It is time to extend your rule-based projects with an enterprise-wide automation strategy leveraging hyperautomation. This blog explores the benefits of hyperautomation and the steps involved in its implementation.

Today, software is omnipresent. Thanks to consistent updates, software is becoming more efficient every day. No wonder it is providing businesses with incremental changes. But is that enough? Ambitious businesses expect more from their technology. Time, cost and effort savings with enhanced efficiency and productivity, ambitious organizations demand these benefits and more. But with their current digital landscape, is there any ray of hope?

Hyperautomation is a business-driven, disciplined approach that organizations use to rapidly identify, vet, and automate as many business and IT processes as possible. – Gartner

Yes, the ray of hope is hyperautomation. Combining multiple automation technologies at once, hyperautomation is helping businesses save not a few hundred or thousand but whopping million-person hours! These time savings can be used to achieve anything that an organization wants, build its rocket to the moon or a submarine that reaches deep into the ocean!

Also, did you know that hyperautomation is set to help Heineken save a million person hours by 2025?

It is time to understand its details. The year was 2019. Gartner coined the term ‘Hyperautomation’ and has not looked back since. To understand hyperautomation, we can break it down into hyper, which refers to the scale of its features and benefits and automation which denotes the process of automating manual labor. Hyperautomation undertakes multiple automation initiatives and crosses the boundaries of restricted tool features and functionalities.

By extending the scale of automation technologies, hyperautomation enhances growth, innovation, efficiency, accuracy, and improves organizational performance. Let us understand why organizations prefer hyperautomation as a natural next step after rule-based and Intelligent Automation.

Hyperautomation Extends Benefits of Rule-based and Intelligent Automation

The size of organizational data is peaking more than ever. Businesses need an intelligent tool that capitalizes, analyzes, and derives insight from ever-increasing data. Hyperautomation has the power to win any size and structure of data, evolving customer needs, and business models.

The promise of hyperautomation is end-to-end automation of office work leveraging various technologies, including RPA, Artificial Intelligence (AI), and Machine Learning. – Automation Anywhere

By combining the forces of multiple technologies at once, it is here to hike the benefits of myriad automation tools and technologies.

Hyperautomation: Benefitting People, Processes, and Systems

Gartner reports that initiatives are now more likely to be driven by business units and fusion teams than IT departments. While cost saving is a key aspect of 90% of hyperautomation srtategies, faster cycle times and higher quality business processes are also key goals.

By combining the features of myriad automation technologies, hyperautomation also combines their benefits. Let us look at ways it empowers businesses.

• Simplify Operations for Maximum EfficiencyImagine a business unit where people, processes, applications, and systems are in sync, and talk to each other. Yes! This is not merely a concept but an actual benefit that hyperautomation offers. It enables seamless integration and interoperability across business units for increased team collaboration and simplified operations.
• Combine Human and Tech ForceManual busy work is neither fun nor productive for an employee. Daily, mundane, and repetitive tasks are thus better performed by automation bots. As digital workers, they ensure everyday tasks are completed faster and better. Also, by freeing up labor-intensive activities, employees can focus on tasks that demand human attention to experience the joy of work.
• Comply More to Standardize BetterAutomation bots are built with rules and conditions which fulfil requirements of various industry and process standards. Whether it is to safeguard and protect employees, rightly serve customers, or be true to market conditions, process automation bots can do it all. Thanks to hyperautomation, organizations can better adhere to protocol and conform to standards for improved compliance ratings.
• Improve Business Value and Reduce HassleThe combination of ML, AI, NLP, OCR, IDP, and ROC in automation bots ensures the highest efficiency, accuracy, and productivity in business processes. Minimal downtime, easy troubleshooting and rule-based operations help you reduce errors, time, and costs. Moreover, you will also experience reduced expenses in recruiting and training employees for everyday tasks. Leverage the current ones to accelerate bot functions instead and scale up operations as per your needs.
• Towards Assured FutureproofingBusinesses are always on the lookout for ways to accelerate go to market of products and services, get speedy feedback, improve, and expand their clientele. Hyperautomation allows people, processes, and technology to synchronize seamlessly. For ambitious businesses, this synchronization means effort, time, and cost-savings, optimized operations and meeting fluctuating market demands.

To sum up, hyperautomation enhances teamwork, eliminates boredom, and empowers the development of great products and services. However, these benefits result from the right strategy and execution. To do so, you need to identify and resolve a few challenges.

Prerequisites to Avoid Hyperautomation Failure

As a business leader, adopting new technologies is in your DNA. You ensure the funds, skills, and resources availability to onboard modern technology. However, the lack of technical awareness fails you and the project. Here are three prerequisites which can help you achieve your goals and avoid failure. They will also help identify challenges of hyperautomation and equip you with ways to combat them.

• Right skillsHyperautomation projects have the potential to transform organizations. However, it requires diverse skills with technical, business and people-specific expertise. Skilled personnel are also crucial to strategize and implement tools and their numerous components. Only proper engineering, management, and technology skills can set the right goals and discover the right processes to be automated.A skilled partner often saves the day by bringing skills and expertise at once.
• Right set of automation toolsThe current automation scenario is an ever- evolving marketplace of products and services. You need a special set of tools to meet your unique business needs. The right automation tool will extract the best features from RPA, ROC, Process Mining, Conversational Bots, and several other automation technologies and provide you desired benefits.
• Right cultureChange is the only constant. With changing technology tools, you can also expect constant adjustments in people’s mindsets and methods of working.

  Furthermore, the key is to remember that a successful hyperautomation strategy is about using the collaborative intelligence of humans and technology. – Raghu Ravinutala, Yellow.ai

  However, the right organization environment will always promote evolution and provide means to adapt to it. Gaining stakeholder and management support is crucial here. As leaders, they can ensure transparency in the following situations and successfully implement hyperautomation:

  • Explaining the role and value of hyperautomation in daily operations
  • Aligning team’s contributions and responsibilities towards business goals
  • Establishing collaboration between people, processes, and technology

Towards Implementing Hyperautomation

Our client, the first neo bank in the US, saves $100,000 with automation. Read the whole story.

Let us understand the roles and resources, involved in implementing a hyperautomation project from scratch.

Looking at the above process of implementing hyperautomation, it is certain that it is in no way a one man’s job. It demands a wide variety of skills and resources.

The project initiates with identifying business objectives and only business leaders can do it. Later, business process consultants use these business goals as the project ‘vision’ and proceed to assess and identify business functions or processes that need hyperautomation. Each function or process is chosen to align with a specific business goal. Commonly desired goals include improving efficiency, reducing manual work, cutting costs, enhancing productivity etc.

Kickstart your Hyperautomation Journey with Bridgenext

We, as IT Partners enter after the business and automation goals are agreed upon. Our services range from identifying and implementing automation tools and technologies, troubleshooting, and maintenance and support. We empower our clients with the benefits of hyperautomation irrespective of their implementation stage.

We are a team of technocrats hungry and passionate about resolving business challenges with technology. As your automation implementation partners, we will help you build your custom digital solutions using our Intelligent Automation suite that includes Robotic Process Automation (RPA) Implementation, Conversational Bots, Process Mining, and Automation as a Service. We are ready to kickstart your hyperautomation journey, are you?

