In today’s fast-evolving digital landscape, mid-market businesses require a scalable, AI-powered, and automation-driven CRM to stay competitive. Salesforce provides the technology, but choosing the right implementation partner is crucial for success.   

DynPro is a preferred Salesforce advisory and implementation partner, offering deep expertise, seamless deployment, and ongoing support to maximize business impact.  

Why Choose DynPro for Salesforce Implementation? 

DynPro brings 25+ years of experience in implementing and optimizing Salesforce Sales Cloud, Service Cloud, Marketing Cloud, Data Cloud, and Einstein AI for mid-market businesses. Our certified Salesforce consultants tailor solutions that align with your unique business needs, ensuring a faster time-to-value.

DynPro’s Unique Approach to Salesforce Implementation 

1. Strategic Implementation That Goes Beyond Setup 

Many partners implement Salesforce, but DynPro ensures a tailored transformation by aligning technology with business goals. Our process includes:  

• Deep-Dive Business Analysis – We assess your existing processes, identify gaps, and define an AI-powered Salesforce strategy that drives measurable ROI.  

• Customized AI & Automation Workflows – Unlike basic implementations, we integrate Einstein AI, predictive analytics, and process automation to help businesses work smarter.  

• Seamless Integrations Across Systems – We connect Salesforce with ERP, BI tools, marketing automation, and third-party applications for a unified ecosystem.  

 2. AI-Driven Customer Engagement & Sales Optimization  

Most Salesforce partners implement standard CRM functionalities, but DynPro specializes in advanced AI-powered capabilities that transform customer engagement. We leverage:  

• Einstein AI & Generative AI – Automate lead scoring, customer segmentation, and personalized interactions.  

• Predictive Sales & Marketing Analytics – Provide real-time insights to improve decision-making and conversion rates.  
• AI-Powered Forecasting & Sales Intelligence – Enable data-driven sales strategies with Einstein Sales Insights.  

3. Cloud-Native Scalability with Hyperforce & Multi-Cloud Expertise 

Many mid-market businesses struggle with scalability and compliance. DynPro ensures a future-proof Salesforce implementation by leveraging:  

• Salesforce Hyperforce – We deploy on a secure, high-performance cloud infrastructure for seamless growth.  

• Multi-Cloud Integration – Our expertise extends across Sales, Service, Marketing, and Data Cloud, ensuring connected experiences.  

• Security & Compliance Best Practices – We integrate Salesforce Shield, Trust Layer, and advanced data protection for regulatory compliance across industries.  

  4. Customization That Goes Beyond Out-of-the-Box Solutions 

Unlike generic implementations, DynPro builds industry-specific solutions that address unique challenges. Our approach includes:  

• Development & Automation – Custom workflows, AI-driven chatbots, and tailored automation with Salesforce Flow & RPA.

• Advanced Data Cloud & CDP Utilization – Unify fragmented data for a 360-degree customer view.

• Seamless Data Migration & Optimization – Ensuring zero downtime transitions from legacy systems to Salesforce.  

  5. Ongoing Support & Managed Services for Continuous Growth 

Many partners focus only on the initial setup, but DynPro provides continuous guidance and support to ensure long-term success. Our services include:  

• 24/7 Proactive Monitoring & Support – Dedicated teams for system performance, troubleshooting, and enhancements.  

• Salesforce Adoption & User Training – Custom training programs to help teams leverage new AI capabilities.  

• Scalable Managed Services – Enabling businesses to adapt to changing market needs without disruption.  

Future-Proof Your Business with a trusted IT solution provider   

Salesforce is the world’s leading AI-powered CRM, but its success relies on proper implementation and optimization. DynPro offers the expertise, AI-driven innovation, and continuous support needed to help you get the most of your Salesforce investment.   

Ready to transform your business with AI-powered Salesforce solutions? Choose DynPro as your trusted partner and accelerate your digital transformation today.  

Reach us for consultation at https://dynpro.com/contact-us/ 

Public sector organizations face challenges in delivering efficient and transparent services to citizens while managing complex operations and regulatory requirements. Traditional methods often result in fragmented data management, inefficient processes, and limited citizen engagement. There is a critical need for a unified platform that can streamline operations, improve service delivery, and enhance citizen interaction and satisfaction.

Now, let’s explore how Salesforce addresses these challenges with its technical solutions tailored for the public sector.

