Companies talk about “automation”, but what does it really mean?



Automating an organization involves implementing various technologies and strategies to streamline processes, reduce manual labor, and increase efficiency. Here are some common methods:

1. Industry Software Platforms:

a) Implement enhanced software platforms that automate current processes with features like automated reconciliations or customizable workflows.

2. Process Automation:

a) Robotic Process Automation (RPA): Utilizes software robots to automate repetitive, rule-based tasks, like data entry or invoice processing.
b) Business Process Management Software (BPMS): Helps in modeling, analyzing, and optimizing business processes.

3. Data Management and Analysis:

a) Data Integration and ETL Tools: Automate the process of collecting data from various sources, transforming it, and loading it into a database for analysis.
b) Business Intelligence Tools: Automate the analysis of data to provide actionable insights.

4. Customer Relationship Management (CRM):

a) CRM systems automate and manage customer interactions, sales tracking, and customer service, improving customer engagement and retention.

5. Human Resources Automation:

a) Automate HR processes like payroll, benefits administration, and employee onboarding.

6. Digital Document Management:

a) Implement a digital document management system to reduce paper-based processes. This includes digital applications, e-signatures, and online document storage, which enhance efficiency and accessibility.

7. Compliance Automation:

a) Automate compliance monitoring and reporting to ensure adherence to regulatory requirements.

8. Artificial Intelligence and Machine Learning:

a) AI and ML can be used for automating decision-making processes, predictive analysis, and personalizing customer experiences.

9. Cloud Computing:

a) Utilizing cloud services for data storage, computing power, and scalability.

10. Collaboration Tools:

a) Tools like project management software and communication platforms to automate and streamline collaboration.

11. IT Service Management:

a) Automating IT processes and workflows, often through ITSM software.

12. API Integrations:

a) Use Application Programming Interfaces (APIs) to connect different software systems and databases for seamless data exchange. This facilitates better coordination between underwriting, claims, and accounting systems.

13. Financial Management Automation:

a) Automating accounting tasks, financial reporting, and budgeting.

14. Interactive Customer Portals:

a) Develop interactive online portals for clients to access their policies, submit claims, and communicate with agents. This improves customer service and operational efficiency.

15. Blockchain Technology:

a) Explore the use of blockchain for smart contracts, fraud prevention, and secure, transparent transactions.

Each method should be carefully evaluated and chosen based on the specific needs and capabilities of the organization. It is also essential to consider the integration of these systems to ensure smooth operations across different departments.  Vigilant specializes in helping organizations automate their business operations and systems.  Please contact us for more information.


Emerging Technologies that are reshaping business

Technologies Reshaping Business

After GPT/ChatGPT, what technologies are next to reshape business?

While still in its infancy, it appears the recent releases of GPT models are the most significant advancements in technology since the advent of the Internet.  No other technology has leapfrogged us forward into the future, faster than the possibilities of what the AI and GPT models present us.  Not only are we able to immediately find answers we are looking for, but we can have discussions to debate merits, challenge, and have AI models find weaknesses in our theories and analysis.  We can have AI models digest data to help us more easily identify content, opportunities, and issues.  At this moment, it appears we have yet to understand how far-reaching this GPT technology can take us, but with caution, since the technology is still relatively new, and the content issues are not yet fully known.

In this article, we will example several emerging technologies that show promise after GPT models and could potentially have the next significant impact in the future for how we conduct business. Here are a few possibilities:

