ensemble

Talha Khan March 25, 2024 No Comments

Agile vs. Waterfall: Choosing the Right Methodology for Your Information Technology Projects

In the rapidly evolving realm of Information Technology (IT) projects, the selection of an appropriate project management methodology holds paramount importance for achieving success. Here at Innovatix Technology partner, we use the methodology that best fits our customer needs. There are two prominent methodologies, Agile and Waterfall, which present distinctive approaches to project execution, each accompanied by its own set of merits and drawbacks. Familiarizing oneself with the disparities between Agile and Waterfall is indispensable for IT project managers aiming to make well-informed decisions regarding the methodology best suited to their project requisites. Agile Methodology: Flexibility and Adaptability Agile methodology embodies an iterative, incremental, and collaborative modus operandi in project management. Within Agile frameworks, projects are dissected into smaller increments or sprints, fostering close cooperation among cross-functional teams to deliver incremental value. Noteworthy features of Agile encompass: Flexibility: Agile accommodates change, allowing real-time adjustments throughout the project lifecycle in response to evolving requirements or feedback. Continuous Improvement: Routine retrospective meetings facilitate team reflection on processes, fostering continuous enhancements that bolster efficiency and effectiveness. Stakeholder Involvement: Agile advocates for active engagement of stakeholders throughout the project journey, ensuring their inputs are seamlessly integrated into the product development process. Agile proves particularly adept for IT projects characterized by intricate requirements, elevated uncertainty, and a requisite for expedited delivery. It empowers teams to promptly adapt to shifting market conditions and evolving customer needs, progressively delivering value with each iteration. Waterfall Methodology: Structure and Predictability Waterfall methodology adheres to a linear and sequential project management approach, whereby each project phase is meticulously executed before transitioning to the subsequent stage. Typically, these phases encompass requirements gathering, design, implementation, testing, deployment, and maintenance. Salient features of Waterfall include: Predictability: Waterfall furnishes a structured framework, endowing projects with predictability in terms of timelines, milestones, and deliverables. Documentation: Waterfall mandates comprehensive documentation at each project stage, ensuring clarity and fostering accountability throughout the project lifecycle. Stakeholder Engagement: While Waterfall may entail less frequent stakeholder involvement compared to Agile, it nevertheless allows for stakeholder input and feedback at pivotal milestones. Waterfall emerges as an optimal choice for IT projects characterized by well-defined requirements, minimal anticipated changes throughout the project lifecycle, and an emphasis on stability and predictability. Choosing the Right Methodology for Your IT Project When deliberating between Agile and Waterfall for an IT project, several factors warrant consideration: Project Requirements: Evaluate the level of uncertainty and volatility in project requirements. Agile proves well-suited for projects characterized by evolving requirements, whereas Waterfall aligns better with projects featuring stable and well-defined requisites. Team Dynamics: Factor in the size and composition of your project team. Agile necessitates close collaboration and self-organizing teams, whereas Waterfall may be more conducive to teams preferring structured delineation of roles and responsibilities. Customer Collaboration: Assess the extent of customer involvement and feedback required throughout the project. Agile facilitates regular customer collaboration and feedback, whereas Waterfall may involve less frequent customer engagement. Organizational Culture: Reflect on your organization’s culture and readiness to embrace Agile practices. Agile necessitates a cultural shift towards flexibility, adaptability, and a culture of continuous improvement, while Waterfall resonates more with traditional hierarchical structures. Conclusion In conclusion, the selection between Agile and Waterfall methodologies for IT projects hinges on various factors, including project requisites, team dynamics, customer collaboration, and organizational culture. Agile offers flexibility and adaptability conducive to dynamic projects with evolving requirements, whereas Waterfall furnishes structure and predictability ideal for projects boasting stable and well-defined requisites. Ultimately, project managers must meticulously evaluate these factors to discern the methodology aligning best with their project goals and aspirations, thereby ensuring successful project delivery within the ever-evolving landscape of Information Technology.

Effective Project Management Strategies for Offshore Resources

In today’s globalized economy, businesses are increasingly turning to offshore resources to execute projects efficiently and cost-effectively. Leveraging talent from around the globe offers numerous benefits, including access to specialized skills, scalability, and reduced operational costs. However, managing offshore teams comes with its unique set of challenges, from communication barriers to cultural differences. Implementing effective project management strategies ensures smooth sailing and successful project delivery. In this blog post, we’ll explore some key strategies for managing offshore resources effectively. In conclusion, effective project management of offshore resources requires a combination of clear communication, cultural sensitivity, defined roles, monitoring mechanisms, and investment in team building. By implementing these strategies, project managers can harness the full potential of international or distributed teams and achieve successful project outcomes in today’s increasingly interconnected world.

