All operational aspects of the telecommunications industry, including customer data management, billing, order fulfillment, and customer support, involve numerous types of documents and databases that are complex to integrate and manage. Part of the complexity comes from the number of stakeholders—there are billions of workers and consumers that participate in the telecommunications industry globally, and the volume and variety of documents they generate is staggering.
Automation tools can help streamline telecoms operations and business processes. More specifically, Intelligent Document Processing (IDP) systems enable the automatic management of various kinds of documents and data, circumventing numerous problems that come with manual processing.
IDP is useful across most domains of the telecom sector including billing, payment processing, customer service, and security verification. Benefits from IDP for telecommunications companies include:
In an ideal world, everything runs like a well-oiled machine. But an ideal world doesn’t exist (it would be boring, anyway). In the real world, problems come up. Learning how to address them is an invaluable personal and professional life skill. When complaints about an organization or product arise, they must be considered and resolved effectively and efficiently.
Most enterprises that deal with clients or customers have some kind of complaint management system. Complaint forms are issued by companies to give dissatisfied customers a method to communicate a complaint and potentially seek resolution, making them an integral component of the complaint management process. Complaints are descriptive, and often emotionally charged. They follow a writing and narrative style that is unique to the person articulating the complaint, often leading to high variability across complaints—even when customers are complaining about the same thing. Complaint descriptions are a classic example of unstructured data, which is more difficult for intelligent machines to extract data from and identify patterns within.
Modern IDP solutions were built to extract useful information from descriptive, non-uniform, unstructured text. For example, some IDP solutions use word embeddings, a methodology in natural language processing (NLP), to map words or phrases from vocabulary to a corresponding vector of real numbers. These vectors, which have varying levels of dimensions, can then be analyzed to identify patterns, make predictions, and ultimately derive semantic meaning from unstructured text. By analyzing unstructured text on customer complaint forms, telecommunications companies can identify hidden patterns among dissatisfied customers to make more impactful decisions, better understand failures and missteps during audits, scale personalized customer service, and much more.
Invoices are essential documents in the client-customer relationship for any business. Not only do they serve as a registry of the details of the products/services rendered, they also act as a record of payment details. Invoices are used by accounting teams as a base for billing customers, and by customers to initiate payments. Invoices also have archival value for audit purposes.
Managing invoices is as important as it is tedious because different companies, and even different products/services within the same company, may use different invoice formats. Invoice content may also vary depending on the nature of the product and the kind of customer. As a company grows in size, the sheer volume of invoices processed leads to increased errors and delays. The automation of invoice processing can ease much of the management process and prevent costly errors.
IDP can capture relevant data from a variety of formats of invoices by learning to recognize important data from new invoice types, which ensures high levels of accuracy and fidelity are maintained.
Payslips or pay stubs are documents used to verify that an employer has paid an employee their salary. Beyond serving as a pointer to salary payment, pay stubs are a proof of employment. Payslips are often required by lenders to check credit-worthiness and usually contain details such as name, address, employee earnings, taxation information, and more. The payment information may include financial information such as gross pay, net pay, withholdings, tax rates, hours of work, payment per hour, etc. Payslip formats differ from company to company. Even in today’s digital age, pay slips are sometimes delivered in paper form, although many companies now use digital alternatives.
The conversion of paystub information into a structured digital format is important not only for archival value, but also for sharing with lenders and banks when opening accounts or approving loans and mortgages. Payslip information is also needed for individuals to file taxes. Depending on the frequency payslips are issued (e.g., weekly, bi-weekly, monthly, etc.), an individual person may have quite a few to process each year. For banks and other financial institutions, the issue is compounded. Data must be entered from numerous paystubs spanning a wide variety of formats and styles. IDP tools can ease the management and processing of paystubs, saving companies and individuals considerable amounts of time and stress.
Employee contracts are legally binding documents that establish the terms of an employment relationship between an employer and an employee. They are a repository of valuable information, often written in legalese that is unintelligible to the average person. In addition, the amount of data contained in a contract can be unwieldy with important data surrounded by supporting verbiage, not to mention critical fine print.
