Author: root

Introduction: In the digital age, Enterprise Resource Planning (ERP) systems have emerged as powerful tools for streamlining operations, enhancing efficiency, and promoting collaboration across various industries. The public sector is no exception, as government agencies have recognized the potential of ERP in transforming their processes and service delivery. This blog will explore how ERP is used in the public sector, discuss its benefits, and delve into future possibilities.

1. Enhancing Efficiency and Integration (250 words): In the public sector, efficiency and integration are paramount. ERP systems offer a centralized platform integrating core functions such as finance, human resources, procurement, and inventory management. By adopting ERP, government agencies can eliminate redundant processes, minimize data silos, and promote seamless information flow across departments. This integration enhances efficiency by reducing manual efforts, eliminating data inconsistencies, and providing real-time insights for informed decision-making. Moreover, by automating routine tasks and workflows, ERP systems free up valuable time for government employees, letting them to focus on higher-value activities and improving productivity.
2. Improving Service Delivery and Citizen Experience (250 words): Delivering efficient and citizen-centric services is a crucial objective for the public sector. ERP systems enable government agencies to improve service delivery and enhance the citizen experience. By automating workflows, agencies can streamline processes such as permit applications, licensing, and citizen service requests. This automation reduces processing time and improves accuracy and transparency, leading to higher citizen satisfaction. Additionally, ERP systems provide self-service portals and mobile applications that empower citizens to access information and interact with government services conveniently. Citizens can submit forms, track applications, and receive real-time updates, improving their overall experience and engagement with the government.

III. Data-Driven Decision Making (200 words): In the data era, making informed decisions based on accurate information is crucial for effective governance. ERP systems generate vast amounts of data, and public sector organizations can leverage this data for data-driven decision-making. By utilizing analytics and reporting capabilities, agencies can gain insights into resource utilization, operational performance, and service demand. This data-driven approach enables evidence-based decision-making, policy formulation, and improved resource allocation, leading to more efficient and effective governance. For example, analyzing data on service demand patterns can help government agencies identify trends, optimize resource allocation, and allocate budgets strategically.

1. Future Possibilities: The future of ERP in the public sector holds immense potential for further advancements and opportunities. As technology evolves, government agencies can leverage emerging trends to enhance ERP systems further. Some future possibilities include the following:

1. Cloud-Based ERP: Moving ERP systems to the cloud offers scalability, flexibility, and cost savings. Cloud-based ERP solutions enable government agencies to access data and applications from anywhere, facilitating remote work, collaboration, and disaster recovery. The cloud also provides opportunities for data sharing and interoperability between government agencies, enabling more integrated and coordinated services.
2. Integration with Emerging Technologies: Integrating ERP systems with emerging technologies like artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) can unlock new capabilities. For example, AI-powered chatbots can enhance citizen engagement and support, while IoT devices can provide real-time data for predictive maintenance and resource optimization. ML algorithms can analyze large datasets to identify patterns, anomalies, and trends, enabling government agencies to make proactive decisions and anticipate citizen needs.
3. Enhanced Cybersecurity Measures: As the public sector deals with sensitive data, bolstering cybersecurity measures becomes crucial. Future ERP systems should prioritize robust security protocols, encryption techniques, and proactive threat detection to safeguard citizen information. Additionally, technologies like blockchain can enhance data integrity and transparency, ensuring trust and privacy in government transactions and interactions.

Conclusion: ERP systems have revolutionized the public sector by enhancing efficiency, improving service delivery, and enabling data-driven decision-making. The future of ERP in the public sector lies in harnessing emerging technologies, embracing cloud solutions, and prioritizing cybersecurity. By leveraging these advancements, government agencies can unlock greater operational efficiency, citizen satisfaction, and informed governance, ultimately leading to a more responsive and digitally enabled public sector. With continuous innovation and strategic implementation, ERP systems will continue empowering the public sector, driving positive change, and transforming how governments serve their citizens.