Let’s delve into aspects of how Salesforce can be applied in the public sector:

1. Case Management: 

Salesforce Service Cloud provides robust case management functionalities. Public sector organizations can create customized workflows to handle citizen inquiries, service requests, and complaints efficiently. automated routing, escalation rules, and knowledge base integration ensure timely resolution and consistency in service delivery.

2. Constituent Relationship Management (CRM): 

Salesforce’s CRM capabilities extend to managing relationships with citizens. Using Salesforce CRM, public sector organizations can maintain a 360-degree view of interactions, preferences, and feedback from constituents. This data helps in personalizing services, improving engagement, and tailoring communications.

3. Service Delivery Automation:

Salesforce allows Public sector organizations to automate routine processes such as permit applications, licensing, and registration. Custom applications built on the Salesforce Platform streamline these workflows, reducing manual effort and improving turnaround times for citizen services.

4. Public Health Management: 

Salesforce Health Cloud enables public sector organizations to manage public health initiatives effectively. It centralizes health data, supports case management for diseases, and facilitates vaccination programs. Integration with external systems allows for real-time data exchange and analytics to track health trends and respond proactively to public health crises.

5. Emergency Management:

Salesforce can be configured for emergency response and preparedness. Public sector organizations use Salesforce’s custom objects and workflows to coordinate resources, track incidents, and communicate with stakeholders during emergencies. Mobile accessibility ensures field personnel can access critical information in real-time.

6. Policy and Program Management:

Salesforce Government Cloud supports program management by tracking policies, initiatives, and outcomes. Customizable dashboards and reports provide insights into program effectiveness, budget utilization, and compliance with regulatory requirements.

7. Data Management and Analytics:

Salesforce provides robust data management capabilities through its platform. Public sector organizations can integrate data from multiple sources into Salesforce, ensuring a single source of truth for decision-making. Salesforce Analytics Cloud enables visualization of data trends, predictive analytics, and forecasting to optimize resource allocation and service planning.

8. Community Engagement:

Salesforce Community Cloud enables public sector organizations to create online communities for citizen engagement. Communities facilitate two-way communication, feedback collection, and collaboration on public initiatives. Customizable portals ensure citizens have easy access to information, services, and support.

9. Financial Management:

Salesforce Financial Services Cloud or custom applications built on Salesforce Platform can manage budget planning, financial tracking, and grants management. Workflow automation ensures transparency in financial operations, compliance with fiscal regulations, and efficient allocation of funds.

10. Collaboration and Communication:

Salesforce Chatter and collaboration tools facilitate internal communication among government agencies and departments. Integration with email, calendar systems, and document management platforms ensures seamless information sharing and teamwork.

In summary, Salesforce offers a versatile and scalable platform for digital transformation in the public sector. At DynPro & Cloudalyze, we offer Salesforce’s customizable features, robust security standards, and integration capabilities that empower public sector organizations to deliver efficient citizen services, enhance transparency, and make data-driven decisions to meet the evolving needs of their communities.

Is most of your time taken up by gathering mountains of tax data?

The tax department spends more than 50% of its time gathering tax data, but less than 30% on strategic tax analysis.

Streamline your Tax process with Alteryx. Discover the benefits below,

1. Data Integration and Cleansing:

Alteryx allows tax professionals to easily integrate data from multiple sources, such as financial systems, ERP systems, and spreadsheets. It provides tools for data cleansing, transformation, and normalization, enabling tax teams to work with clean and accurate data for tax calculations and reporting.

2. Automation of Manual Processes:

Alteryx’s workflow automation capabilities can significantly streamline tax processes. It allows tax professionals to automate repetitive tasks, such as data entry, data validation, and report generation. By automating these tasks, tax teams can save time and reduce the risk of errors.

3. Tax Planning and Forecasting:

Alteryx provides powerful analytics and modelling capabilities that can be leveraged for tax planning and forecasting. It allows tax professionals to analyse historical tax data, perform what-if scenarios, and make informed decisions based on the results. This can be particularly useful for tax planning strategies and estimating tax liabilities.

4. Data Visualization and Reporting:

Alteryx offers data visualization tools that enable tax professionals to create interactive and dynamic dashboards and reports. These visualizations can help in presenting tax data in a clear and meaningful way, making it easier to communicate insights and findings to stakeholders, such as management or regulatory authorities.

