Is Data Entry Easy? What You Need to Know Before You Try It

Is Data Entry Easy? What You Need to Know Before You Try It

Is Data Entry Easy? What You Need to Know Before You Try It

Data entry remains the bedrock on which the edifice of virtualization of the world is being built.

With the advent of software technologies, humans have been building smarter and smarter programs with a view to making the world a better and better place. While this is not the place for a discussion on the ‘better place’ contention, we have all been witness to the flood of software technologies that have continued to swarm us. And since there is greater and greater adoption of these technologies, one must assume that humans see benefit in them.

While technologies and software programs are being built by smart people, they also need data to work on. If a technology does not address a real world need or issue, it may not be of much use to anyone. Hence, it needs to use real world data and address a real-world issue.

The data that the real world is generating, unfortunately, sits outside these software programs. Hence, if these technologies are to deliver their promised benefit, they need to find a way of using the data that is being generated in the real world.

This is where data entry comes in. It takes data from the real world and makes it available to the digital world in the format that they need it. It acts as a bridge between the two. It is generally a manual activity.

Once data is entered into a software or a computer application, it becomes easy to process, easy to retrieve, easy to transfer and, in general, easy to do anything with.

However, merely being entered into a computer application may not always be enough. Data entry may still be required if information is going from one software application to another. For example, if Company A supplies material to Company B, it generates an invoice from its Accounting application and sends it as a hard-copy or email attachment to its client, Company B. As Company B uses a different software for making invoice payments, which does not understand the information coming in from the invoicing system of Company A, there is a need for doing data entry in the software of Company B. Once entered, this information can be used by Company B in many different ways. But a one-time data entry is required.

All industries are touched by data entry one way or another.

The above notwithstanding, “Is Data Entry Easy” is not an easy question to answer.

In the ensuing paragraphs, we will make an effort to examine the arguments in favor and against the question.


Is data entry easy? Yes it is.

Repeated tasks lead to efficiency enhancement

In most cases, data entry is a repetitive task, done again and again, for a large volume of data or transactions. A human being gains proficiency by doing the same thing over and over again. Lionel Messi perfects his free kicks by practicing them hundreds of times a day. Roger Federer is able to execute his serve so nonchalantly in a match because he practices hundreds of them each time he practices.

Similarly, by doing it over and over again, the people doing data entry gain proficiency, resulting in efficiency gains for the business they are working for. The operators also gain insights into the process to be in a position to suggest methods for automation that can give an additional fillip to the efficiency.

Repeatedly identified as one of the top three data entry service providers in the world, oWorkers has delivered on hundreds of client engagements in data entry over the eight years of their existence. Our transparent pricing model results in efficiency gains through repeated performance of a task being shared with clients.

Anyone can do it

If ever there was a democratic white-collar job in the world, it is that of data entry. Everyone who does data entry is equal. It does not require fancy educational qualifications as an entry ticket. It does not require prior experience to be good at it. All it needs is a willingness to learn and work hard based on a defined process and a desire to deliver work of good quality.

It has the potential to create employment and bring disadvantaged communities into the digital world. Not because it is a political initiative to create employment, but because it is a process that can be done with willingness and initiative on part of the operator. It is a process that will not run out of resources. With modern technology, it can be done from any corner of the world. If an operator in Mexico cannot do it, go to Egypt. If vendors in Egypt are unwilling to take it on, go to India. An endless resource supply is available.

With its three centers located within three hours of all major capitals in Europe, oWorkers has access to a wide talent pool for its data entry work. With our deep involvement in local communities, we are a preferred employer in all locations we have a presence in, which gives us access to a continuous supply of candidates interested in working for us. This enables us to provide seasonal ramps based on client needs while keeping employment costs in check.

Limited task, but a part of a bigger picture

Voluminous processes are often broken down into smaller, specific tasks, with defined deliverables and goals for each step. One of the things it does is to affix responsibility for each part of the equation. If not done this way, in case of issues faced with the process or its output, it becomes difficult to affix, or even identify responsibility for the error, resulting in no learnings from the incident that could lead to an improvement in the process for subsequent runs.

It also means that in case of an issue with one part of the process, the entire chain does not need to come to a grinding halt. Since the data entry process is a part of a larger process, it might be easier to source help, in case of need, from an adjoining process that either receives an input from it or delivers an output to it.

oWorkers has been providing data entry services in a number of delivery arrangements, and make it a point to develop a working relation with relevant people on the client side. We find that at times we need to lean on a client for support while on other occasions they may need to ask us for the same. Our endeavour is to keep the big picture in mind and be a contributor to the client’s success.

Potential to release efficiencies

The breakdown and possible outsourcing of data entry tasks releases a variety of benefits, like allowing focus on core activities of the organization, like cost reduction, and others. Though they may not directly contribute to making the data entry task any easier, because they are able to release benefits and efficiencies to the organisation, and make the functioning of the organization easier, the answer to the “Is data entry easy” question should be a resounding yes.

