Month: September 2019

No strategic planning exercise is complete nowadays without prioritizing digital transformation initiatives to improve cost efficiency and unlock new value. Leaders in growth-focused organizations strive to integrate digital technology into mundane operations to streamline them and deliver more value to customers. This way, employees also get to focus on higher value-added tasks and decision making, to a large extent.

Robotic Process Automation (RPA)

RPA is enabled by rule-based deterministic automation tools that delegate repeatable, predictable tasks to bots. The worldwide RPA software market grew 63% in 2018 and is forecast to reach $1.3 billion in 2019, according to a Gartner study, with banks, telecom firms, insurance companies, and utilities alike embracing this change.

Just look around and you can find plenty of examples in action.

Has RPA hit real-world hurdles?

RPA adoption is growing, but you must have noticed several real challenges that have emerged over the recent years.

Most RPA solutions work efficiently in a linear way. They, however, depend on human intervention to correct complex issues that are outside their scope of functioning. They cannot judge how to use specific information contextually, work with exceptions or variants, or work with unstructured data. And in general, 60-80% of organizational data happens to be unstructured. Also, while RPA may automate tasks efficiently, the time taken for it to integrate into overall processes is often underestimated – limiting its success. Most importantly, it doesn’t lead you to real process transformation by redesigning already existing inefficiencies in end-to-end processes.

Recent industry research suggests that RPA-optimized companies with conventional enterprise ops centers only achieve about 30% of their targeted automation goals. You should, in fact, only see RPA as a step towards intelligent automation that enables robots to automate processes with increased context-awareness.

The promise of Intelligent Process Automation (IPA)

This is where IPA or Cognitive Automation, comes into the picture.

It refers to the combined applications of RPA, Artificial Intelligence (AI), and other advanced technologies such as Computer Vision Technology (CVT), Optical Character Recognition (OCR), and Machine Learning (ML). It uses human-like bots creatively to mimic human activities, think and learn on their own, providing reliable support to the workforce using rich data and insights.

Here, you can augment rule-based automation with decision-making capabilities through an intelligent platform capable of processing structured data to generate deep insights. It can support employees by removing routine, repetitive tasks, and can transform customer journeys by making interactions simpler, smoother and faster.

This intelligent automation will enhance your bots with as many human characteristics as possible, including the capabilities to see, sense, learn, communicate, collaborate, empathize, and self-heal.

Recent advances in CVT, OCR, and ICR enable bots to See – read documents, identify images, and recognize objects. Your machines can easily download and analyze complex information contained in scanned images, including text, numbers, logos, and even other objects. Imagine a seeing bot that can scan thousands of invoices, purchase orders, or KYC documents per minute and also deciphers powerful information.

Bots enhanced with AI can capture key attributes of a use case, identify trends and then take the required action. Statistical models like Artificial Neural Networks, Bayesian Networks, and Support Vector Networks can provide the sensing capabilities for applications specific to your processes. Some common examples of Sense and Learn can be seen in the dynamic load balancing of process volumes and bots, business exception management, and triggering of automation based on specified event patterns.

As you know, human-human interaction is required for optimized customer service and employee engagement processes. Speech recognition software, Natural Language Processing (NLP), and Semantic Analysis now let bots understand spoken and written language, and the successful automation of such processes. For instance, chatbots connected to RPA-enhanced bots can now Communicate effectively. They can interpret, understand, and respond to your client or employee queries while also executing transitions on their behalf.

Collaboration between your machines is possible nowadays through Advanced Knowledge Management Systems (KMS), which collate, tag, store, and process data through powerful search engines. A live example of this is your chatbots that answer queries and navigate the customer or employee through a series of preprogrammed solutions.

Empathy is a key factor in customer-facing processes and in processes where customer interactions and customer satisfaction levels are the key performance indicators. Experts now predict that AI will be able to Empathize by helping bots assess human emotions. For instance, sentiment analysis algorithms can detect your customers’ emotions based on their speech, text or handwriting. Once the sentiment is determined, the human worker can be directed to the proper solution much quicker, or the chatbot can adjust its responses and solutions accordingly.

How to approach IPA adoption in your organization

In order for your IPA program to be successful, you will need a strategic approach avoiding random installations of discreet applications. Your C-level executives must definitely be involved throughout the adoption process.

