What Is Robotic Process Automation?

What Is Robotic Process Automation?

What Does RPA mean?

(R)  Robotic 

The “robotic” in RPA is describing the automated component of the robots. RPA is not a physical or mechanical robot but process automation. You can set up RPA to do work like setting up computer systems and applications to run.

(P) Process

“Process” means work that you need to get done.

(A) Automation

“Automation” is making work happen on its own without manual input or human cognition to oversee it.

As part of digital transformation, emerging technologies continue to change business operations. Digital transformation is a lengthy process, one that takes years as businesses adjust to the introduction of technology into systems and processes.

One of such technologies is Robotic Process Automation (RPA). The easiest analogy for RPA is to imagine humans in an office environment doing manual data entry and accounts receivable. Now, imagine these humans being replaced by robotic bots with a remote control in their hands. Think of the bots are a digital workforce that interacts with a system or application.

RPA Improves The Following Tasks

 Bots alleviate a lot of manual and redundant tasks for humans such as:

– copy-paste

– scape web data

– make calculations

– open and move files, parse emails

– log into programs

– extract unstructured data

Industry Overview

Businesses that are committed to successful digital transformations are investing in RPA and it is paying off. The adoption can be attributed to Artificial Intelligence (AI) becoming more accessible across industries. In fact, the 2020 COVID pandemic has seen more adoptation of RPA in the healthcare industry. As of 2021, Gartner research estimated global RPA software revenue to be at $1.89 billion. This shows a significant 19.5% increase since 2020.

RPA and COVID 19

The growth of RPA adoption reflects the influence of COVID 19 on the global economy. As businesses faced cost reductions and shrinking budgets, an investment in RPA can prove to be cost effective and innovative. Enterprises that want to digitally optimize operations would benefit from the improvements in process quality, speed, and productivity offered by RPA.

Adoption Of RPA

Further research showed the trending of RPA across industries. It showed 22% of participants already piloted or fully implemented RPA. 74% of respondents indicated a willingness to explore RPA in the coming years.

Just like digital transformation became more of a requirement than a option for businesses wanting to thrive in the digital age, so will RPA.

RPA seamlessly integrates into an organization without a need to change business systems, applications, or existing processes to make it work. In contrast, some businesses use macros for automation and macros cannot be fully integrated into other applications outside of Microsoft Office suite. This further increases differences between the use of RPA v. macros.

How Does Robotic Process Automation Work

If RPA is to become part of the digital revolution of work, how does the process work?

The effectiveness of RPA is evident in its simplicity and ease of use. RPA bots are easy to set up, use, and share. Advanced technical knowledge is not needed to set up RPA

Businesses Use RPA To Automate Work That Is:

– repetitive

– manual

– drudge work

– zero creative input

– zero human intelligence

An RPA bot executes it better and faster with zero mistakes and zero breaks.

The way RPA works is by accessing information from a business’ existing IT systems. It can integrate with your applications through the front end or the back end.

– Backend: RPA connects to databases and enterprise web services

– Frontend: It makes desktop connections

How RPA connects to the business depends on the needs of the solution. For complete process automation, backend connectivity works well. Front end connectivity can connect with desktop application such as Salesforce and PeopleSoft and read and write data. The frontend connection provides more of a human operator element for functionality.

Fundamentally, RPA recognizes elements on the screen by:

– property

– structure

– hierarchy

In comparison, humans look at the screen and recognize elements on the desktop based on visuals and organization. As a result, RPA is maximally efficient in completing tasks where humans make errors.

Robotic Process Automation Benefits

Effectively implemented RPA can:

– Automate business processes

– Provide greater accuracy

– Organize and process unstructured data

– Eliminate errors

– Ensure compliance

– Improve customer experience

– Improve employee productivity and morale

– Ensure fast ROI

– Provide Scalability

After a business has adopted RPA, it can benefit immediately by seamlessly integrating technology, processes, and people.

Segments Affected By RPA

Everyone in the business is affected:

– users

– customers

– employees

– marketing

– legal

– HR

– finance

– accounting

Best Practices For RPA Process

For the business to experience full benefits of RPA, there are some best practices for the RPA process:

– Process must be based on rules

– Process must have regular intervals

– Process must have definite inputs and outputs

– Task must have enough volume

When properly implemented, RPA can transform an industry in the short and long term.

Industries That Use Robotic Process Automation 

RPA In Finance

Many industries can benefit from an effective RPA process. Highly regulated industries like finance have a lot of repetitive tasks that can use automation as a cornerstone. For example, historically receivables and payables have needed a lot of manual labor by skilled workers. Automation enables those skilled workers to do more meaningful, strategic work and spend more time with clients.