With oWorkers, clients get a partner well versed in the science of data entry, having executed hundreds of projects for global clients. Data entry for Ecommerce products, Invoices, Customer orders, Civil Records, Books. Legal notices, Forms for Healthcare, Banking, Insurance and many other industries constitutes our body of work and experience. 


Is data entry easy? No it is not.

The output is only as good as the input

In order to gain operational efficiencies, many businesses break up business processes into smaller chunks with the following objectives:

  • Making accountability clear for different parts
  • Employing resources of suitable quality for each job rather than rely on the Highest Common Factor (HCF) principle to have the most qualified person for any of the tasks doing all of them
  • Outsource specified, identified segments

Perspective is often important for human beings to perform a task. They need to know and identify with the big picture to be able to contribute to it. Breaking it down into small tasks and taking the big picture visibility out from the operator’s line of sight can often result in errors creeping into the output as the operator will perform her job based on her limited understanding. With the GIGO principle in operation, if the quality of input is poor the resultant process will also be poor.

With a dedicated training team and over 8 years of transitioning hundreds of client projects, oWorkers has built the expertise required to migrate work while embedding itself as an integral part of the outsourcing organization so that our operators keep the big picture in mind while conducting their day-to-day tasks. Our Internal Quality team serves as an additional checkpoint in ensuring quality is delivered to required standards.

A bewildering array of data entry jobs. No two are the same.

Though it may be true that data entry is a process that is relatively simple to execute, the bewildering array of data entry requirements often make it a complex process. No two data entry jobs are alike. While an operator may have gained efficiency while repeatedly doing a particular data entry job, as soon as that job is complete and he needs to move to a new data entry job, he slides back to the starting point and begins his climb to the top of the efficiency hill all over again.

Data entry requirements for two seemingly similar processes may be entirely different. In this situation, for many people, the answer to the “Is data entry easy” question could well be a No.

Our management team, with hands-on industry experience of over 20 years, are on the forefront in every client project. Before a project is transitioned to a Business As usual (BAU) mode, they ensure that expectations are aligned, the work has been converted to a process that can be followed, people have been provided the requisite training, and everything else required. This handling converts potentially difficult jobs into easy ones for our teams of operators.

Operator turnover is high

Human beings are thinking animals. They like to think and exercise some control over what they are doing in order to show themselves to be in good light. While to some extent it is possible to do this in a data entry task as well; an operator can do a good job to stand out from the crowd, by and large the process remains repetitive. Not just repetitive but mind-numbingly repetitive.

For a thinking human being this can lead to frustration in not being able to influence the outcome with your smarts and thought-process, which often leads to burnout. And perhaps, before burnout, errors start creeping into their work as their attention starts to waver. This leads to either the operator leaving of her own accord or the business removing her from that work and either moving on to another project with the company or moving on to another company altogether. Either ways, it ends up with the promise of efficiency enhancement with more practice not being realized and a new person needs to be inducted who would start her own journey from the bottom to the top of the hill.

Human resources are a key differentiator for oWorkers. We work with employed staff and not freelancers, and take upon ourselves the responsibility of monitoring each employee’s performance and providing opportunities for growth. This has enabled us to keep staff engaged and motivated to perform, while keeping our attrition at industry-leading numbers. Our engagement with local communities also gives us access to a continuous pool of talent from which replacements can be found, if required.


In Conclusion

The answer to the “Is data entry easy” question will vary from person to person and organization to organization. It is as easy or as difficult as you make it to be.

oWorkers is GDPR compliant, operating as it does from the Eurozone. It is also ISO (27001:2013 & 9001:2015) certified and operates with facilities & protocols that are secure. We also ask that each member of our staff sign a non-disclosure agreement (NDA) before access to client data is provided.

Our services in over 22 languages are used by global clients for several services, including data entry.

With a pricing model that is transparent, oWorkers provides a choice between rate per unit of output and rate per unit of capacity and is able to share the benefits of scale with its clients. It also leverages developments in technology through its partnerships with a number of technology providers.

We are able to ramp up by almost a hundred people in 48 hours to meet short-term client requirements.

For oWorkers, the answer to the “Is data entry easy” question is a resounding YES.

What Is Data Entry? Your Questions Answered

What Is Data Entry? Your Questions Answered

What Is Data Entry? Your Questions Answered


Data entry could be considered as the bedrock on which the edifice of the digital world stands. Of course, the assumption here is that digitization or virtualization is a beneficial, desirable activity for humankind. At the present moment, with the mad race for digitization and everything virtual being touted as man’s saviour, we don’t have a reason to believe otherwise.

Data entry definition, as provided by, is “the job of entering text or other data into a computer, as by typing on a keyboard or scanning a document.”

Techopedia offers data entry definition as “the process of transcribing information into an electronic medium such as a computer or other electronic device. It can either be performed manually or automatically by using a machine or computer.”

Though most data entry tasks are time consuming in nature, however data entry is considered a basic, necessary task for most organizations.

The data entry definition may vary from person to person, but the key constituents are similar.