  1. Quantum Computing: Quantum computers have the potential to solve complex problems much faster than classical computers by leveraging quantum phenomena. If scalable and reliable quantum computers are developed, they could revolutionize fields like cryptography, optimization, drug discovery, and more. For example, drug manufacturers used quantum computing to help advance COVID vaccines in months, rather than the years they would have typically taken to develop (e.g. Moderna and IBM).
  2. Augmented Reality (AR) and Mixed Reality (MR): AR and MR technologies overlay virtual content onto the real world, enhancing our perception and interaction with the environment. As these technologies continue to advance, we can expect transformative applications in areas such as gaming, education, healthcare, design, and remote collaboration. For example, instruction manuals can be viewed through an AR application on your phone and can walk you through a setup of a device in real time, as opposed to reading poorly written paper copies that were included in the device (e.g. TechSee).
  3. Internet of Things (IoT) and Edge Computing: IoT refers to the network of interconnected physical devices that can collect and exchange data. As IoT devices become more prevalent, the need for efficient data processing and analysis increases. Edge computing brings computational power closer to the devices, reducing latency and enabling real-time analysis. These technologies can enhance automation, smart cities, industrial processes, and more. For example, a connected home has a IoT smoke detector that can identify smoke and shut down the IoT thermostat, so smoke doesn’t enter the ventilation system, then alert the fire department (e.g. Google Nest)
  4. Blockchain and Decentralized Applications (dApps): Blockchain technology enables secure and transparent transactions, and it has gained popularity through cryptocurrencies like Bitcoin and Ethereum. In the future, blockchain could be utilized beyond cryptocurrencies, enabling decentralized applications, digital identity systems, supply chain management, and secure voting systems. Blockchain probably has the highest degree of impact on the future of business, because of the digital transaction certainty, which finally allows for integrated business to business transactions.  While cryptocurrency transactions have been executed, the technology of digitizing transactions is still in its infancy, with no clear winner of the cryptocurrency to be used to conduct business transactions.  Also, security is still an issue that will require greater controls.
  5. Artificial General Intelligence (AGI): While ChatGPT represents a significant advancement in natural language understanding, AGI refers to highly autonomous systems that can outperform humans across a broad range of tasks. AGI aims to create machines with human-like intelligence, capable of understanding and learning any intellectual task. Achieving AGI would have profound societal and technological implications, which has the potential to cause more damage than good, if not carefully and thoughtfully implemented.

These are just a few possibilities, but the next impactful technology could emerge from a completely new technology or be an advancement in an existing technology. While we cannot predict the future, we know that breakthroughs can come from unsuspecting places, such as when the Kellogg brothers Kellogg, changed breakfast forever when they accidentally flaked wheat berries, which led to Kellogg’s Corn Flakes.

ChatGPT is changing intelligent automation and RPA

Chat Bot in RPA/Automation

Everything you need to know about ChatGPT and how ChatGPT is changing intelligent automation and RPA.

What is ChatGPT?

You can’t talk about ChatGPT without talking about GPT, or Generative Pre-Trained Transformers, which is a type of Large Language Model (LLM).  GPT refers to a family of machine learning models developed by OpenAI. GPT models, like GPT-4, are based on the transformer architecture, which is a deep learning model primarily used for natural language processing (NLP) tasks.

GPT models are “generative” because they are designed to create human-like responses by predicting the most likely next word or sequence of words in a sentence without losing context. GPT models are pre-trained on large amounts of publicly available text from the internet, allowing them to learn the statistical patterns, grammar, and contextual relationships between words. This pre-training helps the models to acquire a broad understanding of language and context.

Chat GPT Self-attention Model

GPT models (and Large Language Models) use a Transformer architecture, which is a method in artificial intelligence that teaches computers to process data like the human brain (also known as “neural networks”).  Transformer models excel at handling sequential data, such as text, and employ self-attention mechanisms to capture relationships between words and encode them into contextualized representations.

Once pre-training is complete, GPT models can be fine-tuned on specific tasks, such as text completion, translation, summarization, or question-answering, by providing them with task-specific training data. The models use a technique called “unsupervised learning” during pre-training and then transition to “supervised learning” during fine-tuning.

GPT models have achieved significant advancements in various Natural Language Processing (NLP) tasks, demonstrating their ability to generate coherent and contextually relevant text. They can be used for a wide range of applications, including chatbots, content generation, language translation, virtual assistants, and more.

Overall, GPT models are highly flexible and powerful language models that have gained significant attention due to their ability to understand and generate human-like text in a wide range of contexts.

So, what is ChatGPT?

