Research & Resources

Automating back-office processes in a manufacturing company
June 7, 2020

Practical Process Automation Improves Efficiency in Manufacturing Companies
                                                                  Trushal Thaker, Zoran Gacovski

In order to stay competitive in today’s global environment, manufacturing companies have to adopt some process automation that will optimize their daily operations. The goal for undertaking a new process automation approach is to free up the creativity and time of operations teams, and management to focus on important forward-looking thinking while at the same time leveraging the power of machine learning and artificial intelligence to make better decisions about routine functions.  Modern applications of artificial intelligence applications leverage the availability of large and growing data assets available to the company to teach computers (machine learning) determine the best course of action autonomously (robotic process automation, RPA for short)

The practical applications of such technologies are rapidly making an appearance all around us, some dramatic and visible e.g. driverless cars, self ordering refrigerators, smart homes etc.  and many on the backend e.g. claims servicing chatbots, routine business process handling like automatic purchase ordering, automatic data transfer & management, cybersecurity etc.

Everywhere around us computers are cataloging, synthesizing and learning from data created by us, in hopes of  making increasingly intelligent decisions in real time.

Manufacturers operate broad range of items in form of raw materials, tools and equipment, and ship the products worldwide. They manage the whole production process in-house – from taking the customer order to the delivery of products to the customer’s location. Purchasing materials and delivering products – involves keeping track of different processes, field workforce and facilities in order to be successful and profitable.

In this article we are targeting manufacturing companies who are exposed to various marketing hype about RPA and wonder how to start, what efficiency to expect, what are the most suitable opportunities, and where to begin.

Benefits of RPA for Manufacturing companies

The manufacturing companies have accepted the physical process automation early, introducing robots and conveyor lines to perform daily production tasks in the plant.

Today, as an attempt to achieve automated efficiency in the back-office processes, they would need to adopt some business process automation.

Robotic Process Automation, (RPA), is a tool that can be integrated within business processes – in order to automate the activities, reduce human errors, and increase productivity.

A lot of manufacturers are already implementing RPA – thus automating different scope of tasks:

  • Demand and Supply planning;
  • Invoicing, Accounting and Finances;
  • ERP management;
  • Purchase Order management;
  • Logistics;
  • Making Forecast vs Actual expenditures;
  • Customs Import processing etc.

A well-designed and developed process automation solution will address all drawbacks smartly and will provide a business intelligence environment that will:

  • Optimize time-consuming and recurrent working processes;
  • Increase production speed by maximizing productivity;
  • Increase workflow agility;
  • Reduce cost by minimizing human errors and increasing compliance.

Benefits of using RPA in the manufacturing industry also include:

  • Providing intelligent decision-making; by utilizing the power of intuitive graphics and reports – generated from data of large number of customers, inventory and workforce data.
  • Bringing data from manufacturing process that will help determine working patterns, and ensure minimal risk of failure.
  • Creating efficient supply chain operations, with real-time insights on work processes, employee performance and customer behavior; thus maximizing operational efficiency.
  • Enabling management of thousands of products through a unified dashboard view, that will display the damages and losses incurred every month.
  • Presenting important views of different worker’s activities, and to determine the areas of improvement and boost their efficiency.
  • Enabling consolidated view of the data retrieved from multiple sources; in the form of interactive dashboards.

Summary

So, how can a manufacturer start the adoption of the Robotic Process Automation? According to experts, it is necessary to develop a long-term strategy and align changing business processes with technology needs. Companies will need to remain agile and to adapt to the rapidly changing RPA domain.

Robotic Process Automation will provide companies to become more efficient, productive, and competitive by automating routine tasks at a large scale. We, at Visvero can assure our customers that they will achieve a successful RPA implementation, with first results in 2-3 months.


Trushal Thaker is a Practice Lead for Process Automation at Visvero. He’s been supporting several clients, mainly in Oil and Gas , in helping automate strategic data acquisition process. Over the years Trushal has been instrumental in helping clients adopt innovative, autonomous data acquisition and process technologies.

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Some opportunities to leverage AI in your organization
May 31, 2020

Improving Organization Readiness using AI-led Automation process

Arvind Handuu & Zoran Gacovski

These days you cannot help but see nearly all industries talking about revolution in the offing  as a result of Artificial Intelligence, Analytics, Robotics, Robotic Process Automation and whatever other ‘nom de guerre’ your industry uses.

