The importance of machine learning

The importance of machine learning

Since today, organizations are looking to modernize and optimize their processes, machine learning (ML) is a powerful tool to guide processes and organization automation. Unlike basic automation based on fixed principles (which is usually for standard and predictable processes). Machine learning can manage more complex processes and learn over time, thus increasing accuracy and efficiency. By applying machine learning to processes, they increase the efficiency of the organization’s process by 30% or more, while increasing revenue by 5-10%.

To reduce complexity, the most advanced organizations use a 3-step approach to operationalize machine learning in processes.

first stage:

Since processes often span multiple business units. Instead of trying to apply machine learning to one part of a process, companies can apply it to the entire process. This approach applies to synergy between elements in several stages, such as types of inputs, controls, processing, and documentation.

second stage:

Assessment of capability needs and development methods
Business automation can increase employee productivity and business development, guarantee service delivery and availability 24×7/365 days, and maximize performance.

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third level:

Machine learning makes the nature of data useful.
Even if a company has high-quality data, it may not be able to use this data to train a machine learning model, which requires three distinct and sequential environments for successful machine learning deployment. A developer environment, where systems are built and easily modified. A test environment, where users can test the performance of the system but cannot change the system. and the execution environment that is made available to end users.

Advantages of machine learning:

1- Machine learning reduces the cost of prediction

Forecasting is at the root of all business decisions. Machine learning helps entrepreneurs and business owners change their business models based on predictions. and have an accurate assessment of fixed and variable costs. This predictive modeling by machine learning can answer the question “what will happen in the future” and “what is the best that can happen”.

2- Automate routine and repetitive tasks

Machine learning can automate routine and repetitive IT tasks such as security monitoring, auditing, data discovery, classification and reporting, so the team can focus on more strategic activities.

3- Finding areas to maximize efficiency

Businesses can use machine learning to extract their critical information, which maximizes efficiency.

4- Management of unstructured data

Many organizations today struggle to manage growing volumes of unstructured data. Machine learning gives the right structure and meaning to the data to help in decision making, investment and strategy setting.

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5- Measuring risk more effectively

Risk management is a complex business operation. There are countless variables to consider and managers are forced to make complex decisions with limited data. Machine learning provides a more complete understanding of a business’s risk profile in relation to fraud, errors, loss prevention and other liabilities. Machine learning tools can be tailored to an organization’s unique needs.

6- Improving the efficiency of marketing and personalization

Machine learning and artificial intelligence help entrepreneurs to optimize their advertising spending. AI-based targeting and insight removes the guesswork and uncertainty involved. And it helps marketing managers to identify their target audience faster and better than before. Machine learning can predict customer profiles and send them more targeted and personalized messages. The more personal your marketing message is to people, the more likely they are to notice and take action.

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7- Speeding up research on what customers want

Entrepreneurs and business owners can use machine learning to process customer data more efficiently. And it gives managers the opportunity to see what kind of users are more likely to become customers, how customers behave. A more accurate prediction of products and services related to their needs will help you to increase the revenue obtained from each customer.

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8- It improves its customer service

Customer service and support is one of the most important factors in maintaining customer satisfaction and reducing customer churn. The customer may have a request from you and not receive an answer from you for hours, as a result, it causes their dissatisfaction. Automated chatbots for your website using artificial intelligence can improve customer service. Using a chatbot can reduce your response time to one second and allow customers to communicate with you 24/7. And machine learning tools collect data and provide the right answer.

9- Solving big problems that humans are unable to solve

By understanding the behavior and performance of data in the network, machine learning can help solve complex problems and simplify data analysis. In fact, machine learning has the ability to solve multivariate problems.

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10- Fall forecast

Machine learning algorithms can not only predict customers who are likely to churn in the near future, but can also explain the factors that lead to customer churn and examine its impact.

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11- Identifying trends and time series

One of the best ways to use machine learning is to recognize trends in data in a set. Recognizing time series is very important in business agility and flexibility to change.

some charts

12- Saving time for the cyber security workforce

Different cyber attack styles and threat levels often make it difficult for algorithms to accurately predict a threat. However, as the volume of recorded data increases, new solutions are being developed to improve predictive accuracy and increase the capabilities of the limited cybersecurity workforce.

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13- Prediction of the changing market

Artificial intelligence can be used to predict that the market is changing and to identify potential key partners to strengthen your position or to identify new competitors and threats.

می توان از هوش مصنوعی برای پیش بینی اینکه بازار در حال تغییر استفاده کرد و به شناسایی شرکای کلیدی بالقوه برای تقویت موقعیت خود یا شناسایی رقبا و تهدیدهای جدید استفاده کرد.

14- Hire the best applicants

Big businesses have a huge advantage in finding and attracting top talent, but AI can help small businesses. AI programs can collect data over time to learn the most effective recruiting practices for your business. This includes the applicant’s background, how to contact them, and even details about their work history and qualifications. Machine learning algorithms can review resumes and hire successful candidates.

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15- Medical care

The proliferation of sensors and wearable devices that monitor all human activities from heart rate, walking steps, oxygen and blood sugar levels, sleep patterns, etc., doctors analyze and evaluate the large amount of data generated using machine learning. and can also diagnose cancer by using machine learning.

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16- Financial and accounting services

Insights provided by machine learning allow investors to identify new opportunities and gain insight into when to trade. And also, data mining identifies high-risk customers, especially in the banking and insurance industry, to assess the risk of loans and insurance policies. And in the accounting department, it provides customers with the possibility of creating invoices based on past behavior.


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18- Prevention of fraud

An integrated and cross-cutting approach to anti-fraud, regulatory compliance and security powered by artificial intelligence. By using machine learning algorithms, it is possible to identify payments for fraudulent purposes, unnecessary expenses and abuse before they happen, and avoid threats in the future and minimize the risk of fraud.

Four Ways Machine Learning Can Help Businesses Improve Their Performance

  • Machine learning can help businesses develop software that can understand natural human language.
  • Businesses can use machine learning to improve the efficiency of logistics and transportation networks.
  • Machine learning helps businesses use preventive maintenance to reduce equipment breakdowns and increase profits.
  • With machine learning, businesses can use consumer data to create customer profiles, increase sales, and improve brand loyalty.

1- Natural language

Artificial intelligence-based programs can learn from past interactions and mistakes and understand normal human speech. Businesses should also ensure that they improve their accuracy every day.

Natural Language processing

2- Logistics

The logistics and retail industries are rapidly moving into the fields of data analytics and machine learning. Machine learning helps companies improve their logistics by increasing efficiency at every stage of the transportation, storage and sales process. Retail companies like Amazon are using machine learning to increase efficiency in their delivery network and predict customer needs.

3- Production

Today, industries active in the field of production have taken effective steps in the field of integrating machine learning in each of their production processes and stages. AI-based technologies can help businesses save money by simplifying inventory management, making production more efficient, and predicting equipment failure before it happens. They use machine learning to predict annual production peaks and seasonal fluctuations. And it helps companies avoid unplanned shutdowns or unnecessary overtime. Also, machine learning with the aim of improving operations in the entire production process causes a significant reduction in error rate, waste production and rework.

4- Consumer data

Collecting and analyzing consumer data improves customer service. and provides better insight into customers. which creates better relationships and reduces the loss of customers. 57% of company managers believe that the most important benefit of artificial intelligence growth and learning will be improving customer experience and support.

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