References

The journey to exceptional software development is riddled with roadblocks. Developers are primarily challenged by the need to ensure perfect integration of multiple third-party services and APIs. Without seamless integration, software development is prone to stagnation, extended deadlines, and delayed releases. Not to mention some of the other issues that forever plague the life of a software developer –

• Increased architectural complexity
• Unavailable test data
• Time-consuming data creation for end-to-end environments
• Short testing windows
• Lengthy API testing cycles

The software engineering team is tasked with the need to fill in development gaps and simplify activities for software testers, while maintaining an increased scale of collaboration. A simplified technical architecture and resource optimization goes a long way in amplifying software development.

Service Virtualization: A Must-have in Modern Software Development

In software engineering, service virtualization is a method to emulate the behavior of specific components in heterogeneous component-based applications such as API-driven applications, cloud-based applications, and service-oriented architectures.

It is the best mechanism to transform how an organization develops and releases platform versions and updates as part of a continuous delivery approach. Service virtualization also empowers platform teams to become self-sufficient, meet deadlines, follow timelines, and release updates on schedule. This enhanced agility and technical competency also earn them increased support for a continuous testing/delivery model and helps them deliver new services to stay ahead of the competition.

What’s more, with the aid of service virtualization, platform development teams can save enormous time and costs. Early development and testing cycles pave the way for enhancing team performance and generating better value.

The biggest advantage of using service virtualization is the reduction in time ti complete one test cycle – from 5 to 6 weeks to 2-3 days.

Apart from impacting the organizational big picture, service virtualization can provide numerous technical benefits too. Whether it’s engineers, product designers, software testers, quality assurance managers, or project managers, service virtualization has something for everyone. By reducing third-party and external dependencies, here are a few ways service virtualization accelerates product timelines –

• Eliminates waiting times for multiple stakeholders to provide “finished” services
• Provides the ability to work in independent and on-demand environments
• Performs 100 percent of planned functional testing with better development code quality
• Eliminates system test and integration testing gridlock due to available environments
• Enables creation and execution of tests in a microenvironment
• Covers all negative testing scenarios that can’t be replicated in a live environment
• Helps stabilize automated tests
• Enables test data virtualization i.e., simulation of test data and UI behavior

Multiple Challenges, One Solution

In the speedy and competitive technology space market, with new start-ups, products, and models being developed at the speed of light, service virtualization is a boon like no other. Every organization faces enhanced dependencies on technology and IT vendors and components, and service virtualization assures technical teams of consistency and stability in usually lengthy and bumpy development journeys. Technically ambitious organizations need enhanced abilities to seamlessly integrate components better and faster. Technical teams can develop and offer more sustainable, flexible, user-friendly, and successful product features/platforms to their users using service virtualization.

Data security, a crucial aspect of personally identifiable and sensitive data can be achieved by virtualizing your API itself and saving costs while doing so.

Just like costs matter for an organization, experience plays a significant role in a consumer’s journey of buying and using a product. In the case of an application, it is the digital experience. Service virtualization enables the collaboration of developers, testers, sysadmins, and business stakeholders and pays heed to the software quality in terms of UI for a pleasant and seamless UX.

According to a survey, companies implementing service virtualization have witnessed a 67% reduction in the overall cost.

The Role of Service Virtualization in Shift Left Testing

Service virtualization is a welcome innovation for software testers. It helps testers with increased competencies and benefits by accelerating and improving the expanse of software testing. Along with accelerated testing, it enables the shift left approach.

Shift left testing approach is the integration of testing activities with development, commencing sooner in the SDLC, unlike traditional testing methods. You simply move testing to the left in the project lifecycle. The aim of service virtualization is to compress the defect curve and deliver quality products to end users.

• Reduced development and testing costs: Catch bugs and errors early, save big on fixing effort and cost
• Enhanced automation: Less human errors, more test coverage
• Increased efficiency: Monitor software performance to welcome challenges and generate more value
• Reduced load: Simplified software environment for reduced development and testing load for a thorough software release to the test environment

Next Steps

Lo Giudice, Vice President and Principal Analyst, at Forrester says –

Service virtualization is an essential method to accelerate development and assure improved software quality. A technical assessment of your software architecture, choosing the right service virtualization tool, and building a successful Proof of Concept will help you go to market faster.

Bridgenext’s pre-built service virtualization accelerator allows the creation of mock endpoints to elicit the same responses as the desired application. It can mock various APIs and enable you to thoroughly resolve numerous technical challenges and provide tangible business benefits in return.

Need a partner to help you become agile and build new products faster? Let’s connect

Technology savvy organizations or “modern enterprises” are powered by advanced digital technologies that drive operational excellence and growth. These modern enterprises are highly data-driven, operationalizing big data to capitalize on advanced digitally enabled paradigms and fuel data-driven innovation. So, what are these modern enterprises doing differently that makes them stand out from the crowd?

Characteristics of the modern enterprise

Modern, data-driven enterprises have the following fundamental attributes that help them solidify their market position and drive global growth.

• A sustainable strategy for implementing enterprise-wide Intelligent Automation initiatives to capture maximum business value
• Evolving RPA beyond mere process automation to not only achieve cost and labor efficiencies but also to reimagine the way business is conducted
• Democratization of automation to create an organization-wide culture of driving innovation-led growth
• Infrastructure, technology, cybersecurity readiness to effectively deal with tomorrow’s data today
• Mature process frameworks, established governance standards, robust technology and digital architectures

Intelligent Automation – a pillar for growth of the modern enterprise

Intelligent Automation (IA) is at the heart of digital innovation, driving consistency, velocity, and quality at scale. In the context of the modern enterprise, Intelligent Automation looks beyond bottom-line savings to top-line growth and digital transformation, delivering software-powered digital innovation across the enterprise. Intelligent Automation today is all about –

• Improving employee and customer experiences
• Enhancing operational and process efficiencies
• Achieving business excellence
• Enabling service improvements and innovations
• Facilitating strategic decision-making

Robotic Process Automation (RPA) and Intelligent Automation (IA) are some of the most misconstrued concepts today. In the simplest definition, RPA involves automating routine, mundane, and repetitive rules-based tasks while IA works on processes that need human judgment, intuition, creativity, and problem-solving skills. By learning to mimic human capabilities, IA takes on a more cognitive approach to routine RPA implementations. A combination of RPA and IA helps modern enterprises streamline both rules-based as well as complex intelligence-driven systems, workflows, and processes to create intelligent, future-ready, self-driven enterprises.

RPA optimizes costs. IA turbocharges business transformation.

RPA is great to automate simple processes that follow a set of human-defined rules. However, in the case of tasks with many variations or exceptions, like activities around the processing of large volumes of unstructured data, RPA might create scalability challenges that could impact ROI. Humans are adaptable; software bots that are programmed to follow rules aren’t. This is exactly where AI-driven Intelligent Automation supersedes rules-based RPA.

IA integrates core RPA functionalities with additional capabilities where bots learn to adapt in real time. Rapid advancements in AI have created a whole new breed of cognitive technologies capable of mimicking inherent human capabilities such as image identification and handwriting recognition. These cognitive technologies – when integrated with RPA and advanced analytics – enable end-to-end enterprise automation, driving sustained business transformation.

A report published by Everest Group highlights the critical components of Cognitive RPA or RPA 4.0¹ – the next level of maturity in the conventional enterprise automation model.

