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The pandemic has changed how people around the world live, work, and engage with each other. In late 2019 when covid-19 struck the world, affecting millions of people all over the planet — the healthcare industry was hit the most. The pressing need for resources, information, cost optimization, and supply chain inefficiencies in the sector calls for a major technology overhaul. Therefore, embracing new-age digital technologies is key for healthcare providers in addressing the immediate concerns and driving long-term goals.

Automation makes a revolutionary process change in most of the industries, that has the same or even more potential for the healthcare sector. Introduction of Business Process automation can streamline the healthcare system for simplicity, increase service quality, and manage pen and paper-based manual tasks, saving time and cost without the slightest glitch.

Challenges in Healthcare

Application Disparity: Modern healthcare is a complex environment where many disparate applications work. The complexities also grow with the business. With mergers and acquisitions, modern technologies are adopted to meet new challenges. In this situation managing all technology becomes quite difficult for the healthcare IT departments and business users.

For example, in most healthcare sectors, patient data transfer is still carried out manually in the form of files and documents from one department to another. As the volumes of data are generally high, compiling them in one single process is a tedious and lengthy process. Not to forget, since they are done manually, there is always scope for multiple human errors and miscalculations. The greater the rate of error, the more the cost will be for rectification.

Lack of efficiency in patient service is another challenge that can be a barrier to your organization’s growth and reputation. In most scenarios, customer care executives are busy with paper works and other files and documents compilation that they lack prompt and timely delivery of services to the customers.

I hope you can relate to the problems I discussed above. So now I am going to share how automation becomes an integral part to solve some of healthcare challenges.

 The business automation software works on all programs whether, new applications, legacy programs, cloud-based solutions, or on-prem.

BPA makes human-oriented processes much smoother with greater results like increased speed, productivity, and efficiency. Suppose for a patient, scheduling an appointment with a doctor usually happens online in a matter of minutes, but what happens behind the scenes is a bit more complicated. Healthcare institutions have to collect personal information, diagnosis, insurance details, and confirm the doctor’s availability. If the right information cannot be accessed during the registration process, or if the doctor is not available, it is up to the staff to inform the patient beforehand.

Implementing automation can resolve some of the bottlenecks related to scheduling patient appointments. Bots can automate patient data collection and processing, so patients can be optimally scheduled according to diagnosis, location, doctor availability, and other criteria. By simplifying appointment scheduling, healthcare institutions can focus their efforts on providing exceptional service and other tasks that cannot be automated. Automation tools also enable customer care executives to take the assistance of such tools with automated call and email options.

Inovar proposed Automation Solutions with better ROI

Something similar also happened with one of our US healthcare clients. They were also facing customer support challenges during the pandemic. They were primarily using a pen and paper-based system for information collection and symptom analysis. After the outbreak of the virus, a lot of patients started asking for support in their chatbot regarding diagnosis, vaccination, and other medical support.

With a lot of restrictions, it becomes necessary to give patients the capability to run the assessments on their own from the comfort of their homes. Remote work capability also became especially important, and they needed an infrastructure through which they can achieve that.

To manage the entire scenario, they required VPN, which was not designed for such large-scale use resulting in low bandwidth and frequent outages. Additionally, a lot of the content and manual workflows required the physical presence of the employees on the hospital premises that was quite impossible at that moment.

In this critical situation, the first hurdle to cross was to get them to a cloud-based solution to ride care facilities across all their nation-level operations and provide the best health support to patients. This would make remote work possible for the hospital staff in case they were showing symptoms and had to quarantine at home.

In this situation, Inovar helped a leading US healthcare organization to automate their Covid-19 Helpdesk and Registration process from a pen and paper-based manual system to a cloud-based automated solution.

SharePoint Online became the choice of the platform along with Power Platform as their primary productivity technologies allowed them to create a technology framework with a built-in rapid growth mechanism and assist hospital staff to manage the entire remote work process.

With the implementation of the initial solution, the healthcare organization was also facing challenges to roll out the solution in all other locations of the US that becomes much fair with SharePoint and the power platform.

A simple but practical experience gained a high adoption rate within the healthcare organization. The organization’s IT team also considered it as the best rollout experience with almost a zero-touch provisioning and deployment strategy. Ultimately, with all these solutions 90% of their remote and quarantined caregivers were able to serve the patients over remote calls and Online consultation.