While in the modern world data entry is almost exclusively seen in the context of machines and computers, data entry perhaps precedes the introduction of computers and machines into widespread usage.

Possibly, when the Pyramids were being built several thousand years back, there was someone keeping track of the number of stone blocks that were transported by each team during the day, which he would record as a tally mark on another block of stone. This would help him arrive at the total at the end of the day and work out the payment to be given to each team. In his own way, without computers and machines, that gentleman was doing data entry in his own little accounting system instead of trusting his memory to remember the information or the team to come and own up to the right number at the end of the day.

At the most basic level, what is data entry doing for us? It is helping us collect or organize information. Not just randomly collect and organize information, but do it in a manner that it becomes useful for the purpose it is being collected.

Through his version of a data entry process, the onsite manager/ accountant of the organization building the Pyramids had created a method for collecting information that was helping him manage his business and deliverables.

Data entry, thus, becomes a tool in the pursuit of management of goals and deliverables. The information our Pyramids onsite manager/ accountant was entering on a stone block, might be keyed into a tablet or a handheld device at the construction site of, say, a bridge over the Yellow River in China.

What is data entry could possibly be difficult for some people to understand. What cannot be difficult to understand is that oWorkers has been consistently ranked in the Top 3 providers in the world for our chosen area of expertise, date entry services. oWorkers delivers over 99% accuracy on client projects across a wide cross-section of measurement systems.


Data entry process in the modern world

We will limit ourselves to data entry in the present times where the purpose of data entry remains the same, to collect relevant information together in a manner that it becomes actionable and amenable for further processing. However, almost exclusively, data entry refers to a process through which it is taken through a computing device and eventually becomes available to the digitized world for further processing.

There are many ways in which this process can be dissected for a better understanding.

It could be divided into online and offline data entry. Online data entry directly interfaces with a database on the internet and updates the main database directly without going through intermediary processes. Offline data entry refers to a step where data that needs to be entered is keyed into a system that is not connected to the main database and then subsequently uploaded into the main database. This could be used in cases where there are security concerns about operators directly accessing the primary database, accuracy of data, etc. In this case too, the data entered is in a format that is compatible with the main database and does not need further manual inputs.

It could be divided into manual and automated data entry. Though as a default the term data entry is used in context of manual data entry, data entry can be automated as well. For example, the organizers of a conference would like to maintain a transcribed copy of the discussions at the conference. There are Natural Language Processing (NLP) tools now available that would convert the discussions into text for future reference. Of course, the accuracy of these tools is suspect and it may need a once-over by a human being. Manual data entry, hopefully, does not need explanation. It is the default meaning of the term data entry.

It could be divided based on the type of data which needs to be data entered. For example, raw data could be in the form of an audio file which is the recording of a seminar and needs to be manifested in textual format for storage and analysis and retrieval. It could be a handwritten file in the form of an image that cannot be read by a computer and needs to be converted into a textual file for all further processing. Or, it could be manual data records maintained over many locations by different people which now need to be consolidated into a common database. It could even be an image on which annotations need to be done.

Types of data entry systems could also be another way of understanding what is data entry. The target system could be a standard application software like an MS Excel or MS Access which can handle a wide variety of uses, or it could be a function-specific application that are for specific functions; an applicant’s job application may need to be keyed into the Applicant Tracking System (ATS) while an Invoice received from a supplier will need to be entered into the Accounting system of the company.

Like the data entry definition itself, which is expansive, classification of data entry is also open-ended and cannot be defined by a fixed set. There could be many more ways in which we could look at the data entry process in an effort to understand it.

Whichever way you look at data entry, oWorkers has a ready solution for it. With three centers in some of the most desirable BPO locations in the world, we are able to provide data entry services in over 22 global languages. Other than GDPR, which is a requirement, oWorkers is also ISO (27001:2013 & 9001:2015) certified and operates with facilities & protocols that are secure. We also ask that each member of our staff sign a non-disclosure agreement (NDA) before access to client data is provided.


Types of Data Entry?

Looking at various types of data entry can also help in understanding what is data entry.

The remit of data entry is vast. Limitless. It can be contained within a finite set of activities. The list below is meant to be illustrative, and not comprehensive. And the requirement could arise in any industry or business or organization.

Guest comments and ratings – Shared by guests at checkout from a hotel need to be captured to track client satisfaction levels as well as employee performance

Insurance claim forms – Filled by a policyholder for filing a claim needs o be captured to facilitate processing and recording

School admission form – Completed by parents needs to be captured so that student data is available and can be actioned as per profile and preferences

Discussions in a meeting – Needs to be captured in text format to facilitate retrieval and keyword related searches

Participant list at an industry event – Needs to be captured as it constitutes a potential client list for the business

Golf scorecards – Need to be captured to track golfer’s performance and his accurate handicap

Medical prescriptions – Need to be captured for ease of retrieval, sharing as well as search by keyword

Invoices received – Need to be captured as a record of payments issued by the business

Though types of data entry may be infinite, they are brought together by the same drivers; the need for capturing information in a usable format that will facilitate future processing on a suitable software and lend itself to process improvements as and when the need might arise.