In today’s rapidly evolving digital age, technology advancements continue to reshape industries across the board, and the public sector is no exception. One transformative solution that has gained significant traction in recent years is Robotic Process Automation (RPA). This cutting-edge technology holds immense potential for streamlining operations, enhancing citizen experiences, and improving overall efficiency within public services. This comprehensive step-by-step guide aims to equip public service organizations with the knowledge they need to implement RPA successfully. By highlighting its benefits and providing possible examples that could lead to successful transformations, this guide will shed light on how RPA can revolutionize the delivery of public services.

Step 1: Identifying Processes Suitable for Automation

The first step in leveraging RPA within the public sector is identifying automation processes. These processes typically involve repetitive tasks such as data entry, document processing, and administrative duties. Public service organizations can eliminate manual errors and significantly reduce processing times by automating these tasks. For example, a government agency seeking to enhance efficiency can automate data extraction from various forms and populate databases. Technologies like optical character recognition (OCR) can be used to extract data accurately from the identified forms. While doing so it is essential to continuously monitor the data extraction and population process to ensure its effectiveness and address any issues that arise. This kind of automation eliminates tedious manual work and enables the agency to provide faster and more accurate services to citizens.

Step 2: Conducting Feasibility Assessment and Impact Evaluation

Before diving into RPA implementation, conducting a feasibility assessment and evaluating the potential impact is crucial. Public service organizations must consider process complexity, scalability, and regulatory compliance factors. For instance, a municipality analyzing its permit application process may identify tasks that can be automated, such as document verification and status updates. The agency can expedite the permit processing timeline by automating these steps while ensuring citizens receive real-time application updates. To start with intelligent document processing to extract information from forms is the most important step in this direction. By integrating the permit processing system with an application tracking system, citizens can receive instant updates on their application status. Automated notifications through email, SMS, or online portals can keep applicants informed about any changes in their applicationIt will not only enhance operational efficiency but also improves overall citizen satisfaction.

Step 3: Designing an Effective RPA Solution

Designing an effective RPA solution is a critical factor in successful implementation. Public service organizations should thoroughly understand their existing workflows, identify pain points, and determine desired outcomes. For instance, a tax authority can design an RPA solution to automate the validation and processing of tax returns. This can involve implementing software robots to extract relevant data from tax forms, perform data validation checks, and calculate tax amounts. It seems like a daunting task but can be achieved with careful planning and articulation. This automation reduces manual effort and ensures higher accuracy in the tax assessment process, leading to improved efficiency and accuracy.

Step 4: Selecting the Appropriate RPA Tools and Technologies

Selecting the right RPA tools and technologies plays a pivotal role in the success of implementation efforts. Organizations must evaluate solutions based on integration capabilities, user-friendliness, and scalability. For example, a local transportation agency aiming to optimize revenue management can select an RPA platform that seamlessly integrates with existing systems. This integration allows the agency to automate fare collection processes, synchronize revenue data with the app, and provide real-time updates to passengers regarding fares, payment options, and travel information. By leveraging the app’s capabilities, the agency can enhance passenger experience, improve revenue tracking, and streamline fare management for a more efficient and convenient transportation system.

Step 5: Implementing RPA with a Well-Defined Roadmap

Implementing RPA successfully requires a well-defined roadmap. This roadmap should include conducting pilot projects, establishing governance structures, and providing comprehensive training to employees. For instance, A healthcare organization can automate appointment scheduling and reminders by implementing a digital appointment management system. This system can integrate with the organization’s electronic health record (EHR) system and patient communication channels. Patients can schedule appointments online or through automated phone systems, and the system can automatically send appointment reminders via email, SMS, or mobile app notifications. This initial success is a strong foundation for further RPA adoption across different areas within the organization.

Step 6: Ensuring Security and Compliance

Security and compliance are paramount considerations in RPA implementations within the public sector. Public service organizations must implement robust data protection measures, access controls, and thorough audit trails to safeguard sensitive information. For example, A social services agency can utilize RPA to automate the eligibility verification process for benefits by implementing software robots that extract and validate relevant information from application forms and databases. These robots can cross-check the data against privacy regulations and predefined criteria to determine eligibility. This ensures compliance with privacy regulations while reducing manual effort and processing times.