In fact, a poll asked corporate controllers about RPA finance practices. It has found that 73% of controllers plan to implement RPA in their finance departments by 2020. This figure shows an increase from 54% in 2018.

RPA In Banks

The real efficiency with RPA for financial services comes in changing the nature of works within banks. Banks become more efficient at allocating scarce resources that involve large amounts of paperwork. This has twofold implications: cost reductions and impactful gains in customer experience. Banks being more freed up to focus on customer experience will improve service quality, drive customer acquisition, and increase revenues.

The research supports these productivity gains. It has been found that RPA technologies can “fully automate” 42% and “mostly automate” 19% of finance activities. From opening accounts to fraud inquiries, customer service teams at banks are empowered with RPA to focus on more important tasks that require human intelligence and nuance.

RPA In HR

HR is another industry that can be more productive with the integration of RPA. HR employees can be liberated from repetitive operational tasks such as:

– onboarding of new hires

– processing payroll

– handling benefits

– compliance reports

– employee record management

– time and attendance management

RPA benefits HR operations by automating micro-tasks which integrate processes that legacy systems failed to connect. For example, payroll management is a big time sink for HR operations.

RPA Benefits In HR:

– Accuracy and Increased productivity- RPA technology reduces the margin of errors in HR. With RPA, the HR department can rely on accurate payroll management to free up personnel to work on more strategic, personalized employee tasks.

– Consistency- By investing in RPA, HR departments are guaranteed that microtasks are completed in a consistent pattern. By relying on RPA bots, HR eliminates output variations and maximizes efficiency.

– Scalability – RPA technologies have considerably low cost per task or effort per task than using human labor. The overall HR operation becomes more agile and lean with automation. This enables businesses to scale and sustain long-term growth.

– Reliability- RPA bots work 24/7 with consistent performance, an output that is much more reliable than human performance. The minimal error margin and constant productivity makes managing payroll easier.

RPA In Healthcare

Healthcare is a booming industry in the US especially robust since the emergence of the COVID- 19 pandemic. COVID has only accelerated digital transformation, and automation is the cornerstone of that trend.

In healthcare, providers have a large amount of paperwork and tasks in patient management that take away critical time from patient visits and customer service. By setting up RPA to integrate with internal systems, repetitive grunt tasks that bog down the healthcare system are minimized.

These tasks can include:

– Managing inventory

– Repetitive data entry

– Digitizing patient files

– Scheduling appointments

– Billing patients and processing claims

RPA In A Hospital

A closer look at the function of RPA in a hospital setting can show immediate gains in several important operational areas:

– For a large hospital, RPA can eliminate silos and create more efficient workflows

– Healthcare prioritizes patient satisfaction. RPA can give patients a transparent point of contact to their medical information. Once patient files are digitized, a patient can access from a single platform:

§ Medical history

§ Billing information

§ Scheduling information

§ Reminders

This capability immensely improved:

§ Patient satisfaction

§ Appointment turnaround

§ Payment collection

Conclusion

Whether in finance, HR, or healthcare the outcome of RPA is transformational. To truly understand its impact across industries, a business must look at the big picture. When businesses connect digital islands within the enterprise, real efficiency emerges to push the business forward into the future.

RPA is an emerging practice that evolves with rapid changes in technology. The buzzword for the future of RPA is hyperautomation. A concept that delivers automation of business processes with increasing complexity and input from human knowledge.

A New Era of Work

Today’s RPA practices are just the beginning of the revolution of work. With automation, businesses are progressing in digital transformation and changing the way humans approach work. For a business to become more digital and automated is to become more accessible for human ingenuity and intelligence to thrive

Technologies That Have Advanced Since COVID 19

Technologies That Have Advanced Since COVID 19

The world changed with the COVID 19 pandemic. As health concerns enveloped the globe, the COVID 19 pandemic began a new era in the modern workplace. Office buildings became deserted as workers adjusted to working from home. The upsurge in remote work has elevated the role of technology in the workplace. This trend extended beyond Zoom meetings and chat messengers to influence more advanced technologies in digital transformation such as Artificial intelligence (AI) and robotic process automation (RPA).

As the pandemic forced businesses to limit in-person contact and cut costs, technology is being used as an effective tool for meaningful interactions during a time of isolation and revenue stream. Moreover, it is reshaping and redefining the workplace to rely more on automation of redundant tasks to enable workers to focus on tasks that require human intelligence and ingenuity.

Demand For Digital Transformation Increases during COVID

Digital transformation has been evolving for years as technology progressed in the workplace.

The rise of the COVID 19 pandemic has increased the demand for digital transformation. Research has found that 59% of 373 IT decision-makers are implementing digital transformation at a faster rate due to the pandemic.

