Process Automation: A Complete Guide to Implementation and Optimization

Since 2017, we've been following what's happening with the automation market. It's sometimes been discouraging. For many months, businesses have been trying to implement solutions almost without any knowledge of what they were doing, and when companies do try to implement solutions, there is a good chance they will never work out — the integrations will not work, the requirements have increased significantly, and the end result of the project will likely never be reached. On the other hand, there are many successful examples of properly implemented automation that has changed the outcome of a company from being in a loss situation to being in a stable and growing situation. It is not about the budget; it is about how clearly you understand what needs to be automated and why.

We have tested 43 different ways to apply automation technology, from the simplest chatbot to complex AI agent that automates the production process from start to finish. While there are no perfect solutions, there is a method to help identify the best solution for your situation. In order to determine what type of technology will work best for you, you must look closely at your current bottlenecks and select technologies based upon that as opposed to selecting technologies that you think might solve the problem.

Historically, it took three to four hours to manually collect information about a crypto token. Today, the typical time to collect that information has decreased to ten seconds when using AI to do the collection and generate a full report that includes risks associated with trading that token, ways to detect large players trading in that token, and sentiment analysis of that token on Telegram. Not only have the years of time to complete the task been reduced by a substantial factor, but, in the process of automating the task, the number of errors will be reduced even further, as machines don't become fatigued and miss small details.

What is Process Automation?

Process automation is simply defined as the automation of a process to eliminate the need for human participation in repetitive and routine processes. It's not just simply "hitting the button and waiting"; it's a very complex system where tasks are done automatically based on instructions already written (algorithms): You trigger something, which sets off other things, flowing from one module to another — and then it records everything without any human involvement.

By way of example, our project ArbitrageScanner.io allows you to automate manually monitoring prices across all cryptocurrency exchanges. It wasted time, and you probably missed some. By automating this process, it monitors both spot and futures markets in real-time and calculates the arbitrage (including any fees) and provides "pre-calculated" spreads in just 2-3 seconds from the time you see them.

As an example of this, during the sudden market crash on October 11, 2024 (when a flash crash of 22% occurred), users were able to earn profits of 5%-40% between the time they turned on the software and the time of the crash, while almost all of our competition was still trying to process their data (there's a case study if interested).

The key difference between automated systems and "simple mechanical processes" is the system's ability to adapt to changing conditions. When the market changes, the AI agent will modify its strategy to continue to earn the same profits where other "rigid hardware" or basic script type solutions will either freeze or generate an error at the first sign of change.

The Importance of Automation for Production and Business

Automation plays a large role in production and business, as it solves three basic problems:

• Speed. The ASCN.AI has an AI assistant that uses data from over 30 different sources in 10 seconds, including ads that are on Telegram, by looking at exchange data and through many analytical services. In addition, ASCN.AI will produce a sentiment analysis and keep track of large holders of assets.
• Accuracy. Humans have the potential to make mistakes because they can get tired or have lapses in memory. Machines, however, will always be able to use large amounts of data to accomplish the same outcome without making mistakes like humans do. In a year's time after automation is implemented, human operators' error rates are reduced by about 35%-50%.
• Scalability. Another major benefit is that automated systems can take care of multiple operations at the same time, even though you could manually manage a very large amount of work for one project, as it is much more difficult to do so for 10 different projects. For example, an automated system can monitor 5 different tokens for one customer or up to 500 tokens for another customer without any issues.

In addition to reducing dependencies on third-party data sources, ASCN.AI costs significantly less than traditional alternatives: the average cryptocurrency analyst costs $3,000–$5,000/month, and analytics services such as Glassnode, Messari, or Nansen range from $100 to $1,000/month. ASCN.AI provides similar data for just $29/month and therefore reduces the number of subscriptions by having their own Ethereum and Solana nodes.

Types of Automation Processes

When you think technological processes, you have to understand that they are a sequence of operations that take raw material (data) and turn it into a finished product (car or transaction). For a task to qualify as automated, it must be describable by an algorithm that includes the word "if-then."

There are many steps in the ArbitrageScanner.io technological processes:

1. Scan 15+ exotic markets for price every 0.5 seconds or less.
2. Find pairs of tokens that have enough liquidity to perform arbitrage.
3. Calculates the spread based on transaction costs and slippage.
4. Displays results to the user.

The ability to automate technological processes can effectively reduce the time taken to complete routine tasks by approximately 60 to 80%.

Manufacturing Process

All manufacturing processes are connected together to produce an item. This includes purchasing the materials used to create the product through delivery of the product to the customer or end user and applies to both a robot assembly line and the digital assembly line of an application being processed using many different forms of information technology.