The digitization of call centers was a major bonus as it consisted of Automated Diagnosis for Covid, automatic decision-making capabilities, and other similar tools that ensured self-help services that were non-existent before. This resulted in a reduction of 70% in phone calls.

Businesses transitioning from manual processes to comprehensive workload automation tend to go through several phases on their automation journey. If you are also facing the same difficulties within your organization, then Inovar is the best partner to collaborate with and make your automation journey smoother. Feel free to reach out to us we would love to collaborate!

With every progressive step of technological advancements, the priorities of CIOs are also changing. Process transformation and automation have gained much of leaders’ attention in recent times. Automation, the use of machines to perform work, most commonly refers to using the use of computer technologies to perform the tasks humans would otherwise do as part of their jobs. The use of computer-based process automation is widespread, with organizations deploying a broad range of software automation tools to help them reach the automation goals they set as part of their larger digital transformation objectives.

According to the December 2020 Global Intelligent Automation (intelligence AI) Study from Deloitte, *73% of organizations worldwide use automation technologies. That’s a significant increase from the *58% of organizations using such technologies in 2019. Gartner reported that organizations’ interest in a process of transformation is accelerating, demand for robotic process automation (RPA) software witnessing the growth of **19.5% from 2020.

But, RPA is not the only process automation technology that companies are leveraging to drive goals, efficiency, and digital transformation. The diversified business sector embraces certain other automation options such as business process automation (BPA) and digital process automation (DPA). Each of the three technologies offers benefits, and each has distinctions that separate it from the others.
What is robotic process automation (RPA)?

RPA technology mimics the way humans interact with software via a UI to perform high-volume, repetitive tasks. The technology creates software programs, or bots, that can log in to applications, enter data, calculate, and complete tasks, and copy data between applications or workflows as required. But RPA doesn’t inherently have intelligence or decision-making capabilities. Hence, the work best suited to RPA is rules-based. These are discrete tasks done the same way over and over, with no deviations that require human decision-making. According to Gartner, RPA represents a major portion of the automation market. Experts believe that the primary benefits of RPA are increased efficiency, lower costs, and reduced errors. RPA bots can perform tasks faster and with consistent accuracy and reliability. They can work round-the-clock without taking breaks.

Another reason for RPA’s growing popularity in the enterprise is its relative ease of use. RPA works with an organization’s existing infrastructure and applications. Also, because many vendors offer low-code/no-code RPA platforms that require little to no programming experience, business users can harness RPA, creating their own bots with minimal help from their IT departments. As such, business users are driving much of the RPA adoption.

What is digital process automation (DPA)?

DPA is a software technology used to automate a process and optimize the workflow within an automated process. A big focus of DPA is to improve employee and customer experiences by taking friction out of the workflow. The software is used to create efficiencies and enhance UX experience in various areas of the enterprise, from IT service requests to onboarding new employees and client intake.

Organizations use DPA to automate a process from its beginning to its end. Typically, DPA is used for the longer and more complex processes than the tasks that can be effectively handled by RPA. These processes can contain multitudes of decisions that, if using RPA, would create bots that are too long and too difficult to maintain.

As per a ***Forrester schema, DPA is divided into two types: DPA-deep, and DPA-wide, which is closely related to RPA:

What is business process automation (BPA)?

BPA automates workflows within an organization; as one step in the business process is completed, the BPA software then automatically triggers the next step. BPA software is used to automate complex, multistep business processes that are usually unique to an organization and are part of the organization’s core business functions.

Size of the business process automation system (BPA) market worldwide from 2016 to 2021

BPA’s holistic approach stems from the technology’s capability to work across the multiple enterprise applications and systems required to complete a typical business process. Organizations often first analyze and improve a business process with a BPA approach before automating it, which is different from the mimic-as-is tactic typically used in RPA.

Reworked, optimized processes using BPA remove human hands from the workflow; with human workers no longer involved in the automated process, they’re not introducing individual workarounds or unauthorized changes to the workflow. Consequently, enterprises use BPA in their digital transformation efforts for the accuracy, efficiency, and reliability it brings to each automated process.

Experts Opinion on – RPA Vs BPA Vs DPA

Some experts use BPA as an umbrella term for a wide range of process automation technologies but there are varied opinions on that concern as well.