To start with, your entire organization needs to be clear about the potential benefits of IPA, and how best to maximize the related data analytics and decision-making capabilities. There must be clarity on what the goals of the program are, and where it fits within your existing operations.

Next, prepare a wish list of tasks and problems to address using IPA. Prioritize these tasks based on potential value and feasibility and define realistic ROIs for each.

It is now important to identify the strengths and limitations of your IT team and establish a well-defined governance structure. Seek professional consultation and set up a pilot program to set the ball rolling. Also set up a smart in-house team for data clean-up and integration.

Remember to start small, collect feedback, learn and adjust all along the way, and expand slowly. Plan additional storage requirements as your organization expands its IPA scope. Also, set up a feedback mechanism encouraging your employees to provide feedback.

As your IPA program builds up over time, you will have to address quality and transparency concerns. Pay close attention to protocols like bandwidth requirements, storage capabilities, safety, and security.

Combining AI with your human workforce is a critical component of IPA adoption especially during the first steps of automating complex processes. You will need to find innovative ways to audit the decisions made by these machines. In many cases, only humans will be able to recognize and analyze complex patterns and explain them. In the initial stages, you may even allow your employees to override AI-generated decisions until they gather enough data to validate the results.

The way forward with IPA

IPA is in its infancy stage of adoption, and there are few success stories to substantiate it yet. At the moment, it is only on the draft board of many organizations, but its arrival is near and imminent.

As an innovative organization, you must have already automated a majority of your routine processes and are learning from the resulting data sets and outcomes. Now is the time to identify the right partners to strategically embed AI and ML into your systems, software and hardware infrastructure.

When configured and managed properly, IPA will integrate with predictive analysis technologies, automate even your complex processes, and fundamentally redesign your business processes. Ultimately, with the resulting employee productivity improvements, and enhanced value provided to customers, you stand to gain a significant competitive edge over the others.

All of us who have focused our attention on the technology evolution in business in the last few decades can think back to when companies had a clear delineation between the ‘business’ and ‘IT’. Traditional business lines ran aspects of the company and leveraged technology provided and supported by their counterparts in the IT department. When engaging with a new company on something new, the common question that always sprang up was, “Is this being driven by the business, or IT”?

Of course, today lines of responsibility have blurred. Companies realize that their fundamental strategies and go-to-market plans are highly depending on their available technology. Technology decisions are rarely made without involvement from the business. Most companies have employees in roles that jointly represent one aspect of the business and the IT department.

There’s a similar phenomenon happening with Automation. As Robotic Process Automation (RPA) continues its rapid-paced transformation of business, the strict delineation of responsibilities between human workers and robots is becoming blurred. Particularly with the advancement of ‘Intelligent Automation’ and smart robots, the role of the digital worker and the human worker are becoming more intertwined.

This interconnectedness between the human and digital worker is known as ‘Automation Singularity’.

Here are some of the specific ways that humans and robots are interacting in the age of Automation Singularity.

Strategic Priorities and Centers of Excellence (CoE)

Business is run top-down. Even the most mundane and repetitive business process (including the types often first automated with RPA), should ultimately align with higher-level company strategies and objectives.

Robots will continue to get ‘smarter’, but humans will ultimately always drive company strategy. RPA tends to focus on building automation road maps for processes that are 1) feasible for automation and 2) drive ROI. However, it will be necessary for companies to have Automation Centers of Excellence (CoE) that ensure the automation roadmap aligns with fundamental company strategies, and that strategic importance is a considering in building automation roadmaps.

Process Discovery

The first step in automation focuses on breaking down a process to prepare it for digital workers. This process discovery phase tends to be a human-driven activity. Subject Matter Experts gather with CoE members and use a whiteboard to map out processes as a basis for robot configuration.

Today, RPA technology actually can (and should) help with process discovery. Allowing your RPA platform to leverage tools to monitor a process over time, then auto-create process maps with statistics can improve the chance for automation success. Process discovery is quickly becoming a human + robot activity, and for the better.

Attended Automation

Despite giant leaps in RPA capabilities, including Intelligent Automation where robots learn and improve with time, some processes are still best performed when a human is involved.

For example, think Customer Service personnel at companies who still want to provide a human interface in their call centers. Robots can significantly improve the productivity and effectiveness of CSRs by providing automation in common and often complicated functions. The human + robot “Singularity” in a call center can provide the best overall experience for the customers it services.