We have a marketing agency client that processes leads coming from 10 different sources. Before implementing the ASCN.AI NoCode solution, processing of these leads took approximately 2 hours per day. Now, with our NoCode solution, the ordering process is automated by way of an AI agent that processes the orders that are received and sends the orders for the appropriate managers to approve with the order being processed in under 10 seconds. As a result of this, the marketing agency increased their conversion rate by 28% — this is primarily due to the speed of processing. The NoCode solution has combined many disparate systems (CRM, warehouse, accounting, and delivery) to work together as one integrated system. Therefore, when an order is placed in the CRM system, the NoCode solution will automatically reserve the product in stock, notify the delivery department of the order, and generate an invoice in the accounting system eliminating the need for any manual processes.

Management Process

In management processes, there has been an emphasis on data driven decision making with minimal human intervention. One example is automated budget controls. An expense that exceeds a threshold of $500 will automatically generate a report. If the expense exceeds the threshold, the manager will be notified through the NoCode system. There is also a method of monitoring communication between employees through an AI that monitors chat messages to identify potential risk areas in terms of task delay and/or tone of conversation, and notify the manager of the risk. This type of automation is intended as a proactive tool rather than a surveillance measure. In addition, this type of automation can also help protect ongoing projects. Companies that use management process automation can make decisions 40% quicker and reduce their error rates by 25%.

Business Process

Business optimization is when you optimize all of the processes in your business from the time you generate a lead to when you provide after the sale service to that lead. As an example, let’s say you are in the e-commerce industry. Your sales funnel would look similar to the following: Ad → Landing Page → Application -> qualification -> manager call and request to make payment -> accessing the product/s and billing continues on a recurring basis (approximately every 30 days). All of the items in this example will be generated automatically through a combination of algorithmic advertising, lead qualification with the aid of AI, and automatically distributing emails and notifications without needing to be involved by a manager. The result of all of this automation was an increase in conversion from 8% to 14%, a decrease in application processing time from 6 hours to 15 minutes, and a significant increase in customer retention; from 62% to 78%.

Automated Type Systems

An automated system is a system of software and hardware that work together. It is not only a system that contains your data and tools, it is a cohesive system comprised of multiple different systems within your company to provide a unified system of automated management of your company's broken up and distant systems.

ASCN.AI contains many systems: the AI crypto analysis assistant, arbitrage scanner, NoCode platform, Blockchain API, and many others. An example of how ASCN.AI works: if the AI analysis assistant identifies a deviation from normal occurrence on a token, the assistant would automatically initiate a check via arbitrage scanner.

Classification of Automation Systems

• MES is a system for tracking quality production and Magnetic Line Loading in Factory Manufacturing.
• SCADA is a real-time monitoring & control system for doing real-time monitoring and control of technology-based objects.

Examples of Automation

• Electronics manufacturing plant: Implementing MES resulted in product defects being reduced from 8% to 1.2% while reducing production cycle time from 12 days to 7 days.
• Logistics: Routing automation reduced fuel consumption by 18% and increased on-time deliveries from 78% to 94%.
• Digital development: CI/CD pipelines allowed for release cycles to be reduced from days to 20 minutes.

Management Level

Managers now receive their financial data and reports automatically which eliminated manual work and errors. As of now in ASCN.AI, weekly dashboard reports with key metrics save about 6-8 hours a week, and they allow quick identification of deviations.

Business Use Cases

• eLearning Platforms: Experienced a 22% increase in conversion rates and 34% increase in retention rates. Also reduced support load by 60% by automating onboarding & granting access to their platforms.
• ArbitrageScanner.io: Automated trial subscription process improved their trial-to-paid conversion rates from 12% to 19%, while reducing their churn rate from 38% to 22%.
• Crypto Fund: Was able to integrate with AI technology to increase their available investment opportunities by three times while reducing the time required for analyzing investment opportunities from 4 hours to 15 minutes.

Automation Technology and Tools

• Servers & Clouds. Hybrid connectivity of local server and cloud server. Provides reliability and scalability.
• Blockchain Nodes. Will provide fast & reliable data access to companies using propriety Ethereum and Solana nodes, and provide independent analytics without any intermediaries.
• API Infrastructure. APIs provide an integration point between exchanges, news feeds and aggregators via HTTP requests.
• Monitoring Tools. Logs, alerts and dashboard are all real-time tools to manage the state of the process.