Step 7: Measuring Success and Continuously Improving

Measuring success and striving for continuous improvement are essential aspects of any RPA implementation. Public service organizations should monitor key performance indicators (KPIs) such as cost savings, process efficiency, and citizen satisfaction.

Conclusion

In conclusion, Robotic Process Automation (RPA) has emerged as a transformative solution for the public sector, enabling organizations to streamline operations, enhance citizen experiences, and improve overall efficiency. By following this step-by-step guide, public service organizations can harness the power of RPA to automate repetitive tasks, redirect resources towards value-added activities, and deliver enhanced services to citizens. Embrace the potential of RPA and embark on a transformational journey towards a more efficient and citizen-centric public sector.

As technology continues to rapidly advance, the public sector is exploring how to integrate artificial intelligence (AI) into its services to improve efficiency, effectiveness, and accessibility. However, to truly leverage the potential of AI, the public sector must ensure that its implementation is inclusive and does not exacerbate existing inequalities.

Here are some steps that the public sector can take to plan for the inclusion of AI in citizen services:

1. Identify the services that can benefit from AI: The public sector should first identify the services that can be improved through the use of AI, such as healthcare, education, transportation, and social services. For example, AI can be used to personalize healthcare recommendations based on a patient’s medical history, predict traffic congestion and optimize transportation routes, and provide tailored learning experiences for students.
2. Prioritize equity and accessibility: In planning for AI implementation, the public sector must prioritize equity and accessibility to ensure that the benefits of AI are not limited to a select few. This can be achieved by involving diverse stakeholders, including citizens and community organizations, in the design and implementation process, and ensuring that AI systems are developed with a focus on reducing bias and discrimination.
3. Build capacity and expertise: The public sector should invest in building the necessary capacity and expertise to design, develop, and implement AI systems. This can be achieved through partnerships with universities, private sector organizations, and research institutions. Additionally, the public sector should prioritize training and education programs to equip its workforce with the necessary skills to effectively leverage AI in citizen services.
4. Monitor and evaluate impact: To ensure that AI implementation is inclusive and effective, the public sector should continuously monitor and evaluate its impact on citizens and communities. This can be achieved through data collection and analysis, citizen feedback mechanisms, and regular performance assessments.

Example: One example of the public sector using AI to improve citizen services is the City of Amsterdam’s AI-driven traffic management system. The system uses real-time data from cameras and sensors to predict traffic congestion and optimize traffic flow, reducing travel times and improving air quality. The City also prioritized equity and accessibility in its implementation, by involving citizens and community organizations in the design process and ensuring that the system does not discriminate against any particular group.

Here is a roadmap that the public sector can use to adopt AI in an inclusive and effective manner:

1. Define goals and prioritize use cases: The first step in adopting AI in the public sector is to define clear goals and prioritize use cases. This includes identifying areas where AI can improve citizen services and setting measurable objectives for AI adoption.
2. Assess data availability and quality: AI systems require large amounts of data to function effectively. The public sector should assess the availability and quality of data to ensure that it is suitable for AI applications. This includes evaluating data sources, assessing data quality, and addressing any data gaps or limitations.
3. Build capacity and expertise: To effectively adopt AI, the public sector needs to build capacity and expertise in AI development and deployment. This includes investing in training and education programs, developing partnerships with private sector organizations and research institutions, and hiring AI experts and data scientists.
4. Develop ethical and legal frameworks: As AI adoption increases, the public sector must develop ethical and legal frameworks to guide its use. This includes developing guidelines for responsible AI development, ensuring privacy and security of citizen data, and addressing issues of bias and discrimination.
5. Pilot and scale AI initiatives: The public sector should pilot AI initiatives in a controlled environment to test their effectiveness and gather feedback from citizens and stakeholders. Successful pilots can then be scaled up to a wider audience.
6. Monitor and evaluate impact: It is important to continuously monitor and evaluate the impact of AI on citizen services to ensure that it is delivering the intended benefits. This includes collecting and analyzing data, gathering feedback from citizens and stakeholders, and regularly assessing AI performance.