As a result, it is estimated that global spending on digital transformation efforts will increase by 10.4% in 2020 to $1.3 trillion according to data. As it stands, the innovative way to do business is also lucrative.

For digital transformation to be successful, a business needs to choose the right tools, people, and processes to transform the organization. At the core of digital transformation is content transformation. A business cannot evolve from analog to digital without updating legacy content to address the content needs of the modern audience.

Digital transformation has become a requirement rather than a choice in today’s competitive marketplace. During the time of COVID 19, a business that undergoes a successful digital transformation can expect:

– Enhanced customer experience

– Targeted personalization

– Increased revenues

– New insights

– Innovative business practices

– New opportunities

Artificial Intelligence And COVID 19

One of the core technologies of digital transformation is AI.

Historically, AI has been used in the workplace through HR information systems, marketing systems, and legal systems to help businesses communicate with employees and potential clients.

In the pandemic marketplace, businesses have further adopted AI in their operations. This is a result of pandemic restrictions that raised the need for contactless technologies as well as health and safety monitoring for the workplace. The way workers use technology has also changed. Workers have migrated over to video calls and virtual chats and use more wearables and other sensors in the workplace.

These behaviors have generated more quality data to train AI-based technologies for the workplace. As AI-driven solutions become more customized to the modern workplace, concerns over privacy and the use of data may emerge.

RPA And COVID 19

Another digital transformation technology is RPA, the automation of mundane and repetitive tasks by robotic bots has seen a surge during the COVID 19 pandemic. The economic downturn in the health crisis has only bolstered the adoption of RPA. The sharp increase in remote work requirements has prompted businesses to explore how automation can augment human intelligence.

RPA In Healthcare

RPA benefits the business by automating redundant and repetitive tasks that require zero creative input and human intelligence to execute. For example, healthcare can streamline patient record management and set appointments allowing the healthcare employees to spend more time on patient interactions. As the healthcare industry went virtual during the pandemic, AI was used to automate a lot of the backend of running a virtual healthcare practice. This pandemic shift has irretrievably changed the service delivery of healthcare in the world.

The world can be divided into the before and after of the COVID 19 pandemic. As society adjusts to the consequences of the pandemic, technological advancements in the workplace are having a moment. Increased demand in digital transformation for businesses has seen progress in technologies such as AI, RPA, and content transformation. It is the impact of these technologies on the workplace that is changing the way modern business is done.

4 Advantages of Serverless Computing

4 Advantages of Serverless Computing

What Is Serverless Computing?

Serverless computing is a method of providing backend services on as needed basis that is enabled by microservices. This contrasts with the early days of computing when developers who wanted to build an application had to have the physical hardware needed to run a server. As a result, a business that switches to serverless computing is gaining more scalability and flexibility at a reduced cost.

Serverless Computing Is A Technological Advancement

The world of technology moves fast. Technological advancements are evolving at lighting speed forcing businesses to adapt or risk obsolescence. One of the more recent technological advancement is serverless computing.

According to research, in 2020, 20% of global businesses will have implemented serverless computing. This adoption constitutes a mindset shift in the delivery and impact of technology services.

The 4 Advantages Of Serverless Computing:

Low Cost

For a business, IT services are a capital expense that needs managing. Therefore, it is lucrative to go serverless and cut costs. Instead of managing physical servers, the business outsources the responsibility of managing servers and databases. Besides a cost reduction, a business experiences savings in computing power and human resources. Serverless computing also saves on the operational expenses of servers crashing. If a business drops a new product to 10,000 users and then 10,000 users go to the website, the possibilities of servers being overloaded, and crashing is high. Consequently, customer experience and revenues suffer. Serverless computing is the solution for this problem.

Use Of Microservices

Another innovative way that serverless computing differs from its predecessor is its reliance on microservices. As opposed to monolithic services, microservices supports serverless computing in making precise application-specific developments and deploying individual applications. In fact, research shows using serverless microservices can reduce the standard release cycle by 75%.

A microservice is a self-contained piece of business functionality that can work independently or together as a whole. Overall, the presence of microservices in serverless computing makes the business more flexible at managing workload. It enables the business to estimate the amount of computing power it needs and not provision the servers upfront.

More Efficient

The advantage of serverless computing is that a business only pays for what it needed. When using traditional servers, a business would have to operate them 24/7. With serverless computing, a business is charged only when the server is used. This makes the business more efficient at managing its resources and eliminates the worry about scaling. The outsourcing of serverless computing also eliminates the concerns about:

-infrastructure

– setup

-capacity planning

More “Green” Computing

Increasingly, technology companies have become concerned about the environment and reducing waste. Serverless computing is sustainable. Servers only run when needed thereby reducing the use of electricity. The lack of physical servers and data centers cuts down on radiation and promotes health.