5. Compliance and Regulatory Reporting:

Alteryx can assist tax teams in ensuring compliance with tax regulations and preparing accurate tax reports. It provides functionalities to perform tax calculations, apply tax rules, and generate tax forms or filings. Additionally, Alteryx’s ability to integrate with other tax software or systems can facilitate seamless data exchange and enhance compliance processes.

6. Scalability and Flexibility:

Alteryx is designed to handle large volumes of data and can scale to meet the needs of growing tax departments. Its flexible architecture allows tax professionals to adapt and customize workflows according to specific tax requirements or changes in tax regulations.

DynPro has been providing efficient solutions to clients across various domains to help automate processes in order to reach desired revenue target.

As many businesses have learned over the past two years, managing teams outside of an office requires a different approach. You must connect the various distant experiences among your team members in addition to attempting to humanize video conversations and maintain visibility of all team activities. It is crucial to maintain an emphasis on each individual’s workload, work/life balance, engagement, performance, and experience to reach this goal. The question is, how do you go about it?

Our customers have also navigated to hybrid philosophy and are getting bullish on remote working. To meet the exact needs of our customers, DynPro aligned its resources. We have consultants all over the country.

As an organization with a large geographic spread, here are some ways we can engage with our national workforce:

1. Engaging regularly: DynPro works hard to ensure our employees feel like they are part of our company. We utilize Microsoft Teams to chat and have video calls to check in and keep them in the loop. We also created industry teams to bring together our consultants who work on similar projects to get to know one another better.
2. Electronic onboarding of new hires: Since we are a tech company, we must utilize technology to make onboarding more efficient. Before our employees begin work, our electronic system helps us gather necessary documents and set them up for success! We also host weekly onboarding meet-up calls and get a good orientation for them as they start on their projects. All employees of the company, regardless of the length of service or recent hires, are welcome to contact HR with questions.
3. Quarterly Communications: Using our Ignite quarterly newsletter, DynPro communicates exciting information with our team about forthcoming events, news, and initiatives. Here we also share wins, client success testimonials, anniversaries and birthdays, and philanthropic events.

Remote working is the future of the modern workplace, and the sooner organizations prepare for it, the better. Employee motivation has always played a key role during such transitions and will continue to be vital for team productivity as you migrate and enhance your remote work setup.

It is important to remember that motivating a team never happens overnight in a new type of office environment. It is a long-term investment requiring consistency from you and your management team.

The organizations must implement and drive their automation initiatives using an agile approach to address the challenges of scaling Robotic Process Automation (RPA). It leads to better governance, a more fluid ability to scale, efficiency, and vastly reduced costs by mitigating risk and rework.

To better understand this, consider the following scenario:

A company wants to eliminate manual, repetitive work! It decides to implement Robotic Process Automation (RPA) to automate mundane and repetitive tasks and boost employee productivity. It installs the automation software and holds design sessions to identify potential candidates for automation. For development to begin, process documents are created and approved. A developer completely automates the chosen process. This development time is estimated to be 6-8 weeks for a finished product. End-users test the final product three months after the first session.

Then the bugs or errors begin to appear! The automated process immediately encounters the first set of problems. An employee forgot to mention a workaround for non-US vendors in the process, an IT resource was unaware the process is utilizing employee credentials to login and operate business applications, and the business analyst reports the GUI layout between the production and test environments is slightly different.

The long and unexpected debugging journey begins. The process gets repeated until refined. It may result in project delays, which affects both cost and productivity.

Now, let’s discuss the Agile approach to RPA Implementation.

A company purchased RPA licenses. It expects RPA to fill fundamental gaps in its business structure and systems. How should the automation program be implemented? They decide to use an Agile project management framework.

The Agile framework has the following stages:

Sprint discovery: The company holds a workshop to collect the automation backlog and requirements for inclusion in a Process Definition Document (PDD). The automation backlog is defined with specific needs and advanced to the build stage, including quick and scalable foundations for RPA gain. The whole process is divided into sprints. The sprints are governed by the process functionality and delivered with a human-in-the-loop component.

Sprint refinement: A small team re-evaluates and rewrites backlog items during a sprint. They refine exception criteria for development, escalate issues, remove roadblocks, highlight potential workarounds, motivate the team, and assign story points to the process. The development process and sprint deliverables include input from end-users. Observations and requests are documented at the end of each sprint.

