How do digital Live Permits transform “work orders” into a process that keeps pace with reality?

In many industrial plants, work permits still act as a “handbrake” for organizations: paper, signature circulation, scattered information, lack of up-to-date information, and limited visibility of what is actually happening on site. The problem is not just about convenience – it’s about safety, accountability, and the ability to respond quickly to changing working conditions.

Meanwhile, dangerous and critical work (e.g., hot work, work at height, work in hazardous areas, servicing during plant operation) does not happen according to an “ideal plan” — it happens in a dynamic, changing environment. This is why classic work orders often lose out to reality: they are not updated, they are not consistent with who is actually where, and they do not create a single version of the truth for health and safety, maintenance, and external companies.

Live Permits is an approach in which a work permit is not a document “for the archives,” but a living operational process — updated in real time, linked to the location and status of activities on site. This is how we build the system at InnerWeb®.

The challenge: safety vs. speed vs. complexity of operations

Before we move on to technology, it is worth identifying the sources of friction that almost always arise in work permit processes:

As a result, the organization chooses between two bad options: either the process is “tight” but slow and cumbersome, or fast but risky. Live Permits are designed to resolve this conflict — through automation, consistency, and timeliness, not by “letting go” of safety.

Where do Live Permits provide an operational advantage?

Below are the key areas where the “live” approach really changes the quality of the
process.

1. Digital permits as a common “point of truth”

The work permit becomes the central object of the process, rather than a form.

2) Real-time updates – a process that keeps pace with change

The biggest difference between an “e-permit” and Live Permit is that the permit is not static.

Example: if a new risk arises in the zone (e.g., parallel work, leak, parameter exceedance), the permit can be automatically switched to “suspended” mode until corrective actions are confirmed.

3) Location as a safety context (geofencing, zones, plan compliance)

At the heart of the InnerWeb® approach is the linking of work permits to the
actual workplace.

Implementation example: in one of the EU-funded pilot projects at the MAN Trucks
plant in Niepołomice, the process included monitoring work permits, training
requirements for external companies and visitors, along with familiarization with the
current risks when entering the plant, alongside the location of trucks and drivers
moving around the facility – using the dense infrastructure of InnerWeb® Industrial
Radio Beacons (over 200 BLE transmitters on the plant’s internal roads). This shows
that work permits can operate in the same “data language” as logistics and traffic
safety at the plant.

4) Competencies and authorizations – “who can” is verified automatically

Live Permits is not just a form – it is compliance logic.

Example : if current training and specific qualifications are required for hot work, the
system can block the start of work without meeting the conditions.

5) Particularly hazardous work : standards, LOTO, and condition control

For high-risk areas, repeatability and clarity of standards are important.

Example : Activating a permit to work in a confined space may require confirmation
of atmospheric measurements and a rescue plan – without this, the “in progress”
status is not possible.

6) Cooperation with security and gate –admission and verification at the entrance

In practice, many problems begin at the entrance to the facility: incomplete
documents, lack of confirmations, unclear scope.

Example : security can see whether a person has active access to a specific job and
zone, instead of relying on paper or declarations.

Additional features that complete the picture of the plant’s “operating system”

Live Permits work most effectively when they are part of a broader ecosystem: safety, maintenance, and logistics.

Key success factors for Live Permits implementation

Risks and issues to consider

What’s next: from “LIVE” permits to predictive prevention

The next step is to use data from the process (statuses, holds, conflicts, events,
locations, schedules) to predict risks and eliminate them in advance:

Live Permits is the foundation: if an organization has a single version of the truth about field work, it can realistically move from reaction to prevention.

Conclusions

Live Permits is a practical response to a problem that is commonplace in many plants today: safety requires tightness, and operations require speed. Digital work orders with real-time updates — linked to location and compliance requirements – allow these goals to be reconciled without compromising safety.

At InnerWeb®, we build solutions for industrial environments where it is not only “compliance on paper” that counts, but also real control of working conditions, transparency for stakeholders, and the ability to respond quickly. Our implementations and pilot projects show that this model works when it covers the entire ecosystem: health and safety, maintenance, contractors, security, and logistics on site.

About the Author :

Mr. Marcin Worecki,
CEO & Founder
InnerWeb Sp. z o.o. 

Mr. Marcin Worecki, CEO of InnerWeb®, is a visionary engineer with over 20 years of technical and industrial experience.

Together with his team, Mr. Marcin Worecki creates unique legal technology for modern industrial plants based on his own experience, customer requirements, and a deep understanding of the global problem of work permits in industrial plants.

As a result, the InnerWeb® System covers the entire process of managing external technical personnel, from training upon entering the plant, through written instructions for work and particularly dangerous work, as well as audits, acceptance, and permit renewals. InnerWeb® combine electronics, physics, algorithms, artificial intelligence, augmented reality, blockchain, web and mobile applications.