The research has supported sustainability efforts finding that 30% of servers globally remain unused at a given time. Even further, the physical servers that are in use run at 5%- 15% of total capacity. Serverless computing is not only sustainable but scalable.

Conclusion

All of the advantages of serverless computing indicate that it is a practice that is highly scalable and beneficial for businesses. It is an exciting breakthrough in the world of traditional computing that is gaining momentum. As a result, old ways of doing business are left in the past encouraging businesses to innovate and scale to new heights. Serverless computing is highly efficient, sustainable, and filled with opportunities that take a business into the future.

What Is IT Alignment?

What Is IT Alignment?

IT alignment is an organizational coordination in which IT department objectives are consistent with the goals of the organization and each department within the organization. As a result of the alignment, an IT strategy is formed that includes internal and external customers and enables technological innovation such as the use of microservices and agile methodology.

These days every business is a technology business. As technologies become more sophisticated, the adoption and execution of IT becomes more complex. The complexity of IT requirements furthers the divide between IT and business operations. These departments remain siloed with the business side clueless about IT processes and vice versa.

That is why the goal of IT alignment is gaining traction enterprise-wide. Research shows that by 2022 half of global organizations will achieve more collaboration between IT and business operations.

Alignment Expectations:

– Better tools

– Enhanced resources

– Smarter solutions

These advantages can position IT from being a capital expense in the organization to a business driver.

IT Alignment Benefits

When organizations align results to position IT as a business driver, it has numerous benefits:

– Cost reduction (a cut in the 10% of IT expenditure that doesn’t benefit the bottom line)

– Better collaboration

– Transparency in the organization

– Healthier ROI

– Quicker time to market

– Implementation of agile methodology

– Improved employee knowledge

– Better training opportunities in IT

– Strategic results in IT and across the enterprise

– Enables more efficient decision making in every area of the enterprise

– Increased productivity

– Better responsiveness

IT Alignment Steps

Once an organization realizes the potential of IT alignment, there are certain steps it can take to make it a reality.

1. Establish Processes

The first step of IT alignment is to change thinking processes around the way teams’ function. Most organizations are siloed lacking strategy and collaboration between teams. For increased efficiency and reduced risk, teams must understand cross-functional responsibilities and cross pollinate.

2. IT Transformation

The second step is to utilize IT as a tool for business transformation. Once a conversation has started between silos, IT should be positioned as a value add to other business units. By integrating teams, an organization can find new revenue streams involving IT.

3. Customer Experience

The third step is to focus on customer experience. In a siloed organization, it is difficult to get business units to “speak the same language”. By prioritizing customer experience, an organization finds a common goal to break down traditional silos.

4. Create An Alignment Plan

The fourth step is to create an alignment plan. Organizations should look into change management, how people process change, and management frameworks to encourage IT alignment. By having an actionable plan in place, it is easier to get the buy in across the enterprise to encourage transformational change.

Research has found that almost 90% of leading-edge organizations are integrating IT strategies into the company’s overall strategy. The transformation in process, talent engagement, and business models has been on the rise since the 2020 COVID 19 pandemic.

The COVID 19 pandemic has revolutionized work and made IT alignment a more critical part of a successful organization. As remote work became more prevalent, organizations had to become more agile and lean to accommodate remote working conditions.

It became important for IT and business operations to “speak the same language” and function holistically to achieve goals in a more competitive market. Remote work also fostered collaboration between IT teams and business teams as employees had to learn how to adjust to virtual team environments. It increased the dependency on technology as a solution rather than an expense.

What Is IT Agility?

What Is IT Agility?

IT agility is an organizational capability that requires IT leaders to change the framework of strategic and business operations. It is how a business adapts IT capabilities to market changes.

The way business is done in 2021 is radically different than even a few years ago. As businesses incorporate technological advances such as microservices and serverless computing into operations, they are faced with increased external demands to change internal processes.

The businesses that thrive past the competition are the ones that adapt and anticipate market demands. The marketplace has shown that most flexible businesses have the best chances of survival.

These businesses have mastered IT agility. What is IT agility? It is a business requirement, a part of digital transformation, and the speed at which businesses respond to opportunities. It measures the time between a business being introduced to an opportunity and acting on it.

IT Agility Benefits

Regardless of the size of the business, an agile business is leaner and has more efficient infrastructure. It also has a responsive system for up-to-date business. Other benefits include the business being able to iterate and move fast as the market changes as opposed to the traditional sequential process. Agile practices increase the time to value for a business and can be broken down into two different kinds: range-agility or time-agility.

Range-agility v. Time-agility

The benefits of range-agility are having the systems in place to adjust business services (more or less) based on demand and market conditions. It allows a business to get rid of lesser-used software, hardware, and products and streamline or add more in-demand solutions.