Orchestration

One of the key advantages of digital workers is that they have the capability of achieving 100% accuracy and high levels of productivity. But they also need managing, unlike a popular misconception. While working, robots need direction just like humans, on what to work on, what to do when idle, and how to handle exceptions or problems.

Countless labor management tools have been built to orchestrate humans in working environments (in a warehouse, store, office, etc.). RPA platforms require similar technology to orchestrate robots, and ensure that they are maximized across processes, to deal with exceptions efficiently.

The exciting thing here is that a lot of digital worker orchestration can be automated in itself. We’ve reached a stage where digital workers are being ‘Singularly’ orchestrated by humans + robots.

Trust

Automation is creating a huge transition in work, from humans to robots. This requires a concurrent shift in ‘trust’. The risk management element of RPA is critical as it pertains to security and fraud, which again requires human oversight of digital worker activity and trust.

Automation Singularity thus involves synchronization of governance across humans and robots.

Training and Re-Skilling

There’s a common misconception that successful Automation initiatives manifest value by the replacement or elimination of human workers. Companies having the most success with RPA are getting results with something very different.

The emerging Automation Singularity phase shows us that RPA can maximize the productivity, scalability, and flexibility of both human workers and digital workers. Human workers are optimized and enhanced by robots. Humans can focus on higher-value elements of the business, like customer service and R&D.

This requires a shift in human worker focus, including training to re-skill human workers for their new roles. Successful automation (with robots) generates the most value when humans are optimized through training and re-skilling.

Conclusion — The journey towards Automation Singularity

The impact of automation and digital workers is altering the face of the business landscape forever. Companies on this journey will be completely successful if they build their plans not only around technology but also by focusing on both their human and digital workers. The age of ‘Automation Singularly’ is demonstrating right now that humans and robots can work together seamlessly to co-create the future.

Automation and AI is no more a buzzword; it’s a reality. From our day-to-day tasks to workplace operations, intelligent machines are altering our way of living. This is just the beginning and economists see this disruption on a large scale and complexity that they have deemed it as ‘The Fourth Industrial Revolution’. (Klaus Shwab, WEF)^1

The world is moving towards a new vision, especially when it comes to re-imagining the workforce for enabling efficient business operations. Gartner predicts that 70 percent of organizations will leverage AI and Automation technologies to enable and assist employees in their task productivity^2. The disruption that RPA brought in back office operations is now cutting those boundaries. Thanks to Cognitive technologies, there is an intelligence explosion in functional front-end operations resulting in digital workers with human-centric capabilities driving critical business activities.

However, this progression of Automation and AI permeating across multiple boundaries in the workplace has its limitations. Intelligent Digital workers, if we may call them so, lack core human traits like Intuition. How many times have you applied a break on the car and avoided an accident just because of an intuition or how many times have you made a business decision based on intuition — probably more often than once and mostly it is combination of Intuition and Intelligence. This combination makes us the most advanced species and lack of this is where Digital workers are more vulnerable to mistakes, when it comes to making decisions.

The advancement in technology is surely removing these gaps and concepts like Singularity are gaining traction – Singularity hypothesis^3 suggests that technology advancement will cause an effect that will not only make machines exceed human intellect but will also see human intelligence grow in a non-biological way. While the singularity hypothesis may be a dystopian world, we are already in an era where the convergence of human and machine is paving the way towards Automation Singularity. In our view, Automation Singularity is not where AI-enabled digital workers will replace humans, but it is where digital workers and humans will collaborate to enhance each other’s capabilities, while slowly converging together to create an intelligent future workforce..

To emphasize the journey towards Automation Singularity and how it will work, let us take a flavor of it with an offbeat example:

For a retail company, ensuring that the right inventory is available at the right location at the right time is most critical. To ensure that, they have planners analyzing the inventory day in, day out to see to it that no high selling product goes out of stock and no customer walks out of the store unsatisfied.

In order to plan and send optimal inventory to the store, planners are using multiple data sources, planning tools and mathematical calculations. Furthermore, not all planners are optimized in their way of working; they might be using different tools and logics to fulfill the demand. It’s not a simple job, it is time-consuming and it needs a deep understanding of business, number crunching and decision making

Every item and store has parameters/attributes associated with it like what period of historical sales should be considered or if there is any minimum or maximum item required in a specific store or set of stores. Planners usually work around these parameters along with multiple reports (like out of stock etc.) and additional data sets (like sizing) before applying a model to predict what inventory needs to go to what store. When we think of the current automation landscape, this is probably not the best candidate but let us bring the journey towards Automation Singularity and re-imagine this with a team structure of Human and Digital workers.

