How to Choose a Provider to Outsource Text Annotation
Annotation, as we perhaps know, is the act of adding information to data that makes it meaningful and easy to understand. In other words, we enhance the data by annotating it. When this enhancement is done for data that is textual, we refer to it as ‘text annotation.’
But this is in English.
The reference point here is enhancement of data so that it can be understood by computers. It is generally done as an input to building an Artificial Intelligence (AI) engine through a process of Machine learning (ML). What do we mean by ‘text annotation’ in this context?
Let us take an example. Of Resume parsing. The context here is employment.
Traditionally, the first step, when an employer sought to fill a position, was to request interested candidates to submit a Resume. The Resume, once submitted, would be perused by the HR team to ascertain suitability based on which it would be taken forward for further processing. This has been a manual, resource-hungry task for decades. With increasing volumes and pressure on performance, employers looked for technology solutions.
As technology developed, in order to make processing more efficient, employers developed a database into which interested candidates could directly input their particulars, that would otherwise be submitted by means of a Resume. While this created efficiency for the employer, as they were able to sort, evaluate and process much faster and more accurately, it created additional work for the candidate. She had to input the information already present on her Resume, into a new database. And perhaps as many times as the jobs she was applying to.
Enter AI. Leading to the evolution of Resume Parsing.
What is the process now?
Instead of keying in information field by field on the employer database, the candidate has to upload a copy of her Resume. The employer has a Resume parser at work which reads the information on the Resume and fills up the database fields by itself, only for a final assent by the candidate that she agrees with the final outcome. It is perhaps limited to large employers currently but adoption is rapidly increasing.
This has been made possible through ML for which inputs have been created with the help of text annotation provider. Human text annotators have annotated thousands and millions of Resumes to identify what part of the text should be placed in which field of a manpower database. After being trained with enough data and with enough variations, the AI engine used by the employer can read the next Resume that gets submitted, and correctly classify it, even though it has not been annotated by a human being.
This is the contribution of text annotation outsourcing to AI and ML. In more technical terms, it can be referred to as the addition of metadata to text so that it becomes meaningful for machines to read (or view) and understand. And, of course, it needs to be done by human hand.
Text annotation being a critical input for AI and ML, for an outsourcer, it is important to ensure that they have the right and reliable partner to outsource text annotation.
The ensuing paragraphs suggest a set of criteria based on which the selection should be made and questions that should be asked during the evaluation process. This would enable you to separate the grain from the chaff and select suitable provider/s out of a long list.
To make the process simple, for each criteria, a set of questions is listed that an outsourcer should be asking vendors interested in providing text annotation outsourcing to them. These are neither mandatory nor sequential but meant as an indicative set to display the range that you might need to cover during the evaluation process. Depending upon the work that is being outsourced, you may need to shift your emphasis, leave out questions that may not be relevant and, at times, perhaps even go beyond this set.
So, here we go.
Domain and Functional Knowledge
- Do they possess prior experience of doing similar work for other clients?
- Have any of our competitors, or any other company from our industry, outsourced text annotation to them in the past or are currently sourcing?
- Will an existing client be willing to certify their ability?
- Will they be in a position to do our work accurately?
Depth of Coverage and Experience
- Text annotation providers have applications in a wide range of industries like Medical science, Aeronautical, Robotics, Agriculture, Retail, Self-driving cars, etc. To what industries have they been exposed?
- Which of the following text annotation techniques are covered by their capability?
- Text Categorization
- Semantic Annotation
- Phrase Chunking
- Entity Linking
- Does their capability extend to annotations of various types like grammatical, sentiment, mood, etc.?
Quality and Accuracy
- If we outsource text annotation to them, will they have a process of sample monitoring done by a team of Quality Analysts (QAs) based on which coaching is provided to agents?
- Will this be an independent team or within the delivery structure?
- Do they have a Quality Control (QC) process in their processes?
Speed and Turnaround
- What turnaround time are they willing to commit for delivering text annotation outsourcing?
- Do they have a 24×7 delivery model? Will it be an extra cost if we were to opt for a 24×7 delivery model?
- Which global time zones do they operate from? Can it enable us to benefit from the difference between our time zones?
- Will they be willing to transfer existing skills with this kind of work to our project which can help us get off the ground faster?
Pricing
- What is the price point for providing text annotation outsourcing?
- Is the price per unit of time or per unit of output? Can they give us a choice between the two?
- What is included in the price?
- What is not included in the price? In other words, what is it that we will need to pay for over and above this price?
- How much will it enable us to save in comparison to our existing cost?
- How does their price compare with other vendors bidding for our project?
- Are they ‘off the ballpark?’ In other words, is their quote vastly different from those of others? If yes, what could be the reason?
- Is the price too low for them to be able to make it profitable? What guarantees should we take so that they do not ignore this work? What is the justification for the low price?
MultiLingual Capability
- How many languages are they in a position to provide support for in text annotation outsourcing?
- Which are these languages?
- How long does it take to add resources for non-core languages?
- Will they be able to add a language currently not covered? How long will it take?
- What is the depth of these skills? In other words, how many people for each language can they provide?
Technology and Data Security
- If we outsource text annotation to them, will they be able to work on our technology or can they only work on their own tools?
- What technology tools do they intend to use for our work?
- Have they connected with client systems in the past or only worked on their own technology?
- What file formats, data exchange protocols will be required?
- Do they have an ISO (27001 and 9001) certification?
- Are they GDPR compliant?
- How secure are their work from home arrangements for staff?
- What security measures do they implement to isolate the network and servers for our processing?
- Can they implement physical access control?
Scalability and access to human resources
- Do they use employees or freelancers and contractors for doing work?
- What is the depth of resources in their catchment area? In other words, what is the annual availability of fresh resources of the profile who work for them?
- Do they have direct access to educational institutions from where they do campus hiring?
- What do their employees rate them on Glassdoor?
- What does the screening process for hiring look like?
- What is the scaling up volume they can handle per day?
- Do they offer flexibility to staff to work from home if and when required?
- How do they equip and train the new hires for work on a project?
Financial health
- To take on as well as outsource text annotation are decisions of responsibility and require commitment and financial strength to execute, especially for the provider. For starters, are they a profitable enterprise?
- How many years have they been profitable?
- Are their regulatory requirements in place and updated?
- Where do they pay taxes?
- Are warning signs visible on their Balance Sheet that could lead to possible curtailment of operations in future?
General Management
- When you outsource text annotation, it is important to assess the provider management’s commitment to the project. How active is the senior management in the day-to-day operations?
- Does the management team have hands-on experience of the kind of work we propose to outsource?
- Do they have centers in multiple geographies for delivery?
- Are they in a position to offer a Business Continuity Plan to support our work by switching it to an alternate location in case the primary location cannot be accessed?
- Do they possess a ‘project management’ framework and commitment?
- Do they have processes through which support services are delivered so that delivery can continue unaffected?
- Are they GDPR compliant?