If deployed systematically, Intelligent Automation offers multiple benefits to the enterprise

• Enhanced accuracy due to low/no manual intervention
• Regulatory compliance and improved governance through clear process definitions
• Cost savings – optimized resource utilization and reduction in operational manpower delivers lower costs (20%-70% based on the process)
• Increased productivity and process efficiency – bots can work 24×7 and scale as needed, resulting in higher throughput
• Reliability, consistency, and scalability – no changes to IT architecture or integration with existing systems
• Low technical barriers – no programming skills required
• Improved employee engagement levels – freeing up human resources for more high-value, strategic tasks boosts motivation
• Superior customer satisfaction – automation of customer-facing tasks with AI helps resolve customer queries quickly and with greater accuracy

Bridgenext’s 5D implementation strategy for successful Intelligent Automation

Bridgenext (former Emtec Digital) offers a robust suite of Intelligent Automation services that deliver dynamic process workflows to drive enterprise-wide business transformation. We work closely with clients to measure organizational readiness for IA and build a comprehensive automation roadmap that unlocks maximum value from Intelligent Automation initiatives. Our end-to-end IA solution suite uses factory-based agile development methodologies to deliver high quality, optimized solutions utilizing best-of-breed RPA tools and AI technologies.

Extended capabilities in Intelligent Automation powered by a dedicated Center of Excellence

Our Intelligent Automation services enable clients to address critical process and operational challenges in a cost-effective manner, while optimizing and enhancing the performance of the existing automation stack with more control and less risk. Our end-to-end consulting services help enterprises achieve more agility and speed in executing enterprise automation initiatives. Post implementation, our dedicated IA Center of Excellence (CoE) provides extended bot support for efficient process automation. Our value-driven Intelligent Automation deployments are supported by the best automation experts in the industry, advanced tools and accelerators, the latest technology stack, best practices in governance and automation, and industry leading partnerships.

We help clients across a diverse set of industries intelligently automate critical process functions across human capital, finance and accounting, customer service, and IT.

If you are looking to accelerate enterprise automation projects by incorporating advanced Artificial Intelligence and Machine Learning technologies, Bridgenext can help. Our automation experts will study your existing tech stack and identify potential candidates for automation, while suggesting the appropriate technologies that will augment RPA to deliver enhanced efficiencies and facilitate business transformation.

Contact us today for a no-obligation consult to understand how advanced automation technologies can transform your business.

Reference

¹ https://www.rpaforum.net/threads/if-you%E2%80%99re-only-automating-with-rpa-you%E2%80%99re-playing-the-short-game.11199/

It is not uncommon today for customers to interact with a bot instead of an actual human representative to get their questions and concerns resolved. This wave of automation is taking over many industries – including banking and fintech, delivering substantial impacts on customer service functions.

According to Gartner¹, organizations that implement a Virtual Customer Assistant report up to a 70% reduction in call, chat, and/or email inquiries. With these advantages, it’s no surprise that usage of self-service bots and virtual assistants is on the rise like never before.

In fact, simple FAQ or rule-based bots are now being replaced by next-generation bots using advanced AI, NLP, and ML technologies. Smart bots, aka conversational bots, are practically running customer service functions for most digital banking platforms

According to a Facebook², 53% of people would prefer to message rather than call customer service.

Over and above the benefits of shorter waiting times, quicker responses, more personalized experiences, and enhanced user preferences, here are some additional reasons firms are choosing conversational bots for their dedicated customer service agents –

• 24/7 availability
• Elimination of human errors
• Enhanced compliance, efficiency, and productivity
• Speedy issue resolution
• Scale up and down based on the demand

Ambitious organizations in the banking and financial services industry are investing in context-aware bots that leverage a conversational user interface (CUI) for enhanced customer experience and support. Besides being super-efficient, these bots help banks to gain tangible operational and financial benefits.

A Juniper Research survey³ states – nearly 90% of bank interactions (internal and external) are automated through AI chatbots. Also, the operational cost savings using chatbots in banking will reach $7.3 billion globally by 2023, up from an estimated $209 million in 2019.

Organizations that integrate a conversational bot into their customer service applications make optimal use of their human and digital resources and transform their customer and employee experience for the better.

As stated by PwC⁴, the consumer mindset has shifted in today’s fast-paced world, with the demand for immediate satisfaction and convenient resolution of queries in all brand interactions.

Consumers are willing to pay a nearly 16% premium to businesses providing superior levels of service.

Types of Bots

So, we know the demand is there for this technology. But what are the different types of bots to consider?

1. FAQ Bots

   As an automated support system, FAQ bots answer simple user questions with a conversational interface. They can provide yes/no or brief answers to simple user questions. As entry-level bots, they bring answers to your users rather than them needing to search for a dedicated FAQ page to look for answers themselves.

   

2. Rule-based Bots

   Rule-based bots, also called decision-tree bots, are simpler than AI bots in terms of technological advancement and implementation. Since they do not require modern features but work on flow-based designs and predefined outcomes, they are easier to develop and implement. Here is an overview of the main features, benefits, and shortcomings of rule-based bots –

   

3. Context-aware bots

   Context-aware bots are smart bots, powered by AI, ML, and NLP. By accessing the enterprise’s system of records, these bots recognize users, remember their behavior history, act as virtual assistants, and provide a human-like personalized experience. They provide the most value as they can identify, learn, and respond to user intent to deliver faster and better query resolution.

   

Context-aware Bots

Here are other interesting use cases of deploying AI-based contextual chatbots –

In Scenario 1, Banko knows that the Mastercard that has reached the user. It proactively asks the user if he/she wants to activate and start using it. After activating the card, Banko can provide support on its usage as well.

In Scenario 2, Banko helped the user resolve his/her query by being smart and context-aware. With the ability to access pertinent enterprise systems of record and historical data, the bot was able to prompt the user to select the right amount and accordingly raise a dispute.

Getting started with context-aware bots

Context-aware bots empower organizations to deliver unparalleled customer service and transform their customers’ banking experience. Trained to be self-taught, these bots leverage historical and real-time data to deliver accelerated and accurate human-like responses. Banks can employ these bots to help simplify banking interactions for their customers including –

• Making payments
• Checking bank balance
• Applying for loans
• Transferring funds
• Accessing and downloading bank statements, credit card reports, bills, etc.
• Reporting fraudulent activities
• Blocking a lost or stolen card
• Issuing new cards/check books
• Reminding customers about bill payments/loan repayments
• Sending information on offers, discounts, etc.
• Opening/closing bank accounts
• Resetting passwords for enhanced security

Want to see a smart context-aware bot in action?
Reach out to us to schedule a quick demo, today! Let’s Connect

References

¹https://www.gartner.com/en/newsroom/press-releases/2018-02-19-gartner-says-25-percent-of-customer-service-operations-will-use-virtual-customer-assistants-by-2020

²https://insights.fb.com/2016/12/01/messaging-means-business/

³https://www.juniperresearch.com/press/chatbots-a-game-changer-for-banking-healthcare

⁴https://www.pwc.com/us/en/services/consulting/library/consumer-intelligence-series/future-of-customer-experience.html

More and more organizations are leveraging Robotic Process Automation (RPA) to streamline critical processes and increase efficiencies. McKinsey predicts that disruptive and emerging technologies such as RPA will have a potential economic impact of about $6.7 Trillion by 2025¹. According to Gartner, an increasing number of organizations will shift to digital-first business models and cloud-native operations in 2022, accelerating the pace of RPA and creating fully automated value chains². The additional inclusion of Artificial Intelligence, Machine Learning, and Natural Language Processing technologies within RPA initiatives will further boost digital transformation across the enterprise.