In the journey towards Automation Singularity:

The above example depicts how human and digital convergence can be a win-win for the organization’s core operations. As RPA is becoming part and parcel of organizational processes, the shift towards convergence is the next logical step for organizations. The removal of boundaries and leveraging digital workers will not only enable cost-saving but will also generate revenue and increase customer experience.

References:

https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/

https://www.gartner.com/en/newsroom/press-releases/2019-01-24-gartner-predicts-70-percent-of-organizations-will-int

https://conceptsystemsinc.com/singularity/

“Tomorrow’s Enterprise needs a boost in employee productivity while reducing operating costs”

Automate your business processes with AssistEdge RPA 18.0

The biggest worry for a typical Fortune 500 enterprise is around its burgeoning processes and application ecosystem. While the dawn of 2020 led to a splurge of applications for every need, enterprises are gradually trying to reduce their IT footprint by way of keeping a lean yet niche application ecosystem which in turn is expected to streamline their business processes too.

The key to a lean IT footprint (and of course, streamlined processes) is to kick things off by identifying processes/tasks that don’t need human intelligence but are still required in the value stream for its hygiene factor. These tasks are then piled up for automation. This ensures the employees dedicated to such workstream(s) are re-purposed for other high-value work yielding better ROI.

AssistEdge RPA 18.0, through its cutting-edge algorithms and cognitive behavioural patterns, can help enterprises magically identify tasks with potential for automation and can stitch together connected tasks (via guided human intervention) to form processes that can be queued up for automation cycles. A purely metric-driven platform, AssistEdge helps automate redundant tasks across the enterprise and continually monitors the automation run cycle for increased productivity and optimized efficiency.

The three core tenets of an enterprise

Employees, Business Processes and Applications are the three core tenets of an enterprise.

The operating cost of an enterprise looms large primarily due to its expanding digital application ecosystem and redundant processes.

Five relevant questions enterprises should start asking themselves:

Enterprises should try to dig deeper into business unit specific processes and its relative application touchpoints. The purpose is to measure the relative importance of each process, application (and its corresponding tasks) touchpoints to attain the goal of the Business Unit.

For instance, an HR Business Unit might have a suite of COTS product(s), home-grown applications for handling onboarding processes. However, there might be scenarios where its sub-contracted to external agencies to gather all the essential information and conduct background checks.

In cases like this, the overall usage aspect for the process must be done along with the TCO (Total Cost of Ownership). The unused assets would call for optimization either via automation or through retirement until further need.

The effort in such a case would span across multiple initiatives including — automation, process streamlining, application ecosystem rationalization, while also having a purview at aspects like governance, compliance, auditing, etc.

AssistEdge RPA 18.0: Stitching and Executing an Automation Blueprint

As automation is a journey to bellwether the fruits of cost savings and productivity maximization, AssistEdge helps to empower enterprises with an automation ecosystem to kick-start the journey with a discovery of automation potential for an enterprise; arrive at an automation blueprint; identify processes and tasks with a higher potential for automation — value and efforts (and compare various ways of actual task execution in current state); stitch the missing parts of a process/task (if any) and make it holistic; run automation cycles; manage/optimize and monitor automation across other RPA products too; achieve an integrated aspect of support ecosystem, whereby agents can focus more on maximizing Customer Satisfaction Index than on the customer’s query and indirectly resulting in a reduced AHT.

Here’s a list of values packed in AssistEdge RPA 18.0 platform:

And the walnut is about to be cracked: In future, AssistEdge would go beyond and help enterprises to stitch a full-fledged TO-BE SOPs (based on AS-IS findings), create Business Requirement Documents, Software Rationalization, Compliance and so on.

The Benefits:

Interested in learning more about AssistEdge RPA 18.0? Write or talk to us now.

“Towards an Intelligent and Insightful Call Center Experience”

Transforming Customer Service Experience

As every enterprise aims to maximize the potential of its after-sales customer service, one of the biggest challenges faced by a present-day call center is around swiftly identifying the support query of a customer and instantly service the query. This will not only reduce Average Handling Time but also boost Customer Advocacy Index.