According to Gina Schaefer, intelligent automation lead at Deloitte Consulting LLP said- “DPA, BPA, and RPA — are practically interchangeable.”

She further added – “Digital, business process and robotic process automation are essentially the same. When applied appropriately, these refer to comprehensive end-to-end process automation. Specifically, these terms refer to the use of scripted automation software to mimic human actions in the execution of rules-based ‘swivel chair’ type tasks, typically where an individual accesses and processes data from multiple applications.”

difference between RPA, BPA and DPA

InovarTech is ready to improve your automation experience. With our smart forms and streamlined workflows, you will be ready to tackle process technologies and know-how to adapt them to your institution. Reach out to us today to get started. You can take comfort in the fact that we know process automation and how to implement them effectively. Let us deliver high-volume processes to your doorstep.

Resources:

*https://searchcio.techtarget.com/tip/Process-automation-technologies-evolve-RPA-vs-BPA-vs-DPA#:~:text=Another%20difference%3A%20While%20RPA%20and,as%20they%20do%20their%20work.

**https://www.information-age.com/rpa-revenue-reach-nearly-2-billion-2021-gartner-123491711/

***https://www.forrester.com/report/RPA+DPA+BPM+And+DCM+Platforms+The+Differences+You+Need+To+Know/-/E-RES145378

Business process automation now becomes the new norm at the workplace to cope with a fast-paced economy and growing challenges for modern business. While a few organizations may very well consider automating their IT tasks, RPA likewise means to help them rehashing the way they work together, uplifting their consumer loyalty and fortifying employee work values. The necessity of bringing automation has given a boost to Robotic Process Automation (RPA) solutions. But AI (Artificial Intelligence) comes into the center stage as entrepreneurs craving more assistance from robotic process automation. Near future, it would be hard to imagine the RPA solution without AI integration.  

According to Forester’s 2019 predictions, the combination of RPA and AI is becoming the new strategic

investment in the corporate world. AI and RPA are emerging automation technologies with enormous potential. The combination helps businesses in achieving tremendous growth in such a competitive market. 

You may curious why a business should combine these two technologies? 

The reason is simple- RPA has no capability of cognitive awareness, and AI brings it in the customized solution. This combination of AI and RPA adds up to intelligent process automation (IPA). In interest to machine learning algorithms and RPA, IPA also incorporates process management software, natural language processing, creation, and cognitive agents, or “bots.” According to McKinsey, IPA can – 

Make an improvement in ROI in triple-digit percentage. TMR (Transparency Market Research) has predicted RPA will be prevalent in the corporate world that its market to reach up to $16 billion by 2024. On the other hand, AI focused on imparting intelligence in the machines and connected devices through speech recognition, decision making, and predictive analysis. 

As AI is gaining ground swiftly across the world, it can be integrated with other emerging technologies like IoT and Blockchain to realize the futuristic concepts of smart cities and secure transactions sequentially. McKinsey foresees AI to deliver around $3.5 to $5.8 trillion in value to the world per annum.  

How AI enhances RPA services 

AI and RPA combination enables modern enterprises to leverage the benefits of both these technologies in accomplishing incomparable tasks with higher efficiency. It is like something beyond the range of a customized RPA solution because it develops to perform the same and repetitive type of work.  

At the point of a substantial change is anything but a reasonable alternative for companies, RPA can go about as a facilitator to enable organizations to grow and include value. It also permits them to appear with strategic frameworks around investment they’ve efficiently made into their custom frameworks. The assimilation into AI is the following stage of this granular, more responsive type of change, with more business exercises either completely or partially automated by progressively refined means. It is known as cognitive RPA or CRPA.  

RPA alone imitates human action through different AI capabilities, machine vision, speech recognition, and pattern identification capacities and can deal with organized, semi-organized, and unstructured data. However, infused with machine learning gives robots a chance to figure out how to process and enhance tasks that ensure probabilistic conduct.  

AI integrated Robotic Process Automation solutions bring the capability of gathering and sharing valuable information with different systems for better decisions. Customized RPA solution can utilize data fetched by AI and performs the complex task with ease. Adding up, AI, commonly with cognitive technologies and ML (Machine Learning), enables robotic process automation by preceding a human response in the workflow. 