It’s official – bots are here to stay. However, RPA doesn’t end with bot development and deployment. A critical and often overlooked element is what happens after bots are implemented. Regular and ongoing maintenance of bots is crucial to ensure smooth performance. This is where a Robotic Operations Center (ROC) comes into play.

This blog highlights the criticality of devising a strong bot maintenance and optimization strategy before process automation planning begins, and the downside of not having a sound bot maintenance plan in place. It also addresses the tricky question of “In-house vs Outsource”, highlighting the many benefits of outsourcing ongoing bot management to a trusted technology services provider.

A comprehensive strategy for RPA factors in people, process, and technology

Effective enterprise automation initiatives need a strong strategy that focuses on successfully integrating three key components – people, process, and technology – to ensure measurable business outcomes. For any RPA strategy to be efficient, organizations need to –

• Define the overall vision for the automation strategy – what are the organizational expectations from RPA initiatives?
• Gather the requisite skills for automation – what skills are required, what are the current in-house capabilities, how to acquire skills missing in the internal teams?
• Delegate the management of enterprise automation initiatives – should RPA be managed through an in-house Center of Excellence (CoE), or should this function be outsourced to a skilled third-party vendor?
• Identify and measure Key Performance Indicators (KPIs) – how to measure the success of the enterprise RPA strategy?

A sound RPA strategy serves as a blueprint for scalability of future automation projects, as well as preventing wastage of critical resources including money, time, and efforts.

How can a Robotic Operations Center (ROC) help maximize your RPA investments?

Enterprise RPA initiatives are geared towards identifying the right tool, selecting an experienced implementation partner, and establishing strong governance models to ensure seamless bot deployment. However, it is important to continuously monitor and track bot performance to prevent downtime, mitigate risk, and identify opportunities for bot optimization through a structured Robotic Operations Center (ROC).

In its simplest definition, an ROC is an extension of the RPA Center of Excellence (CoE) and is usually led by a hybrid IT + operations team. The ROC empowers IT and DevOps teams by monitoring bot performance 24×7 with continuous support and maintenance to resolve incidents and mitigate inherent risk in production. The ROC ensures that bots seamlessly deliver the business value expected from enterprise automation projects while complying with organizational frameworks and rulesets. Here are the top reasons why you need a dedicated Robotic Operations Center:

• Increases ROI from enterprise RPA initiatives: The ROC ensures bots are consistently monitored and optimized, helping ensure expected ROI is achieved from strategic automation initiatives. Once initial process automation pilots are successful, increased demand for additional automation RPA use cases will inevitably arise. The ROC serves as a scalable resource for management of an expanding suite of bots across the enterprise.
• Allows end-to-end visibility of automation projects: Often, enterprise RPA initiatives across geographically distributed lines of business are quite complex and increase overheads. The ROC has total visibility into the various organizational functions and facilitates the creation of a centralized scenario of the RPA landscape. This enables the prioritization of critical use cases for future automation projects based on overall business goals.
• Ensures adoption of robust cybersecurity protocols: RPA operations experts within the ROC are accountable to provision and maintain bot credentials in secure password vaults. Assigning multiple roles to bots violates the NIST 800-123 principle of least privileges⁹ and risks exposing the enterprise to cybersecurity threats. ROC security experts create strategies to mitigate risk and ensure that all cybersecurity protocols are in place.
• Strengthens accountability and communication among RPA stakeholders: The team structure in the ROC follows pre-defined guidelines that outline key responsibilities and tasks for each team member. This robust structure and accountability model effectively tracks the performance of enterprise RPA implementations and strengthens communication among key stakeholders. The result is a streamlined and powerful process automation engine that brings higher operational efficiency and tangible ROI.

Why you should build a strong ROC strategy before implementing process automation

For RPA to be successful, you need to have a strategy in place for ROC – prior to making any automation investments. A solid enterprise ROC strategy will lay the foundation to leverage automation capabilities effectively within your organization. The ROC will help you identify use cases, provide recommendations for the smooth functioning of bots, guarantee bot governance across all levels, and offer technical training and workshops for all key stakeholders. It will enable you to create an enterprise automation library to identify potential candidates for process automation, evaluate lessons learnt from previous automation attempts, and build RPA best practices. Most importantly, an ROC helps you establish a culture of success for your automation initiatives. It provides the critical support needed to ensure your automation initiatives are successful now and into the future as your business, processes, systems, and people inevitably change over time.

The following process can help you create an effective ROC strategy that factors in people, process, and technology to deliver measurable value to the business:

The downside of not having a sound ROC strategy while planning for RPA

The success of RPA rests solely on the foundation of a good bot monitoring and optimization strategy. What happens when you lack a strategy for ROC? Besides a very haphazard enterprise automation implementation, here are some of the common pitfalls:

• Change management issues in bot operations
• Lack of quality and consistency in bot performance
• Tendency of key stakeholders to overlook important aspects pertaining to governance, legal, and regulatory mandates
• Adoption resistance by IT security teams (owing to data privacy and security threats)
• Inability to measure the business value generated by RPA
• Potential abandonment of automation due to lack of ROI

Build an ROC in-house or outsource ROC?

When it comes to bot maintenance, a most common strategy is to ask RPA developers to manage the numerous bots in production. This uses up substantial developer time for routine maintenance tasks, which will inevitably slow down additional automation development. This is when the “in-house vs outsource” conundrum comes into question. The table below summarizes the pros and cons of building an ROC in-house vis-à-vis outsourcing ROC services to a trusted partner.

	Building an ROC in-house	Outsourcing ROC services
Cost	Increased costs and downtime when developers get involved in routine maintenance tasks	Significant cost savings with better quality bot maintenance and optimization
Productivity and efficiency	Delays in maintenance and support when small teams manage a large batch of bots causing new bot development to slow down	Increased productivity owing to better developer focus on high-value automation tasks
Scalability	Assembling RPA support and backup teams that function 24×7 is difficult and expensive	Support for bot maintenance is available 24×7 with high automation scalability owing to dedicated focus on current as well as new automation initiatives
Continuous improvement	Lack of skilled professionals with the necessary capabilities to monitor and maintain bots	Continuous support for critical business processes by identifying and resolving issues to minimize downtime, reduce query response times, and provide quick issue resolution for increased bot uptime
Data privacy and security	Better data protection as access to sensitive enterprise data stays within the organization	Risk of data breaches and privacy issues pertaining to sensitive enterprise data

Here’s how a trusted technology partner can accelerate your enterprise automation journey

For organizations who lack the skills or resources to efficiently scale their automation operations, outsourcing is the order of the day. With managed ROC services, there is an immense amount of business value that a trusted automation partner can bring. An experienced technology services provider can address critical automation challenges, solve your internal bandwidth issues, and deliver a higher ROI on your enterprise RPA initiatives.

Bridgnext’s broad spectrum of managed ROC services is geared to provide 24×7 bot deployment, monitoring, support, optimization and maintenance, and reporting. We help organizations amplify their automation efforts by addressing critical production challenges and improving process efficiencies.