The benefits of time-agility are for a business to be able to act in smaller time increments. It is about being in the right position at the right time to adapt IT systems to opportunity. It is having the systems and personnel in place to go from inception to production in a short period of time.

While range-agility and time-agility are implemented in similar ways, they lead to different outcomes. Therefore, a business should choose which one is more appropriate for its goals.

How Customer Experience Impacts Agility

For businesses IT agility is a part of a larger initiative of digital transformation. Much more than new strategic plans and development practices, true agility requires a rethinking of the IT organization to succeed.

When a business takes steps to become more agile, it should do so with customer-centric delivery principles. That entails designing solutions around customer experiences, a focus on user feedback that dictates steps and improvements to the development.

In 2020, businesses faced a tremendous paradigm shift as the COVID-19 pandemic transformed remote work conditions. This forced agile practices to shift from software development to an enterprise-wide initiative that is adapted to change.

During COVID- 19, teams were focused on being internally efficient which made agile processes more relevant to the modern workplace. The adoption of agile processes that eliminate barriers and enhance improvements is freeing up businesses to work on the next steps of digital transformation.

For IT business being agile is not as much of an option as it is being part of the next wave of the future.

What Is A Microservice

What Is A Microservice

The general definition of microservices is a style of architecting applications as independent services, each of which serves a particular function for the business.

The pursuit of a digitized, data-centric enterprise has transformed IT teams globally. A part of the paradigm change is advancement in technology that shifted the requirements of IT departments.

Modern IT department Requirements:

– Encourage innovative thinking within their department

– Generate business applications that are always available

– Accommodate business users who want new ways to process data

These rigorous demands are almost impossible to meet, therefore a new class of business automation tools has been developed.

How IT Is Preparing For Microservices

Technological advancements place a demand on the enterprise in cost, execution, and adoption. Today’s enterprise is riddled with diverse and complicated problems that require innovation and disruption to resolve. Recently, the trend towards enterprise innovation has shifted towards business automation. A new practice that requires the agility and alignment of an IT department to succeed.

IT Agility 

For an IT department to become agile, it depends on the response of the enterprise to new business needs and desires of customers. However, the response of the enterprise is more than just recognizing a new requirement or desire, it is about being responsive in real time with new applications.

IT Alignment 

New business automation is better for the alignment of the IT department. This is because IT leaders are replacing C suite executives in leading efforts to create new applications that deliver a better UX experience.

IT leader concerns:

– reliability

– availability

– security

Business automation tools enable business users to design applications in secure and efficient ways.

The proliferation of this trend is seeing IT departments invest in ways to shift from monolithic applications to developing apps that are interchangeable with the rest of the organization’s infrastructure.

This practice began the rise of microservices in the enterprise.

Microservice Features

– Microservice is a singular process independent of one another

– Together microservices build a process

– The right microservice is a complete program that could run on its own

– Together microservices create an entire user experience

– For microservices, IT departments write components that do something and solve a problem

– Microservice processes are complementary yet independent

Microservice Vs. Client Service Microservice

The transition from monolithic services to microservices is based on trying to solve problems for a customer. Microservices have varying working definitions. One is a microservices architecture and the other is a client service microservice. While both microservices have general commonalities and are used as a solution to customer problems they differ in some ways. The former typically exists on the cloud and the latter is typically installed on a client interface.

Microservice Architecture

Components Of Microservice

Services

A microservice can be broken down into numerous component services. This is due to each service being independent; it should be able to be deployed, improved, and redeployed independently without compromising the integrity of the application. This gives the developers the flexibility to change one or more services without having to change the entire application.

Decentralized

By definition, microservices include a variety of technologies and platforms making traditional methods of centralized governance obsolete. The lack of reliance on centralized governance also makes microservices favor decentralized data management. While monolithic architecture uses a single database across different applications, in a microservice application, each service pulls from its unique database.

Scalable 

The essence of microservice architecture is taking one process and orchestrating it into a loose framework. A good example is a LEGO construction kit, which is a collection of blocks that can work together or stand-alone. Each component is doing its part for business goals. These parts contribute to a whole and together form a service. The services are joined in an API (application program interface) that regulates the interaction between system components. The independence of each service ensures its simplicity in development and maintenance as a standalone component. As a result, IT departments that use microservices for a system ensure its agility and scalability.

Client Service Microservice Architecture

Another microservice is client service microservice that typically exists on a client user interface. It is an orchestration of putting together “puzzle pieces” to solve an unknown problem for a client.

For example, the Content Analytics Platform (CAP) from Scion Analytics uses textual information as input to solve problems for a client. For enterprises, increasing client needs led to the refinement of the customer engagement process.