With oWorkers, clients get a partner well versed in the science of data entry, having executed hundreds of projects for global clients. Data entry for Ecommerce products, Invoices, Customer orders, Civil Records, Books. Legal notices, Forms for Healthcare, Banking, Insurance and many other industries constitutes our body of work and experience.  


To outsource or not to outsource the data entry process

Though this debate has been held on numerous occasions in meetings in many businesses, the outcome is increasingly becoming obvious with more and more organizations opting to outsource data entry to a provider.

While each organization has its own unique perspective on the subject, given below are some of the salient advantages and disadvantages of the decision to outsource, so that future decisions may be better informed:


Focus on core business – The need for data entry can arise in any industry, in any type of organization. Companies can be engaged in a bewildering array of businesses, specializing in their area of work and trying to excel in it. Data entry is perhaps not one of the skills that makes them stand out from the crowd. Moreover, the need to excel in an additional skill, and even understanding what is data entry, may take attention away from their core business, resulting in losing ground to competition. By outsourcing data entry, the business stays true to its objectives and mission.

Lower cost – In most cases, data entry requires limited prior experience and no advanced educational qualifications. This results in resources available to do data entry being relatively less expensive than specialists in other businesses that often require experience as well as educational qualifications. Outsourcing providers have access to talent pools that will readily do data entry and enable the work to be handled at a lower price.  

Benefits of scale – By aggregating similar processes, vendors create an environment where innovation becomes possible as a result of scale. With their individual small volumes, each outsourcer may not have adequate interest in investing for technology enhancement, but a provider, with aggregated volumes, does. If he can create enhancements to technology or processes, the gain is substantial because of the volumes.

With a pricing model that is transparent, oWorkers provides a choice between rate per unit of output and rate per unit of capacity and is able to share the benefits of scale with its clients. It also leverages developments in technology through its partnerships with a number of technology providers.


Quality and accuracy – With BPO being a global business, the search for the best arrangement could take a business away from its cultural and geographical roots. This could result in the vendor and their staff not being in a position to appreciate and understand the cultural underpinnings of the business which could lead to taking wrong decisions impacting on quality. Addressing this will perhaps require greater investment in training as well as a tighter monitoring regimen.

Processor boredom and burnout – One of the factors that makes it possible to outsource business processes is that they can be broken down to a level of detail where it can be performed repeatedly, almost mindlessly, without the need for any significant knowledge or prior experience. The factor for success also becomes a disadvantage on many occasions. Being blessed with a mind, operators can become disillusioned and burned out as a result of doing the same thing over and over again.

Lack of control – Whether labor practices followed by a vendor are in line with global best practices or not, whether there is adequate data security that keeps our content safe and Intellectual Property (IP) uncompromised, are there likely disruptions that could arise as a result of local politics, are just some of the ways in which an outsourcer could have a feeling of being not fully in control of his business.

The requirements and rhythm of data entry often being different from the business for which it needs to be done, outsourcing of data entry is the accepted norm, to BPO companies specializing in the task.

Unlike many competitors, oWorkers operates with employed staff, and not freelancers or contractors. This places upon us the responsibility for managing the growth and aspirations of our staff. Each staff is appraised on performance and has a personalized development plan. Staff are also provided opportunities to switch between projects for growth as well as keeping them fresh.

Moreover, many of our clients being in Western Europe, we are culturally closely aligned with them, reducing the gap for errors to creep in.


The oWorkers Advantage

oWorkers is trusted by clients from around the world in different industries, including unicorn marketplaces, web aggregators and tech start-ups.

We operate as a locally registered company in all our delivery locations. We are active, contributing members of our communities and a preferred employer. Our hiring costs are low as we attract a steady stream of interested jobseekers. We are also able to ramp up by almost a hundred people in 48 hours to meet short-term client requirements.

The data entry work you outsource to oWorkers will enable a few more people from disadvantaged backgrounds to understand what is data entry, find jobs and become a part of the digital revolution sweeping across the world.

What Is Data Labeling? Everything You Need To Know

What Is Data Labeling? Everything You Need To Know

What Is Data Labeling? Everything You Need To Know

Let us begin with a definition of data labelling by Amazon which defines it as “the process of identifying raw data (images, text files, videos, etc.) and adding one or more meaningful and informative labels to provide context so that a machine learning model can learn from it. For example, labels might indicate whether a photo contains a bird or car, which words were uttered in an audio recording, or if an x-ray contains a tumor. Data labeling is required for a variety of use cases including computer vision, natural language processing, and speech recognition.”

Like most definitions, it says a lot but perhaps leaves room for more explanation.

The labelling of data highlights properties in the data that can be understood by a computer and used to establish patterns that enable it to predict what is known as the ‘target.’ In a data set for training autonomous vehicles, for example, these ‘targets’ could be traffic lights, pedestrians or lanes on the road. It allows the software program to assign meaning to raw data and establish patterns.