ChatGPT is a chatbot powered by an Artificial Intelligence (AI) model that was developed by OpenAI.  The ChatGPT chatbot is accessible from a website, where you can engage and converse (via typing) with an AI model and get instant responses to your questions.  Where Google search will give you results to questions by connecting you with relevant websites, ChatGPT will give you the answers to your questions.  ChatGPT will also allow you to follow-up on your questions with additional questions, keeping your entire history of questions and responses relevant to the subsequent questions.

ChatGPT launched in December 2022, with GPT-3.5, which was trained on 175 billion parameters, whereas ChatGPT-4 is estimated to be trained on 1 trillion parameters.

OpenAI is an American company, founded in 2015, as a non-profit, open-source company, by a large group of Artificial Intelligence scientists and investors.  OpenAI has transitioned from a not-for-profit company to a for-profit company and has a partnership with Microsoft, as its primary investor, investing over $1 billion with an additional $10 billion committed to OpenAI for further research and development.

How should questions be asked to ChatGPT?

  • Keep it simple. Ask straightforward questions.
  • Be specific. Include specific details with your questions.
  • Use keywords. Use specific keywords in your questions to help refine the results.
  • Refine questions and regenerate. ChatGPT allows you to regenerate responses if you want ChatGPT to write another response.  Alternatively, if ChatGPT is not returning the desired response, try asking the question with an alternative approach.

What can ChatGPT be used for?

  • Brainstorming and ideation.
  • Get personalized recommendations.
  • Understand complicated topics.
  • Use as a writing assistant.
  • Summarize research.
  • Assistance with coding and debugging.
  • Translate text from 95 different languages.
  • Create multiple choice questions on a variety of topics and varying difficulties.
  • Get assistance with travel plans, such as restaurants, cultural attractions, flights, and more.
  • Analyze sentiment and tone for positive, negative, or neutral.
  • Find data sets for research, business intelligence, training machine learning models, and more.
  • Train ChatGPT on your own data.
  • Interview preparation and job preparation.
  • Write songs, poems, and stories.

How can ChatGPT be used in RPA/Automation?

ChatGPT can be used in Robotic Process Automation (RPA) in several ways to enhance automation capabilities and improve the interaction between bots and users. Here are a few examples:

  1. Improved solution design. ChatGPT can be used to help explore and consider alternative technologies.  Recently, we worked with a client that was capturing personal information in an Excel form.  We are experienced enough to identify this is not a secure or compliant process to automate as-is, so we suggested and agreed with the client to build a web-based form.  We have seen too often that RPA firms will just automate the as-is process without consideration for best practices, security, or compliance, so process owners, subject matter experts, and RPA CoEs can consider ChatGPT for improving their solution design capabilities.
  2. ChatGPT can help write Excel Marcos, Excel Formulas, Regular Expressions (RegEx), SQL Queries, Python, JavaScript, C++, C#, HTML/CSS, R, Ruby, Java, and more.  You can also use ChatGPT to summarize the code into human language to help with business process owner reviews to ensure the coding is meeting the requirements of the business case.
  3. Intelligent Chatbots. ChatGPT can be integrated into chatbot frameworks used within RPA systems. These chatbots can understand natural language inputs from users and provide context-aware responses, allowing for more intuitive and conversational interactions.
  4. Data Extraction and Validation. ChatGPT can assist in extracting and validating data from unstructured sources such as emails, documents, or web pages. By training the model on specific data extraction tasks, it can automate the process of understanding and extracting relevant information accurately.
  5. Process Documentation and Training. ChatGPT can be used to generate process documentation or training materials by converting technical information into easily understandable language. This can be beneficial for onboarding new employees or documenting complex workflows in a more user-friendly manner.
  6. Exception Handling and Error Resolution. In complex RPA workflows, exceptions and errors can and will occur. ChatGPT can help identify the nature of the issue and suggest appropriate actions for error resolution. It can also provide real-time troubleshooting assistance, reducing the need for human intervention.
  7. Workflow Optimization and Decision Making. ChatGPT can analyze large sets of data and provide insights for optimizing RPA workflows. By processing and interpreting data from various sources, it can make intelligent recommendations for process improvements, resource allocation, or decision making.
  8. User Support and Self-Service. ChatGPT can handle user queries, provide assistance, and offer self-service options within RPA systems. It can guide users through various tasks, answer common questions, and help troubleshoot issues, reducing the need for manual intervention and improving user experience.