Components Of Client Service Microservice 

For Scion Analytics, it generated an innovation cycle with phases of:

Discovery And Planning 

The client and Scion Analytics team choose the best value use case from past experience and select and inform critical team members. They hold meetings to define input, output, and goals. Together, they identify measurable goals for the project.

Design 

The team does a gap analysis of the current process v new process and fleshes out the use case from the Discovery phase (input, output, test plan). The team prepares for the Development phase.

Develop

Critical team members work on the use case application. They create appropriate training material and documentation using the new application.

Test

 Team members develop test cases for the new application. Testing of courseware and documentation is done.

Implement

 After testing, the team deploys, supports, and maintains the platform and documentation for users. At the same time, they take note of issues and problems.

Measure

In the final phase, the team measures effectiveness and satisfaction. They make sure to deliver results in scheduled intervals (quarterly, semi-annual, or annual).

By taking a client through the innovation cycle, Scion Analytics determines the highest value and best use case for client needs with the CAP.

The Benefits Of Client Service Microservice

Time Savings

Client service microservice replaces human interaction with complete automation. It highly improves productivity because it runs without human involvement. The time savings for an enterprise are truly exponential. For example, Scion Analytics use cases have found that each time a client uses 1 microservice for every use it saves the client 8 hours. When 8 hours is saved in tangent with 30 employees at the same time, 240 hours is saved per use. The time savings grow exponentially when calculated annually and across the enterprise.

Automation

A user can analyze large amounts of documents quickly by setting up a client service microservice. By dropping the document into a folder, the user triggers the client service microservice to pick it up and process it. Once the client service microservice is done processing the document, it emails an output to the user. Conversely, without automation, a user would have to manually select the document and run the process.

Security

Another benefit that is particular to a client service microservice is security. By having a client service microservice installed on a client system, an enterprise ensures that sensitive and classified documents are protected.

How Microservice Enables Serverless Computing

To complement technological advances, another benefit of microservices is that it supports serverless computing. For example, if an enterprise has a system, it can have microservices running in the cloud. If this system is rolled out to a 10,000 client set at the same time it encourages 10,000 people to use the platform at the same time. This strains the servers and puts them in danger of crashing.

However, serverless computing in the cloud will give the enterprise the resource and computing power it needs. Serverless computing can only be set up if the system is written using microservices. Therefore, by adopting microservices, the enterprise also becomes more flexible with managing workload. If an enterprise is unsure about the amount of the workload on the servers or is using lots of servers but not provisioning them upfront, serverless computing will be the solution.

Conclusion

The Future of Work

By adopting microservices into the business process, an enterprise redefines the way work is done in the present and future.

By going through the customer engagement process, an enterprise ensures uniformity and consistency of processes and minimizes error. These are the features that are necessary for an enterprise to free up its workforce for more high-value tasks. This drives up employee satisfaction and as a result, it increases innovation in the enterprise. As the enterprise maximizes human intelligence and ingenuity, it opens itself up more to opportunity and scale. Thus, an enterprise that incorporates microservices is an enterprise transformed for the future.

Text Analytics, Nuns, and Language Density

Text Analytics, Nuns, and Language Density

The Age of Text Analytics

Welcome to the Internet. A stratosphere of content that is humming, exploding, and lighting up with content every minute. As of 2020, 78 million WordPress posts are going up every minute, 4.4 million Google searches a minute, and 350 million Tweets every minute. That is a lot of content to generate data for text analytics for marketing nerds everywhere.

Any experienced content creator knows that there is a difference between pushing out content to an audience and an audience engaging with content. The stratosphere is full of noise, chatter, waste but what about the content that influences, trends, and even goes viral?

The Nun Study

Text analytics can slice and dice data to uncover insights about consumer behavior. But science has a say in content creation as well. In 1990, the University of Minnesota did a “Nun Study” to look at the onset of Alzheimer’s. The population chosen for the study were nuns from the School Sisters of Notre Dame. A sample of 678 nuns from the congregation was chosen to have their brains examined post-mortem.

The findings were interesting.

The study looked at the “linguistic density” of essays written by the nuns at the age of 22. The evaluation of “linguistic density” could predict with 80-90% accuracy whether the nuns would develop Alzheimer’s later in life.

What is Linguistic Density?

A simple way to understand linguistic density is that it represents the number of ideas in a sentence divided by the number of words in a sentence. For example,

The girl’s cotton candy is pink.

This sentence has 3 ideas: The girl has candy.

The candy is cotton candy.

The color of the cotton candy is pink.

3 (Ideas)/6(Number of words)= 0.5 language density

Therefore, linguistic density is correlated with the complexity of language. Young people who write with a high linguistic density have lower instances of neurodegenerative diseases in old age.

