Author: Team 6e

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, as data volumes increase, traditional methods of data analysis are no longer sufficient. Artificial Intelligence (AI) can help organisations analyse large volumes of data efficiently and accurately, enabling informed decision-making. 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 automate tasks, improve accuracy, and predict 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 on-premises data centres interact with and share 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