Data annotation is not an easy process at all. The sampling of raw data, preparing it for labelling, extracting the required information, etc., all of this requires time and effort. And still, it’s a core part of most machine learning activities and AI projects. For this reason, many organizations prefer to outsource the entire data annotation process instead of using internal resources for it. It helps them save time, energy, money and maintain the confidentiality of the project in the long run.
Apart from the above discussion, this topic has a debate as still some companies prefer to use in-house resources for the purpose. So what to do in that case. Let’s discuss.
What is the Best Option to go with? In-House vs Outsourced Data Annotation
To be honest, going with the in-house resource is quite tricky to implement. One of the primary reasons is that it’s pretty expensive.
If you know, these kinds of projects include thousands of images, texts, etc., to annotate, and it is quite costly while using the in-house resource. So, in that case, the best option to go with is Outsourcing your data annotation projects. It allows you to focus on other projects while having the services at a much cheaper rate.
Benefits of Outsourcing Data Annotation Work
Let’s take a deeper look at outsourcing machine learning and AI data annotation projects.
There are many benefits in outsourcing data annotation projects which are as follows:
Better Time Availability & Focus
Once you outsource these critical projects, you get more time for focusing on and performing the critical tasks of your business. It helps rebuild the strategies related to customer services, marketing, etc. Not only this, but it enables to handle the product and its prospective customers better.
Cost savings opportunities
It’s always a good idea not to use the company’s internal resources for this purpose as they’re already on the payroll. Not only does it saves time but a huge amount of additional money as well. The experienced professional for this task in the market works at far better rates with greater management experience.
Higher quality of work with more accuracy
A reliable and experienced person will be able to handle the task with far more accuracy as compared to the in-house resource. There’s no doubt here as the outsourced team has entire guidelines and dedicated tools for data annotation. The team doesn’t compromise on the speed and productivity of the project.
Some of the other notable advantages are,
- Better scalability,
- Increased level of Data security, etc.
Risks of Outsourcing Data Annotation Work
While having so many benefits of outsourcing the data annotation project, there are some drawbacks to it:
- There’s a lot of competition in the market, and it is hard to choose the right one.
- You would have to transfer some of the control of your project to another party.
As per the industry experts, it is preferred to outsource health, automotive, and agriculture projects.