Here is an attempt to catalog a few opportunities for a business executive responsible for helping the companies take advantage of the opportunities ahead.

Background

Digital transformation becomes highly-integrated into the business processes and AI is leading the business technology upsurge. Applying AI in the business process automation is bringing a lot of benefits that come with it.

The automation of processes is a strategic approach that can help organizations to improve the workflow efficiency and responsiveness in their environments. Automation will lead to speeding-up the processes, ensuring flawless outcomes, while reducing the overall costs.

AI-led Automation Use Cases

AI-led automation process is based on different business intelligence and analytics solutions, applied in different scenarios – from decision-making to customers care. This is typically classified in the following categories:

– Decision Support and Strategic
– Operations efficiency
– Engagement Experience

Here we present a few opportunities for you to explore:

1.Decision-making at managerial level:

AI-led automation models can assist the managers in making decisions within a business process. The advancements in AI introduced multiple machine learning algorithms (decision trees, neural networks etc.). These algorithms can help the managers and business-owners to solve problems by applying previous datasets for getting the expected output. For example, the models can help to decide whether a customer should be sent a product recommendation, or needs a follow-up call.

2.Repetitive tasks automation:

Automation of the recurrent tasks is one of the most common applications of AI. AI-based process automation as a tool that applies machine learning and AI methods – can help to handle a large volume of repetitive processes that otherwise need a committed human workforce.

3.Recognition and prediction:

The AI can be used to learn, observe, and analyze data sets that are collected from various channels and identify patterns that humans cannot. Businesses can apply AI methods to determine their course of action. For example, analysis of the data patterns for fraudulent activities related to online transactions, or segmenting clients based on their buying behavior for marketing purposes.

4.Customer Experience :

Let’s consider an example of calls handling at a telecom provider, a chatbot, which, based on Artificial Intelligence, presents the customer with best offers, and subsequently starts automated process for recording the order in an order management system. The benefits are higher turnover, faster and more effective handling time and lower costs.

5.Cost-effectiveness:

the management of business processes is an intensive process that requires significant financial resources, as well as time. The automation, on the other hand, is cost-effective and can use the available resources. Thus, process management steps can once be implemented within an automation technique – and applied many times later.

6.Estimation of Claims:

: At insurance companies, as an example, the AI-based tool can assess the level and accuracy of the claim by analyzing photographs of the damage. Then the tool will ensure that the damage data is recorded in the claims handling system.

7.Handling of paper-based information or records::

AI tools can be trained to scan a large number of records and extract the information to database and made available for future processing. Companies can leverage AI-based automation tools to manage typically paper-based processes, e.g. legacy land records, invoice to payment cycles, oil well leases and exploration rights management, Title insurance, data exchange between otherwise disconnected applications.

8.Handling of remote processes:

in energy providers – data about meter readings are gathered from incoming unstructured emails using AI technology. These meter readings are then recorded in the backend system and processed as necessary.

Summary

AI-facilitated process automation solutions will help businesses to overcome performance barriers and improve their work efficiency and responsiveness. AI is no more a technology that is frightening and hard to adopt.

Small, as well as large organizations can deliberately understand the power of AI-based automation tools for optimizing their business processes. In the upcoming years, the adoption of AI for business process automation will become ubiquitous and more accessible for all organizations.

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Digital Transformation : Conagra Case Study
July 23, 2019

CIO Helps Conagra Turn Food Trends Into Products

A case for how  Conagra’s CIO, Mindy Simon, leveraged the AI platform to use technology to help drive growth, including the launches of new products under the company’s existing brand names. The platform sources data from the likes of Facebook, Google, Instagram, Pinterest as well as from various Market Research companies, with frequent updates. Pulling Data is automated, as is prepping it for analytics applications.

The tool lets the business identify “pockets of growth” that might have otherwise gone unnoticed. This is largely because the platform can tie data together in one place. Click on the link below to read about this project.

Conagra AI application ( 2 pages / 850KB)CIO

 

Copyright (c) 2019 Dow Jones and Company, Inc. CIO Journal 07/22/2019

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