InnerWeb® has based their legal technology on a real-time location system, which also allows InnerWeb® to supervise the work being carried out, improve safety and alert in case of danger, which InnerWeb® protect with a patent in 23 countries (EU and US).

New technological solutions are InnerWeb®‘s passion, allowing InnerWeb® to fully realize their potential. InnerWeb® is open to cooperation and focused on completing the tasks assigned to them. InnerWeb® deliver extremely difficult projects and objectives, making the impossible possible. InnerWeb® operate quickly, dynamically, effectively, and proactively.

Mr. Marcin Worecki can be contacted at:

LinkedIn | E-mail 

About InnerWeb® :

InnerWeb® provides technologies for industrial environments, focusing on safety, maintenance, and organizational efficiency.

InnerWeb® combine software and infrastructure (including BLE) to build location and process solutions, such as Live Permits (mobile work permits) and systems that support real-time risk control.

InnerWeb® carry out projects in the form of implementations and pilot programs, including co-financed projects, where, in addition to process digitization, verification of operational value in real plant conditions is key.

InnerWeb® can be contacted at :

InnerWeb®
ul. Michała Grażyńskiego 14
43-300 Bielsko-Biała, Polska

InnerWeb®’s Social Media Handles :

LinkedIn | Website | Youtube | Facebook

For InnerWeb® Technical Support : Email 

Tel: +48 668 669 621

For InnerWeb® Commercials Service : Email 

Tel: +48 668 669 328

The post Live Permits: real-time Permit-to-Work (PTW) appeared first on Industry4o.com.

1. Start Small and Focus on One Problem

About the Author:

Mr. Glen Young 
Fractional Chief Data Analytics Officer (CDAO)
Fraction8

Mr. Glen Young is an experienced Data & Analytics Executive with over 15 years of expertise in designing and building scalable data platforms.

Mr. Glen Young is a proven leader in driving data architecture, technical direction and implementing strong data governance frameworks.

Mr. Glen Young is a passionate about fostering innovation, enhancing data capabilities, supporting data science, machine learning, and AI initiatives.

Mr. Glen Young is committed to making a meaningful impact through data-driven decision-making and continuous improvement.

Mr. Glen Young is excited to collaborate with cross-functional teams and stakeholders to achieve strategic objectives and drive business success.

Mr. Glen Young is Bestowed with the following Licences & Certifications :

https://www.linkedin.com/in/glenyounginaustralia/details/certifications/

Mr. Glen Young  can be contacted at :

LinkedIn | Website

About Fraction8

Fraction8 Australian Fractional Chief Data Analytics Officer (CDAO) offers expert remote leadership, providing strategic guidance in data and analytics without the need for a full time executive. This role drives data-driven transformation, enabling businesses to leverage data and AI for strategic growth and innovation.

At Fraction8, our mission is to serve as your fractional partner for data-driven success. The benefits of our service include cost-effective access to top-tier data expertise, flexibility in engagement, and the ability to scale data initiatives according to business needs.

Fraction8‘s Services :

Fraction8 play a crucial role in assisting small to medium businesses in Australia and New Zealand by providing a functional Chief Data Analytics Officer (CDAO). This enables our clients to effectively leverage data without the necessity of employing a full-time executive. Designed for organisations seeking expert-level guidance without the commitment of a full-time executive, Fraction8 provide strategic leadership, data-driven insights, and tailored roadmaps to empower smarter decisions.

Services Provided by Fraction8 :

Business Consulting • IT Consulting • Information Management • Business • Analytics • Change Management • Corporate Training • Database • Development • Application Development

Fraction8 can be contacted at:

LinkedIn | Website

The post SMEs to Automate & Integrate AI appeared first on Industry4o.com.

Businesses are akin to complex algorithms—always in need of fine-tuning. But what if you could make your operations not just efficient but also intelligent?

This is where integrating knowledge bases together with business software comes into play.

It’s not enough to just have a set of data or a set of automated positions; you also need to make sure they function efficiently together.

This piece goes into depth about how knowledge-base-driven automation can change things, showing how it may help make your business not just better, but exceptional.

What is knowledge base driven automation?

Knowledge Base Driven Automation refers to the integration of a knowledge base—a centralized repository of information—into automation systems. This enhances the decision-making capabilities of automated workflows, making them more intelligent and adaptive.

What’s a Knowledge Base?

A knowledge base is an organized library of information. It contains data, facts, guidelines, and procedures that are crucial for a business.

But building a knowledge base is about more than just collecting information; it’s about making a dynamic database that your automatic systems can use. This connection is the fundamental basis of many parts of your business, from organizing your inventory to assisting consumers.

Think of it as being the brain of the organization since it holds all the details you need.

And Automation Software?

Automation software like Zapier helps systematize work procedures and perform tasks without human intervention. It’s the muscle that carries out actions based on predefined rules or algorithms.

How Does It Work?