Talha Khan August 21, 2023 No Comments

Power Automate AI Builder and Scenarios

AI Builder: Pre-Built and Custom AI models Ready to Use within the Microsoft Power Automate Platform This blog is about AI Builder, as it is used within the Microsoft Power Automate tool. We describe what AI Builder is, its major capabilities, the different types of models it has built-in, and the different types of scenarios where AI Builder can be very useful in process automation. AI Builder brings the power of AI models (many pre-built) directly into your automation efforts without the need for coding or data science skills. This is another paper in our series on the Microsoft Power Automate toolset[1]. We are writing this continuing series of papers to cover all the major features and functionality of Power Automate. We are also writing a companion series of papers on real-life case studies using Power Automate. These are case studies describing how we have implemented Power Automate solutions for specific business process challenges of our clients or internal business process automation within Innovatix Technology Partners. We consider both series of papers as practical and hopefully learning guides. We are writing them to generate interest in this field and to provide down-to-earth information for our clients and potential clients on Power Automate. We strongly believe this tool is the best way forward for mid-sized businesses to achieve quick and meaningful process automation and to move forward on digital transformation. This is especially true if the company is already Microsoft-based. For those not familiar with Power Automate, it is a service that helps you create automated workflows between apps and data stores to synchronize files, get notifications, collect data, and many more such process automation. [2]  It fits within the technical scope of robotic process automation (RPA) and is highly rated compared to its RPA competitors. Overview of AI Builder? AI Builder, used in conjunction with Power Automate, provides AI models for optimizing and automating business processes. Many of the models are pre-designed and ready to use out of the box; others can be custom built/tuned within the tool itself to fit a company’s specific data and process needs. AI Builder allows Power Automate to automate process steps where an AI model is essential, for example, those requiring various forms of text analysis, vision and image detection, and predicting future outcomes. AI Builder brings the power of AI through a point-and-click experience, so you do not need coding or data science skills to access the power of AI. With AI Builder, you can build custom models tailored to your special needs or choose a prebuilt model that is ready to use for many common business scenarios. So, what kinds of things can you do with AI Builder and what kinds of business problems can it tackle. In fact, there are many things you can do with AI Builder for example: With AI Builder you can also refine AI models to your specific business needs. Available models for refinement include those listed below. We also describe a specific use case where the model would be very useful. Of course, there are countless other use cases for these models: Category Classification: This model can be used for a variety of use cases for example analyzing customer feedback for a hospital. In this case, this will free up the time of a hospital administrator from categorizing customer feedback, therefore leaving that person with more time to act on it and providing a better patient experience. This model extracts entities like color, person, city, country, etc. This type of model is helpful in multiple use cases, for example in a retail company with branches in multiple cities. They can use an entity extraction model to extract city entities from customer complaints data, and then route those complaints to a specific customer service center or designated person in the organization. This will help the retail company streamline its operations and save time. A form processing model can be used to extract specific and useful data from forms. This could include any type of form, such as a candidate validation form, and any type of text data within that form, such as candidate name, date of birth, etc. This model helps in recognizing and extracting things within images, and it can also count these objects within images. This is useful for example in a retail shop where there is a maximum number of people allowed in the shop at any given time. An object detection model can be trained to count the number of people in the shop, therefore, helping the retail shop in maintaining compliance. Prediction models help us predict future outcomes based on historical and current data. A well-cited use case for a prediction model is within a bank, where the prediction is whether or not a potential customer will default on a loan? In the Model Description section below, we give a more complete list of the types of models currently available in AI Builder. In the Business Scenarios section below, we go into more detail on the types of business scenarios where AI Builder is essential to automating a process. How to Use AI Builder This section describes at a high level the process you use to invoke an AI Model within Power Automate. Using AI Builder makes it easy thanks to its seamless integration with Power Automate and its intuitive UI. Adding AI intelligence to your business processes is simple! Referring to the user screen below, the five top-level tasks proceed from it as follows: Model Types in AI Builder Let’s look at the different model types that are available in AI Builder, and how they are classified. Later, we will look at common business scenarios and the model types that are suited to each of them. Please note that Microsoft is constantly adding new models to the mix, and upgrading existing models, so this list will change and expand with time. MODEL TYPES Model type Category Build type Category classification Text Prebuilt and Custom Entity extraction Text Prebuilt and Custom Key phrase