Automation + Intelligence - The only way forward

Sudhir Sen

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Sudhir Sen, Products Head of JiffyRPA asks, while automation is the poised to be the driver of change, has it truly embraced its potential as we see it today?

Intelligent automation

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Enterprise transformation has been accelerated with the rising capabilities of automation. While automation is the poised to be the driver of change, has it truly embraced its potential as we see it today? Its benefits are evident and results have been promising, and intelligent automation is vaunted as the next big step for automation. Yet the pace in which Intelligent/Cognitive automation is being adopted is rather slow. My conversations with senior leaders across different industries and functions have changed over the last 12 months. Intelligent Automation was unheard of/new to the picture back then, and now it’s quite the flavor, but still remains a grey area. Decision makers explore long term benefits with their automation journey planned in different stages of execution, with cognitive capabilities becoming a requirement only after they’ve established a degree of familiarity with current automation. I had highlighted this in my earlier article.

Let me throw more light into why cognitive automation makes sense, and why it needs a Day 1 approach.

Cognitive is beyond rules

With enhanced automation levels, businesses can automate the decision-making processes by itself. This is where most businesses struggle to remove the manual dependency on repetitive processes. These tasks are considered complicated and rarely given a thought to be automated. If the software bot can train and learn on itself, and semantically understand the process and data and understand from history what the next course of action is to be taken, it will free up more time for staff and increase the levels of automation for business.

Exceptions always require interventions, and with self-learning capabilities, bots can minimise these interventions, thereby increasing process efficiency and enhancing accuracy with their cognitive capabilities to assist decision making. The right automation solution will even help you bring down automation costs from investing in unnecessary licenses for bot farms. It will even decide based on load and the availability of bots how to distribute work and get things running without pausing for allocation of resources.

Let’s take the example of a common challenge of invoice processing and compare two scenarios.

Typically, with rule-based automation:

  1. Bot designers manually define templates for each supplier graphically
  2. Bot reads new incoming invoice and identifies the template to be applied
  3. Bot extracts information based on template and loads into ERP
  4. Bot tags invoice for manual processing if a suitable template could not be identified
  5. Operator manually loads the invoice to ERP
  6. Bot designer manually adds the templates for invoices which could not be read

See the point? Each time a new invoice enters the system and the bot is not able to read it, the designer needs to train the bot with the new template.

The same process when executed by a cognitive bot:

  1. Bot designer extracts historic invoices and ERP data
  2. Bot reads the invoices and generate Machine Learning model
  3. Bot reads new incoming invoice and applies ML model to extract invoice details
  4. Bot loads the data into ERP
  5. Bot tags invoice for manual processing if it cannot read with sufficient confidence level
  6. Operator manually loads the invoice to ERP
  7. Bot self learns how operator read the invoice and handles it the next time

The difference is visible. It’s equivalent to how we think, without rules. Cognitive automation understands the context and content and handles changes intuitively.

Get your worth out of automation

Cognitive automation reduces manual effort to unprecedented levels once RPA is implemented. It can handle a wide range of complexities and unstructured data within a short span of time, and give you higher automation levels without restricting to rules/creating new templates each time the process encounters and exception. It is not something to be kept for later stages as an afterthought to existing automation, and needs to be a key strategic asset while looking for automating from day 1.

It is important for enterprises to educate themselves on revisiting their approach to automation, when the possibilities are endless with an automation platform that has real cognitive capabilities.

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