The humble bot 

Organizations aren’t looking for just a bot. They have been looking for a platform with orchestration and integration where, they could readily adopt modern technologies and combine them with intelligence. Now, most organizations are strategizing to automate most of the steps of a business process and then applying a different level of intelligence. Hence, when picking vendors for their bots, the enterprises keep their eye towards that future.  

Just like, Germany’s ZF Group, an automotive supplier has started applying intelligence to its business processes just over a year ago and created a bot to answer the most repetitive questions. According to the company’s IT manager around their corporate communication, they have a lot of repetitive work. Furthermore, they receive a lot of emails with repetitive questions coming into their inboxes. Automated integrations and orchestration were their first goal, and they also wanted a platform with built-in checks and balances. Finally, they choose a bot platform that offers a management, governance, and language support layer underneath the bots, called stateful network for AI process (SNAP), which will stop a bot if it demonstrates anomalous behavior.  

Real-time Decision support system  

Decision points are another way to add intelligent decision points into a traditionally automated business process. Nevertheless, cognitive technologies and machine learning direct out to be even more severe. In general, when AI technologies are integrated with RPA stages will automate the emotional and judgment-based process. 

Just like American Fidelity Assurance, an insurance policy provider turned to UiPath, an enterprise RPA vendor, and AI platform Data Robot, to add intelligence to its processes. A system that can manage and execute real-time decisions through AI is the best option for automating complex decision processes. Applying high-level analytics and machine learning those systems to become intelligent and continually adjust and discover from new, contextual data. They set up a real-time decision-making system in form of RPA that helps to transfer highly complex problems in real-time applying AI-based analytical decision-making. 

For investment firms, real-time decision-making can analyze thousands of business inputs, constraints, and options and arbitrate between multiple internal targets and trading decisions. It can apply an analytical constraint-based optimization approach to models across thousands of possible actions – whether it be specific content, an offer, a price, a sort order, or a recommendation – and determine the best outcomes for the organization. sometimes it qualifies those choices upon certain criteria from profitability, risk, or revenue perspective.

Sometimes, the traditional approaches to RPA may hit a decision point that is too complex for simple automation. Considering the facts, organizations are also looking at using AI for process mining to automate process discovery rather than have business analysts figure out what happens in the company.  

Process mining  

RPA-Robotic Process Automation is transforming the system many organizations function. Process Mining enables companies to holistically experience their methods and recognize process advancement possibilities to boost efficiency and overcome costs. Its 360° view of processes enables hyper-automation—standardizing and accelerating enterprise automation using technologies, such as machine learning (ML) and artificial intelligence (AI).  

The conventional way to business process management involves business analysts talking to managers and employees, carrying audits, then creating charts that illustrate the organization’s various business processes. 

Sumeet Vij, director of the strategic innovation group at Booz Allen Hamilton, has mentioned how clients are presenting process workflow automation and how things happen, bottlenecks are different. When it comes to process mining, machine learning helps people experience a picture of how things are actually happening. New tools will update the processes and spot anomalous behavior in real-time with the evolvement of business.  

 Sometimes, a business process may be viewed as charts, such as Visio diagrams, and managers can drill down into the process, down to the level of individual transactions.  

Business process analytics  

Some organizations have sufficient business process data that they can instantly view the overall picture of what’s happening and make analyses and forecasts. Organizations are taking the exhaust from the RPA process and trying to capture that, learn from it, and make those processes smarter.  

Seann Gardiner, senior VP of business development at Data-Robot (an AI platform provider), mentions if a company has a strong focus on process-level automation and can manage that data, then it might be ready. But strong leadership is also mandatory to make the process successful. Business leaders who believe in automation and an AI-first mentality can make the organizational changes needed.  

The use-cases of intelligent automation will likewise keep developing as new AI procedures and solutions enter the marketplace, drastically changing the future working environment. It can perform even complex and unique business actions like humans as an advanced solution. However, there is no point in believing that this combination will replace humans as they remain the controller of the RPA +AI combination by building the rules and manage the operation. The combination of RPA and AI had aimed to bring a digital transformation in the companies and adding more value over the period.  

For organizations to use this innovation completely, they initially need to see how these solutions can change their procedures and apply strict governance to settle on beyond any doubt their decision-making is paramount. If organizations attempt to actualize these connected yet granular solutions over their companies, it will enable them to drive a double speed change and pursue new heights in Business and IT maturity level.