It’s important to note that while ChatGPT can enhance RPA capabilities, it’s crucial to consider its limitations and ensure appropriate safeguards are in place to handle scenarios where the model may provide incorrect or misleading information.  We find that ChatGPT is very good on common knowledge, but abstract thinking is still rudimentary in some areas.  ChatGPT is still evolving and growing, so many of these limitations will continue to be resolved.



  1. Open AI: OpenAI is an AI research and deployment company
  2. The Best Examples Of What You Can Do With ChatGPT
  3. Image Source: Cheng et al., 2016.

Digital Transformation: Beyond RPA and IPA Automation

Digital Transformation, Automation, Vigilant, IPA, RPA

Unleashing the Next Frontier Beyond RPA and IPA Automation: Digital Transformation

In the rapidly evolving and shifting landscape of business, organizations striving to remain competitive and relevant must be agile and responsive. While the deployment of Robotic Process Automation (RPA) and Intelligent Process Automation (IPA) has provided substantial improvements in efficiency and cost reduction, it’s essential for organizations to recognize that these technologies merely scratch the surface of the transformative potential that digitalization can offer. As the dust settles on the era of automation, a new horizon emerges: a comprehensive digital transformation strategy that encompasses not just automation, but the entire spectrum of technological advancements.

1. Automation: A Stepping Stone, Not the Summit

Robotic Process Automation and Intelligent Process Automation have proven their mettle as essential tools in streamlining repetitive tasks, minimizing errors, and maximizing operational efficiency. However, organizations must resist the temptation to perceive these technologies as the pinnacle of innovation. Vigilant recommends to our customers that RPA/IPA should be considered as a transformation tool in a wide-ranging digital transformation toolbox. Other transformation tools may include system upgrades, system parameter enablement, report development, system integration, data governance, and more.

2. From Process-Centric to Customer-Centric

While automation technologies undoubtedly enhance internal processes, digital transformation transcends these confines. It’s time to shift the focus from process-centric improvements to customer-centric enhancements. Seamlessly integrated digital experiences, personalized interactions, and anticipatory services are now the gold standard. Vigilant is helping our customers to leverage data insights from automated processes and AI chatbots to craft custom customer journeys that resonate with today’s tech-savvy clientele.

3. Embracing Data as the New Currency

Digital transformation marks the era of data enlightenment. RPA and IPA generate a treasure trove of data. The next logical step is to harness this data for predictive analysis, AI-driven insights, and informed decision-making. Vigilant helps our customers to unlock hidden patterns, discover untapped opportunities, and optimize their operations with unprecedented precision.

4. Agility and Innovation as Cornerstones

The digital age is characterized by its unrelenting pace of change. To thrive in this environment, organizations must cultivate agility and innovation. While automation laid the groundwork, true transformation involves reimagining processes, products, and business models. Vigilant is helping our customers to adopt emerging technologies such as Artificial Intelligence, Internet of Things, and Blockchain to create new value propositions and revenue streams.

5. Cultivating a Culture of Adaptation

The success of digital transformation hinges on fostering a culture that embraces change. Employees should be empowered to acquire new skills, experiment with novel technologies, and contribute to innovative initiatives. Vigilant works with our customers to develop a culture of continuous learning and adaptation to ensure the organization remains at the vanguard of technological advancements.

6. Navigating Challenges and Mitigating Risks

Undertaking comprehensive digital transformation involves challenges and risks, including technological complexities, change resistance, and security concerns. However, these should not deter organizations from embarking on this transformative journey. Instead, leveraging Vigilant’s experience and depth of expertise allows for opportunities to grow and improve with less risk. Vigilant utilizes effective change management, stringent project management, robust cybersecurity and compliance measures, and thoughtful and practical strategic planning to help mitigate unforeseen challenges.

7. The Holistic Digital Ecosystem

As organizations venture beyond automation, they should strive to create a holistic digital ecosystem. Vigilant helps customers to become data-centric by consolidating technologies, data sources, and processes to deliver a unified and seamless experience across departments, functions, and touchpoints. Data-Centric organizations maximize the benefits of business intelligence and analytics to support data-founded decision making.

