Automation Archives - Page 5 Of 38

Low-code Market Realities: Understanding Common Myths to Avoid Costly Mistakes

June 23, 2022

Despite their growth, low-code platforms are still surrounded by much confusion. Many enterprises incorrectly believe that real developers don’t need low code, anyone can do it, and it’s only for simple problems. To debunk three common myths in the low-code market, read on.

With its increasing importance, low-code platforms are also subject to several myths and misunderstandings. As with every evolving technology, enterprises have many questions about optimally using these platforms.

Based on our conversations with multiple enterprises confirming the lack of understanding about the low-code market, we tackle the common misperceptions below:

Myth #1: Low-code platforms are meant for use by citizen developers

The term low code generally evokes the impression of an HR manager who, tired of following up with the IT team multiple times, decides to create a leave approval workflow application. While this impression is not incorrect, professional developers and enterprise IT teams are key stakeholders in the low-code ecosystem as well.

Professional developers increasingly use low-code platforms to improve their efficiency. Some of these platforms can provide code quality alerts and Artificial Intelligence (AI)-powered recommendations, not to mention custom solutions that require minimal tuning.

The built-in DevOps capabilities in these platforms also encourage a culture shift from the commonly used waterfall model among users. For example, supply chain management software provider Nimbi significantly reduced developers in their team from 40 to 24 when they switched to OutSystems from traditional platforms.

We strongly believe central IT teams have a meaningful role in the ecosystem to provide effective oversight and governance, in addition to strategizing the use of the best low-code platforms at the enterprise level. In the absence of centralized governance, low-code platforms may proliferate across the organization leading to aggravation of the shadow IT issues and higher spend.

Myth #2: Low-code development does not require technical skills

As much as we may want to believe, low-code platforms are not a panacea to the ongoing talent crisis. Misleading promises by certain technology vendors have created a common impression that any user can develop any application using low-code platforms. However, low-code development does not imply zero technical skill requirement.

Most low-code platforms enable the extension of their capabilities through traditional programming languages like Java and C#. Off-the-shelf solutions have their limitations, and most applications need custom logic at some point. Typical job descriptions for low-code developer profiles outline technical qualifications like JavaScript, HTML5, and CSS3, alongside Continuous Integration (CI) and Continuous Delivery (CD) pipeline tools like Jenkins.

Thus, it is unrealistic to expect an army of business users to step in and take over all application development-related needs from the IT organization. Low-code development remains a role with a highly demanding skillset across various technologies.

Myth #3: Low code cannot be used for enterprise-grade development

Many enterprise leaders and service providers believe that low-code platforms are only suitable for small-scale department-level needs. However, our conversations indicate that low-code platforms are being rapidly adopted for critical applications used by millions of users. Here are some examples of how low code is solving complex IT problems around the world:

A large US commercial insurer has built its entire end-to-end multi-country comprehensive, business-critical application that manages claims, billing, and collection on Appian
One of the largest consumer goods companies in the world built a huge global application for financial management on Microsoft Power Platform

As we witness the adoption of low-code platforms garnering pace, a lot of myths and misunderstandings need to be cleared up about low code versus traditional development. Technology providers and service partners play a key role in helping their clients navigate the abundant options to orchestrate a carefully crafted low-code strategy and select the best low-code platforms.

At Everest Group, we are closely tracking the low-code market. For more insights, see our compendium report on various platform providers, the state of the low-code market report shedding light on the enterprise adoption journey, and a PEAK Matrix assessment comparing 14 leading players in the low-code market.

To share your thoughts and discuss our low-code market research, please reach out to [email protected], [email protected] or [email protected].

You can also attend our webinar, Building Successful Digital Product Engineering Businesses, to explore how enterprises are investing in next-generation technologies and talent and the most relevant skillsets for digital product engineering initiatives.

Healthcare Payer BPS Market: Automation Adoption, Potential, and Technologies | Market Insights™

June 6, 2022

Healthcare Payer

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5 Intelligent Process Automation Trends to Watch | In the News

June 3, 2022

Financial services organizations are digitizing and automating more processes to keep up with competition, and intelligent process automation (IPA) — which has been growing in use about 20% across all fields — is now becoming ubiquitous. Market research firm Everest Group in a recent report ranked IPA technology vendors and looked at the market for process automation.

Three Ways Companies Can Cope with the AI and Analytics Talent Crunch | In the News

May 26, 2022

With inflation in the United States at a 40-year high and unemployment near a 50-year low, these are tough times to attract and retain employees in just about every sector. When you add the growing demand for talent in high tech sectors like big data and AI, you get a job market that’s great for these workers, but tough for companies.

David Rickard of Everest Group, a respected provider of insight for the global BPO industry, says that while countries like India have a lot to offer now, there are some other locales that should be on your radar, including Africa.

Everest Group Enterprise Intelligent Automation Adoption Maturity Report | In the News

May 16, 2022

This fully comprehensive study of enterprise intelligent automation adoption maturity from respected research firm Everest Group offers actionable insights for intelligent automation strategy and implementation.

Is AI Emotion Detection Ready for Prime Time?

