Month: October 2022

Digital transformation is all about driving fundamental change in their current approach to common issues. It is a continuous adaptation to a constantly changing environment. Digital transformation primarily covers three key areas:

Digital transformation is important because it paves the way for organizations to quickly adapt to ever-changing industries by driving continuous improvement in their operations. It offers greater business agility, improves process efficiency, and amplify employee productivity, and adds value for customers and stakeholders. Simply put, digital transformation is a gradual shift from traditional thinking to a more collaborative and tech-driven approach, spurring company growth at a fundamental level.

Digital process automation is possibly one of the strategic steps taken toward it. The global digital transformation market  is expected to reach USD 6.78 Trillion by 2029, growing at a CAGR of 20.9%. Regardless of less than a 30 % success rate, 87% of senior business leaders are prioritizing digitalization. Investments have ramped up since the global pandemic, and digital transformation spending will exceed $10 trillion over a five-year period from 2021-2025, as per IDG.

The role of Automation and AI in driving transformation at scale

The pandemic brought AI and Automation to the spotlight as ventures worldwide realized that they no longer had the luxury of years to transform digitally. These two technologies and their family of capabilities are key drivers of change. And many organizations tasted their benefits by making Robotic Process Automation part of their operations. However, the given limitations of RPA tools have compelled businesses to use more advanced solutions to make existing systems and processes more efficient incrementally.

Automation, powered by artificial intelligence (AI) and other technologies, has opened up new possibilities and driven real benefits for owners, from capturing insights to improving performance, addressing time, cost, and labor-intensive factors to augmenting customer service quality, and many more. But they can reach their full potential when people and technology work hand-in-hand. In order to accelerate enterprise digital transformation maturity, owners have to make changes at the granular level, starting by improving tasks and gradually shifting towards full-scale business process automation.

Process automation – The first step toward digital transformation

Business processes orchestrate tasks between employees and systems and find the fastest way to achieve the best possible outcomes. But a process that has worked for two years might not keep up with the changing times.

The first step to digital transformation is to determine what digital transformation means to your organization. This will help you prioritize which areas need immediate attention for transformation. Following that, digital process automation takes an enterprise a step closer to transformation effectively. Hence, as mentioned earlier, this is the first strategic step toward building a connected enterprise.

What is digital process automation?

Process automation connects people, applications, devices, and information to build an agile and digital enterprise. It automates, partially or otherwise, processes spanning multiple applications that typically require human interaction in some form. For example, automating the invoice processing workflows reduces time and human errors effectively, ensuring correct invoices always reach the right person.

How is digital process automation different from RPA?

Robotic Process Automation or RPA uses bots to automate recurring, time-intensive, simple tasks. Contrarily, process automation uses AI-enabled solutions and the power of automation to simplify complex business processes from end to end. These processes involve multiple departments, people, tasks, and workflows across the length and breadth of the organization.

However, a powerful DPA solution embedded with RPA capabilities can be the ideal solution to transform more complex processes digitally.

Digital process automation vs. Business process automation

Business process automation is often used interchangeably with digital process automation. But there is a thin line of difference between the two terms. The former automates multistep processes, whereas the latter scales up workflows that rely on human-machine interactions.

Business process automation, or BPA, streamlines existing processes via API integration. Contrarily, DPA improves user experience by optimizing digitalized processes. The former reengineers existing processes to deliver optimum value, wherein DPA creates more responsive user interactions with software systems.

Benefits of digital process automation

Creating connected workflows: Optimizing workflows and negating process silos connect an enterprise end-to-end, allowing stakeholders to participate in business operations activities and enabling employees to work anytime and anywhere.

Amplifying user experience: Digital process automation n enhances user experiences; workflows are optimized and streamlined.

Optimizing time and cost: Task or process automation frees employees from time-intensive recurring work. Hence, they can focus more on value-added services and reduce the time taken to complete lengthy ones effectively. And automation doesn’t require human involvement.

Improving communication: DPA improves document management for the enterprise, ensuring less likelihood of lost files and keeping employees updated with real-time insights.

Modernizing legacy systems: DPA modernizes existing legacy processes to help them keep up with changing market expectations. It streamlines comprehensive workflows and enhances process efficiency.

Leveraging new-age capabilities: In order for organizations to stay competitive, they need to embrace new-tech powers in their operations. And digital process automation is the right way forward.

Use cases of digital process automation

Healthcare industry: The health sector involves too many repetitive tasks, from scheduling appointments to collecting payments, alerting patients for appointments, and many more. By automating these tasks, the industry can address the time-intensive functions and improve process efficiencies.

Banking and finance industry: DPA has a broader scope in this sector and is extensively leveraged in accounts payable, accounts receivable, loan processing, and customer service. Tasks like customer KYC, data entry, account reconciliation, and fraud detection usually have too much human involvement; hence, the chances of human errors remain high. Automating them relieves employees of cumbersome tasks and eliminates errors.