By following this roadmap, the public sector can adopt AI in an inclusive and responsible manner, ensuring that it delivers maximum benefits to citizens and communities while minimizing any potential risks.

In conclusion, the adoption of AI by the public sector has the potential to greatly improve citizen services, but it must be done in an inclusive and responsible manner. To ensure that AI implementation is inclusive, the public sector must prioritize equity and accessibility, involve diverse stakeholders in the design and implementation process, and focus on reducing bias and discrimination. It is also important to build capacity and expertise in AI development and deployment, develop ethical and legal frameworks, pilot and scale AI initiatives, and continuously monitor and evaluate the impact of AI on citizen services. By following these steps, the public sector can harness the power of AI to improve citizen services and create a more equitable and just society.

Introduction

In today’s world, data has become a valuable asset for organizations. Every organization collects data from various sources, and it is essential to analyze this data to make informed decisions. However, with the increasing amount of data, traditional methods of data analysis are no longer sufficient. Artificial Intelligence (AI) can help organizations to analyze large volumes of data efficiently and accurately, making informed decisions. In this blog, we will discuss the benefits of using AI in data analytics.

What is AI?

AI is a technology that enables machines to learn and adapt to new situations without explicit programming. AI makes use of algorithms and statistical models to analyze data and make accurate predictions. Machine Learning (ML), a subset of AI, allows machines to learn from data and improve their accuracy over time. Deep Learning (DL) is another subset of AI that uses neural networks to analyze complex data.

Why use AI in Data Analytics?

The benefits of using AI in data analytics are as follows:

1. Automation: AI can automate tasks that were previously done manually, reducing the time and cost of data analysis. AI can also help in automating the data cleaning process, which is crucial in data analysis.



2. Accuracy: AI can analyze large volumes of data accurately and identify patterns and anomalies that might be missed by human analysts. AI can also help in reducing errors caused by human bias.

3. Efficiency: AI can analyze data much faster than humans, enabling organizations to make informed decisions quickly. AI can also help in optimizing resources by identifying areas where improvements can be made.

4. Predictive Analytics: AI can predict outcomes based on historical data and identify potential risks and opportunities. AI can also help in forecasting future trends and predicting customer behavior.

How AI is used in Data Analytics?

1. Natural Language Processing (NLP): NLP is a subset of AI that enables computers to understand and interpret human language. NLP is used in data analytics to analyze text data such as customer reviews, social media posts, and emails. NLP can help in identifying sentiments, opinions, and trends.

2. Image and Video Analytics: AI can analyze images and videos to identify patterns and anomalies. Image and video analytics can help in identifying defects in products, detecting fraud, and improving customer experience.



3. Recommendation Engines: Recommendation engines are used in data analytics to recommend products or services to customers based on their previous purchases and preferences. Recommendation engines can help in improving customer engagement and increasing revenue.



4. Predictive Analytics: Predictive analytics is used in data analytics to predict outcomes based on historical data. Predictive analytics can help in identifying potential risks and opportunities and forecasting future trends.

Challenges of using AI in Data Analytics

1. Quality of Data: AI depends on the quality of data for accurate analysis. Poor quality data can lead to inaccurate predictions, which can result in incorrect decisions.

2. Lack of Transparency: AI models can be complex, making it difficult to understand how they arrive at their predictions. This lack of transparency can make it difficult to trust AI models and can raise ethical concerns.

3. Cost: Implementing AI in data analytics can be expensive, and organizations may need to invest in new hardware and software.

