Data entry supervisor

Data entry supervisor article illustration

Description

Data entry supervisors manage the day-to-day operations of data entry staff. They organise the workflow and tasks. 

The duties of a data entry supervisor typically include, but are not limited to:

  • Establishing procedures for data entry staff to ensure accuracy and efficiency
  • Providing training and feedback to data entry staff on industry best practices
  • Training new hires on how to use computer programs such as Excel or Word
  • Ensuring that all data entered is accurate and up to date, including updating records when needed
  • Coordinating with marketing teams to ensure that product catalogs contain the latest information about available products
  • Communicating with clients to answer questions about orders or billing issues
  • Scheduling staff to meet deadlines and ensuring that they meet quality standards
  • Developing new methods for improving staff productivity or efficiency
  • Reviewing reports to determine if there are any errors, inconsistencies, or other issues that need to be addressed

Other titles

The following job titles also refer to data entry supervisor:

data processing coordinator
data records supervisor
data entry coordinator
data processing supervisor
data control clerk supervisor
data entry clerks supervisor

Working conditions

Data entry supervisors work in office environments, overseeing the work of data entry clerks. They typically work regular business hours, although they may occasionally need to work evenings or weekends to meet deadlines. Data entry supervisors may experience some stress due to the need to meet deadlines and to ensure the accuracy of the data entry clerks’ work.

Minimum qualifications

Entry-level data entry supervisors are typically required to have at least a high school diploma or equivalent. Some employers prefer candidates who have an associate’s or bachelor’s degree in computer science, information technology or a related field.

Data entry supervisors typically receive on-the-job training to learn the specific processes and procedures of the company. They may also receive training in computer programs and software the company uses.

ISCO skill level

ISCO skill level is defined as a function of the complexity and range of tasks and duties to be performed in an occupation. It is measured on a scale from 1 to 4, with 1 the lowest level and 4 the highest, by considering:

  • the nature of the work performed in an occupation in relation to the characteristic tasks and duties
  • the level of formal education required for competent performance of the tasks and duties involved and
  • the amount of informal on-the-job training and/or previous experience in a related occupation required for competent performance of these tasks and duties.

Data entry supervisor is a Skill level 3 occupation.

Data entry supervisor career path

Similar occupations

These occupations, although different, require a lot of knowledge and skills similar to data entry supervisor.

big data archive librarian
data centre operator
medical practice manager
ICT help desk manager
medical records manager

Long term prospects

These occupations require some skills and knowledge of data entry supervisor. They also require other skills and knowledge, but at a higher ISCO skill level, meaning these occupations are accessible from a position of data entry supervisor with a significant experience and/or extensive training.

data quality specialist
data analyst
data scientist
computer scientist
chief data officer

Essential knowledge and skills

Essential knowledge

This knowledge should be acquired through learning to fulfill the role of data entry supervisor.

  • MDX: The computer language MDX is a query language for the retrieval of information from a database and of documents containing the needed information. It is developed by the software company Microsoft.
  • Documentation types: The characteristics of internal and external documentation types aligned with the product life cycle and their specific content types.
  • XQuery: The computer language XQuery is a query language for retrieving information from a database and documents containing the needed information. It is developed by the international standards organisation World Wide Web Consortium.
  • Database: The classification of databases that includes their purpose, characteristics, terminology, models and use such as XML databases, document-oriented databases and full-text databases.
  • SPARQL: The computer language SPARQL is a query language for retrieving information from a database and documents containing the needed information. It is developed by the international standards organisation World Wide Web Consortium.
  • Resource description framework query language: The query languages such as SPARQL which are used to retrieve and manipulate data stored in Resource Description Framework format (RDF).
  • Query languages: The field of standardised computer languages for retrieval of information from a database and of documents containing the needed information.
  • Information confidentiality: The mechanisms and regulations which allow for selective access control and guarantee that only authorised parties (people, processes, systems and devices) have access to data, the way to comply with confidential information and the risks of non-compliance.
  • LDAP: The computer language LDAP is a query language for retrieval of information from a database and of documents containing the needed information.
  • LINQ: The computer language LINQ is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Microsoft.
  • N1QL: The computer language N1QL is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Couchbase.
  • Company policies: The set of rules that govern the activity of a company.

Essential skills and competences

These skills are necessary for the role of data entry supervisor.