For example, an AI model being trained for identifying facial expressions and emotions may need to be trained by enabling it to first identify a human face and thereafter connect it with human emotions through the complex interplay of facial features. For example, drooping lips could be an identifier of sadness.

Context is important. Labeling varies based on the requirement and objective of the AI model which it is being created for.

oWorkers has been providing data entry and labelling services to power the AI ambitions of its clients. Its partnership with leading technology providers provides it access to the latest technologies for the task. The fact that 75% of its clients are technology companies, while a challenge in terms of high technology expectations, also ensures it stays ahead of the curve in leveraging technology solutions for its work.


The need for data labelling

An understanding of ‘what is data labeling’ cannot be complete without an understanding of the need for data labelling.

While data labelling and data annotation are sometimes used interchangeably, data annotation is also usually referred to as the process through which data labeling is achieved, or we produce labeled data.

A research by Global Market Insights put the market for data annotation at $700 million in 2019, and projected to grow to $5.5 billion by 2026.

What is driving this growth?

Artificial Intelligence (AI) and Machine Learning (ML).

Is it surprising?

Perhaps no. Analysts say that almost every piece of technology now has an element of AI embedded in it. In your pocket. In your car. In your home. The search engine recommendations that are tailored to our preferences, the expected time you will take to reach a particular place, the chatbot response to your query, the identification of a weapon in a video grab, there is AI everywhere, though we may not recognize it at the point of our interface.

And Machine Learning (ML) is the handmaiden of AI, working in the background to produce training data sets that will make the AI models smarter and smarter.

Training data sets produced for training AI models use labelled data, that make raw data understandable to a computer. It is estimated that 80% of the time spent on AI projects is in the process of creation of training data-sets and labelling them.

An AI model being only as good as the training data, it is a task of great responsibility. After all, we don’t want an autonomous vehicle not running over pedestrians 8 out of 10 times. The model needs to ensure that it does so 10 out of 10 times. There is no scope for error. 8 in 10 is just not good enough.

Operating as locally registered units in the three geographies it has centers located in, oWorkers leverages its position as an aspirational employer for local jobseekers to access deep talent pools to handle all kinds of labelling requirements. It also has the flexibility of seasonal or other ramps to the tune of a hundred people in 48 hours. With its preference for employed staff over freelancers for working on client projects and stable, transparent employment policies, oWorkers experiences best in class attrition and provides stable solutions to clients for all data labelling needs.


What is data labeling – Key Concepts


A label is the tag or additional information added in the process of annotation to trigger the development of associations with identified features of the data. It is the basic unit of information on which training models are built. It needs to be remembered that labelling is contextual. Labels added to an image of a roadside for building AI for an autonomous vehicle may be very different from labels that need to be added to build AI to detect depletion of greenery in a particular location, even though the image may be the same.

For an image, a label might identify buildings or shops. In case of an audio, a label might associate the noise/ sound with some part of the language, like words or phrases. Understanding a ‘label’ also provides a good understanding of ‘what is data labeling.’

Computer vision

Visual data is much richer than textual data. Unfortunately, software coding has no place for visual cues to be given or received. Through AI, we are keen to teach computers to see and understand visual data in the same manner that humans do.

Computer vision is a broad term used to refer to the ingestion of visual data by a computer and its interpretation.

Training data

Typically, a large number of labels put together will constitute training data. The collected information that enables a software program or computer to make sense out of raw or unstructured data.

Humans in the loop

This is a term used to refer to the process through which human beings are allowed to add inputs into the model and provide insights that purely statistical data may not have been able to provide.

While one could argue that the training data used should have been of adequate quality and quantity that such feedback loops should not have been needed, in reality building training data is a tedious and expensive task. Therefore, for some applications that may not present a risk of injury or death, limited data-sets with a human-in-the-loop feedback cycle are used to refine models.

Ground truth

Ground truth refers to the reality check. The point where ‘the rubber meets the road.’ Often used at the initial stages after the AI model has been trained and unleashed on an unsuspecting world. At the initial stages it is important to keep track of its results and ensure that the results delivered are in line with human expectations.

With hands-on experience of over 20 years, the leadership team of oWorkers is well aware of the answer to the ‘what is data labeling’ question and well placed to provide guidance on data labelling projects to all its projects and team members. With support for 22 languages, a GDPR compliant business and operating from ISO certified facilities, oWorkers offers  a compelling proposition for data labelling services.


Labeling common data types


Creating structured text and having a computer interpret it and act on the interpretation is a science mastered by humans and computers many decades back. That is called software programming.

When we talk about text in the context of AI, the reference is to unstructured text. How do we get a computer to understand and interpret text that was not created for the specific purpose of being interpreted by the computer. A computer would need training to even comprehend the phrase ‘what is data labeling.’

There are concerns these days about the destructive force that some of the social media platforms can be when they propagate falsehoods and hatefulness. A small, tiny, pathetic human being might enjoy his moment in the sun through such a message, but the cost and implication for society could be high. AI models trained to read and interpret text can be used to head off the potential damage by suppressing or deleting such messages and identifying and apprehending the perpetrators. 