May 13, 2022

Artificial Intelligence (AI) solutions that aim to recognize human emotions can provide useful insights for hiring, marketing, and other purposes. But their use also raises serious questions about accuracy, bias, and privacy. To learn about three common barriers that need to be overcome for AI emotion detection to become more mainstream, read on.

By using machine learning to mimic human intelligence, AI can execute everything from minimal and repetitive tasks to those requiring more “human” cognition. Now, AI solutions are popping up that go as far as to interpret human emotion. In solutions where AI and human emotion intersect, does the technology help, or deliver more trouble than value?

While we are starting to see emotion detection using AI in various technologies, several barriers to adoption exist, and serious questions arise as to whether the technology is ready to be widely used. AI that aims to interpret or replace human interactions can be flawed because of underlying assumptions made when the machine was trained. Another concern is the broader question of why anyone would want to have this technology used on them. Is the relationship equal between the organization using the technology and the individual on whom the technology is being used? Concerns like these need to be addressed for this type of AI to take off.

Let’s explore three common barriers to emotion detection using AI:

Barrier #1: Is AI emotion detection ethical for all involved?

Newly launched AI-based solutions that track human sentiment for sales, human resources, instruction, and telehealth can help provide useful insights by understanding people’s reactions during virtual conversations.

While talking through the screens, the AI tracks the sentiment of the person, or people, who are taking the information in, including their reactions and feedback. The person being tracked could be a prospective customer, employee, student, patient, etc., where it’s beneficial for the person leading the virtual interaction to better understand how the individual receiving the information is feeling and what they could be thinking.

This kind of AI could be viewed as ethical in human resources, telehealth, or educational use cases because it could benefit both the person delivering the information and those receiving the information to track reactions, such as fear, concern, or boredom. In this situation, the software could help deliver a better outcome for the person being assessed. However, few other use cases are available where it is advantageous for everyone involved to have one person get a “competitive advantage” over another in a virtual conversation by using AI technology.

Barrier #2: Can discomfort and feelings of intrusion with AI emotion detection be overcome?

This brings us to the next barrier – why should anyone agree to have this software turned on during a virtual conversation? If someone knows of an offset in control during a virtual conversation, the AI software comes across as incredibly intrusive. If people need to agree to be judged by the AI software in some form or another, many could decline just because of its invasive nature.

People are becoming more comfortable with technology and what it can do for us; however, people still want to feel like they have control of their decisions and emotions.

Barrier #3: How do we know if the results of emotion detection using AI are accurate?

We put a lot of trust in the accuracy of technology today, and generally, we don’t always consider how technology develops its abilities. The results for emotion-detecting AI depend heavily on the quality of the inputs that are training the AI. For example, the technology must consider not only how human emotion varies from person to person but the vast differences in body language and non-verbal communication from one culture to another. Users also will want to consider the value and impact of the recommendations that come out of the analysis and if it drives the desired behaviors that were intended.

Getting accurate data from using this kind of AI software could help businesses better meet the needs of customers and employees, and health and education institutions deliver better services. AI can pick up on small nuances that may otherwise be missed entirely and be useful in job hiring and other decision making.

But inaccurate data could alter what would otherwise have been a genuine conversation. Until accuracy improves, users should focus on whether the analytics determine the messages correctly and if overall patterns exist that can be used for future interactions. While potentially promising, AI emotion detection may still have some learning to do before it’s ready for prime time.

Learn more about recent advances in technology in our webinar, Building Successful Digital Product Engineering Businesses. Everest Group experts will discuss the massive digital wave in the engineering world as smart, connected, autonomous, and intelligent physical and hardware products take center stage.

Resilience and Stability in the Workers’ Compensation Industry – This is the Right Time for Claims Transformation to Secure Future Growth | Blog

April 22, 2022

As the workers’ compensation industry emerges from the pandemic, leveraging digital technologies to transform claims handling and taking a customer-centric approach will help carriers maintain profitability. By using automation, analytics, and digitalization, players can differentiate themselves. To learn about the key workers’ compensation trends to pay attention to, read on.

The workers’ compensation industry has remained profitable through the pandemic, with claims severity remaining consistent and frequency continuing to decrease. But reduced net written premium, low-interest rates, and the economic slowdown are creating top-line pressures. Moreover, the sustainability of profits is not guaranteed.

As COVID-19 subsides and most industries return to normal workways, the workers’ compensation industry could face difficulties in holding on to gains if it doesn’t chart a dedicated plan to improve productivity, employee experience, and employer mandates to create market differentiation.

Process standardization and simplification are the need of the hour. The workers’ compensation industry must move from the “repent and repair” model to “prevent and prepare” by leveraging business intelligence through an end-to-end real-time data flow across processes to enable a more customer-centric approach toward claims handling.

Currently, efficiency is impacted by the lack of information that results in back-and-forth requests on multiple claims touchpoints. By integrating processes, carriers can obtain real-time data to design standard workflow for Straight-through Processing (STP), exception handling capabilities, fraud detection and claim reserves calculation, and reduce overall claims function cycle time.