Sprint retrospectives: At the end of a sprint, the development team assesses its effectiveness. Before beginning the next sprint, they modify the work to meet success and growth criteria. As work progresses, sprint retrospectives provide the opportunity to incorporate lessons learned into the overall RPA effort to avoid repeating mistakes and implement good practices quickly.

Then, because sprint planning is iterative, leveraging an agile project management framework for a company’s RPA implementation yields tangible project results. Scrums create and update process backlogs. New requirements are incorporated and addressed in deliverables.

Automations are delivered in attended packages and tested with end-users for improvements. As far as the As-Is process is concerned, an agile framework makes it easier to add a new automation opportunity to the backlog. When the automation is finished and delivered, it will already have tried and true testing roots in an application.

DynPro promotes a hybrid approach for complex and medium complex automation projects. Our approach is a harmonious combination of the Traditional (Waterfall) and Agile models. As per RDLC (Robotic Development Life Cycle), the traditional approach is used for the first few steps, followed by the Agile sprint method for the development. Then, it moves back to the Traditional methods for UAT, go-live, and support. It allows seamless development of RPA tools by integrating them with enterprise and regulatory constraints, policies, and controls.

Call or write to us to learn more about how DynPro fosters cross-functional collaboration and an Agile approach to RPA at scale.

Processes such as loan management require a great deal of paperwork, data checks, and dependencies. Today’s customer expects quick, easy access to loan services at the time, place, and channel of their choosing. They seek loan products tailored to their specific needs that are available through their preferred channel and have quick approvals.

Robotic process automation (RPA) has been assisting lenders in gaining a competitive advantage during the loan origination process. RPA’s use in loan management has allowed banks to automate processes.

Simply put, robotic process automation is the technology that replaces human action for repetitive and redundant tasks by extracting and processing structured data. Robots mimic human tasks based on a set of instructions. They can process error-free applications much faster. The ‘bots’ can read an email or invoice, download files to a specific location, copy-paste, scan through data and file it. It is designed specifically for process-oriented industries.

Implementing RPA in loan processing can speed up processes, increase reliability, and reduce labor-intensive tasks by shifting the burden to robots and freeing the workforce to perform more complex tasks. RPA in loan processing can strengthen existing banking mechanisms while also assisting the industry in scaling its growth.

Challenges that RPA can overcome in loan processing and management 

• Automatic Report Generation: RPA can generate compliance reports that flag fraudulent transactions and generate Suspicious Activity Reports (SAR). It scans compliance documents and sorts data quicker than humans.
• Customer Onboarding: Manual verification makes customer onboarding a time-consuming and inconvenient process. RPA can extract data from documents and compare it to the information provided.
• Mortgage Lending: Loan initiation, document processing, and financial comparisons are all aspects of mortgage lending that can be automated, resulting in a faster loan approval process. It also improves customer satisfaction.
• Loan due report: RPA robots can detect loans approaching their due date. RPA can collect files from various branches, combine them, and send them to the appropriate stakeholders. The process can be completed within a predetermined period, such as 15 days before repayment or EMI payments.
• Balance Register: RPA can be used to check the balance register and determine which charges must be collected. Using a set of instructions, accounts can be automatically updated to add balances.
• Loan Closure NOC: Non-Disclosure Certificates can be generated automatically. The bot receives the documents and the pending loan amount cheque and then searches the system for any remaining funds. If there is a bug, the process stops, and the remarks are updated. Otherwise, the bot designs the NOC and sends it to stakeholders for approval.
• Retail Asset Detail Modification: RPA bots examine the documents they receive, and if there is a difference in information, they update it in the banking system by a designated person in the bank. If there are no existing savings accounts and only the loan account, the bot modifies it with the help of a human approver.
• Loan Exposure Sheet: RPA can be used to collect social security numbers from the banking system and generate a final exposure excel sheet that can be auto-sent to stakeholders. It will help you calculate the loan exposure.
• SME Credit Management: With the help of robots, RPA can manage small credit lines and the capital needs of small and medium-sized enterprises (SMEs). Automated credit platforms speed up the application process while facilitating SME loan applications.

Next Steps

Several ways can be used to implement RPA for loan processing. The organization can decide which use cases to focus on after conducting a thorough assessment of its operations. You can speak with a DynPro expert  at any time, and we will assist you in making the best decision for your company.