Linguistic Density Of Writers

This principle can be applied to published writers as well. The University of Toronto did a study on the works of famed British author Agatha Christie. Christie was a prolific author throughout her life until the later years when her writing had become erratic and vague.

The research examined her book, “Elephants Can Remember” in which the main character cannot solve a crime because of her faltering memory. In that book, the size of Christie’s vocabulary decreases, she became repetitive, and the complexity of her words diminished significantly. Later in life, Christie became reclusive, and many fans hypothesized that she succumbed to a neurodegenerative disease.

Real Life Creates Content

Why is language density important when considering content on the Internet? Scientific findings have shown that the command of complex language is better for cognitive functions. But what about the consumption of complex language? Content that is more language dense provides more value to the reader. It intellectually challenges the audience and encourages them to exercise their brain.

High language density in content is more engaging to the reader. It paints a picture, tells a story, and makes for good data for Text analytics. In the content stratosphere that is the internet, high language density content is a bright star.

What is Text Mining?

What is Text Mining?

Text mining is an Artificial Intelligence (AI) technology that uses Natural Language Processing (NLP) to gain insights from unstructured text.

According to research, less than 1% of the data in the world is analyzed and processed. As businesses learn how to leverage data, they did not even know they had, they experience a paradigm shift in the way business is done. By using text mining and text analysis, a business can gain quantitative insights by tapping into text analytics.

The vast amount of data generated every day represents a tremendous opportunity for businesses across the world. It can be used to gain granular insights into customer feedback on a product or service.

This can be achieved by the flow of data from:

– Emails

– Product reviews

– Social media analytics

– Customer surveys

All these sources of data need to be processed to be actionable. That is where the practice of text mining comes in.

How Text Mining Works

Text Mining v. Text Analytics

To establish how text mining works, a distinction between text analytics v. text mining needs to be made. Text mining can be distinguished by the fact that it works on qualitative insights while text analytics produces quantitative insights. For example, text mining can analyze customer feedback to determine if customers are dissatisfied with a product. Text analytics can gather deeper insights on customer behavior from unstructured text, such as identifying a pattern or trend of customer behavior. For example, text analytics can be used to interpret a decline in the popularity of a product over time.

Qualitative insights from text mining can be enhanced using NLP. For example, one of the common uses of NLP/text analytics is social media monitoring. Social media monitoring is done on a large sample of user-generated content to understand behavior trends, emotional sentiment, and awareness about a given topic. Once that data is processed new and valuable insight can be gleaned into the collective customer mindset from social media behavior.

Types of Text Mining

There are different types of text mining that can be used for analysis:

1. Word frequency

Used to find recurrent terms or concepts in a data set. Finding patterns of recurring words in the unstructured text is beneficial in analyzing customer reviews as well as feedback and social media conversations. For example, if the word “overpriced” is recurrent on customer reviews, it may be a sign that the business needs to adjust pricing.

2. Collocation

A collocation is a sequence of words that are next to each other. Typically, collocations are either bigrams such as a pair of words (enterprise-wide, decision making) or trigrams, a combination of three words (go the distance, see you later). When text mining can identify collocations in a data set it improves granularity and delivers better results.

3. Concordance

This is used to identify the context of a word. Since human language has so many ambiguities and nuances, concordance can recognize the exact meaning of a word in a particular context.

How NLP is Used in Text Mining

NLP is a subset of AI that deals with communication. It can be powerful when combined with text mining to read information and identify what is most important. What is impressive about NLP/text mining is the sheer volume of data that can be analyzed across millions of documents in a data set for meaning and patterns.

Text mining And NLP Advantages:

· Saves time and resources

· Higher efficiency and less margin of error than human analysis

· Managing information flow

· Gather insights into valuable data

Text mining is a powerful resource for businesses to gain insights into large data sets and evaluate opportunities that are going to drive the business forward.

Text Analytics vs. Text Mining

Text Analytics vs. Text Mining

Text analytics vs. text mining can be distinguished by the fact that text mining works on qualitative insights while text analytics produces quantitative insights. For example, text mining can analyze surveys and reviews to see if customers are happy with a product. Text analytics can yield deeper insights on customer behavior from unstructured text, such as identifying a pattern or trend of customer behavior. Text analysis is an evolving technique that is revolutionizing the global economy. Part of this evolution has been the development of an array of techniques to derive meaning from text.

Text Analytics And Text Mining Use Different Approaches

While text analytics and text mining are often used interchangeably, they differ in that text analytics delivers quantitative insights and text mining delivers qualitative insights.

Text Analytics Approach

Quantitative insights: rely on statistical modeling for “out of the box” solutions to any text analysis problem.

