Data Transcription Challenges: The Overly Not-so-simple Obstacles

Data Transcription Has Challenges That General Transcription May Not Possess despite Being Slightly Indifferent. Accordingly, What Are Those Challenges?

 

 

Data transcription is slightly indifferent from general transcription.

Both transform information, either audiovisual or audio, into a written format.

However, dissimilar to general transcription which basically produces a transcript, data transcription creates transcripts for research or business purposes, specifically case studies and white paper.

Considering the difference between data transcription and general transcription, their challenges also vary. General transcription does not serve specific purposes, but data transcription does.

As mentioned above, data transcription results in data for research or certain business use; thus increasing challenges a data transcriptionist face.

What are those obstacles? To elaborate, here are data transcription’s biggest challenges.

 

Data Transcription and Its Biggest Challenges

 

Data transcription services pose challenges that can be classified into (1) workflow, (2) quality control, and (3) technical difficulties.

 

1. Workflow

 

data transcriptionWorkflow, or work funnel, considerably becomes the first and foremost challenge due to diverse individual competencies and teamwork collaboration.

To simplify, it consists of individual and collective challenges.

Regarding each transcriptionist in a team, it is unlikely that everyone shares the exact same competencies.

To some degree, differences affecting their workflow exist.

Some examples are the necessary time to do a task or the transcription quality.

This, therefore, challenges each individual to adjust to deadlines without discounting service quality.

 

Another challenge is regarding project management, both manual and automatic.

Each of them has its own strengths and weaknesses, specifically pertaining to tradeoff.

Manual management allows more flexibility.

Scheduling can be based on each transcriptionist’s workload.

It, however, induces rough task estimation and requires more energy for scheduling.

The automatic one, in contrast, puts the start date, duration, and target per day into the digital calculation.

This enables a more accurate estimation of the cost of working under tight automated scheduling.

Moreover, there is another challenge during this pandemic.

As in-house collaboration is strictly limited, telecommuting collaboration may cause communication difficulties that lead to misunderstanding within a team and misinterpretation of what the project is about.

Should the problem prevail, such bigger problems as delay may occur.

 

 

2. Quality Control

 

data transcriptionService quality delivery presents challenges for numerous industries ─ transcription is no exception.

To get the best quality possible, a transcriptionist has to translate not only the language but also the context.

Furthermore, translating context is difficult due to its sub-aspects such as background information, language style, and tone.

For example, context translation varies from one field to another.

As transcription is not exclusive to certain business sectors, its projects’ coverage is wide.

To produce comprehensible transcripts, context must be present and each business sector, topic, and field are dissimilar to one another (compare Banking to Engineering).

Ergo, this necessitates transcriptionists to, at least, understand what the document is about.

This is to provide clearer or semantically similar information even after the original language has changed.

Rework and revision also affect service quality levels. Before a transcript is ready to use, editors will review it.

Should a room for improvement exist, either rework or revision is necessary.

Rework refers to addition or modification through elaboration for details of the context.

Meanwhile, revision is any correction to make a text more understandable.

As a result, these processes may cause a longer time to complete a project.

 

 

3. Technical Difficulties

 

Technical difficulties also exist in transcription and data entry services.

This is for probabilities of software and network failure exist.

Oftentimes, the problem is out of the transcriptionists’ control.

One of the issues, for instance, is downtime.

Today’s transcriptionists mostly utilize an online portal as a submission entry and collaboration playground.

In the event of downtime, this portal will be temporarily inaccessible.

That might be due to either server or network downtime.

Server downtime happens when problems occur in the web server hosting the portal.

Whereas, the causes of network downtime are either a device’s failure to detect internet connection or internet unavailability at the range.

Another one is pertinent to files.

In some cases, a file size is too large, resulting in longer access time.

Another common case is due to file quality. Inaudible or low audio quality and overlapping voices are the examples.

Additionally, corrupted files also become an obstacle.

The last resort is by contacting the customer(s) to inquire about backup files.

 

 

The Bottom Line of Data Transcription Challenges

 

Data transcription services have three major categories of challenges: (1) workflow, (2) quality control, and (3) technical difficulties.

While some challenges such as workflow and quality assurance are controllable, the other, technical difficulties, are not.

Despite everything, mitigating the risks of problems resulting in challenges is not far from possible.

While a good transcriptionist team strictly follows a plan to finish a job, a better team prepares a backup plan in the event of a worst-case scenario.