DynPro is a UiPath and Automation Anywhere partner, bringing the best solution to the customer’s needs. Our RPA solution automates processes, identifies inefficiencies, and provides insights, making the path to digital transformation quick and cost-effective. It makes use of existing systems to reduce disruption.

iRPA Impact and Use Cases in Energy Resources and Utility (ERU)

The utility industry is evolving from a traditional, regulation-driven market to a technology-driven market. In the last two decades, the usage of cutting-edge gadgets and technology for infrastructure optimization and supply-demand balancing has expanded tremendously. The systems create a significant amount of data. Most Energy & Utility Industry products use predictive analytics, which combines historical data, predictive algorithms, and data analytics approaches to forecast future events. These circumstances result in manual data entry and repetitive manual processes, increasing the danger of human error.

Intelligent Robotic Process Automation, or iRPA, is a beneficial technology that uses software robots to mimic human workers to automate regular activities. Billing, payments, move-in and move-out procedures, and other administrative chores are usually tied to these activities. It combines AI and machine learning skills to perform high-volume, repeated jobs, ensuring that the entire operations process is error-free.

Here are some of the use cases of iRPA in ERU:

• Meter Reading Validation:  Utility companies read the meter before billing the customer for consumption. A human error might result in the generation of an incorrect bill, causing the consumer to be overcharged or undercharged. The errors like these harm the company’s reputation. iRPA verifies the consumer’s meter reading and processes it if it is correct. If an error occurs, it alerts the appropriate department, which then remedies the problem. It eases the workload of the meter reading validation team and minimizes the number of complaints resulting from incorrect billing.
• Billing and Statements:  iRPA handles everything from extracting utility bill data to performing validation checks, quarantining an incorrect invoice, and transferring the bill to the accounting system. Everything is done automatically and in a fraction of the time. As a result of robots retrieving and storing bill data, confirming invoices, and paying them all in an automated manner, companies are moving beyond simply paying bills quickly to quickly recognizing billing errors and saving operational costs.
• Payment Reversal:  Due to third-party bill payment intermediates, many consumers have issues with incorrect payment amounts or inaccurate data. The client then submits an incorrect entry claim, which the business strategy and claims teams can verify before being forwarded to the operations team for reversal or record correction.
• Complaints Management:  Utility providers must monitor and respond to customer complaints, which typically revolve around the switching process, billing issues, and power outages. Incoming complaints can be identified, recorded, and sorted using iRPA and then assigned to the appropriate person in your organization to handle them. Benefit from faster answers to client complaints and ensure that you meet your service guarantees.

iRPA is now the only option for all stages of the ERU business. Suppliers have been using these manual methods for a long time. Majority of business process stages (80-90%) are considered reliable and continuous process steps.

What are the advantages of deploying an iRPA solution?

• Lowers costs:  One of the most significant benefits of iRPA is the rapid cost reduction. Because software robots are less expensive than a full-time person, a business can save up to 30% of its total costs by automating tasks.
• Lowers operational risks: Some businesses decide to outsource hectic work to third-party entities, which increases the risk of human mistakes and inefficiency. iRPA is a better solution since it keeps the job in-house, reducing operational risk.
• Accuracy and quality: iRPA technologies can automate processes with a high risk of human error. These bots are dependable, consistent, and capable of working indefinitely.
• Scalability: Companies can use iRPA to scale up and down operations in response to changing conditions.
• Reduced workload: By decreasing their workload, staff may focus on more vital tasks by automating tasks like report writing.
• Increased customer satisfaction: Customers want higher-quality material because it improves accuracy and lowers operational risk.
• Better business results: Robotic process automation allows businesses to achieve better overall results by allowing staff to focus on tasks that provide more value to the firm.

We believe that firms who adopt a new digitalization and automation culture will be able to innovate, create new business models, and expand at the expense of those that do not.

Write to us for more information on how DynPro may assist you in implementing Intelligent Robotic Process Automation in your business.

About the author

Suman Mahapatra is working as Delivery Manager- RPA for DynPro and has overall 17 years of experience spanned across RPA, Testing, Software Development and Business operations. He has been instrumental in team management and delivering RPA projects in ERU, Healthcare, Banking, Media sectors across US, UK and Australia.

What makes an automation solution a good solution?

You have started your RPA journey, and your first projects are live, but you are not observing the results you expected. The processes are failing, the reports are not coming on time, and somehow it seems like your team has to put more effort into the same process even though the robots were supposed to cause the opposite.

