Artificial Intelligence is taking almost every industry by storm. AI-led Digital Transformations are displaying sensational advancements. As 2020 stagnated many business’ growth plans and made us re-question the strategies; now everyone is geared up to turn 2021 into a year of innovations and applied AI. Two months down, we already can see companies being laser-focused on understanding AI capabilities, accelerating adoption, learning through mistakes, overcoming data issues, and embracing new talents. But jumping in with both feet into AI can be highly risky, especially financially. Every practitioner would agree that starting the AI journey with RPA is only practical. Business functions can adopt RPA in any desired extent from basic data copy-paste actions to intelligent analytics-driven decision making using a pre-set logic.
Four principles of a progressive Digital Business:
Deliver personalized experiences that are functional and usable
Build agile operations focussed on things your customers value
Develop a test & learn culture with multiple innovation pipelines
Build platforms and partnerships to accelerate and scale
Let’s look at various business areas and how are they can exploit Automation in the lines of above-mentioned areas for their benefit.
Being one of the business functional areas with most predictable tasks to perform, Accounting has many segments that can be standardized and automated. Analytics from proven practices show that RPA can automate at least 80% of data transcribing tasks and at least 69% of data processing tasks with no manual intervention. Similar to Banking sector, Accounting is also struggling with the limitations of legacy and disparate systems. Robotic Accounting seems to be the only light at the end of the tunnel.
Areas that are safe to start automating across Accounting are:
Invoice Creation & Validation
Data Input & Output
Data Quality Management
Pre- & Post-payment Validations
Identify duplicate payments
- Optical Character Recognition (OCR) is going to save the day. Leading automation service providers are focusing on Intelligent Document Capture and Extraction accuracy, natural language understanding, processing and other data-rich challenges posed by finance and accounting processes. As the visual sensors are increasingly displaying greater capabilities, the precision of data capturing is more likely to be expected. This may even lead to wide adoption of IQ bots.
- In addition to Attended models, Unattended RPA will mature soon to improve speed and quality at the same time. The aim of no-back-office continues here. We can see symbiotic relationship forming between human employees and self-triggered soft bots working in collaboration. With remote and real-time access to the RPA bots and ability to analyze and deploy scheduling, reporting, auditing, and monitoring within a centralized hub; lights-off back offices aren’t very far away. Based on a survey done by Everest group last year, more than 50% RPA bots are attended, and rest are on-prem and cloud-based unattended bots. But Gartner predicts there are going to be dramatic changes in these ratios by 2022.
- Traditional RPA tools were only trained to handle structured data - from a database or electronic spreadsheets. But generally, when Accounts payable teams deal with invoices, they have to deal with documents, not database tables. With the help of emerging engines, categorizing documents as structured, semi-structured and unstructured; pulling various formats of data and processing them into known set of data fields will be possible. Incorporating centralized RESTful APIs provide access to orchestrate external AI blocks, which will create a richer set of features to address the given challenge.
By the end of 2021, for many Financial accounting tasks such as bank reconciliation processes, sales ordering & invoicing, payables & receivables management, budget preparation, external reporting, tax planning… operational staff would just say, ‘There’s is a bot for that!’
With the growing customer expectations and business complexities, digitizing this aspect of an organization became a challenge. Even though Chatbots and Virtual Assistants are filling the gaps here and there, the maturity of these innovations is still not stable enough. Fortunately, RPA (Robotic Process Automation) and VCA (Value Creation Automation) are making their entry here. When trained soft bots are employed to streamline the support operations, the human agents can focus on solving more complex problems and create more personalized experiences to the customers. Potential use cases of RPA bots in here are:
Data Extraction & Entry
Filter Junk Requests
- Self-service is going to go one step ahead with RPA. Many B2C and B2B businesses are working on building such applications where the end-user is granted access to the back-end systems and will be able to fetch the data themselves without reaching to the customer care. This might sound risky right now, but within a couple of years everything from secured encryptions to self-service portals will evolve so much and it’ll soon become a common practice.
- Documentation will be even more digitized using automated speech to text with reduced errors, improved data quality, all the while enforcing consistency and compliance – not to forget enhanced no-human-involved security.
- The future of RPA in customer service is not just limited to customer-facing front-end businesses cases but also going to revolutionize the operations in the back office too. With AI-powered solutions, the consultants will be able to cut down the time takes for actions such as customer’s identity, discovery of the problem, possible solution – which will collectively impact the Average Handling Time (AHT).
According to Grandview research, the global robotic process automation (RPA) market size is expected to reach USD 3.97 billion by 2025.