Automated systems consult the knowledge base to make informed decisions. When you combine these two, you get a system that not only knows what to do but also how to do it efficiently.

Consider the case in customer service, a chatbot could pull data from a knowledge base to answer complex queries without manual assistance.

Here’s how it works:

1. Data Retrieval: The automation software queries the knowledge base for information.
2. Decision Making: Based on the retrieved data, the software makes decisions.
3. Action: It then performs tasks, whether it’s sending an email, updating a database, or initiating a process.

Why It Matters

This approach elevates automation from mere task execution to problem-solving. It reduces errors, speeds up processes, and often results in cost savings.

In a nutshell, Knowledge Base Driven Automation makes automated systems smarter and more efficient.

How can knowledge base integration improve business automation?

The fusion of knowledge base and automation software serves as the backbone for a more agile, secure, and responsive business model.

Now, let’s explore the specific ways this integration can revolutionize your business operations.

Knowledge base integration allows automation to adapt to growing business needs.

Incorporating a knowledge base into your business automation systems allows for greater adaptability, which is especially important given the rise of remote-first companies.

As your business grows, so do its complexities and demands. A knowledge base serves as a centralized repository of information that your automated systems can tap into.

For instance, if your business expands into a new market, the knowledge base can update automation rules to comply with local regulations. This adaptability ensures that your operations remain efficient and compliant, even as your business landscape changes

Enables real-time inventory management by pulling knowledge base data.

A knowledge base can house real-time inventory data, which can be accessed by automated systems for accurate inventory management.

For instance, if an item is running low in stock, the system can automatically reorder it. This eliminates the need for manual checks and reduces the risk of stockouts.

Tip: Implement a system that pulls inventory data from the knowledge base at regular intervals to keep stock levels optimized.

Utilizes knowledge base analytics to predict and prevent system outages.

System outages can be costly. By integrating analytics from your knowledge base into your automated systems, you can predict potential issues before they occur.

A knowledge base can store historical data on system performance, which can be analyzed to predict future outages. Automated systems can then take preventive measures, such as rerouting traffic or adjusting server loads, to avoid downtime

Tip: Use analytics tools to monitor patterns and set triggers for automated preventive actions.

Improves security by cross-referencing threat data in the knowledge base.

Your automated systems can cross-reference data from the knowledge base to identify and mitigate security threats.

This isn’t just about flagging suspicious activity; it’s about having a security certification that validates your system’s robustness.

When a dubious IP address attempts entry, the system doesn’t just raise an eyebrow. It cross-references the address with the knowledge base.

If there’s a match with known threats, access is denied. No loopholes. Just secure, certified operations.

Speeds up customer service with quick, accurate responses.

Automated customer service can be a double-edged sword. While it’s fast, it can also be inaccurate. However, by pulling data from a well-maintained knowledge base, automated customer service systems can provide quick and accurate responses.

FAQs, troubleshooting guides, and other relevant information can be instantly accessed to resolve customer queries without manual help.

Knowledge base data tailors automated interactions to individual preferences.

Personalization is key to customer satisfaction. Automated systems can pull data from the knowledge base to tailor interactions based on individual customer preferences.

Whether it’s product recommendations or targeted marketing, personalization can significantly boost customer engagement and sales.

Tip: Collect and categorize customer behavior data in the knowledge base for more personalized automated interactions.

Enables dynamic pricing strategies by consulting real-time market data.

A knowledge base can store market trends, competitor prices, and customer behavior. Automated systems can then consult real-time market data stored in the knowledge base to meet any changes or demands.

By integrating this data into your pricing strategies, you can automatically adjust prices to maximize profits or market share.

Tip: Implement real-time market data tracking in your knowledge base and set pricing algorithms to consult this data for dynamic adjustments.

Conclusion

As you ponder the future of your business, consider this: integrating a knowledge base into your automated systems is like discovering a new dimension of possibilities. And in this dimension, your business doesn’t just survive; it thrives.

By integrating a knowledge base into your automation processes, you’re not just staying ahead of the curve—you’re drawing a new one. Therefore, it’s time to move beyond traditional automation and step into a realm where technology and intelligence coalesce to drive business success.

About the Author :

EDRIAN BLASQUINO is a college instructor turned wordsmith, with a passion for both teaching and writing. With years of experience in higher education, he brings a unique perspective to his writing, crafting engaging and informative content on a variety of topics. Now, he’s excited to explore his creative side and pursue content writing as a hobby.

Mr. EDRIAN BLASQUINO can be Contacted at :

LinkedIn | Email

Banner image credit : Pexels

The post Knowledge Base Driven Automation appeared first on Industry4o.com.

Intelligent Automation is one of the key drivers in business transformation today. It has now become a part of the enterprise strategy of many large organizations. From back-office automation of manual, labor intensive processes, it has become a key enabler in enterprise transformation, automating customer journeys spanning across front, mid, and back offices. It is now one of the key pillars of the digital and process transformation which delivers the promise of adaptive, intelligent, and smart processes across the enterprise.