  • Manage schedule of tasks: Maintain an overview of all the incoming tasks in order to prioritise the tasks, plan their execution, and integrate new tasks as they present themselves.
  • Motivate employees: Communicate with employees in order to ensure that their personal ambitions are in line with the business goals, and that they work to meet them.
  • Gather feedback from employees: Communicate in an open and positive manner in order to assess levels of satisfaction with employees, their outlook on the work environment, and in order to identify problems and devise solutions.
  • Apply information security policies: Implement policies, methods and regulations for data and information security in order to respect confidentiality, integrity and availability principles.
  • Evaluate employees: Analyse employees’ individual performance over a certain time span and communicate own conclusions to the employee in question or higher management.
  • Introduce new employees: Give new employees a tour in the company, introduce them to the colleagues, explain them the corporate culture, routines and working methods and get them settled in their working place.
  • Supervise work: Direct and supervise the day-to-day activities of subordinate personnel.
  • Manage employee complaints: Manage and respond to employee complaints, in a correct and polite manner, offering a solution when possible or referring it to an authorized person when necessary.
  • Estimate duration of work: Produce accurate calculations on time necessary to fulfil future technical tasks based on past and present information and observations or plan the estimated duration of individual tasks in a given project.
  • Supervise data entry: Supervise the entry of information such as addresses or names in a data storage and retrieval system via manual keying, electronic data transfer or by scanning.

Optional knowledge and skills

Optional knowledge

This knowledge is sometimes, but not always, required for the role of data entry supervisor. However, mastering this knowledge allows you to have more opportunities for career development.

  • Optical character recognition software: The software that electronically converts printed and typed images into machine-encoded text so that documents can be electronically stored, edited and digitally displayed.
  • ABBYY finereader: The computer program ABBYY FineReader is software that electronically converts printed and typed images into machine-encoded text so that documents can be electronically stored, edited and digitally displayed.
  • Data storage: The physical and technical concepts of how digital data storage is organised in specific schemes both locally, such as hard-drives and random-access memories (RAM) and remotely, via network, internet or cloud.
  • OmniPage: The computer program OmniPage is software that electronically converts printed and typed images into machine-encoded text so that documents can be electronically stored, edited and digitally displayed.
  • Data models: The techniques and existing systems used for structuring data elements and showing relationships between them, as well as methods for interpreting the data structures and relationships.

Optional skills and competences

These skills and competences are sometimes, but not always, required for the role of data entry supervisor. However, mastering these skills and competences allows you to have more opportunities for career development.

  • Manage ICT data classification: Oversee the classification system an organisation uses to organise its data. Assign an owner to each data concept or bulk of concepts and determine the value of each item of data.
  • Normalise data: Reduce data to their accurate core form (normal forms) in order to achieve such results as minimisation of dependency, elimination of redundancy, increase of consistency.
  • Coach employees: Maintain and improve employees’ performance by coaching individuals or groups how to optimise specific methods, skills or abilities, using adapted coaching styles and methods. Tutor newly recruited employees and assist them in the learning of new business systems.
  • Establish data processes: Use ICT tools to apply mathematical, algorithmic or other data manipulation processes in order to create information.
  • Recruit employees: Hire new employees by scoping the job role, advertising, performing interviews and selecting staff in line with company policy and legislation.
  • Perform data cleansing: Detect and correct corrupt records from data sets, ensure that the data become and remain structured according to guidelines.
  • Implement data quality processes: Apply quality analysis, validation and verification techniques on data to check data quality integrity.
  • Maintain data entry requirements: Uphold conditions for data entry. Follow procedures and apply data program techniques.
  • Discharge employees: Dismiss employees from their job.
  • Manage data: Administer all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit for purpose, using specialised ICT tools to fulfil the data quality criteria.
  • Manage data collection systems: Develop and manage methods and strategies used to maximise data quality and statistical efficiency in the collection of data, in order to ensure the gathered data are optimised for further processing.
  • Develop working procedures: Create standardised series of actions of a certain order to support the organisation.
  • Apply organisational techniques: Employ a set of organisational techniques and procedures which facilitate the achievement of the goals set. Use these resources efficiently and sustainably, and show flexibility when required.
  • Process data: Enter information into a data storage and data retrieval system via processes such as scanning, manual keying or electronic data transfer in order to process large amounts of data.
  • Implement data warehousing techniques: Apply models and tools such as online analytical processing (OLAP) and Online transaction processing (OLTP), to integrate structured or unstructured data from sources, in order to create a central depository of historical and current data.

ISCO group and title

3341 – Office supervisors


References
  1. Data entry supervisor – ESCO
  2. Data Entry Supervisor Job Description: Salary, Duties, & More – Climb the Ladder
  3. Featured image: Photo by Scott Graham on Unsplash
Last updated on March 24, 2023

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