Logistics industry: This industry is cost and labor-intensive and involves tasks including generating and collecting invoices, scheduling, and tracking shipments, securing proofs of delivery, resolving payment disputes, and many more. These recurring tasks can be easily automated to cut down the overall operation time and cost. Hence, digital process automation can be a game-changer in the logistics industry.

Customer onboarding: This is a standard process existing across every sector. And customer onboarding can be tedious, especially for the banking sector. Moreover, the cumbersome manual steps can only add to customer dissatisfaction. But automating the whole process will scale up workflows and increase user experience for both employees and customers.

How to successfully implement DPA?

Digital transformation and automation are a continuous journey. To ensure a successful implementation of DPA, enterprises need to chalk out a clear roadmap and strategically execute each step. Here is a list of helpful tips to get you started:

Get everyone onboard: Any form of transformation within an organization requires collective acceptance and teamwork. Everyone within the scope of operations should be on board with the upcoming changes.

Map out current processes: It is essential to understand how each process in an organization works. With the help of process discovery, enterprises can easily view the implementation of every individual task, identify bottlenecks, and recognize which process needs immediate attention for improvement.

Identify the right process candidates: Bringing the entire organization under the automation umbrella at once can be the biggest mistake. Instead, enterprises should start small and focus only on critical areas that need urgent improvement. Bringing those small tasks under automation will help businesses to scale up transformation end-to-end gradually.

Plan for ongoing maintenance: To ensure the successful implementation of digital process automation, continuous updates and maintenance are needed. It is not a one-time effort, and a dedicated team should be kept in place for constant monitoring and improvement.

Conclusion

Robotic Process Automation is an important step for businesses to embark on its automation journey. But digital process automation requires something more than mere intelligent bots could accommodate. It needs innovative tech-enabled solutions that imitate how humans think, analyze, and execute the appropriate actions. Moreover, it should be adaptable, scalable, and offer a broader scope for improvement. The future of digital process automation is bright since AI capabilities are still expanding, and smarter solutions are coming to the forefront to help enterprises find optimized ways to improve existing systems and complete their end-to-end automation journey.

With the world still reeling under the impact of the pandemic, companies have begun to accept the new normal post-pandemic and incorporate digital transformational strategies. Organizations have adopted this initiative as customers are looking to implement a more digitally agile system and enhanced customer-centric experiences through better and faster automation services.

According to a survey by Deloitte, 85% of the CEOs revealed that their companies had fast-tracked their digital transformation process during the pandemic by developing new business collaborations. However, this sudden transformation is never easy, and embracing smart automation is the way forward. This is where the role of Intelligent Automation solutions comes into play.

Need for digital process transformation

Digital transformation puts technology at the core of a business strategy to reinvent the future business model for long-term survival and growth. Through a unified model, this strategy can lower operating expenses and ineffectiveness and alter the overall course of a business landscape. Digital transformation is an elementary change in the way an organization works, interacts, and engages with customers. It is an approach to developing a digital culture and upskilling the employees within a company, as it requires teamwork to bring about change.

Challenges of traditional automation

Traditional automation is the process of automating repeated tasks with little human intervention by integrating different systems. Traditional automation programs are designed to incorporate user applications with the backend organizational systems to independently operate pre-defined tasks such as Desk booking, user service ticket submissions, and troubleshooting without human labor.

Unfortunately, traditional automation has some limitations while performing critical tasks. As a result, this model of automation can only run tasks as per the accumulated processes, as the traditional automation systems are not intelligent enough to adapt or learn the advanced tasks. Therefore, humans have to frequently invest their time in traditional automation workflows to make the necessary modifications.

How can Intelligent Automation solutions fill the void?

Intelligent Automation fills this void by integrating Robotic Process Automation (RPA) with advanced technology solutions like artificial intelligence (AI), optical character recognition (OCR), intelligent character recognition (ICR), analytics, and process mining to create sound business processes that learn and adapt on their own. Thus, IA becomes effective only after RPA has been employed and is part of a long-term digital transformation strategy.

Digital transformation & Intelligent Automation

What is digital transformation, and why are businesses undergoing digital transformations?

Digital transformation is the process of using digital technologies to create new or amend the already existing business processes and customer experiences to meet the changing business and market requirements. This reinvention of the business model in the digital age is digital transformation, which goes beyond traditional roles like sales, marketing, and customer service.

According to research, nearly 58% of the consumers are willing to pay more money in return for better customer service. Sensing this opportunity, the companies, in response to the needs and wants of the customers, have laid down strategies to provide the customers’ hassle-free service.