In conclusion, while RPA and IPA have played a pivotal role in automating tasks, they are just the beginning of an organization’s digital evolution. To remain relevant and competitive, organizations must shift their focus from isolated automation efforts to a comprehensive digital transformation strategy. By prioritizing customer-centricity, data-driven insights, agility, and innovation, and by fostering a culture of adaptation, organizations can unlock the full potential of the digital age and secure a prosperous future in an ever-evolving business landscape.

We’d love to hear from you and learn how Vigilant can help guide and support you through your Digital Transformation journey.

Current digital transformation projects:

  • OpenText to SharePoint Migration with Microsoft Syntex to categorize and apply metadata to documents.
  • Customer AP chatbot to connect external customers with invoice and payment status to free employee’s time.
  • Migration of RPA processes to Power Automate.
  • Legacy SharePoint and Intranet migration to SharePoint 365.
  • Human Resources data warehouse – Consolidation of 4 HRMS systems.
  • Accounts Payable – AI Invoice Automation.
  • Application development – Internal healthcare application portal.
  • Employee human resources chatbot to allow employees to self-serve HR functions.
  • And more!


Oracle Fusion, ERP RPA automation use cases to consider

Oracle Fusion, ERP, RPA, automation, Vigilant
Oracle Fusion, ERP RPA automation use cases to consider

Oracle Fusion ERP, with its extensive suite of applications covering various aspects of enterprise resource planning, is an ideal platform for integrating Robotic Process Automation (RPA) solutions. RPA can automate routine and repetitive tasks, thus enhancing efficiency, reducing errors, and freeing up human resources for more complex and value-added activities. Here are several use cases for RPA automation in Oracle Fusion ERP: 

1. Accounts Payable Automation:

  • Automated invoice data extraction and entry into Oracle Fusion ERP. 
  • Automatic matching of invoices with purchase orders and receipts. 
  • Automated vendor payment processing based on predefined rules.

2. Employee Onboarding in HR: 

  • Automated creation of new employee records in Oracle Fusion HCM. 
  • Automatic assignment and tracking of onboarding tasks. 
  • Auto-populating forms with employee information to reduce manual data entry. 

3. Expense Reports Processing: 

  • Scanning and extracting data from expense receipts. 
  • Automated entry of expense report details into the Oracle Fusion ERP system. 
  • Auto-routing of expense reports for approval based on preset criteria. 

4. Sales Order to Cash: 

  • Auto-creation of sales orders based on customer purchase orders. 
  • Automated credit checks and order validation. 
  • Automatic triggering of invoicing and payment follow-ups post-delivery. 

5. Monthly Financial Close: 

  • Automation of repetitive tasks like journal entries, account reconciliations, and consolidation of financial statements. 
  • Auto-generation and distribution of financial reports to stakeholders. 

6. Supplier Onboarding and Management: 

  • Automating the collection and entry of supplier information into the system. 
  • Automated checks for compliance and risk assessment. 
  • Regular updating of supplier data, including performance metrics. 

7. Inventory Management: 

  • Automated monitoring of inventory levels. 
  • Triggering restock orders when inventory falls below predefined thresholds. 
  • Automated data entry for goods received. 
8. Compliance Reporting: 

  • Auto-compilation of data required for regulatory reporting. 
  • Automated generation of compliance reports and submissions to regulatory bodies. 

9. Customer Relationship Management: 

  • Automated updating of customer information in Oracle Fusion CRM. 
  • Automatic tracking and logging of customer interactions. 
  • Automated creation of service cases or sales opportunities based on customer actions or requests. 

10. Payroll Processing: 

  • Automated calculation of employee pay, deductions, and taxes. 
  • Automatic generation of payslips and tax forms. 
  • Automated payroll disbursements and posting to general ledger. 

11. Data Quality Management: 

  • Regular scanning and cleansing of data in Oracle Fusion ERP to ensure accuracy. 
  • Automated detection and correction of discrepancies or duplications in data. 