Challenges to overcome for claims transformation

In addition to concerns and uncertainty about the long-term effects of the pandemic, the workers’ compensation industry faces the challenge of outdated workflows with heritage issues such as:

Lack of information at each node in the claims management process that increases cycle time and leads to poor end-user experience
Paper-based processes that are roadblocks to enabling a virtual ecosystem consisting of digital payments, paperless documents, e-signature, e-inspection, and sundry processes
Cumbersome manual functions that should be automated
Lack of a framework for standardized processes and segregating functions, requiring customization such as objectionable and non-objectionable items having to follow the same workflow
Claims not being linked to risk assessment and reporting, which impacts new business and renewals and the mapping of profitable and loss-making segments
Inability to benchmark claims, assess claims performance, and understand market impact

To continue its growth, workers’ compensation industry players should look to implement digital transformation and optimize processes to reduce claims turnaround time. Carriers who focus on digital solutions and leverage data through automation and analytics will successfully pivot for the future.

Traditional claims versus digital claims

Exhibit 1: Everest Group

Three workers’ compensation industry trends to watch

1 – The role of automation

Workers’ compensation claims consist of workflows requiring minimal manual intervention where automation can work as an enabler providing numerous benefits such as:

Enhanced user experience through conversational Artificial Intelligence (AI) for First Report of Injury (FROI)
Improved data validation and elimination of human error, enabling early-fraud detection and reduction in leakages
Automated claims routing for risk assessment through SOPs for STP, exceptions, and large claims
Auto approval of bills based on claim and treatment parameters can shorten handling time
Better claims capacity, improved backlog on open claims, speed to adjudication, and faster return-to-work solutions

Digital intake can remove friction and deliver a captivating experience for all stakeholders. By focusing on automation, workers’ compensation carriers will not only improve operational efficiency but also reduce operational costs – resulting in bottom-line benefits.

2 – Advancement in analytics

By adopting enhanced analytical capabilities, workers’ compensation carriers can increase their focus on the end-user experience and take a more proactive, prevention-based approach. Here are some ways this can be done:

Predictive and prescriptive analytics for insights on safety parameters will help prevent accidents and injuries
Predicting risk upon claim intake will smoothen the claim cycle for all stakeholders
Auto assignment of claims to an adjuster with relevant experience for backend issues
Individual and aggregated claims-based rules with persona-specific dashboards for different injury types
Implementing Key Performance Indicators (KPI) for assessing analytical potential

Advancement in analytics with proper predictive modeling techniques will reduce claims cost and improve claims severity, which, in turn, will deliver enhanced profitability.

3- Digital ecosystem and a safe workplace

The evolution of workers’ compensation claims in the future will depend largely on the assessment of intake efficiency, moving away from redundant processes, and instituting digital and data-led workflows. Technology usage will not only depend on the number of datasets with a carrier but also on the value generated to create new models for transforming the entire claims solution.

The cornerstone for transformation should be prevention and preparedness. With many organizations choosing to operate in a hybrid working model post-pandemic, it is imperative to assess the long-term impact of such changes. Internet of Things (IoT) and telematics can help achieve this through initiatives such as:

Smart workplaces with sensors, cameras, and other intelligent devices for continuous supervision
Digital collaborations for safety training and mechanisms with loss controllers
Wearable devices for loss prevention and control
Creating digital safety communities

With the pandemic pushing workforces to stay at home, telemedicine has gained popularity providing employees with medical consultation and reducing the away-from-work time. It is offering immediate care and a faster inquiry process by having expert medical professionals available. Telemedicine also helped promote claims advocacy and assisted in intake and triage through digital authorizations and workflow development for assigning priority to claim categories.

In the end, employers want stability and predictability of final claim costs. Regardless of how these macro trends affect the Workers’ Compensation industry, the focus should be on creating a safe workplace and taking all measures to prevent injuries and hazards.

To discuss workers’ compensation industry trends, reach out to Abhimanyu Awasthi at [email protected], Somya Bhadola at [email protected], or contact us.

Workplace leaders are also now able to focus more on creating an experience-centric workplace through digital technologies, delivering superior user performance and job satisfaction. Learn more in our webinar, Top Strategies for Creating an Employee-focused Digital Workplace.

Deconstructing the Future of Work | In the News

April 12, 2022

Four-day weeks, on-demand pay, “rural” talent, digital workers… in recent times, we’ve heard these ideas accompanied by seemingly teleological questions about work as a construct.

The timing is understandable given the confluence of factors at play – the rise of digital, labor pyramid issues, and the after-effects of a global pandemic, including a desire for more meaning in work and convenience through remote work. After years of navel-gazing, society is finally waking up to the fact that our jobs, the way we do them, the time we spend, and the very fundamentals of the nature of work itself are perhaps incongruent with the world we now live in.

This realization opens up the very promising possibility of re-examining and perhaps reconstructing work for the new era. But, beyond the clarion call, what exactly does it entail, how do we understand the future of work, and how do we design for it? Fundamentally, we can break it down into three distinct components: the how, the where, and the who.

Read the full article on Business Reporter

Low-code Adoption: Three Phases | Market Insights™

March 25, 2022

Low-code

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Low-code Pricing Model Dependent on Adoption Maturity | Market Insights™