When I started working in Intelligent Automation in around 2015, it was primarily RPA centric. The tools were still maturing, and automation was still to prove its full potential beyond a few back-office operations. Today, it’s a different scenario altogether. Industry 4.0 has automation powered by AI as its key lever and discussions on automation are prevalent across all segments and industries today. Intelligent Automation has proved that it is here to stay.

I learnt automation mostly on the job, starting from designing core automation solutions, driving their delivery and deployment, to consulting Fortune 500 clients on Intelligent Automation Strategy and transformation. I have been a part of the evolution – basic  automation to Intelligent Automation and soaked in the buzz around it. The idea of this book emerged with the thought to pass on the knowledge and experience I have accumulated over the years, to younger professionals, and help them get a holistic idea about this from a practical perspective. This book is meant to help and guide professionals implement Intelligent Automation in their respective organizations. It’s written in simple language to allow readers to get the essence of it without sounding too technical about it. I have embedded practical tips, design samples and stories from my experience to help readers navigate through real projects in their jobs.

This book assumes that the reader is familiar and has got basic exposure on how to design and deliver software development projects. It also assumes that the reader is familiar and has a basic concept about software component design principles. Since this book is not a deep dive on any particular technology component, it assumes that the readers have initial familiarity on AI , RPA, Blockchain , IoT, Integration.

The content of this book is purely a practical perspective and guide for business engagements to aid professionals who are new to Intelligent Automation. This book may not address any research or theoretical questions.

Over the 7 chapters in this book, the readers will learn the following :

Chapter1  introduces Intelligent Automation as a concept and how it has evolved. It then focuses on the different levels of automation, the various components on this and finally touches upon some of the impacts of automation in the context of future of work.

Chapter 2  discusses Robotic Process Automation in detail, with its characteristics and capabilities. It tells you how to decide which use cases are best suited by RPA and how to go about developing them. It touches upon some of the leading products and solutions

Chapter 3 focuses on Artificial Intelligence, what it entails and the various capabilities of AI that are relevant in the context of Intelligent Automation and how to decide which use cases are fit for AI implementation.

Chapter 4 discusses the other technological components that make up Intelligent Automation like BPM, Blockchain, IoT, Integration and best practices for implementing them in the enterprise.

Chapter 5 is the most important chapter of the book. It describes several key use cases across business and IT automation. It describes the processes, tells you how to select the automation levers, how to design this solution with the aid of detailed component design diagrams. This is my favorite chapter ?

Chapter 6 is a key chapter which discusses, in depth, the enterprise automation journey, why we need an Intelligent Automation Center of Excellence and what are the key capabilities of a CoE that can help an enterprise scale automation.

Chapter 7 is the last chapter and before wrapping up, touches upon some of the key trending topics around automation today. Citizen development, Process Mining and AIOps are discussed in detail before ending the chapter with Future of Work – the impact of Intelligent Automation.

Technology is rapidly evolving, and the pandemic has forced all of us to adapt and thrive in the new environment. I am certain, that over the next few years, we will see more evolution of Intelligent Automation as it becomes farther mainstream and touches every aspect of our lives.

Ms. Debanjana Dasgupta book Intelligent Automation Simplified is available in :

https://in.bpbonline.com/products/intelligent-automation-simplified

https://www.amazon.in/Intelligent-Automation-Simplified-Enterprise-Use-cases/dp/9391392547/

About the Author :

Ms. Debanjana Dasgupta
Associate Partner & Executive IT Architect – Intelligent Automation at IBM India Pvt. Ltd.,

Author : Intelligent Automation Simplified

Ms. Debanjana Dasgupta is an experienced IT architect and consultant, who for the past 25 years have been working with customers across the globe, designing various technological solutions to resolve their business problems. She completed her engineering from Jadavpur University, Kolkata majoring in Electrical Engineering and started her career with a leading IT company. In her career, she has worked with several Indian and Global IT majors, serving plethora of global clients across industries. She is currently employed with a leading MNC and focused on Intelligent Automation. She is based out of Delhi, India.

Apart from her job, Debanjana loves to coach, mentor, teach and is actively involved in mentoring IT architects and technical professionals in her organization and beyond.

Outside work, she is an avid traveler and a passionate musician.

Ms. Debanjana Dasgupta is Bestowed with the following Licenses & Certifications :

https://www.linkedin.com/in/debanjanadasgupta/details/certifications/

Ms. Debanjana Dasgupta can be contacted at :

LinkedIn : https://www.linkedin.com/in/debanjanadasgupta/

E-mail : debanjanad@gmail.com

Twitter : https://twitter.com/debanjanad

The post Intelligent Automation Simplified : A Synopsis appeared first on Industry4o.com.