Key drivers for digital transformation through IA

Improved customer experience: Digital transformation, through Intelligent Automation solutions, helps boost the speed and agility of the insights generated, besides providing a transformational customer experience by designing and digitizing customer journeys. Hence, this helps companies earn authority, trust, and respect from their customer.

Actionable data-driven insights: The data unlocked by a company must be utilized to its fullest potential as it is one of its most invaluable assets. Intelligent Automation uses structured and unstructured data to generate highly personalized and appropriate insights that facilitate real-time feedback along with agility.

Insights retrieved by IA are more reliable compared to traditional models as the digital channels offer the necessary numerical explanations by evaluating real-world insights rather than merely qualitative suggestions.

Enhanced cooperation across departments: Regular and crystal-clear communication among various company departments should be the priority, and everyone should be accountable for their defined roles during this transformational journey.  In such a cordial atmosphere, a sense of unity among the employees develops, leading to successful transformations. Hence, this ‘work together’ approach makes digital transformation easier and vice-versa, thus leading to a win-win situation for everybody.

Improved agility and digital innovation: Agility is an organization’s ability to improve and develop continuously, which also holds true for digital processes as well. Research suggests that 68% of companies believe agility to be within the top three considerations for digital transformation.

Why IA can be a catalyst for digital transformation?

In the wake of uncertainties, firms have been applying technologies to address various hurdles, such as fragmented supply chains and work-from-home mandates. Also, due to the readiness of advanced mobile technologies, cloud, and Intelligent Automation Process solutions, consumers have begun to anticipate better products and services with instant response times. Companies are thus using IA to minimize manual processes so that the staff can focus more on productive tasks.

Although most companies are on a rampage for digitizing their business processes, employees still find themselves involved in tedious and monotonous processes like invoice customer details and responding to basic customer queries through chat. As a result, these unautomated processes have become tougher for the staff to connect with customers, make new products and adjust to the changing business environment.

Benefits of Intelligent Automation

As intelligent automation automates tedious and time-consuming tasks, it increases efficiency, reduces human errors, and frees up employees to work on other things. Hence, the benefits of eliminating wasteful processes and the associated costs are far-reaching in IA:

Conclusion

Businesses were hit hard by the COVID-19 pandemic. It reminded the world about the significance of resilient, flexible, and end-to-end business processes. Therefore, organizations are leveraging the power of Intelligent Process Automation solutions to cater to the ever-evolving customer needs and forecast the future precisely.

Robotic Process Automation automates high-volume, repetitive tasks by emulating human-machine interactions. It has captivated the business masses, thereby pushing the RPA market value to US$ 2.65 bn in 2021. Yet surprisingly, some reports state that many companies spent less on RPA tools in 2022.

Enterprise automation is outgrowing RPA – key reasons to justify

RPA has undoubtedly paved the way for automation and digital transformation initiatives, enabling new-age technology across on-premise hardware footprints. However, the bot-based architecture hinders scaling end-to-end enterprise process automation.  And for obvious reasons, the latter is superseding RPA:

It is unscalable: Enterprises struggle to scale automation using only RPA bots. However, when too many bots are deployed, they become fragile and hinder automation scalability.

Maintenance is challenging: It goes without saying any ‘maintenance-hungry’ tool impedes deployment and scalability. Because of the fragile nature of RPA bots, maintenance becomes a hassle for the IT team.

Other tech stacks required: In order to bring every process under the automation umbrella, enterprises need added capabilities beyond RPA’s limits.

It can trigger governance issues: IT-driven governance and best security practices become harder to implement when too many bots are deployed organization-wide.

RPA can turn into economic debt: RPA bots will require another army of bot managers for maintenance. RPA bots are deemed a savior for human workforces, relieving them of cumbersome tasks. But the reality is different. Here, humans are needed to take the load off of the bots. Definitely not an economical approach.

How is enterprise automation filling the technology gap?

Presently, the enterprise automation industry is dominated by standalone solutions, namely:

However, industry heavyweights are more interested in defining process efficiencies economically by acquiring multiple automation solutions sourced from a single platform. Therefore, to enable process efficiency and resiliency, once siloed collection of technologies is clubbed together to create an automation stack for a uniform end-to-end application.

Robotic Process Automation faltered when enterprises attempted to expand bots’ capabilities in need to scale automation. And this very need compelled enterprise software giants to look beyond RPA for a more comprehensive one-stop-platform solution. As a result, enterprise process automation emerged as the missing piece of the technology puzzle. However, it is still at the nascent stage but evolving nevertheless. It sounds like the dawn of a new era in automation software, promising big opportunities for savvy investors and end-to-end platform players.

What is enterprise automation?

Enterprise automation refers to the full-service integration of automation, streamlining complicated processes and driving operational efficiencies. It enables a synergy of people, processes, and systems to augment human intelligence, foster seamless customer journeys, and scale unlimited possibilities for organizations.