Our ROC team includes experienced automation engineers who work within customized ITIL frameworks and advanced governance and data security policies to help enterprises fulfill their automation and business goals. We provide flexible operating models and multiple levels of support to align bot performance with our clients’ strategic automation objectives, leading to lower TCO and higher ROI.

Have you considered implementing a Robotic Operations Center to support your enterprise RPA initiatives? What challenges have you faced and how have you addressed these?

Let’s connect.

References

¹https://www.uipath.com/blog/rpa/the-evolution-of-rpa-past-present-and-future

²https://www.advsyscon.com/blog/gartner-it-automation/

³https://www.gartner.com/en/newsroom/press-releases/2021-04-28-gartner-forecasts-worldwide-hyperautomation-enabling-software-market-to-reach-nearly-600-billion-by-2022

⁴https://www.gartner.com/en/newsroom/press-releases/2021-04-28-gartner-forecasts-worldwide-hyperautomation-enabling-software-market-to-reach-nearly-600-billion-by-2022

⁵https://www.gartner.com/en/newsroom/press-releases/2020-09-21-gartner-says-worldwide-robotic-process-automation-software-revenue-to-reach-nearly-2-billion-in-2021

⁶https://www.forrester.com/blogs/predictions-2022-the-pandemics-wake-drives-automation-trends/

⁷https://www.forrester.com/report/the-rpa-market-will-grow-to-usd22-billion-by-2025/RES177085

⁸https://www.forrester.com/report/predictions-2022-automation/RES176466?ref_search=0_1646982447710

⁹https://nvlpubs.nist.gov/nistpubs/legacy/sp/nistspecialpublication800-123.pdf

According to the 2019 Open Source Security (OSS) and Risk Analysis (OSSRA) Report, 96% of codebases contain open source components. With the average codebase containing 298 open source components, they account for 60-80% of all software code.

Engineers leverage these open source licenses and their components to help create, accelerate, and innovate their software development processes. For development teams that utilize open source and third-party code, understanding usage guidelines as well as following them is critical to maintaining quality and reducing risk.

For example, in the above report, it was also reported that 85% of codebases contained components that were more than four years out-of-date or had no development activity in the last two years. Such incidences pose a legal, financial, and security risk to organizations who utilize software with these components. While many organizations have dedicated Legal/Audit/Engineering/Management teams in place, it is the responsibility of the developer to understand and mitigate risks that come with OSS licenses as well as the guidelines for proper usage.

Back to Basics: Types of Open Source Software Licenses

Open Source Software Licenses Compared

Today, engineers have a wide array of OSS licenses to choose from, which has given rise to the domination of permissive open source in comparison to copyleft licenses. The Apache 2.0 license and the MIT License are far more popular than the GPL family, together comprising over 50% of open source licenses currently in use.

Source: WhiteSource

License Preferences

Certain licenses are leveraged far more than others as they satisfy numerous requirements of both engineers and businesses too. Of course, specific license permissions and limitations determine license preference for many and hence, the MIT license is predominately preferred as per WhiteSource.

Source: WhiteSource

Understanding the Types, Permissions, Conditions, and Limitations of Licenses

Now that we know the names, types, and categories of open source licenses, let’s deep dive into how to actually use them. With every type of OSS license, there are different permissions, conditions, limitations you need to follow. We have included the most commonly used and preferred OSS licenses below.

The above table highlights the multiple aspects you should consider before utilizing, sharing or distributing your work using OSS components. Be sure to also lean on the expertise of your legal, engineering, and management teams to guide you.

Role of the Opensource / Third-party software Review Board (OSRB)

Opensource/ Third-party software Review Board (OSRB) is a team comprised of members responsible for establishing and reviewing licensing terms as well as reviewing against known security vulnerabilities before adopting new OS libraries/components. The OSRB also provides strategy, communication and guideline manuals (set of rules and regulations to be followed) for IT professionals in organizations. It also consists of the following aspects to regulate the use of OSS licenses-

• Recommended Guidelines

  Any open source component licensed under the following commonly-used licenses can be freely used without additional disclosure or approval by the OSRB.

  • Apache License, 1.0, 1.1 and 2.0 variants
  • Eclipse Public License (EPL)
  • MIT License
  • Berkeley Software Distribution (BSD), 3-clause, 2-clause, and 0-clause variants
  • Mozilla Public License, 1.0, 1.1 and 2.0 variants
  • Common Development and Distribution License (CDDL)

  Any other software other than those mentioned above will require review and explicit permission from OSRB.

• Approval Process

  Every organization has a predefined process to identify, review, leverage, manage, and distribute components associated with diverse open source licenses. With this process in place, organizations can identify risks and regulations associated with OSS licenses and also gain other benefits including accelerated delivery schedules and preemptive actions to mitigate risks or surplus costs.

  

Licensing Compliance

Whether permissive or copyleft, all open source licenses have notice requirements. Typically, this means you need to include a copy of the applicable license when distributing open source software.

• OSS licenses for Mobile Applications

  Mobile applications are no exception to the above guidelines. According to a report by OpenLogic, 71% of apps using open source licenses were deemed non-compliant. Since mobile applications are installed on user devices, they fall under the “distributed” category and you are obligated to provide a copy of the license itself along with any notices or attributions required by the license. Below are examples of OSS licenses used by popular applications such as MS Outlook, Zillow, Facebook and Instagram respectively.

  

  

  Follow the instructions below to include the licenses of the software used in your applications. If you are using components which don’t fall under the guidelines provided, contact the OSRB for further advise. Here are some helpful links to guidelines on how to use opensource licenses from Google, LinkedIn, Github etc.

  • https://developers.google.com/android/guides/opensource
  • https://www.linkedin.com/legal/open-source-mobile-apps
  • https://github.com/carloe/LicenseGenerator-iOS
  • https://github.com/mattwyskiel/LicensesKit

• OSS licenses for Web Applications

  Web Applications render or deliver HTML, JavaScript, CSS & plugins to consumers which are executed in their browsers. You are obligated to keep and provide the attribution information for these libraries.

  • Keep and provide the license & copyright information in the JavaScript files and other assets that are delivered to client machines.
  • Make sure this information is not excluded or removed after minification & bundling process.
  • If this is not possible, include a credits page that lists all OS libraries used in the application.

• OSS licenses for Windows Applications

  Web Services/ REST APIs

  Other Internal Components

  Applications or services that run on internal servers and are not distributed to end customers are mandated to provide attribution. However, there are some license types which require attribution. As a precaution, you should leave the license and copyright information of the libraries in the code.

• OSS licenses for Stack Overflow

  Stack overflow is one of the largest communities of developers who share their knowledge. However, the solutions or code snippets contributed by users on Stack Overflow are released under the Creative Commons Attribution-Share Alike 3.0 Unported (CC BY-SA 3.0) license which requires attribution to the source. Though we don’t encourage or support borrowing code from such sites, if it can’t be avoided you need to provide the right attribution to the source.

  As per the CC BY-SA 3.0 license terms, you need to fulfill the following requirements.

  • Section 4(a): include the URL to the license.
  • Section 4(c)(i): give credit to the original author, by name or pseudonym.
  • Section 4(c)(iii): give a URL to the SO source code. (If the source code is in an answer, use the ‘share’ button on the answer to get a perma-link.)
  • Section 3(b): If you make any changes to the source code, add a comment saying “The original code has been modified.”