Intelligent Document Processing can help with employee contract management. The semantic intelligence tools these solutions provide make it possible to automate the extraction of pertinent information from convoluted contracts and sort them into metadata elements, terms and conditions, legal provisions, obligations, and more. Contracts are highly sensitive and confidential, so it’s important that any IDP solution used to process them safeguards contract data from theft and mismanagement through multiple levels of security.
Forms are ubiquitous. In the telecom sector, we fill forms to get an account, to prepay for future services, postpay for the services that were used, and terminate engagement. While most forms are in online mode, some forms continue to be on paper-based systems, which results in a large variety of formats and forms of data that must be extracted from forms.
The classification of data extracted from forms is particularly important in terms of the outcome activities. For example, a form to start an account must contain data that the telecom company uses to check for identity. The prepaid form details are necessary for the chosen services to be allocated to the customer. Postpaid form data are necessary for continuation or termination of services as required.
Manual categorization of such data is overwhelming, considering the variety of outcomes. Intelligent document processing applications come with built in functions for categorization. In addition the “intelligent” aspect of these tools allow customization and learning from experience, all of which help in smart extraction of data from forms. IDP can extract data from emails, scanned documents, PDF form, and online forms, and sort them intelligently into categories such as name, email address, phone number, etc. The data are stored in a central platform from which required data may be imported to other programs such as spreadsheets, word processing software, etc. The data output can also be obtained as CSV, JSON, and other well-structured data formats, which can in turn serve as inputs to other automation software doing other processes.
A services agreement is a legally binding contract between a service provider and a client. This contract lists the services that the company will provide to the clients, along with the costs and time frames associated with the service. Many service contracts also list the rights and limitations of both parties, including liabilities and guidelines of confidentiality. Contracts help avoid disputes, and in the event of disputes, aid in resolution.
In addition to the details of the service to be provided, a service agreement contains fields such as ownership, relationship, insurance, contingency clauses, non-compete clause, assignment and roles, and termination clauses.
Given that a service agreement is a legal document, it can be filled with legal verbiage that may be hard for a layperson to identify and understand. IDP solutions can help in extracting the relevant information from the contracts, and can intelligently sort and store them for context-specific extraction of details.
Whether you are applying for a diplomatic visa or buying a bottle of bourbon in the local liquor store, an ID is usually required. The kind of IDs that are produced for various purposes are different. In some cases, it can be something as simple as the Social Security Card, that contains a name and number and not necessarily a photo or other details. A driver’s license, on the other hand, can have more information such as date of birth, photo, address, and so on. A passport is a multipage ID that contains, in addition to what the driver’s license contains, other information about citizenship, foreign travel, etc. The language on the ID can also vary, depending on the country.
Various kinds of data are also necessary for ID check. In the liquor shop, the shopkeeper merely looks at the ID and your face and if there is a rudimentary match, and you are lucky, gives you the Scotch. A foreign embassy is a lot more diligent in checking your ID and storing the information in their system. Other applications that require ID checks take in different types of information from the ID cards.
Thus, the extraction of data from IDs can be time consuming and complicated, not to mention error-prone and repetitive. Smart document systems such as IDP can ease the ID data management process. Many IDPs have inbuilt systems to detect various fields in various types of IDs, and even multiple languages. In many cases, the ID is shoved under a scanner or a camera at various angles and distances. IDPs can factor in corrections for these and detect fields of interest from all kinds of IDs. IDPs can also be configured to check for fraudulent or false information, or tampered IDs, which can save a lot of time and trouble in the long run.
Although the telecommunications industry has a history of early adoption in technology spanning various fields, it has relied on rules-based automation for too long. Intelligent automation tools powered by artificial intelligence (AI) and machine learning (ML) like IDP are only beginning to see wider adoption. IDP can automate basic document management tasks like updating customer records and documenting the accounts payable setup. Combined with other AI processing tools, IDP can complete the automation process and provide better delivery of services—leading to more satisfied customers, greater customer retention, and increased customer acquisition, all of which lead to higher profits and better visibility.