Conclusion

AI has revolutionized the field of data analytics, enabling organizations to analyze large volumes of data accurately and efficiently. AI can help in automating tasks, improving accuracy, and predicting outcomes. However, implementing AI in data analytics comes with challenges such as poor quality data, lack of transparency, and cost. Despite these challenges, AI is an essential tool in data analytics, and organizations that embrace AI will have a competitive advantage in the market.

Hybrid Cloud at a Glance

A hybrid cloud is where the on-premises data centre interacts and shares data and applications with the public cloud. Although there are many definitions of hybrid cloud, the benefits are the same. Any business can instantly scale capacity up with this capability to handle the excess workload. It’s a bet for government agencies as it offers flexibility to use the public cloud for data that can be stored outside of premises and keep the confidential and agency-specific data on-premises and avoid any risk. The shifting landscape of technology offers a constant challenge for public agencies. Governments are looking for cost-effective ways to efficiently deliver essential services on tight budgets, and a hybrid cloud is one solution.

Hybrid clouds also eliminate the need for expensive data centers and reduce operational costs. Here are ten reasons why pivoting into a hybrid cloud is the best way forward for your agency:

• Successfully manage risk
• Fast-track digitization with a clear hybrid roadmap
• Maximize flexibility
• Keep the lights on while transforming.
• Innovate faster based on hybrid cloud data insights
• Create a network without data silos
• Adopt DevOps and agile methodologies
• Bring your legacy to the cloud safely and securely
• Bring order to data chaos with a unified interface.
• Utilizing the hybrid cloud, especially in their data and IT departments, for compliance

Hybrid cloud solutions offer public agencies the opportunity to build a foundation for future innovation and security concerns. By utilizing this solution, agencies can ensure that their information is flexible and secure. A hybrid cloud is no longer an option for agencies looking at innovative ways to improve their tech. It’s a requirement if they hope to be up to date with the latest technologies and services.

Data analytics is transforming the public sector by enabling agencies and departments to make more informed decisions, improve efficiency, and increase transparency. By analyzing large datasets, agencies can now identify patterns, trends, and relationships that may not have been apparent otherwise. This allows them to better understand their operations, serve their constituents more effectively, and allocate resources more efficiently.

One example of how data analytics is being used in the public sector is in farming. This area will be a focus of 6e Technologies in 2023. By analyzing data on farm yields famers and associated businesses can identify best practices and areas for improvement, which can help to improve the yield per acre while simultaneously reducing costs.

In addition to the farming sector, data analytics is also being used in a variety of other areas in the public sector, such as transportation, healthcare, education, and public safety. By leveraging the power of data, agencies can gain valuable insights and make more informed decisions that can have a positive impact on society and allow them to be good stewards of taxpayer funds.

 

2022 Changes that Occurred

There have been many changes in automation over the past 12 months. Some of the key developments in this area include the increasing use of robotics and artificial intelligence in manufacturing, the development of self-driving vehicles, and the growth of the gig economy and the use of on-demand labor.

In manufacturing, advances in robotics and AI have led to the development of more flexible and adaptable production lines, as well as the use of robots for tasks such as inspection, sorting, and packaging. These developments have helped to improve efficiency and productivity in manufacturing and have also led to the creation of new job opportunities in areas such as programming and maintenance.

Self-driving vehicles have also made significant progress over the past 12 months, with several companies developing and testing autonomous cars and trucks. These vehicles have the potential to revolutionize transportation, improving safety and efficiency while also reducing the need for human drivers. This also applies to farming where self-driving harvesters could harvest crop 24/7 during season.

In addition to these developments, the gig economy has grown significantly over the past 12 months in a respond to COVID and at-home work policies, with more and more people working on a temporary or on-demand basis. This has been made possible by advances in technology, which have made it easier for businesses to connect with workers and for workers to find and perform tasks. The gig economy has also led to the automation of certain tasks, as companies seek to use technology to streamline processes and reduce the need for human labor.