It is recommended to add the following attribution when you are using code from Stack overflow.

OSS Licenses are significant and can pose significant risk to organizational operations and reputation.

If you need a partner to help analyze your requirements and identify the right opensource solutions and also ensure adherence to opensource and 3rd party licensing, we are here to help you. Our teams can help you analyze the right stack, identify licenses, get reports, understand and mitigate risks.

Contact our experts, today!

References

opensource.org/licenses

github.com/todogroup/policies/blob/master/linuxfoundation/lf_compliance_approval.pdf

www.slideshare.net/blackducksoftware/you-cant-live-without-open-source-results-from-the-open-source-360-survey

www.ibrahimatlinux.com/uploads/6/3/9/7/6397792/opensourcestrategyforum-haddad-1.0.pdf

Organizations often need rapid deployment of bots to automate their business processes and go-to-market initiatives. Speedy bot deployment enables firms to accelerate their processes, improve accuracy, deliver greater value, and enhance their market position.

The success of process automation involving multiple systems of record requires technology and process specialists with diverse skills. Along with skills and resources, it takes time, effort, and investments for a successful rollout.

RPA enthusiasts are always on the lookout for newer methodologies and processes to shave time off their sprints and rapidly deliver maximum value. Thanks to Bridgenext’s (former Emtec Digital) innovation team, they need look no further! We have developed an accelerator that empowers development teams to deploy bots with increased speed, precision, and quality.

Where the Challenge Lies: Delayed RPA Development

Unavailability of APIs and integrations for all systems in play

As part of process automation, bots need to interact with various enterprise systems such as ERP, CRM, HRM, and SCM. Often, getting access to these enterprise systems/APIs can be challenging, causing delays in the bot development process. Also, to address corner cases and negative scenarios, developers need a lot of data in the “System of Record” which isn’t always easily available. Typically, this data originates in upstream systems and flows into the “System of Record” after going through various approvals and rules. Generating data in the source systems can be tricky and time-consuming and this can cause additional delays in the overall development process.

The Solution: Service Virtualization

In computing terms, virtualization refers to the act of creating a virtual version of something, including virtual computer hardware platforms, storage devices, and computer network resources.

Taking virtualization a step further, Service Virtualization is the process of creating mockups of APIs or required services with desired features to enable multiple teams to continue their respective tasks without hassle or interruption. It uses mock data/dummy APIs to get a head start on development that can later be switched over to the actual APIs, once those are developed.

Service virtualization ensures the application’s components integrate early in the development cycle, for significant time and cost savings and improved application quality. Some of the other benefits offered by service virtualization are-

• Considerable increase in test rates, with more than a quarter of companies doubling their test execution rates.
• More than a third of companies reduced their test cycle times by at least 50 percent.
• Nearly half of respondents saw a reduction of total defects of more than 40 percent.

Service Virtualization for RPA Development

Today’s fast-paced world demands “faster time to production” for rapid digital transformation and enhanced ROI. Stakeholders are on a constant lookout for ways to accelerate their enterprise software development process. At Bridgenext, we apply the concept of the “Software Factory Model” to RPA to accelerate the development of bots using predefined standards, accelerators, and re-usable components. Using this approach, we deliver bots in 4-6 weeks by optimizing the development process to achieve significant improvements in the quality of the bots we deliver without compromising on the business objectives.

Bridgenext’s Accelerator and Service Virtualization Tool

At Bridgenext, we utilize an internal accelerator for “Service Virtualization” to deliver quality bots on an accelerated timeframe. Service virtualizations simulate the behavior of select components such as REST APIs, Web Services, and Databases within heterogeneous component-based, service-oriented / Microservice-based applications. This service allows rapid creation of API stubs and simulates the behavior, data, and performance characteristics of real services to create efficient development and test environments.

Benefits of Service Virtualization: Enhanced Productivity, Accelerated Development, Resilient Bots

• Allows developers to work in parallel on different parts of the bot
• Accelerates testing cycles by reducing dependency on external/internal services
• Facilitates test edge cases and negative scenarios without changing the “System of Record”
• Reproduces production bugs with ease
• Creates less dependency on infrastructure for non-production environments
• Addresses the concern of calling third party services during performance/load tests

Business Drivers

• Faster time to production
• Lower cost of development
• Enhanced quality of code and testing

In deploying RPA projects using Service Virtualization, we have observed several advantages –

• 60% of development time saved by using mock APIs and databases instead of waiting for actual application resources
• 30% of post-production enhancements / fixes resolved
• Bot development can be continued by leveraging mock APIs 100% independent of production data
• 100% success rate conducting Root Cause Analysis for bot failures

Do you wish to accelerate bot creation for automating and optimizing core business processes? Contact our RPA experts, today!

Source: https://www.gartner.com/en/documents/3087717/market-guide-for-api-testing-and-service-virtualization

Technology is the driving force behind process optimization and efficiency in the logistics industry. Organizations are leveraging the benefits of advanced digital technologies to streamline routine operations and boost both productivity and efficiency. Robotic Process Automation (RPA) is the new industry favorite for third-party logistics (3PL) companies and freight brokers looking to optimize two of their most critical functions – carrier onboarding and compliance.

Carrier onboarding is the process of adding a new carrier and their associated transportation services to your logistics center. As the industry grows and freight movement expands globally (road transportation accounts for 70% of worldwide shipments¹), it is important to partner with carriers that cover specific geographic regions. For example, if a shipper has deliveries for the west coast, they need to partner with a carrier that operates in that area, thereby streamlining shipment delivery and boosting supply chain efficiency.

However, carrier onboarding is not a simple task, with lengthy screening and compliance procedures that are time-consuming and labor-intensive. As your list of carriers expands, the more fine-tuned your organizational structure and data collection must be. In this blog, we discuss the different elements of the carrier onboarding process, and how automation streamlines these tasks for 3PL companies, guaranteeing efficiency and scalability.

Carrier Screening and Federal Motor Carrier Safety Administration (FMCSA) Mandates

As the demands placed on the logistics industry evolve, selecting the best carrier service from the wide variety of available options has become increasingly difficult. Carrier services are subject to strict compliance upheld by the Federal Motor Carrier Safety Administration (FMCSA), designed to mitigate risk, cargo theft, insurance issues, lost cargo, and other events. This protects the industry and all stakeholders, but for logistics companies, it can add extensive costs and additional paperwork. To ensure onboarding the ideal carrier that meets the necessary regulatory requirements and lowers your risk as a freight broker, adhering to detailed screening processes and compliance checklists is critical, even though this is a time-consuming and expensive task. Common carrier screening criteria include:

Why Is Carrier Compliance Important?

Carrier compliance is extremely important as it maintains an industry standard for freight delivery and regulates risk across the supply chain. In 2020, close to 900 cargo thefts occurred with an average value of over $166,000.² Insurance claims increased by 22% in 2020, leading to a spike in bankruptcies as well.³ How a carrier manages risk has a massive impact on your business and overall financial exposure.

The FMCSA’s Compliance, Safety, and Accountability (CSA) scores are designed to limit carrier fraud, detect false insurance claims, and check carrier services that present a danger on the road. These industry compliance standards, across seven categories, focus on maintaining best practices for record-keeping, freight qualifications, safety assessments, and insurance filing — for the benefit of all stakeholders.