What happened? Why your robots aren’t the super employees you were promised?

In this blog, I hope to provide you with insight into what you should look for in an RPA solution and what you can expect from a good RPA provider/team.

Reliability

The first thing any good solution needs is to be reliable. You expect your human employees to be available and perform their work, so you should expect the same thing from your robotic colleagues. A good RPA team will have solution architects and experienced developers that will be able to create robust solutions with redundancy, fail-safes, and in the worst-case scenarios, exception handling and escalation routes.

Maintainability

Your robot will fail.

Even if RPAs can make excellent virtual workers, they are still robotic machines. They need to be taught how to operate, what elements to interact with, and how to make business decisions. No matter how flexible these can be to accommodate changes, the bot will eventually be unable to handle everything.

During the lifecycle of your virtual colleagues, applications will update, your business will evolve, and many other things will change. To teach the new business rules to the robot, someone will need to dive into its code and make the necessary changes. It may seem like a straightforward action, but as the automated processes scale and become more complex, this can be a very challenging task. Your solution architect should organize your projects so that any developer can retrieve enough information from error messages and navigate efficiently through the robot’s interiors to find the bits of code that need to be changed.

Efficiency

You now have a very reliable virtual workforce, but there is still an issue. Robots are taking too long to complete the tasks assigned to them. It can have business implications. You want the reports to be completed on time so that your human employees have the information they need at the right time.

An experienced developer will ensure the robots and applications interact most efficiently. Along with a business analyst, your solution architect ensures that the redundant tasks get avoided and process optimized.

Scalability

Now that your automation is as fast and reliable as possible, you may reach a point where there is so much work for your bot to perform that it’s just not possible to do it in time. That’s where scalability becomes necessary.

The solution sounds simple, add more robots, right? While this may seem the correct answer, it may not be as straightforward as just adding more machines. Automated processes should be ready to support multiple bots working simultaneously. Otherwise, various errors can occur, including reworking work items, paying twice, locking files by a single person, etc. A business analyst will identify the need for a process to be scalable, and a solution architect will ensure the process is ready to be scaled when required.

Conclusion

That is a lot to consider, and it can be a bit overwhelming, but you don’t need to worry as there are experts who specialize in solving all these issues. Whether you have problems with your current solutions or would like to embark on your automation journey with the right set of tools, DynPro can help. We have a growing team of developers, solution architects, and business analysts with a vast array of professional backgrounds and certifications at your disposal to help your business make the most out of these new and exciting technologies.

About the author

Gustavo Mattei is working as an RPA Business Analyst and Solution Architect for DynPro. He has over five years of experience working with RPA for multinational corporations in the Healthcare, Insurance, and Financial sectors. You can contact him at [email protected].

IPA Vs RPA

With the digital revolution in full swing, and companies striving to become more resilient than ever before, automation is gaining momentum. To have successful automation, businesses are turning to various automation technologies like Robotic Process Automation (RPA), Intelligent Process Automation (IPA), Artificial Intelligence (AI) and so on. As a lot of comparisons have been drawn between RPA and IPA, businesses are confused on which to implement for their needs.. Here we discuss the key differences between RPA and IPA.

a. What is IPA? What IPA can do?

Intelligent process automation (IPA) is a combination of technologies used to manage and automate digital processes. IPA should increase operational efficiency, worker performance and response efficiency to customers. They should also reduce operational risk, with the goal of creating an effective operations environment.

Intelligent Process Automation (IPA) can do following things:

• Reduce your business costs.
• Save time for more important tasks.
• Avoid the risk of human error.
• Ensure traceability for analytics and audits.
• Reconcile data from various systems.
• Improve service times for clients.
• Increase end customer satisfaction.

b. What is RPA? What RPA can do?

Robotic process automation (RPA) is the use of computer software ‘robots’ to handle repetitive, rule-based digital tasks such as filling in the same information in multiple places, re-entering data, or copying and pasting.

Robotic process automation (RPA) is a software technology that makes it easy to build, deploy, and manage software robots that emulate human actions interacting with digital systems and software.

c. Key Differences

RPA vs IPA:

The difference between Robotic Process Automation and Intelligent Process Automation is that RPA is a component of IPA rather than an alternative to it. RPA is used to perform repetitive tasks with minimal variation whereas IPA (RPA + AI) is used to tackle more complex end-to-end processes.