 

Upcoming in 2023

There are several trends in automation that are expected to continue to develop in 2023 and these will be a focus of 6e Technologies in automation. Some of the key trends we see are:

1. The increasing use of artificial intelligence: AI is expected to play a larger role in automation in the coming years, with more advanced machine learning algorithms being developed and more companies adopting AI technologies.
2. The growth of the internet of things (IoT): The IoT refers to the interconnected network of devices that can communicate with each other and exchange data. This technology is expected to continue to grow in the coming years, with more devices being connected to the internet and more automation being enabled using IoT devices.
3. The continued evolution of autonomous vehicles: Self-driving vehicles are expected to become more common in the coming years, with several companies working on the development of autonomous cars, trucks, and other vehicles.
4. The increasing use of robotics: Robotics is expected to continue to play a significant role in automation, with the development of more advanced and flexible robots that can perform a wider range of tasks.
5. The continued escalation of the gig economy: The gig economy, which refers to the use of temporary or on-demand labor, is expected to continue to grow in the coming years, with more companies using technology to connect with workers and automate tasks. This could solve a particular issue in the federal government. With the retirement of a large number of public employees, the federal government has had a hard time finding people to fill the gap; utilizing a gig economy system might allow workers the flexibility to work for the government who may have not considered it otherwise.

Federal agencies face new regulations and contract management challenges for procurement and vendor-related issues. In addition, the Freedom of Information Act (FOIA) covers contract-related requests are an all-time high. Maintaining records of all the vendors and other business relationships can be exhausting. Agencies must manage these contracts efficiently; otherwise, it can open them up to several problems. Automation can be the right solution for contract management, as it can help agencies handle multiple contracts daily.

Contract lifecycle management (CLM) automation is the current industry standard to streamline contracting processes. However, with artificial intelligence in the picture, the next level is contract intelligence. Contract intelligence uses a combination of AI and machine learning (ML) to automate tasks and natural language processing (NLP) to understand the legal areas of any contract can reduce the time of the CLM lifecycle. This automation uses and provides higher contract performance while lowering the risk for the agency. This approach ensures that the intent of every contract is fully realized, from start to finish.

How is automation used in contract management?

The automation starts at the ingestion stage, where a large amount of contract information is ingested; it is compared with historical data for any correlations and patterns. These patterns help to make predictions and suggestions, making a given contract better for the organization.

Benefits of Contract Intelligence

1) Automation achieved with tools like AI and ML can help scale compliance across thousands or even millions of contracts across all agencies.

2) Contract intelligence reduces wastage and provides value by generating new insights with every transaction.

3) Quickly understand the risk and take measures to reduce the risks.

4) Fast turnaround of contract and shorter review processes of the contract.

5) Efficient maintenance of the clauses and terms across all the contracts

6) Advance search feature to analyze the terms and clauses across contracts

7) AI-based predictions based on historical data analysis

This more innovative and powerful technology will help agencies instantly analyze the contracts at one glance but also will help gain a comprehensive overview of the complete management. It acts as an initial quality check enabling legal operations to identify inconsistencies. It also helps the operations look for critical terms that might need re-negotiation before renewal and can help increase the agency’s reputation. To mitigate risk and uncover potential opportunities, now is the time for federal agencies to push the boundaries. Are you ready to improve your operations with new-age technologies that you never imagined?

Automation has existed for over a decade but has seen exponential growth with recent advances. The advances have seen significant change as there has been an increase in automation tools that replicate and automate transactional processes while improving process accuracy and speed. RPA offers the untapped potential of removing human bias and providing valuable insights that have further catapulted digital transformation. We can define automation maturity level as the extent of RPA used in the public sector, based on using data effectively to deliver citizen services while transforming and managing operational workflows. The public sector can increase this capacity and tackle its tactical priorities by using new innovative solutions such as AI, machine learning, and the Internet of Things.

Automation and Cognitive Technologies Aren’t Magic Bullets — But They Can Take You a Long Way.