Liberating the human resources teams from the repetitive administrative and operational chores by automating them saves a lot of time which can rather be spent being face-to-face with the employees and be more productive and efficient. RPA comes with a great deal of data management capabilities and these bots can execute all the rule-based, highly transactional actions with little to no human intervention. Not just improving accuracy and speed, but automation can bring down the operational costs of HR department. Here are some of the business use cases where HR can exploit RPA for their benefit.
CV Screening & Shortlisting
New hire onboarding
Employee Induction and Training
Employee Data Management
Employee Exit Management
Shift Allowance Calculations
- Whether you call it Intelligent Automation or Hyper-automation; Software bots powered with Artificial Intelligence performing deductive and predictive analysis are going to augment human capabilities and enhance decision making in organizations across globe. Gartner predicts this advancement of technology to cut down 30% of the operational expenditure.
- Recent studies suggest that about 63% of activities during the employee H2R (Hire to Retire) cycle are predictable, repetitive, and structured. There are already various automation tools that are handling HR activities in different stages of employee lifecycle. Via corporate acquisitions and partnerships, there will soon be RPA ecosystems and shared services that’ll handle end-to-end HR processes.
- Cognitive Automation and Process Standardization will improve more natural interaction between the bots and humans and also identifies scaling opportunities by creating large-scale organizational intelligence.
- Shared service models will gain popularity as various departments are going to utilize automation, the data they collect can be correlated to acquire untapped insights. In addition to a considerable cost reduction, sharing the provisioned services centralizes the data that can be turned into insights which can unveil number of opportunities to explore deeper AI and Big data.
It goes without saying that Data became one of the most valuable corporate asset and businesses are leaving no stone unturned to find efficient ways to procure it, process it and protect it. Sorting through the mountains of data manually is next to impossible. That is where RPA can make an elegant entrance. Scripts prepared using special algorithms can automate rule-based, mundane data-related tasks with 100% accuracy. The reading capability of RPA bots is improving every day. Electronic outputs in nearly every form such as MS Word, Excel, XML, PPT, PDFs, or scanned images can be captured, transformed, and sorted.
Data Input and File Submission
Data Access Verification
Screening Data Irregularities
Data and Log Mining
Optical character recognition
- Correlating information from various sources and updating the Data will be accelerated further. By combining Optical Character Recognition (OCR) with Data entry and modification algorithms with sufficient access control can reduce the repetition rate of data update requests to mere 0.1 seconds.
- The functions that are using Optical Character Recognition (OCR) now will soon mature to a completely automated Natural Language Processing (NLP) through Embedded Machine Learning models.
- RPA accelerates Data recording and Maintenance of Bills of materials in businesses that deals with goods, materials, and vendors every day. Giants such as Walmart, AT&T, Amazon, and Xerox have already started implementing it. It’s only matter of time RPA becomes the new conventional method for Data Management.
- RPA will add an additional layer of security to Data with automated no-human-involved Data encryption.
Supply Chain Management
It is already proven that Automation can bridge the gap between the customers and brands as well as brands and their vendors. Receiving queries and responding to them automatically using RPA bots has already started. From manufacturing to food to pharma, every industry has witnessed the out-turn of unpredictability due to recent pandemic. During the second half of 2020, the only industries that dodged overstocking and understocking bullets are those who adopted Automation and Machine Learning in Production and Supply Chain Management, respectively. Here is a glimpse into use cases that can leverage RPA to their benefit.
Status Update Notifications
Order & Refund Processing
Digital Twin of Supply Chain
- RPA joining forces with Artificial Intelligence is going to normalize Data Evaluation and Predictable Analytics.
- The concept of Digital Twin which was limited to construction, real-estate, and automobile verticals is about to make an entrance into Supply Chain Management. Simply put, a Digital Twin is a virtual simulation of the supply chain that is made of separate parts such as components, assemblies, teams, or the entire manufacturing plant/warehouse that can be combined in multiple ways to create a unified access point to numerous sources of data and information.
By the way, a Retail Chain based out of India achieved Demand Prediction and Inventory Optimization using state-of-the art AI/ML engine by Qentelli and witnessed 27% lesser under/over stocking occurrences. Read full Case Study here
In the age where frequent restructuring of the business is inevitable, RPA promises to focus on simplifying the processes with the three fives: fewer than five decisions, fewer than 500 clicks, and fewer than five apps accessed. Forbes predicted that, RPA services market will grow to reach $12 billion by 2023. There are surely concerns around the growth of Automation as it may impact the employment or human workers, the tech leaders are saying Automation is more of an accelerator than an alternate.
Being a fastest growing IT services company who is transforming businesses using the enormous power of technology, we believe – ‘If it can be automated, it should be automated.’
Didn’t find your business function up there? Stay tuned because, we are constantly working on bringing you more insights every day. But if you have any specific question about Robotic Process Automation and how can be transform the way your business operates, do not hesitate to drop us an email. email@example.com