CSA Categories

The better your screening and compliance process, the more secure you are in ensuring rapid and error-free movement of freight. Collecting performance data on the quality and authority of any potential carrier protects your customers and your reputation, building better trust. Carrier compliance directly benefits your business in multiple ways:

• Creates quality partnerships with carriers and shippers
• Ensures a positive reputation for the organization
• Protects all key stakeholders and business assets
• Guarantees enhanced safety in freight delivery
• Provides visibility into freight processes for increased efficiency
• Optimizes costs by eliminating future fines
• Helps informed business decision-making with an enhanced ability to manage risk

Steps Involved in the Carrier Onboarding Process

Carrier onboarding can be done either manually or through automation technology. Most logistics service providers have moved to custom web applications or logistics management systems for faster onboarding. Paperless, digital mechanisms offer several distinct advantages over paper-based, manual processes that are time-consuming and error-prone.

Typically, carrier onboarding comprises the following steps:

Challenges in Carrier Onboarding

While digital innovation has done much to help logistics companies streamline carrier onboarding, there still are several challenges to the compliance process:

• Each carrier may have a subtly different onboarding process with unique or specific logistics criteria. For example, additional compliance registration is mandatory for shipments of hazardous materials (Title 49 of the Code of Federal Regulations has more information on handling dangerous goods).⁴ Singular technical systems have difficulty managing the unique requirements of each shipment or carrier.
• Another challenge is the quality of data. Sharing data requires trust between the provider and receiver, and without clean and efficient systems that can locate and categorize the information, an entire database can become convoluted.
• There are varying levels of technical maturity amongst freight brokers and carriers, and some systems cannot integrate these efficiently. Errors can occur, or information may not be stored correctly in the database (for instance, missing insurance information when an event occurs or shipping of non-compliant items). This puts all parties at risk.
• The entire process can be time-consuming and labor-intensive, putting strain on support teams. Manual re-entry can lead to human error and result in slow processing times.

Streamlining Carrier Onboarding Through Automation Technology

Robotic processes and multi-modal networks enable carriers and freight brokers to share data in real time, helping produce actionable insights around the carrier onboarding and compliance process. Verified Carrier Aggregator Platforms can take on the extensive task of carrier onboarding – improving business efficiency and offering analytical insights to maximize growth. Visibility of this kind, matched with data cleanup and computing power, will streamline critical business functions, allowing you to make more confident business decisions for an organized supply chain.

Robotic Process Automation (RPA) benefits carrier onboarding and compliance in three ways:

1. Lower time and cost

   By replicating input fields in a database or locating mistakes associated with human error, robotic processes automate, collect, and store clean data. Bots can verify carrier compliance according to custom sets and delist services that fall below the required standards. Automated compliance documentation allows systems to pull data in real time, resulting in seamless communication between brokers and other parties, better organization of data, and reduction in errors – all with less manual work and cost.

2. Speedy, streamlined onboarding process

   Automation allows seamless integration with CRM and ERP systems, enabling accounting information, shipment tracking details, and quotations to be shared with stakeholders. Locate documents you need without effort and perform carrier audits quickly. Acquire direct access to carrier FMCSA data and peruse reviews to mitigate risks associated with non-compliant carriers. Increase the speed at which you validate and onboard carriers without lowering quality standards.

3. Operational efficiency

   Automation can handle multiple tasks associated with carrier onboarding, facilitating heightened scalability. By automating routine compliance tasks, the strain on support teams is reduced. Use the collected data to make informed decisions, whether the information is gleaned from drivers, customers, or even granular updates on optimal shipping routes in certain regions.

Automation technology lowers costs, reduces documentation errors, boosts efficiency, and helps form better partnerships with carriers.

An Experienced Technology Partner Can Make All the Difference

While the benefits of automation are clear, implementing robotic processes or integrating with verified carrier aggregator platforms is a substantial technical task. Partnering with an experienced technology consulting firm with expertise in platform enablement can help you build advanced transportation management systems to garner tangible business benefits such as:

• Free up time to focus on mission-critical business operations
• Rapidly build technical platforms at scale
• Install high-performance systems with fewer errors
• Create user-friendly interfaces with advanced customization
• Implement robust technical solutions with greater efficiency and transparency
• Ensure 24×7 access to professional support teams

Bridgenext (former Emtec Digital) can help you optimize the carrier onboarding process and transform your logistics business. Our rich experience in platform re-engineering enables clients to streamline critical processes and achieve scalable business growth. As a global technology services provider, we would love to discuss how advanced technologies can modernize your carrier onboarding and compliance. Contact us today!

References

https://www.shippeo.com/blog/the-3-way-win-approach-to-onboarding-carriers-onto-transportation-visibility-platforms

https://www.ccjdigital.com/business/article/15064734/recorded-cargo-theft-incidents-average-values-increased-in-2020#:~:text=The%20total%20number%20of%20cargo,233%20in%20the%20fourth%20quarter

https://www.freightwaves.com/news/commentary-the-changing-landscape-of-cargo-claims-after-covid-19-how-to-cut-losses-for-shippers-globally

https://www.shipbob.com/blog/shipping-hazardous-materials/

It’s the era of rapid digitalization and organizations are riding the transformation wave with enhanced speed and dexterity. Robotic Process Automation (RPA) is the most obvious choice when it comes to dealing with mundane, repetitive, and rule-based tasks that eat up both resource effort and processing time. RPA has witnessed massive adoption in the last few years with organizations pumping in huge amounts of money to digitize day-to-day activities.

This leaves us with the question – is RPA alone enough to drive sustained digital transformation? Though RPA provides an incredible value proposition to enterprises, the path to Cognitive RPA (RPA 4.0) demands seamless integration with intelligent technologies such as Artificial Intelligence (AI) and Machine Learning (ML). For enterprise digital transformation to take off systematically and with speed, it is important to integrate RPA and intelligent technologies into your business strategy roadmap.

Intelligent RPA can bridge operational gaps between multiple disparate enterprise legacy systems to accelerate ROI. It is also a critical enabler of sustained transformation and one step closer to the adoption of advanced and emerging technologies such as deep learning, computer vision, natural language processing, and cognitive computing.

Maximizing ROI with intelligent automation

A global financial leader achieved a whopping 1300% ROI by combining human intelligence, machine power, and cognitive capabilities to automate hundreds of routine back office processes

Automation first – if there’s any chance you can automate, you should

Automation has become the core of organizational digital transformation initiatives – yet the gains fail to measure up. So, what are organizations doing wrong? Well, we can say with conviction that it’s not about technology adoption as much as it is about the overall approach to the transformation. Consider this – we are living in a century where devices speak to each other (the Internet of Things); data is exploding beyond measure so much so that silos cannot contain this information any longer; the power of on-demand cloud computing is creating immersive and next-gen digital experiences. It’s high time organizations took an “automation first” approach to digital transformation.

What exactly is an automation first approach? Does automation first imply people second? Far from it. An automation first mindset ensures human talent is freed from routine, complex, time-consuming tasks to focus on more strategy-oriented activities. Activities that are essential to resolve challenges standing in the way of sustained business growth. Unlike traditional processes, an automation-centric approach begins with automation and answers one simple question – what are the tasks that can be automated and don’t require human intervention? This not only widens the scope of activities that can be automated; it also sets off a spark of innovation allowing businesses to think big and outside of the box. An automation first mindset strategizes new solution design and deployment and drives continuous process improvements through tools refinement.