Text Mining Approach

Qualitative insights: use linguistic rules to deliver complex outputs with more precision.

Text Analytics vs. Text Mining Examples

Texting Mining Used For Sentiment Analysis

Text mining is an older technique than text analysis. It has found an application in sentiment analysis or opinion mining on social media. Social media is a perfect breeding ground for text mining with:

– Tweets

– Facebook posts

– Instagram posts

– LinkedIn posts

Sentiment analysis uses Machine Learning and NLP to automatically analyze text for the sentiment of the writer. A single tweet can have a positive, negative, or neutral connotation for a brand based on the analysis of the sentiment of the writer.

– For example, the more information a business has about customers at its disposal, the more it can determine whether customers are happy with a product.

The unstructured data of social media posts presents an opportunity for businesses to become more responsive to customers and sustain long-term growth.

Text Analytics Used For Linguistic Approaches

Text analytics uses a linguistic approach for extracting value from unstructured textual data. Text analytics is more complex than text mining requiring sophisticated taxonomies or other structured lists as guidelines.

Once those guidelines are in place, text analytics works on large collections of unstructured data to discover new insights. Whereas text mining is better used to solve a particular problem, text analytics looks at the big picture of a problem.

– For example, a large data set of tweets are analyzed to predict a trend in customer behavior.

Actions made on data rather than guesswork enables informed decision-making that revolutionizes the course of business operations.

Conclusion

When it comes to leveraging the untapped value of unstructured data, text analytics and text mining are complementary techniques with different approaches. Text mining uses statistics while text analytics uses linguistics to wrangle unstructured data. Each can be practiced independently yet the most effective solutions combine their strengths.

Businesses can benefit from the balance of precision of linguistically based text analytics and the powerful recall of statistical text mining. With such a combination, great progress is being made on the future of text analytics in the world. A variety of textual analysis challenges can be met with text mining and text analytics leaving room for innovation.

Text Analytics Benefits

Text Analytics Benefits

Text analytics is shaping the future of how data is used to do business.

Using unstructured data (free form text that is not organized), text analytics can provide valuable new insights to help businesses:

– make data-driven decisions

– simplify data

– become more responsive to customers

The benefits of text analytics are redefining societal progress across industries. It happens when businesses identify, prioritize, and leverage text analytics results with real-world applications to the core of each business.

Identify Value In Unstructured Data

Text analytics enables businesses to analyze previously untapped large sets of unstructured data. Traditionally, unstructured data is difficult to get to and hard to work with. It is labor-intensive like “data trapped in virtual or physical filing cabinets”.

Discover New Opportunities In Your Text

It is estimated that 80% of unstructured data has not been accessed by businesses.

By using text analytics, businesses discover new opportunities to mine and analyze large data sets of customer feedback to identify trends in behavior from:

– social media

– live chats

– surveys

– emails

This newfound information takes the place of guesswork when it comes to concerns and decision-making for the business.

Prioritize Consumer Information

It also enables the business to be more sensitive to the changing needs of customers. Text analytics empowers businesses to prioritize decisions based on informed results. For a business, knowing the “who, what, where is being talked about” is part of the solution. Being able to prioritize that direct, verbatim information and execute on it is what makes text analytics transformational for businesses.

Leverage Text Insights

 When a business discovers text analytics, it can take a single insight into a customer’s mindset to cause a paradigm shift in business operations. A business experiences increased productivity, revenues, and cost savings with the ability to:

· Improve user experience

· Enhance business intelligence

· Conduct market research

· Detect product issues

· Monitor brand reputation

Other than practical applications, text analytics has strategic benefits for businesses.

Simplify Unstructured Data

For one, text analytics makes unstructured data simple. Now, it is easy to filter, search, and cross-reference unstructured data in an instant making it much more scalable.

Scale Your Enterprise

It is precisely this scalability that makes text analytics an effective enterprise-wide solution for data-driven decisions. It has no organizational boundaries making it a process that can create a foundation for enterprise-wide analytics.

Innovate Your Enterprise With Text Analytics Insights

Today’s business climate can change drastically overnight, in response to new technology, feedback, or innovation. Text analytics can empower businesses to find new opportunities and gain a competitive advantage. A benefit of text analytics is accessing new insights that were previously unknown or unavailable to the business. This capability drives business innovations into new markets and products.

Conclusion

The new generation of text analytics tools, such as the Content Analytics Platform (CAP) from Scion Analytics, leverage Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies to enhance capabilities for quantitative insights.

The bottom line is that there are many benefits of text analytics for businesses. It enables enterprises to uncover hidden signals in data to make smarter decisions. Confident and prompt decisions not based on guesswork sustain the long-term growth of the business. This is the way text analytics is shaping the future of businesses across industries.