Introduction

Automation of human work in the services industry has evolved dramatically over the last two decades. End User Computing (EUC) programs like spread sheet applications and macros scripting were used earlier to automate mundane and repetitive tasks like reformatting data. However EUC would work only with few applications and was limited in its ability to scale across multiple applications. Advancement in EUC technologies eventually made way for Robotic Process Automation (RPA) technology which seamlessly interacted with multiple applications, just like a human worker would do. RPA is very efficient in executing repetitive tasks at scale but is limited in its ability to communicate with users, comprehend information and make decisions on its own. This gap was filled by Conversational AI and Machine Learning (ML). Conversational AI systems, also called Virtual Assistants, automated the communication with users, understood their queries and provided an appropriate response. Machine Learning techniques build models from historical data in order to predict future outcomes that can be used in decision making. RPA, Conversational AI and Machine Learning technologies are part of the Intelligent or Cognitive Automation wave and they will largely define the future of work automation in the services industry.

Robotic Process Automation (RPA)

RPA refers to a software program, known as a bot, which can automate a business process and execute it from start to finish without any manual intervention. The bot can replace a human worker either partially or entirely depending on the nature and extent to which a process can be automated. The key business benefits of RPA include faster turnaround time, increase in data accuracy and cost savings resulting from employing fewer human workers. It was observed that when RPA is implemented at scale, it can deliver a return on investment in approximately three to six months (Source: Accenture Research). RPA works best when a process is rule based and the data is available in a structured format.

A RPA bot is different from the earlier software programs used for automation like screen scraper, macros etc. in many ways:

• it can be configured without any programming knowledge
• it interacts with the presentation layer of any application
• it is highly scalable in terms of its ability to work with multiple applications and processes across the organization
• it can scan a document (word, excel, pdf etc.) and read data from it using OCR (optical character recognition) and other image processing techniques.
• it can execute the process without anyone attending to it

RPA adoption has significantly grown over the last five years across several industries in the services sector. In 2016 the RPA market was sized at $250 million and is expected to grow to $2.9 Billion by 2021 (Source: Forrester).

Conversational AI

Conversational AI refers to chat and voice based virtual assistants that automate the communication with users and create a personalized experience at scale. The chat based virtual assistants are called Chatbots and voice based virtual assistants are called Voicebots. Chatbots and Voicebots are powered by Natural Language Understanding (NLU), Natural Language Processing (NLP), Machine Learning (ML) and Deep Learning (DL) algorithms that can understand text or speech from a user, generate an appropriate response and then share it with the user in the form of text or speech. The business benefit of a Conversational AI based virtual assistant is that it can handle 1000s of queries at the same time, be available 24/7 and reduce the need for live customer support thus creating a direct cost savings on employee salary, overhead, training etc. It also enhances the customer service experience resulting in a happy and satisfied customer.

It is estimated that the global Conversational AI market size will grow from USD 4.2 billion in 2019 to USD 15.7 billion by 2024, at a CAGR of 30.2% during 2019–2024 (Source: Research and Markets).

Machine Learning

Machine Learning (ML) refers to a methodology of analysing data by learning from the patterns and inter-linkages that exist in historical data. ML is a branch of AI where the underlying concept is that it is self-learning and has the ability to draw inferences and predict outcomes on its own without any human intervention. ML relies on training a pre-selected model with historical data and then using the model to generate the outcome for a new set of data. The benefit of ML over classic statistics based model building is that it does not make any assumptions on the data and lends the data dictate the entire analysis.

Machine Learning is pervasive across data intensive industries. In 2017 the global machine learning market was around USD 1.58 billion and is expected to reach approximately USD 20.83 billion in 2024, growing at a CAGR of 44.06% between 2017 and 2024 (Source: Zion Market Research).

Robotic Process and Cognitive Automation – New-age, Intelligent Digital Worker

Automation of work is evolving rapidly and technologies that once worked in silos can now be clubbed together to create a new-age, intelligent digital worker (i.e., a bot) that can not only replicate human actions but also make decisions like a human. RPA, Conversational AI and Machine Learning can come together to provide a comprehensive, no-touch, automation solution that will overcome their individual limitations and enable the business to derive maximum benefits from them. The intelligent digital worker will use Conversational AI (Chatbot or Voicebot) to automate interactions with the customer, RPA to automate all back-office processes like customer on-boarding, verification, email communication etc. and Machine Learning to add cognitive capabilities in order to facilitate automated decision making without any human intervention.

It has been observed that when AI technologies are combined with RPA, the market size of the opportunity is almost 13 times bigger when compared to that of a stand-alone RPA solution (Source: Digital Workforce, Rob King).