RPA is rules-based and applies rules stipulated by humans to perform a task, for example, sending an automatic reply to an email. IPA, meanwhile, incorporates AI technologies such as machine learning and so it can perform tasks that require judgement and analysis (a loan approval is a good example), without the need for human intervention. Plus, IPA is capable of handling exceptions and continuously learns from patterns in data to improve performance.

Additionally, RPA can only deal with structured data whereas IPA can handle both structured and unstructured data.

Although RPA alone can do wonders for productivity and cutting costs in a short timeframe, IPA’s extended capabilities provide insights into process improvement opportunities across the enterprise enabling you to transform the way you work for long-term success.

d. What is suitable for your business?

Both are suitable. Preferable is RPA where we are the key partners of Ui Path & Automation Anywhere RPA tools.

About the author

Suman Mahapatra is working as Delivery Manager- RPA for DynPro and has overall 17 years of experience spanned across RPA, Testing, Software Development and Business operations. He has been instrumental in team management and delivering RPA projects in ERU, Healthcare, Banking, Media sectors across US, UK and Australia. You can reach out to him at [email protected]

Most of the organizations stress on using Agile delivery approach over Waterfall method. However, there is another approach that can be used in executing RPA projects, called as KATA Model.

What does RPA bring to the table?

Step 1 – Define Challenge/s that we wish to solve. Leadership team plays an active role in defining these challenges that the implementation team can solve

Step 2 – Grasp the current condition and figure out what’s the current performance or system of work as it is today. Various stakeholders need to understand the current condition of the system/process that needs to be improved

Step 3 – Focus on the target condition wherein we define the aspirational goal that we wish to achieve. Stakeholders that have a buy-in need to push their knowledge beyond the existing threshold. By doing this, it will force them to think in a different way to put stress on the existing systems of work and make new discoveries

Step 4 – Execution wherein we focus on how we execute that we believe will help us to move from current condition to target condition and is aligned to our goal. At times, teams are afraid of setting goals that they think can’t be achieved or hard to achieve and sometimes they set the targets that are easy to achieve and hence Leadership and Stakeholders need to pitch in to ensure goals are achievable, sustainable and benefits the business post execution.

KATA Cycles

To achieve the end goal, KATA model requires the following technique in the form of multiple cycles. Each KATA cycle consists of following steps:

Step 1 – Cross functional teams and stakeholders that have a buy-in or interest in a problem that needs to be fixed/solved need to come together

Step 2 – Stakeholders need to sit down together and describe some of the target outcomes that need to be achieved

Step 3 – Work together to understand how the current system/process is performing

Step 4 – Together define some interesting target conditions that can be worked towards

However, it is of utmost importance that the success is defined before commencing these KATA Cycles to provide some details about the accountability and a feedback mechanism to understand if the Leadership team is moving towards the desired goal.

I believe that the KATA Model will certainly play an important role during RPA Consulting and Implementation phases of a project.

Let’s take an Example of using KATA Model for an RPA Project

Primarily, top reasons for adopting RPA Automation are

1. Process optimization by – Reducing the processing time, Reducing the error rate
2. High number of applications
3. Improve customer satisfaction by minimizing / eliminating SLA breaches by taking advantage of application availability (in PRODUCTION Environment)
4. Scalability (handling high volumes)
5. Better FTE Utilization

With the above reasons in mind let’s see how KATA Model can be applied for RPA Project:

Define Challenge – Optimize process by reducing the Average Handling Time (AHT) of the process

Current Condition – The applications are available 20x7x365 (4 hours normally considered for application maintenance activity), however, the Manual Average Handling Time (AHT) is very high thereby causing SLA breaches

Target Condition – Reduce Average Handing Time and Improve Process SLA, optimize FTE’s for another set of processes

Execution –

Process SME needs to:

• define the keystrokes and shortcuts that can be used
• provide insight to whether couple of steps can be eliminated to achieve the end goal
• eliminate conditions that do not add value or don’t get cases that make use of these conditions

Implementation Team needs to:

• build multi-bot type of model that runs on multiple machines to handle volumes
• get some experience on the applications they would be working upon and understand how the data flows / interacts between applications
• define the conditions that have been built and conduct testing

Leadership Team needs to:

• verify if the target condition is achieved
• if no, the above KATA cycle needs to be repeated till the end goal is achieved