Let’s take a look at a standard customer service scenario

A Corporate Customer: “Can you clarify when will I get the shipment of my 1000 iPhone X, 500 data dongles and, I need to de-activate an active SIM card, enable corporate roaming for 5 SIM cards?”

Agent Z (Telecom ABC): “Thank you, Sir. First, I would like to introduce myself. Next, I would like to know about you before taking your queries one by one”.

A Corporate Customer: “Well, let me introduce, I am Rick….”

Agent Z (Telecom ABC): “Thank you, Sir. I might have to run you through some security questions”.

Rick: “Well, let’s go through it. But this is the 10th time I am repeating it. I am tired of it”.

! Check: That’s a dip in Customer Advocacy. How does Telecom ABC know about it and address it?

Many enterprises are facing the same challenge where the process of customer acquisition is proactive, smooth while the after-sales service gets trivial in terms of the following:

Many back-offices have a suite of disjointed applications, and it varies from legacy applications to graphical user interfaces, excel based applications to desktop-based interfaces and so on. Thanks to a varied set of application ecosystems, enterprises are now finding it difficult to manage them operationally and leverage it to address the query of a customer.

In the above mentioned example, a call center agent must navigate around 10 applications to service the query. The agent might have to navigate to an application to know the customer or conduct a quick authentication check, then navigate to a different application to gather background details of past/current requests, navigate to a suite of applications to address the current query and finally, post a resolution, and log a comment with detailed notes for the query that was addressed by the agent.

In such cases, the average call handling time would typically exceed 30 minutes considering each application is backed by a different technological facet.

Hence, the whole experience needs to be reversed. Instead of enterprises focusing on application-driven experiences to address a customer query, the customer’s intent should drive the whole experience.

The experience needs to be transmuted across all service channels including e-mail, chat and service tickets (via call).

Addressing the Need: Unification of Information(al) Facets

While an ideal scenario calls for a UI Portfolio Analysis covering all applications used in a call center, it also needs significant investment costs as the results of portfolio analysis might demand an application consolidation (or) standardization (or) workflow streamlining initiatives that might incur huge investment.

What is the near-term solution then?

The key to address the problem statement is to probably start with the intent of the customer (caller). By placing the intent at the core, the set of informational facets surrounding the intent need to be unified/displayed to the user.

For instance, when a customer calls up, an automatic customer identification process along with the set of products/services owned by the customer can be instantaneously fetched/shown to the user. Hence, even before the customer support agent picks up the phone, he/she should know about the caller.

Post identification, all informational facets falling within the ambit of the support call needs to be quickly retrieved/shown in the same UI.

It will empower the user to spend more time conversing with the caller, build a strong relationship, cross-pollinate products/services rather than keeping the customer on hold and doing a data entry operation and struggling to address the need. Besides, this will also avoid a scenario where the user is required to navigate across multiple applications for various data points.

AssistEdge Engage: One-Up Above the Notch

The objective of AssistEdge Engage platform is to unify key information from multiple applications, enable automation of mundane/repetitive tasks, tap into relevant information with zero-clicks, while for a composite workflow involving a sequence of tasks, allow the user to navigate to the respective application to complete the detailed task flows (but) from within the AssistEdge Engage platform itself.

AssistEdge Engage platform enables enterprises with a set of tools to quickly ideate/build a WYSIWYG 360^o dashboard with all the right set of information that is required for every agent’s day-in-a life journey, be it to view self-performance snapshot or getting to know key informational insights to service a customer.

Backed by a powerful services’ support from EdgeVerve Systems Ltd, enterprises can penetrate the AssistEdge Engage platform to quickly ideate/launch a customized call to action dashboard, and address automation needs depending on the specific business and user scenarios.

AssistEdge Engage also goes a step further to enable an agent to run processes queued for automation at the user’s end and to have complete control on the automation execution too.

Backed by a patented technical solution, UI platform with standardized aesthetics and widgets and a detailed think tank on the business needs, AssistEdge Engage platform represents the intersection of the three areas for a quantifiable customer support ecosystem solution. The platform targets to optimize some of the KPIs like Active Waiting Calls, Longest Call Hold, Call Abandonment, Average Handling Time of a Call and of course, Customer Satisfaction Index.

Key Benefits of AssistEdge Engage platform:

Click here to find out more about the AssistEdge Engage.