Accelerating business transformation with RPA

A leading IT consulting firm witnessed a 50% increase in productivity with ZERO errors by deploying a fully automated solution supported by a digital workforce (software robots)

The dawn of the intelligent digital enterprise

Today, it’s not enough to be a digital enterprise – only an intelligent digital enterprise will emerge successful. Participants of the new intelligence revolution will survive in this disruptive age; those that fail to embrace RPA, AI, ML, and Intelligent Automation (IA) will fall away without a trace.

Organizations that have intelligently matured digitally often have multiple workforce layers comprising humans and machines enabled by advanced technology for speedy execution of tasks. To accomplish this, it is essential to build a strategic roadmap that factors in the digital disruption likely to impact key pillars of the business such as organizational culture, day-to-day operations, and solution delivery.

Top-down RPA or bottom-up RPA?

Enterprise-level automation can either be top-down or bottom-up across three levels – task automation, process automation, and organization-wide automation. A top-down approach borders on the automation first mindset, requiring total C-level buy-in to implement automation at the organizational level for business transformation. While top-down is unarguably the best way to go, it is important to consider that most automation happens at the individual task and process level. This is where a bottom-up approach will be more beneficial. A bottom-up approach also eliminates “automation anxiety”, enabling organizations to progress steadily on their digital transformation journey. To strike a good balance between both approaches, it is important to ensure technological compatibility across the three levels of automation. Enterprise-wide automation needs to be agile and scalable with magnified automation orchestration capabilities, while retaining its simplicity and algorithm integration capacity. Successful implementation of enterprise-wide automation is possible by striking a balance between the top-down and bottom-up initiatives leading to sustained automation at all levels.

The necessary hype around hyperautomation

The IT industry is famous for coining new phrases; but the fact that Gartner includes hyperautomation as one of the top 10 strategic technology trends for 2020 makes it worthy of mention. Hyperautomation is basically “automation on steroids” – an amalgamation of intelligent tools (RPA, AI, ML) supported by a very powerful AI-driven decision-making strategy. Hyperautomation is key to scaling a speedy and efficient automation first approach and brings together disruptive technologies for end-to-end automation. Hyperautomation is the first step towards creating a digital twin that enables enterprises to visualize the interaction and performance of disparate functions and processes within the organization.

Achieving audit compliance with process automation

Top home appliances manufacturer gained 70% improvement in productivity with over 50% reduction in TCO and further achieved audit compliance by automating critical enterprise processes

Any mention of hyperautomation wouldn’t be complete without highlighting the importance of democratization of RPA. In simple terms, RPA democratization is about facilitating easy accessibility to automation tools and skills for everyone in the organization. Democratization enables smooth and efficient operations; builds productive and happy teams; and creates superior customer experiences – leading to overall business success.

Why a Robotics Center of Excellence (CoE) should be at the heart of your intelligent RPA initiatives

Top-down RPA deployments involve acquiring a centralized view of the business to identify high-volume, high-value, and time-consuming processes. This can be easily achieved by building a dedicated Center of Excellence (CoE). The CoE not only manages high-impact processes, but also establishes standard governance models that adhere to RPA best practices and policies for automating day-to-day processes through the bottom-up approach. A CoE is a unified approach to scale enterprise-wide automation and offers several key benefits.

• Accelerated ROI from RPA implementations
• More accountable, centralized teams
• Efficient operations
• Increased productivity
• Good governance
• Enhanced security

An experienced implementation partner makes all the difference

With RPA implementations becoming mainstream, it can be a daunting task to identify the right partner who can provide a consultative approach to automating your business processes. While the market is full of vendors dabbling in RPA and intelligent automation, the following parameters are worth considering while selecting the right partner –

• Impeccable RPA portfolio
• Implementation speed
• Platform scalability
• Robust reporting tools and methodologies
• Capabilities in technology and design innovation
• Failsafe data security and compliance protocols
• Delivery excellence
• Dedicated CoE

End-to-end RPA solutions from Bridgenext

Bridgenext’s comprehensive RPA consulting and agile development services help organizations maximize the ROI on their automation initiatives. Backed by robust standards and governance models, we offer focused RPA solutions across the intelligent automation spectrum.

Contact us today to learn how we can help you drive sustained digital transformation through structured RPA initiatives.

“Don’t talk to strangers” is a common instruction we give to children, because of privacy and security concerns. Back home, Alexa, Google Home and Siri were strangers once, but are now family members! We are happy to keep these AI powered voice assistant technology at various locations in our homes and interact with them frequently. These assistants offer immense flexibility using natural language to interact and get information or complete tasks. These technologies make tasks much easier for us to accomplish.

Need to turn on a light? Just ask Google Home. Want to make sure your oven cooks dinner just right? Send a command to Siri. Need a birthday gift recommendation for your friend? Alexa is here to save the day!

It is now the age of voice assistant technology. Voice your wishes in natural language and AI-enabled devices will process them. It doesn’t matter where you are- at home or work, driving the car or even shopping, it’s time to welcome the digitalized customer experience.

How Smart Speakers are driving voice technology

The ability to have natural conversation with these AI powered devices has triggered a new era in the digital transformation across all environments. Not surprisingly, millennials lead the pack for smart speaker ownership. As depicted in the graphic below, at the beginning of 2019, 34% of American 18-29 year olds owned a smart speaker.

However, based on Microsoft’s voice report, 41% of users raised concerns around trust, privacy, and passive listening. The bedroom (45.5%) is a common place for these devices, followed by living room (43.2%).

The flexibility and convenience these devices offer have outweighed the concerns, and trends indicate that adoption of these devices will continue to grow.

To complement voice-first experiences with visuals, smart speakers with screens are slowly gaining traction, providing rich interactive voice & visual experiences that include graphics, images, slideshows.

According to the forecast released by Loup Ventures, 75% of U.S. Households will have smart speakers by 2025. It’s now easier than ever to attract a younger audience to voice and screen-enabled products with gamification. Millennials routinely conduct their daily tasks via these devices. Now, marketers have the golden opportunity to leverage this habit to build new strategies that strengthen brand loyalty for their products. With less cost and a localized target audience spread globally, the near future promises a high ROI with minimal effort.

Gamification with Voice

Gamification is all about applying gaming mechanics in non-game contexts where users are rewarded with badges, points as they progress through different levels. These badges, points can be exchanged for real goods, which in turn allows consumer brands to build loyalty and awareness of their products.

Brands can engage consumers in a better way using smart speakers and displays that capture customer information through a gamified interface while also encouraging customers to check out newer products offered or inviting them to experience the latest loyalty program. While gamification makes the interaction interesting and engaging for consumers, it also allows brands to extract volumes of insights into customer preferences, pain points, suggestions etc which can drive the evolution of their products. Insights gained from gamification for one product can also be utilized for other products as well.

Imagine a scenario where a confectionery brand provides fun learning activities that lets users accumulate reward points for completing each round. The users can then redeem these reward points to buy products from their brand catalog. Similar gamification techniques, when combined with voice enabled devices, will enable B2C brands to drive new-age brand loyalty for huge benefits.

To get started, they just need to conceptualize and engage with an IT partner like Bridgenext to bring their concept to reality.

Are you ready to give voice to your goals? Let’s connect and discuss a PoC!