Labeling textual data is also useful in applications that use Natural Language Processing (NLP) like Voice Assistants and Speech Recognition. Audio converted to text through speech recognition technologies and used as training data-sets can also provide a variety of applications. Chatbots that are increasingly becoming popular for responding to customer queries have been trained with labeled textual data.


Making sense of unstructured data being the key objective of AO models, working with images has become an increasingly important requirement. Videos are also often handled as a sequence of images in rapid succession.

What is an image for a computer? It is an image. That is all. At best, in the digital world, a computer may be able to identify an image as a collection of pixels.

Labeling an image is the process of making the image, or certain parts of it, meaningful to a computer, so that it can create associations and patterns out of it.

A hundred years back estimating the level of summer ice on the North Pole may have been a manual exercise done by accessing each floe and measuring it. Today, it can be done with the help of AI models. By training the model to recognize sea ice by feeding it millions of images where the ‘target’ is made distinguishable to the computer by its features being called out, it becomes capable of identifying sea ice on an image where it has not been marked, thus doing in an instant what it took probably hundreds of mandays to achieve earlier.

Some common techniques for labelling images:

Semantic Segmentation – Pixel level labelling, used for more precise recognition of objects in a single class to differentiate them from each other.

2D Bounding Box – To facilitate the detection of certain objects, rectangular, close-fitting boxes are drawn around the target objects.

Polygonal Annotation – Similar to a 2D Bounding Box, but the figure drawn around the object to be identified is not rectangular, but polygonal instead.

Cuboid Annotation – Also called 3D cuboid annotation, cuboidal annotation is used where the third dimension of depth is relevant for the AI model. A case in point could be autonomous vehicles here the model needs to know how long it might take for a truck to pass


Software programming has developed along textual pathways, with programs coded in textual formats being read and understood by machines. Audio remained a ‘bridge too far’ for computers. But that is changing with AI. With the creation of training data sets created to train AI models, this field is developing rapidly along with developments in what is known as NLP or Natural Language Processing.

The most obvious use of audio capability in AI appears to be to convert speech to text. Being the most precise method of communication, with a finite set of characters and words and symbols in each language, text is the preferred language of communication for computer systems. Therefore, the path to any operation on an audio file lies through text. If one needs to search for a certain string in an audio file, it would be searched as a text string and not as an audio string. If it is searched as an audio string, the computer, with the use of AI, will perhaps convert it to a text string and match it with the original audio file which it is searching against, which presumably is also stored as a text file. Development of AI models has greatly speeded up the growth of NLP.

Examples of audio capability application:

  • Conversion of speech to text, automating transcription
  • Voice response units for customer service
  • Emotion and sentiment identification and management of potential danger signals


With its combination of visual and audio content, video remains the richest and densest media that is handled by AI models. As discussed elsewhere, videos are generally handled as a sequence of images, with the additional element of changes taking place in the identified variables from one frame to the next further enriching the information contained.

Autonomous vehicles, security surveillance and virtual examination proctoring are some of the applications of AI that is trained through video labelling.

In Conclusion

oWorkers excels in its chosen area of specialization, having consistently been identified as one of the top three providers of data services in the world. Its rankings on Glassdoor have always been above 4.6 out of a possible 5. Though not specific to data labelling, our spread of centers also provides clients the capability of contingency planning, with capacity being made available in more than one location for the same service. Your work enables us to bring a few more people from disadvantaged backgrounds into the digital economy and change not only their own, but lives of their families as well.

We know the answer to ‘what is data labeling’ as well as ‘how it can be done efficiently,’ ‘what are the right tools to be used’ and ‘how to create value for client AI models.’

Advantages and Disadvantages of Outsourcing Your Data Entry

Advantages and Disadvantages of Outsourcing Your Data Entry

Advantages and Disadvantages of Outsourcing Your Data Entry

Businesses are constantly striving to outshine competitors in the race for more customers and revenues. Their efforts result in generation of data all the time. With the help of technology, businesses then make efforts to draw meaning from this data in pursuit of their business goals.

Some of the data generated is in a format or media that can be directly accessed by technologies used by the business. Visitors at an industry event might be requested to key in their contact information on a simple interface at the booth. A job applicant may be requested to apply directly on the Applicant Tracking System (ATS) of the recruiting company.  

In many cases data is not in a compatible format or not on a media that can interface with the technology. This creates the need for data entry so that the data that is generated becomes usable. If the visitor to your booth at the event drops a name card, it would need to be manually added to the database your business maintains of client leads. If the job applicant emails her Resume to you, it would need to be taken apart and keyed into the ATS or any other system used by the company to manage jobs and applications.

Data entry, thus, is a critical function that powers the digitization of information so that it becomes a part of the digital world and can be sliced and diced as per needs of the owning business.