Enterprise intelligent automation is born out of the need for an end-to-end automation platform bringing people, processes, and data together.

Common enterprise process automation challenges and remedies

Lack of IT readiness: Organizations rely on internal IT support to implement automation solutions. But only a handful are equipped with the right technology, infrastructure, and security. And most of them lack appropriate standards controlled by an intelligent automation center of excellence. The CoE ensures that only a select group of people can access data to avoid any plausible risk to the organization. Addressing this shortcoming should be a top priority for businesses.

The skill crisis: Skilled workers with sound knowledge of automation, AI, and other evolving technologies are hard to come by. And in the absence of this, implementing, maintaining, and scaling automation capabilities will remain a distant dream. Expecting every recruit to understand technical jargon elucidates the short-sightedness of recruiters. But redirecting the hiring focus only to tech experts will only supersede the allocated budget. Instead, companies can re-utilize their existing resources by upscaling their knowledge through proper training.

Process fragmentation: Fragmented processes are significant barriers in the enterprise automation journey. Process fragmentation occurs when critical business processes are not managed in a unified workflow. These standalone processes increase the risk of error and delay the seamless transition. Hence, care should be taken first to break down those existing siloes and bring them on a unified platform.

Lack of clear vision: Having a clear vision and strategy is a prerequisite for Intelligent Automation implementation at scale. And some of the crucial decisions owners have to take should center around key business objectives for automation – maximize business performance and returns on investments. So, enterprises should make well-informed choices about how and where automation might be applied and the level of change the organization is willing to undertake.

Apprehensive mindset: None of the above-mentioned remedies will work if the top-notch decision-makers in a company are apprehensive about trusting and adopting automation. This apprehensiveness is the byproduct of the constant fear that worries most decision-makers – automation replacing humans altogether. Therefore, educating people about the various benefits of automation followed by a constant assurance of scaling unlimited possibilities through a human-machine synchronized approach.

Key elements of scaling enterprise-wide automation program

According to a survey on workforce automation, over 90% of respondents² saw immense value in their enterprise intelligent automation pursuit. And organizations that have achieved scale started their journey with a clear vision and strategy. Many such organizations have approached automation as an enterprise-wide challenge and started building an arsenal of new tech capabilities required to extend the scope of RPA bots. Their objectives are similar – augmenting their workforces and broadening the scope of work.

The additional technologies and capabilities needed to continue stretching the use case and doing more strategic E-E automation could be summed up in the following points:

Evaluating the best route to scaling automation

When integrating smart automation resources in a singular platform, the size and complexity of the use cases grow two to ten times what RPA is capable of alone. Intelligent enterprise automation comprises the following key components:

Process
Choosing the proper process to automate at a detailed level is probably the most significant challenge enterprises face. To successfully automate, a complete understanding of the work and how it is executed is essential to route the work for automation properly. And that involves understanding process complexities and business rules. By leveraging process mining and task mining tools, highly detailed data about what happened is collected and fed to machine learning models.

People
When humans and machines are connected, enterprise automation becomes more capable, a fact that debunks the myth of automation and AI replacing humans. By bringing humans in the loop or citizen developers, automation doesn’t need to stop and restart. However, in the absence of tech experts, low code/no code technologies are employed to enable rapid design and deployment of human-bot interactions. These little applications optimize digital information, predict what additional information might be needed or valuable, and receive the input back.

Data
Taking the friction out of processes and delivering fast, accurate fulfillment requires strategic process transformation. And to reach that point, enterprises need data in their structured or semi-structured form. Because technologies like AI, ML, and automation cannot work in the absence of data. By using different tech capabilities, data is reduced to its distilled essence and fed to the system orchestrator. This determines the correct workflow that should follow the initial interaction.

These different components should be connected in a meaningful way to make the automation build simple and effective. Enterprise automation is increasingly a part of its transformation or digitization programs.

Benefits of enterprise automation

Enterprise automation maturity model – where enterprises are currently standing?

Enterprise automation maturity model presents a comprehensive view of how business automation has evolved over the years delivering greater outcomes, the present technologies and strategies employed today, and where automation is heading.

The different stages of the model include:

Currently, most enterprises fall into one of the first three stages, while a handful is striving to reach stage four. Enterprise process automation is a continuous journey that is still evolving alongside other tech capabilities. And it will take quite some time before enterprises enter the final two stages of the maturity model.

Future scope of enterprise automation

Enterprise automation has already exceeded its expectations, as responded by 31% of companies surveyed in a report on the imperatives for automation success. Hence, the following year will likely be significant for intelligent automation.

Enterprise automation offers a full spectrum of intelligent solutions to address process inefficiencies at the granular level. As a result, it is the best bet for businesses to build a fully functional autonomous enterprise where every component works seamlessly towards a greater goal.