12. Batch Job Scheduling and Monitoring: 

  • Automating the scheduling of batch jobs like data backups or report generation. 
  • Monitoring the execution of these jobs and flagging any issues for human intervention. 

13. Audit Trails and Governance: 

  • Automated logging of all transactions and changes within the ERP system. 
  • Generating audit trails for review by internal or external auditors. 

14. Demand Forecasting: 

  • Automated collection and analysis of sales and market data. 
  • Generating demand forecasts and adjusting procurement plans accordingly. 

By leveraging RPA in these areas, organizations can significantly improve the efficiency and effectiveness of their Oracle Fusion ERP systems, leading to cost savings, increased productivity, and enhanced accuracy. 

Oracle EBS ERP, RPA automation use cases to consider

Oracle EBS ERP, RPA automation, Vigilant RPA automation use cases in Oracle EBS ERP

Oracle EBS ERP, with its extensive suite of applications covering various aspects of enterprise resource planning, is an ideal platform for integrating Robotic Process Automation (RPA) solutions. RPA can automate routine and repetitive tasks, thus enhancing efficiency, reducing errors, and freeing up human resources for more complex and value-added activities. Here are several use cases for RPA automation in Oracle EBS ERP: 

1. Accounts Payable Automation: 

  • Automated extraction and entry of invoice data into Oracle EBS. 
  • Automatic matching of invoices to purchase orders and shipment receipts. 
  • Automated approval workflows and payment processing. 

2. Accounts Receivable Management: 

  • Automation of customer invoice generation and distribution. 
  • Automated tracking and application of customer payments. 
  • Automatic follow-up on overdue accounts. 

3. Payroll Processing: 

  • Automated calculation of salaries, taxes, and deductions. 
  • Automatic generation and distribution of employee pay slips. 
  • Integration with financial modules for general ledger entries. 

4. Procurement Process Automation: 

  • Auto-generation of purchase requisitions based on inventory levels. 
  • Automated vendor selection and purchase order creation. 
  • Automated goods receipt and reconciliation processes. 

5. Order to Cash Cycle: 

  • Automated order entry from customer purchase orders. 
  • Automatic credit checks and order validation. 
  • Auto-generation of shipping documents and invoicing. 

6. Human Resources Management: 

  • Automation in employee on-boarding processes like data entry and document management. 
  • Automatic tracking and updating of employee records for promotions, transfers, and exits. 
  • Automated leave and attendance management. 

7. Inventory Management: 

  • Automated monitoring of inventory levels and auto-triggering reorder processes. 
  • Automatic update of inventory records post receipt or issuance of goods. 
  • Automated generation of stock aging reports. 
8. Financial Close Process: 

  • Automation of repetitive tasks such as journal entries, reconciliations, and intercompany transactions. 
  • Automated consolidation and reporting for period-end closing processes. 

9. Data Migration and Integration: 

  • Automated data extraction from legacy systems for migration to Oracle EBS. 
  • Regular data synchronization between Oracle EBS and other business systems. 

10. Customer Service Management: 

  • Automated ticket creation for customer queries received via email or web forms. 
  • Auto-assignment of customer issues to relevant departments or personnel. 
  • Automated follow-up and feedback collection from customers. 

11. Compliance and Reporting: 

  • Automated data gathering for regulatory compliance reporting. 
  • Automatic generation and submission of required reports to regulatory authorities. 

12. Asset Management: 

  • Automated tracking and recording of asset acquisitions, depreciation, and disposals. 
  • Schedule and monitor maintenance activities for assets. 

13. Supplier Relationship Management: 

  • Automating the on-boarding process for new suppliers. 
  • Continuous monitoring and evaluation of supplier performance. 
  • Automated generation of supplier scorecards and reports. 

14. Budgeting and Forecasting: 

  • Automated data collection and consolidation for budget preparation. 
  • Automated variance analysis between actuals and forecasts.


These use cases demonstrate how RPA can optimize various processes within Oracle EBS ERP, leading to increased operational efficiency, reduced manual errors, and better data management. As Oracle EBS comprises a wide range of modules and functionalities, the potential for RPA to add value is significant across many areas of the enterprise.