Software Solutions

• ASCN.AI NoCode. You can build a process using ASCN.AI NoCode, connect to popular third-party applications, and securely store tokens in your processes.
• RPA. Robotic Process Automation (RPA) is used to automate processes that do not have an API so that the tasks can be completed without human intervention.
• AI Agents. You can use artificial intelligence agents, which are smart bots that can adjust to their environment and autonomously execute the process or escalate to an operator for assistance when needed.
• Integration Platform. You will use an integration platform such as Zapier, Make (formerly Integromat), or n8n to call multiple service APIs and transfer data between services without having any coding experience.
• Cloud Technologies. Services/tools are available in the cloud from AWS and many other providers allowing for reliable storage and processing of data.

Phases of Process Automation and Business Solutions

The process audit is the first phase of process automation / solution development; without understanding how a company is currently functioning, you will only automate the process’s flaws. The order of this step is as follows:

• Map out the process — list out the major components of the process.
• Identify any potential bottlenecks — where you can conserve time, money, and quality.
• Prioritize the enumeration for what should be automated first.

Common bottlenecks include but are not limited to: manually entering data into a system, data being duplicated across systems, and delays in decision-making due to not notifying the appropriate parties when there is a critical event.

Selecting Suitable Technologies and Tools

There are several key criteria that determine whether or not a tool is a good fit for automating your process:

• Task fit — the tool used must address a specific business need.
• Integration capabilities — the ease with which you can connect the tool with existing tools.
• Scalability — the tool’s ability to scale for increased workload.
• Cost and ROI — the trade-off between cost and the results you will receive from using the tool.

ASCN.AI among others NoCode platforms are very commonly used by small businesses however larger companies tend to rely more on ERP systems and other specialized software solutions combined together to create a successful automation program.

Steps for Implementing Automation

• Stage one - Process Audit (one to two weeks): Reviewing and re-mapping processes, reviewing data sources for potential bottlenecks, and prioritizing tasks.
• Stage two - Tool Selection (1 week): Selecting software/tools based on type, method of integration, scalability, and costs.
• Stage three - Pilot Launch (2-to-4 weeks): Configuration and testing of first automation and obtaining feedback.
• Stage four - Stabilization (1-to-2 weeks): Resolving issues and training employees how to use it.
• Stage five - Scaling (1-to-3 months): Implementing the solution into remaining processes, documentation, and optimization of automated processes.
• Stage six - Optimization (ongoing): Regularly monitor the effectiveness of the current automation solution(s), updating the program to improve efficiency through updated algorithms and increased automation functionalities.

Tips for Successful Launch and Adaptation

• Involve your employees — it is crucial that employees understand what business reasons you have behind the desire for an automated process.
• Start with something simple — it is better to have one working automated process than ten bad ones.
• Make documentation changes — ensure that you keep good records of all of the configuration settings/logic used to build the automation systems.
• Consider gathering outside feedback — using the feedback from your employees will help you to constantly improve how well you are automated through actual experience working with the automated system.
• Calculate ROI — monitor how much time/money you are saving with using the automated systems.

FAQ

How much does automation cost?

Costs range from $500 to $2,000 for small business/simple NoCode projects. Large companies/corporate automation systems can start at $50,000. Monthly subscription costs for service providers typically range from $29 to many hundreds of dollars.

How long will it take to implement an automated process?

Pilot projects can take 2 to 4 weeks. Scaling of an automated process will take 2 to 6 months depending on complexity of project and volume of business using automated systems.

Is a programmer needed?

It is generally not necessary to build custom integration solutions for NoCode platforms, but they may be necessary if the platform requires a custom integration due to the scope of the solution or its complexity. If you find that you are not successful with a NoCode platform, you should try to find a platform with 24/7 support and implement a monitoring and alerting system.

Is there an automated solution for everything?

No. There will always be areas of creativity, negotiation, or tasks that are too unique to be automated.

How do I calculate the results?

The ROI calculation is simple. Multiply the time saved (in hours) by the hourly pay rate. For example, if you saved 4 hours a day at $30/hour, your ROI for that day is $120.00.

What is ASCN.AI's unique value from ChatGPT?

ASCN.AI provides a specific specialized AI assistant for the crypto market. It is trained on Web3 data and maintains its own indexed blockchain data to provide unique insights and analytics that cannot be found using traditional AI solutions.

Conclusion

The goal of automation is simple: reduce time, cut costs, and improve quality. Start by identifying which processes are eligible for automation, then choose the right tool — NoCode platforms for basic tasks, AI agents or RPA for more complex ones.

Roll out gradually: launch a pilot, measure results, then scale. Involve your team, track your ROI, and keep refining. Automation should free your people up for creative thinking and strategy — not replace it.

Ready to start? Contact ASCN.AI for a free consultation. Your first project could be live next week.

Disclaimer

The information in this article is general in nature and does not replace investment, legal, or security advice. Using AI assistants requires a conscious approach and an understanding of the functions of specific platforms.