Intelligent Digital Worker is a work-in-progress

The ultimate objective of robotic and cognitive automation is to create an intelligent digital worker that becomes a reliable virtual assistant and a trusted partner for a human worker. Future of human work will involve active collaboration with a digital worker. Advancement in Conversational AI and other AI, ML technologies, coupled with RPA has created an intelligent digital worker with strong cognitive capabilities that can read data from unstructured documents and respond to non-standard business situations. However adoption of robotic process and cognitive automation by the industry in still in its infancy and it will increase significantly in the coming years. It is expected that these technologies will continue to evolve as adoption increases and it will get closer to achieving its desired objective within the next two years.

Conclusion

It is inevitable that automation of work in the services industry will move beyond data intensive tasks that are considered to be routine, repetitive and mundane and increasingly involve cognitive, decision making tasks. Intelligent work automation is enabled by robotic process automation and cognitive automation technologies like Conversational AI and Machine Learning. The success of work automation lies in the ability of the business to harness these technologies and create an intelligent digital worker that can execute tasks at light speed and at the same time process information, make decisions and communicate like a human.

About the Author

Mr. Sushant Gaonkar

Digital Transformation Leader | Iconic Career Mentor | Best Selling Author

Sushant Gaonkar is a Digital Transformation leader with more than a decade of experience and expertise in leveraging new age digital technologies for solving business problems.

He is also seasoned corporate leader turned professional career coach and mentor. Sushant Gaonkar is recipient of India’s Top Career Counsellor award.

He has worked for global corporations like Deloitte, Xerox and Vistaprint in various managerial and leadership roles in both USA and India.

He is on a mission to empower experienced working professionals to get clarity, growth, rewards and build an Iconic career.

He has coached several hundred working professionals on career clarity, career growth and career transition.

He is also a Best Selling Author of the book ‘Iconic Career’, where he has condensed his 16+ years of corporate experience in the USA and India and 3+ years of professional career coaching and mentoring experience.

He is an alumnus of Cornell University (USA) from where he obtained his Master of Engineering degree, University of Rochester (USA) from where he obtained his MBA degree and National Institute of Technology Karnataka, India from where he obtained his BE degree.

He can be reached at:

Ph : +91 97010 01162
e-mail : sushant@careersuccessbp.com
website: https://careersuccessbp.com/
Facebook : https://www.facebook.com/groups/iconiccareer/
LinkedIn:  https://www.linkedin.com/in/sushantgaonkar
Instagram:  www.instagram.com/sushant.gaonkar_10xcareer
Facebook:  https://www.facebook.com/sushantgaonkar10x/
YouTube:  http://bit.ly/YouTubeSushantGaonkar

Read my #1 Best Seller Book:
https://www.amazon.in/dp/9390156890?ref=myi_title_dp

Also read his book review

The post Future of Work Automation appeared first on Industry4o.com.

Workflow automation is an approach to create series of automated work performed independently by various stakeholders in a process. The steps in the workflow are performed based on predefined rules one after another or in parallel. When workflow automation is implemented rightly, the automation will be a simplified way of executing work on a day-to-day basis.

How to decide if a workflow can be automated? 

• It is a repetitive work
• Errors occur when performed by human 
• It’s a series of simple actions which needs to be performed based on the preceding action leading to an outcome

Workflow automation will help organizations to streamlining their daily tasks and identify new opportunities for automating other areas of work. Workflow automation can be as simple as a Leave/Petty Cash Approval process to as complex as Procurement Management. 

Importance of workflow automation

You need to automate your workflows whenever possible for various reasons, including faster Turn Around Time(TAT) resulting in saving time. It also increases the efficiency and accuracy of the work. The other advantages of workflow automation are:

• It allows the employees to use the time saved from automated workflows to work on other tasks which are nonautomated
• As the productivity of employees goes up with more work getting done, you will have cost savings
• Workflow Mapping, a method to diagram an entire process with different symbols to document one process step and actions, when implemented paves organizations the way for a more visible and transparent top-down view of their workflows
• Workflow automation addresses communication improvements among your team. Once a visible workflow is automated, employees know what needs to be done next and by who accurately
• It also allows your employees to collaborate in completing work collectively
• Visible workflows let you identify unnecessary tasks easily and eliminate the redundant tasks from your process
• Digital workflow platforms enable you to easily review organizations business operations

Benefits of workflow automation

Some of the benefits of workflow automation are:

• helps you with optimized workflow cycles
• saves man-hours by automating repetitive and redundant tasks
• eliminate manual intervention involved in completing a work
• improved visibility to the process
• helps you identify bottlenecks in the process and eliminate it
• improves employee satisfaction, and work-life balance 
• Dashboards and Analytics Tools gives you complete visibility to Key Performance Indicators (KPI) and improvement areas 
• improved internal and external communication
• it offers flexibility to modify the process to the changing business need with easy to use no-code platforms 
• with the ability to integrate with your email, calendars, and other applications, it offers efficient ways of task management

Uses of workflow automation

Workflow automation can be implemented from admin to finance and IT to marketing. Here are some of the departments in your company which can benefit from workflow automation:

Human resources

• Reduce paperwork
• With automated approvals, Sourcing to recruiting of candidates is made faster
• Process Compliance 
• Enhanced employee onboarding/offboarding experience

Finance

• Document management 
• Faster approvals
• Auto-payments of recurring invoices
• Setup a simpler Payroll management system
• Seamlessly transfer data to other accounting software for better management

Marketing

• Delegate repetitive to the system
• Collaborate with teams in multiple locations
• Ensure content gets approved by the right authorized individuals

Some of the key features to look for in Workflow Automation Software:

• Online forms
• Individual and Team assignment
• Scheduling
• Progress tracking
• Communication tools
• Customizable notifications
• Reporting
• Document management
• Integration capabilities
• Prebuilt Templates

Conclusion:

Streamlining your processes with a highly visible, intuitive workflow management tool, will help you improve team efficiency and reduce room for error. There are many tools like monday.com, Kissflow, asana, cflow in the market. Each of these platforms has its advantages. Carefully evaluate a solution that suits your organization’s needs or contact a certified implementation partner like Scalerater for a seamless transition. 

About the Author

Mr. Vijayanand S.
CEO, Scalerater LLP

Scalerater, a Start-up based out of Coimbatore, is focused on releasing bottlenecks to Scale & Accelerate Business. Our Partnerships are chosen carefully to aid End Users. They allow Business Owners complete Flexibility & Control in managing and growing their business. Scalerater is an authorized reseller & implementation partner for leading CRM, BPM, Customer Experience, Productivity and Mobile Device Management Tools.

Linkedin Profile: https://www.linkedin.com/in/vjanands/

He can be contacted at Mobile : +91 90940 43330 or e-mail : vijay@scalerater.com

Also read my earlier Article

How to Monitor Remote Employees in these Critical Times?

The post What is Workflow Automation and how organizations make process awesome & wonderfully simple & productive? appeared first on Industry4o.com.

A Netlabs Global Point of View

When one thinks of Automation in Manufacturing context, the first thing that comes to mind is Robots in the assembly lines. However, the advent of digital transformation technologies like Robotics Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), etc. has also led toSoftware Robots (Bots) being adopted by the Manufacturing sector.

While the horizontal use cases in functions like Finance, IT, HR, etc. are common and cuts across industry types, below are some use cases of RPA & AI in some core process areas of Manufacturing, viz, Supply Chain, Costing, Procurement, Sales & Distribution.

• Inventory Management: Monitor, manage & track inventory at various stages, including near real-time Work in Process (WIP) inventory updates to ERP systems like SAP.
• Stamping Die Process Costing: Read die process sheet for stamping part. Cross reference with financial information and part information from PLM. Calculate cost and load it back in PLM system against the part.
• Inventory Shortage Reporting: Pull open ticket information from systems related to inventory shortages for all plants. Analyze and sort it based on plant and part. Determine target supply plant and create a supply notification.
• Just-In-Time Inventory Delivery: Pull Manufacturing schedule and sequence. Generate part list on the fly. Load it to ERP systems. Deliver and report.
• Supply & Demand Planning: Forecast inventory needs examiningcomplex records &market indicators, and using complicated techniques. Bots can do this faster and more effectively than humans.
• Freight Management: RPA in supply chain can enhance other aspects of freight management, such as route optimization, freight accounting, and freight claim management.
• Order Management: Creation of PO, SO and PR in ERPs can be done faster with Bots.
• Vendor Selection & Procurement: RPA can be used in preliminary analysis of vendor documents evaluating the vendor and running a credit check, as well as finalizing the vendor selection.
• Shipment Status Communication: RPA can be used to track, manage and communicate with the customers on the shipment Status.
• Procure to Pay (P2P): Data extraction and integrations with multiple systems can be achieved through RPA & AI which will make the Procure to Pay process fast and efficient, with enhanced vendor satisfaction levels.

• Price Update: Run price and scale price; mass uploads the purchase grid price into ERPs from data into MPS.
• Source to Pay (S2P): Data extraction and integrations with multiple systems.
• Vendor Master Data Management:RPA can be used in several pre-checks, like VAT validation, IBAN validation in a country-specific website.
• Procurement Analysis:Identify invoices where contracted price and terms are more favourable and adjust payment to reflect contracted items.
• Invoicing Process Automation: RPA can be used for automation of invoice processing from vendors in volumes.
• Sales Analytics: RPA can be used for gathering data from multiple sources on a daily basis and presenting comprehensive reports to the decision-makers regarding the market performance of their product lines.
• Direct Store Delivery: RPA can be used to enhance the sales behaviour to increase revenue, reduce the number of hours, reduce the turnover rate by bypassing the Distribution Centre.
• Capex Creation: Initiation of approval and tracking of CER requests done using RPA.