Data entry is not for a finite list of activities. You may need to do data entry for Guest comment cards, Survey results, Ecommerce product description, Insurance claim, School admission application, Conference transcription, Invoices, Restaurant menu, Job application, Client name card…it can go on.

And for any business or industry.

The requirements and rhythm of data entry often being different from the business for which it needs to be done, outsourcing of data entry is the accepted norm, to BPO companies specializing in the task.

What are the advantages and disadvantages of outsourcing your data entry?

Advantages and Disadvantages of Outsourcing – Advantages

Permits focus on core business

An evaluation of the pros and cons of outsourcing needs to recognize that hundreds and thousands and millions of people and organizations are engaged in a wide variety of endeavours to make a difference in the world and enable them to lead a respectable and comfortable life. They could be making watches, stitching clothes, publishing books, growing food, or many other things. They build expertise in the area of work that enables them to stand out. While there are many other functions that may be required for running an organization that will contribute to the business, some of them take time and often require their own expertise, like accounting. There is an opportunity cost to every minute that an expert spends away from the core business, hence, where feasible, businesses look to outsource such activities so that they stay true to their business and expertise.

Data entry is one such task that, if outsourced, enables the business and its employees to stay focused on their core activities and ensure they are done successfully. By doing data entry, the experts would be doing a task they are not very good at, and ignoring the work that they are good at. So, it is a double whammy. By outsourcing, they create conditions for that work to be done in a more efficient manner, while ensuring their own business does not suffer.

oWorkers has been rated as one of the three top data entry providers in the world and has executed work for over a hundred clients in the short period of eight years of their existence.

Enables cost savings

Data entry often being a rules-based activity, does not require advanced educational degrees or experience to perform needs to be understood while analyzing pros and cons of outsourcing. As a direct result, operators for doing data-entry work can be hired at a reasonable cost which is often lower than the business specialists and professionals that the company employs for doing its core work. These higher paid staff are not equipped to do the work any better than the comparatively lower cost resources. In fact, they may be worse off doing data entry as they do not have any training or experience in it. And no interest too. Hence, by outsourcing, the same work can be completed at a lower cost, even if we ignore the savings in terms of time.

oWorkers operates from some of the most highly rated locations for outsourcing in the world. Our clients report savings of up to 80% when they outsource to us. Our operational efficiencies enable us to save costs which we are able to share with our clients.

Creates operational efficiency

We have seen that people who specialize in a task or activity will make efforts to develop expertise in it which leads to efficiency, and that is a factor in understanding the advantages and disadvantages of outsourcing. Though data entry, it is believed, does not have any specific requirements of knowledge or skills to execute well, aptitude and attitude perhaps being the more important requirements, operators engaged in it, as they gain experience, also develop expertise. Employment for data entry roles typically being from sections without advanced educational degrees, realizing that their employment options are limited, also make an effort to develop expertise to advance their prospects. This impacts the outsourced operation beneficially by making it more efficient; more can be done in a shorter period of time, with greater quality.

Data entry being a part of its chosen area of specialization, oWorkers delivers over 99% accuracy on client projects across a wide cross-section of measurement systems. With our expertise, in many cases, clients have chosen to initiate and implement a new data-entry process directly with us, instead of first implementing inhouse and then transitioning out.

Releases benefits of scale

Outsourcing pros and cons recognize that doing the same, or similar, work for a number of clients provides vendors the benefits of scale that can be shared with clients. Being known as the provider of a certain type of work can act as a ‘lead magnet’ with prospective clients viewing the vendor as an expert or leader in the space and approaching it for giving more business.

Scale tends to lower the cost of processing at a unit level. This is because the Fixed Costs of the organization are now spread over a larger number of transactions, lowering the share borne by each.

The existence of scale creates opportunities for investment in technology. Ten clients each with limited quantities of data entry work may not be able to justify investment in technology that a provider doing outsourced work for all ten of them, with the aggregated volume, can. This creates further efficiencies in the process, with all stakeholders benefiting.

oWorkers, with its transparent pricing model, is able to share the benefits of scale with its clients. It also leverages developments in technology through its partnerships with a number of technology providers, with the benefit shared with clients by deploying relevant technologies for their work.

Gives access to resources globally

Evaluation of the pros and cons of outsourcing cannot be completed without a discussion on resourcing.

It is said that water flows from high ground to low ground. This is what outsourcing of data entry does in business.

The typical direction of data entry outsourcing is from a relatively more prosperous society to a relatively less prosperous one. The relatively less prosperous society is at that stage in development as it has lesser opportunities and greater unemployment. For data entry work, there is far greater availability of a willing and able workforce than would be the case at the point of origination of that work.

Not only does a larger workforce become available, it releases the business from the shackles of the local labor market forever. Once outsourcing is decided upon, any labor market anywhere in the world could be leveraged, of course while keeping many other factors in mind, for this work.

As a side benefit, which is more of political relevance than business, data entry outsourcing creates employment opportunities in many places, which is why often governments provide incentives and support for setting up centers for such work.