The public sector has been growing, with organizations and service delivery adopting automation technologies to improve efficiency, respond to increased demands and maximize resources. However, before we jump on this bandwagon and start using automating agencies, there are a few things you need to know about automation. Artificial intelligence and RPA are essential in the public sector, how they can be used by small and large agencies alike, and why your federal agency won’t be left behind if you choose an adaptive approach.

Government Agencies Are on the Cusp of Major Transformation — Many Won’t Realize It.

We’re in a unique moment in time for public sector organizations. Government agencies are facing an aging workforce, budget reductions, new expectations from citizens, and new standards for efficiency and transparency. In recent times, technology has been touted as THE ANSWER. The popularity and use of digital tools rapidly find inroads into governments and governance worldwide. It develops operations with a series of “if/then” decision-making that handles tasks based on those guidelines, ultimately freeing up staff to focus on activities of higher value. The rapid growth of technology and AI will be a game changer and define the future of government agencies’ operations. It will also create incredible opportunities for people who work in these organizations. The good news is that there are plenty of examples where RPA has already transformed businesses and agencies; for example, The U.S. Postal Service automated 80 percent of the supplier request with RPA. The bots now run one hour daily, five days a week, processing 375 transactions with 100% accuracy.

Government and public sector organizations can leverage automation for the following activities:

1. Data digitization: By converting physical data into digital data, agencies can provide services that fulfill citizens’ expectations.
2. Data migration: Can help governments run crucial administrative processes across from a centralized locus, thereby enhancing data-driven processes and eliminating errors
3. Communication with the public: Enhanced communication channels can help in information dissemination to citizens, peer-to-peer sharing of data, and co-creation of solutions
4. Public opinion analysis: Automatically extract relevant information and help analysts derive actionable insights.
5. Healthcare management: Manage public records of healthcare and vaccination information, communicate with citizens about healthcare updates, and generate timely reports for Government action during health crises.
6. Public security: The security can enable the safe storage of citizens’ sensitive data, such as their Social security numbers, license numbers, tax IDs, and other sensitive information behind layers of security.

The Path Forward for Public Sector RPA and Intelligent Automation Is Governed by Rules, Processes, Data, and Analytics, All together!

Automation, leveraging artificial intelligence (AI) and other technologies, has opened up new possibilities. In the real world, people working with technology can deliver the most outstanding value if the automation aligns with their vision and purpose. A clear strategy and implementation plan can effectively manage digital transformation. Not to forget, this will bring datasets together and insights that would not previously have been possible. So rules, processes, data, analytics, and good governance can get relevant, significant, and proportionate changes.

We believe intelligent automation will change everything about the public sector, radically rethink how these agencies deliver services to the public and find newer ways to tackle national, regional, and local issues.

 

Source:

“RPA Streamlines Payments, Powers Efficiency.” Cognizant https://www.cognizant.com/us/en/case-studies/postal-service-robotic-process-automation

With the world embracing its new norm of vastly accepting flexibility at the workplace, businesses are spearheaded toward changing work dynamics. The pandemic taught us to attain maximum productivity within four walls, and organizations have continued to succeed in this remote culture. Public Sector is not far behind. Government employees embraced digital tools to facilitate remote work when their offices reopened.

As rightly said, ‘The future is remote,’ with digitalization conquering the world along with Intelligent Automation (IA) and Artificial Intelligence (AI), the workforce now focuses on flexibility. With the pandemic, many businesses had to ensure all employees had every resource to work efficiently from home; although it was tedious, we all adapted well for two long years. The information the federal workers deal with is crucial and needs no additional flub; instead, a structured approach. A survey conducted by Accenture in early 2021 shows that the fastest shift to the road of effectiveness is digitization; even then, some agencies have not been able to adapt to this fully. The remote working culture has been thrilling and challenging. Remote work accompanied by next-gen technologies like AI and IA has its positives and negatives. Here are a few points of discussion:

Time management – While working from the office involves time on the commute, remote work helps to stay away from these distractions and saves time. This flexible future for government work can improve employee morale as it gives time to deal with other things. If allowed to be in a hybrid system, most federal workers could complete jobs faster, as automation takes care of the daily tasks, allowing federal workers to be flexible and more productive in less time.