In summary, below are some of the key benefits that Manufacturing companies can achieve from adopting RPA & AI:

• Optimizing time-consuming, manual and repetitive routine processes
• Increasing go-to-market speed by maximizing productivity and efficiency
• Reducing cost by minimizing human errors and increased compliance
• Increasing agility in operation, thereby enhancing revenues & optimizing costs

Enhancing stakeholder satisfaction levels – employees, customers, vendors

About the Author

Ms. Rhea K M

Netlabs Global IT Services Pvt. Ltd.

The post Hyper Automation appeared first on Industry4o.com.

Automation of business processes and activities (not to be confused with the ones associated in Manufacturing and Logistics like assembly line, physical Robots, etc.) per se is not a new concept. Software-led automation started with the Materials Resource Planning (MRP) concepts in late 1980s. From thereon, it spread its tentacles to encompass/integrate a variety of enterprise wide business processes (Manufacturing, Finance, Sales, Procurement, Supply Chain, Inventory, HR etc.) and became the behemoth called Enterprise Resource Planning (ERP).

In essence since the early 1990s, apart from being positioned as a single integrated piece of software that ran enterprises worldwide, ERP systems also automated a slew of manual business processes. Various fancy sounding names started being given to ERPs like “single version of truth”, “systems of record”, etc. etc. The benefits were simply overwhelming and ERP-led automation initiatives cornered the lion’s share of IT budgets/spends of enterprises globally. This also heralded the “golden era”(to be read as – laughing their way to the bank!) for ERP platforms like SAP, Oracle, JD Edwards, Peoplesoft, Infor, etc, and for a category of service providers (called System Integrators or SIs) like IBM, Accenture, Cap Gemini, Infosys, Wipro, etc.

Since the ERP days, it is the author’s considered belief that two other technologies which have significantly disrupted the ways that businesses are being run and will be run, are Cloud and “Intelligent” Automation (Gartner calls it Hyper Automation). While Cloud is fully mainstream now and is like an adult in its full prime, Intelligent Automation is the new buzzword and is today like a teenager raring to make its mark in the enterprise and IT world.

Software-led automation in its current and evolved avatar is known as Robotics Process Automation (RPA), which kind of appeared in the horizon since the past 4-5 years or so. They are covering the existing manual business processes in organisations which are not still catered to by packaged ERP/CRM/SCM applications. RPA platforms like UiPath, Automation Anywhere, Blue Prism, etc are leading the charge and raking in the investor dollars and also early customer adoption moolah. SIs are busy ramping up their RPA practices to ride the wave. All this seems too familiar like what happened during the ERP wave.

The big question is whether the earlier template can be re-used, as-is. A significant number of customer asks are now no longer just about, can you automate this manual process? They are also asking can there be intelligence built in to it, can it self-learn, can it self-analyse/diagnose & self-heal, etc?So, this brings into the picture another big disruptor, possibly the biggest and most powerful of them all (in terms of both positives, and also negatives if one believes Robots will overpower humans one day!). It’scalled Artificial Intelligence (AI) and when combined with RPA, the mix becomes a potent potion called “Intelligent” Automation, which has the key to what customers are asking for now.

While RPA leaders like UIPath are scrambling to re-position themselves and get AI into their product and marketing story, even IT biggies like Microsoft are making their moves in their own inimitable style (rebranding their existing PowerApps & Flow stack as an AI+RPA stack). These are interesting times and there is also talk of the giants gobbling up the best of breeds (read, acquisitions).

Remains to be seen how Intelligent Automation aka Hyper Automation evolves from being a teen to an adult!

About the Author

Mr. Subham Sarkar
President & COO – NETLABS

He can be contacted at subham.sarkar@netlabsglobal.com

The post Intelligent Automation – In Its Early Teens appeared first on Industry4o.com.

Status Quo:

Currently, the B2B automation of supply chain management frameworks over the internet requires custom implementations. Having standard protocols for such automation will help reduce TTM significantly. We will need both technical as well as business standards.

Why Automate SCM:

Every business faces global pressure to increase their profitability. Cost Reduction could seem like a viable approach but actions like cutting on manpower, reducing capabilities of computer center might affect the entire company negatively.

Automation software would be a better alternate in such situations.

Automation leads to:

Cost Reduction

By reducing the manpower needed, the error margin incurring due to human intervention etc.

Productivity

As the system runs 24×7, without fatigue and also gathers valuable data which can be analysed by other processes and departments to improve productivity.

Availability

Automation is as effective as the underlying hardware, internet connectivity and maintenance of the system. If the connectivity part is taken care of, there are no shifts for this system, it’s at work without a break.

Reliability

Unlike its human counterparts, an automated system is highly reliable as there is a minimal margin of error.

Performance

Automation when in combination with artificial intelligence, leads to unmatched performance and consistent information flow among all parties of the supply chain management system.

The post To Automate or not to Automate SCM? appeared first on Industry4o.com.