As a locally registered company in all its locations, oWorkers is an active, contributing member of local communities. It is a preferred employer for the workforce in its catchment areas, and regularly receives unsolicited applications that reduces its hiring costs as well as attrition numbers. It also enables oWorkers to hire short-term resources to manage peaks, to the tune of almost 100 resources in 48 hours.

Advantages and Disadvantages of Outsourcing – Disadvantages

Processor boredom and burnout could impact quality

An effort that often leads to outsourcing is the breaking down of work into small, defined processes that can be trained easily as well as measured and monitored, and this is a key element in any review of the advantages and disadvantages of outsourcing. While great for the business, it is not so great for the people doing the work. Whether academically qualified or not, all humans are intelligent, thinking creatures. They crave variety and challenge and new experiences. Doing the same limited process repetitively without any scope for thinking or creativity can lead to burnout for the operators involved. This can result in switching off from work, boredom, looking for other opportunities, all resulting in the quality of work suffering.

This is one of the reasons management of people in a BPO is seen as such a critical role. The employing organisation needs to constantly monitor the output as well as the state of mind of their staff so that the work does not suffer and they are able to support their staff with their issues before it is too late.

The performance of each individual is monitored by oWorkers. Our independent Internal Quality team monitors performance at a transaction level and supports agents through coaching and feedback sessions where required. Our location in the Eurozone makes it a requirement for us to have fair and transparent employment practices. We work with employees, not freelancers, and actively support their career progression, including job rotation.

Risk to Intellectual Property could impact business

Interpretation of rules can be different between the client location and the outsourcer location and administration, and should be accounted for in an evaluation of outsourcing pros and cons. Focus can also be different, with a lower emphasis being placed on intellectual property (IP) by locations lower on the developmental index, where some of the outsourcers are located, as a result of cost and labor pool advantages.

A threat for the intellectual property owned by the client that is shared with the vendor engaged, is a real risk under the circumstances. IP being violated or versions of processes and products being available soon after, are not unheard of.

In addition to GDPR compliance, oWorkers is also ISO (27001:2013 & 9001:2015) certified and operates with facilities & protocols that are secure. We also ask that each member of our staff sign a non-disclosure agreement (NDA) before access to client data is provided.

Labor malpractices could tarnish the brand

An assessment of outsourcing pros and cons cannot be complete without understanding that there are many contributors to outsourcers being able to provide low-cost solutions. One of them is labor practices, or rather, the lack of them. In an environment where job opportunities are fewer and monitoring lax, it is easy to get carried away and try to squeeze the maximum out of the money being spent on resources. Such malpractices, like child labor, could get associated with the client’s brand and cause much greater harm than the money being saved or efficiency created. Justifying it by saying that it is the vendor’s issue might not be of much help in such a situation.

oWorkers is committed to the career progression of its staff, having adopted the model of working with employed resources as opposed to freelancers. It offers a fair and transparent work environment drawn from best practices around the world. Our staff are also free to choose to work from home as long as the shadow of the Covid-19 pandemic looms. Our physical presence in the Eurozone ensures the highest standards of people practices.

Cultural differences could impact on accuracy

“A rose by any other name would smell as sweet” argued Juliet in William Shakespeare’s play Romeo and Juliet. Of course, she may not have needed to analyse the pros and cons of outsourcing.

In business, however, the issue could be more complex. If an operator working for a vendor in India and doing data entry for a men’s clothing e-commerce store, were to label an upper garment as ‘kurta’ as per his knowledge of a corresponding local wear, instead of the ‘shirt’ it is known as in the client’s parlance, potential customers looking for a ‘shirt’ will never be able to find it.

Culture and practice keeps changing as we move from one place to another. The greater the distance, the greater the variance. For delivery centers located far from the originating center, cultural issues could cause errors to creep into the output. Language might be different.

oWorkers, with a center in Europe, which is within three hours of flying tome away from any major city in Europe, is culturally aligned to support customer business for Western European clients. In addition, our chosen areas of specialization that focus on data related work, mostly involve interaction with client staffers and not customers.

Hidden costs might impact viability

While the business case looks promising, any analysis of the advantages and disadvantages of outsourcing needs to know that there are hidden costs that could tilt the balance. Grid-supplied power supply may be erratic requiring investment in private generating capacity. Travel costs could increase as there will be a likelihood of outsourcer staff needing to travel to the delivery destination to ensure processes are followed and issues resolved. Local events like political unrest and demonstrations could jeopardize business continuity resulting in down time.

oWorkers provides transparent pricing to clients including a choice between rate per unit of output and rate per unit of capacity. Once a price is agreed, all additional costs are borne by oWorkers. We make arrangements to augment resources like power supply in centers where grid supply could be erratic. All costs are factored in when we quote a price so that there are no surprises for clients.

Advantages and Disadvantages of Outsourcing – In Conclusion

While there are clear benefits that data entry outsourcing delivers to a business, it comes with its own set of limitations which should not be disregarded in an assessment of outsourcing pros and cons, and need to be managed. Successfully managing the downsides while taking advantage of the benefits results in creating value for the business.