Work-life balance – No doubt remote work opportunities can offer work-life balance opportunities. For example, a federal worker could acquire different skills or pursue a hobby while doing his or their job remotely; this keeps up his or their morale. The Office of the Revenue Commissioners in Ireland (Revenue) is a use case. Receiving a vast three million customer service calls a year, John Barron, CIO at Revenue, took this as an opportunity to integrate AI into his workforce. In just the first six weeks of initiation, 50-60% of calls were handled entirely by a voice bot. Employees not only got a chance to focus their efforts on tasks that can help them grow in and outside the workplace, rather than answering calls all day.

Increased employee loyalty – Federal workers are bound to be loyal, and there can be a decline in resignations if the work environment is wholesome. Although working from home can dampen an employee’s creativity as there is less human engagement. With some simple programming, the monotonous, repetitive tasks can be fully autonomous and can make employees happier when their day-to-day projects are intriguing. Why use human intelligence on redundant tasks when automation can take up this role?

Effective decision-making – Imagine a specific decision that needs to follow a traditional method, especially in the age of zoom meetings and digitized collaboration. Wouldn’t it be time-consuming? Of course, it will. Imagine an automated system set to specific rules that links data to decision-making, equipped with a feedback process that continuously self-learns and self-corrects. This system is IA at work. Having an artificial assistant inform you when it needs human revision for difficult judgment calls rather than pouring over volumes of issues by hand sounds nice, right?

Save Resources– Automating data storage processes is moving towards a green system. According to the Lawrence Berkeley National Laboratory, the transfer of widely used software applications to the cloud would reduce energy usage by 87%. With remote working culture, all organizations encourage and support reducing the carbon footprint. Intelligent automation in the small world can help the agencies’ sustainability efforts.

Although there are some issues like security as a growing number of remote workers means a vastly distributed network with numerous access points, fortunately, zero trust architecture is a way forward that will vet every digital interaction. 2-way or 3-way authentication, i.e., can further enhance security. To avoid the human error that primarily causes the security breach, if more efforts can be put into training and changing workforce management, this issue can be dealt with efficiently.

According to a report by CISCO, as of July 2022, 58% of federal employees are working from home five days a week, and 52% are satisfied with the current remote work arrangement. In this technology-driven world, getting ahead and staying ahead, the benefits mentioned above can help us weigh both sides of the coin of evolution in the workplace. Remote or hybrid work certainly brings a lot more to the platter and can be improved from time to time with newer technologies. All this brings us to the conclusion that ‘The future is hybrid’ With so many job opportunities, it doesn’t matter which part of the earth you may be all you need is a set of skills, secured systems, and proper remote working structure to embark on this journey.

“Artificial Intelligence: Paving an Easier Path for Remote Working.” AI Paving the Way for Remote Work | IEEE Computer Society, www.computer.org/publications/tech-news/trends/remote-working-easier-with-ai.

“Automated Decision Making.” Oliver Wyman – Impact-Driven Strategy Advisors, www.oliverwyman.com/our-expertise/insights/2016/aug/automated-decision-making.html.

A Real Conversation Starter – Accenture. www.accenture.com/_acnmedia/pdf-96/accenture-hps-ira-creds-d5-final.pdf.

Truly Human Automation – Accenture. www.accenture.com/_acnmedia/accenture/redesign-assets/dotcom/documents/local/1/accenture-truly-human-automation-manchester-metropolitan-university.pdf.

“Uncovering the Environmental Impact of Cloud Computing.” Earth.Org, 30 Sept. 2021, earth.org/environmental-impact-of-cloud-computing/.

Cisco_Hybrid_Work_in_Government_Survey_Report_FINAL, Cisco, July,2022

https://www.cisco.com/c/dam/m/digital/elq-cmcglobal/OCA/Assets/Federal/Cisco_Hybrid_Work_in_Government_Survey_Report_FINAL.pdf