| Terms | Definition | Team |
| Transformation | A strategy to fundamentally change the way technology supports our business goals and needs - moving from IT-enabled to being more IT and Data-driven | Transformation |
| Unattended Bot | A bot that is meant to run without intervention and is able to start itself, execute the task, and build outputs of the desk without any employee interaction. | Transformation |
| Attended Bot | A bot that supplements an employee's workload but still requires some inputs or operation from the employee | Transformation |
| Data Analyst | A data analyst collects, cleans, and interprets data sets in order to answer a question or solve a problem. | Transformation |
| Data Engineer | A data engineer is an IT emloyee whose primary job is to prepare data for analytical or operational uses. | Transformation |
| Data Lake | A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. While a hierarchical data warehouse stores data in files or folders, a data lake uses a flat architecture to store data. | Transformation |
| Data Warehouse | A data warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. Data warehouses are solely intended to perform queries and analysis and often contain large amounts of historical data. | Transformation |
| Sheet (on Quicksight) | A page that displays a set of visualizations and insights. | Transformation |
| Dataset | A set or collection of data. Data sets describe values for each variable for unknown quantities such as height, weight, temperature, volume, etc of an object or values of random numbers. | Transformation |
| Robotic Process Automation (RPA) | A type of automation carried out on graphical user interfaces (GUI) where it mimics the activity a user would perform using the same tools that an end user would use. | Transformation |
| Data Visualization | Also known as a visual, this is a graphical representation of data. | Transformation |
| Process Critique | An analysis of a process that focuses on its strengths and limitations. Critiquing is a systematic process for evaluating areas of improvement and the results reported. This is not a judgement on the efficiency of a function or a person. | Transformation |
| Application Programming Interface (API) | An API is a set of definitions and protocols for building and integrating application software. | Transformation |
| API Integration | API integration is the connection between two or more applications via their APIs (application programming interfaces) that allow systems to exchange data sources. API integrations power processes throughout many sectors and layers of an organisation to keep data in sync, enhance productivity and drive revenue. | Transformation |
| Artificial Intelligence (AI) | Artificial Intelligence is the simulation of human intelligence in machines, often performed via a technology known as Neural Networks. They attempt to make decisions in similar ways that humans would, given a series of inputs. | Transformation |
| Business Analytics | Business Analytics is the process by which businesses use statistical methods and technologies for analyzing historical data in order to gain new insight and improve strategic decision-making. | Transformation |
| Business Intelligence | Business intelligence comprises the strategies and technologies used by enterprises for the data analysis of business information. BI technologies provide historical, current, and predictive views of business operations. | Transformation |
| Chatbot | Chatbots are a type of automation where a user is presented with an interface resembling a standard chat system, not unlike a live help box, social media messenger, or instant messaging. The system responsible for interpreting requests, and responding to the end user | Transformation |
| Vertical | Composed of the following: Healthcare, Financial Services, LPC Contact Center, Contact Center, AQR Financial Services, Data and Research, Administration | Transformation |
| Computer Science | Computer science is the study of algorithmic processes, computational machines and computation itself. As a discipline, computer science spans a range of topics from theoretical studies of algorithms, computation and information to the practical issues of implementing computational systems in hardware and software. | Transformation |
| Conversational Chatbot | Conversational chatbots attempt to use fewer interfaces and ask natural questions. They mimic interacting with a human as much as possible and present the user with a natural experience when initiating the chain of automations desired. | Transformation |
| Data Architecture | Data architecture is a framework for how IT infrastructure supports IO's data strategy. The goal of any data architecture is to show the company's infrastructure how data is acquired, transported, stored, queried, and secured. | Transformation |
| Data Warehouse | Data Lakes are special kinds of data stores that accept any kind of structured or unstructured data without needing to transform the data before loading it | Transformation |
| Data Scientist | Data scientists are big data wranglers, gathering and analyzing large sets of structured and unstructured data. They analyze, process, and model data then interpret the results to create actionable plans for companies and other organizations. | Transformation |
| Data Transformation | Data transformation is the process where data is extracted, sifted through, and subsequently understood, so that it can be transformed into something that can be analyzed. Data transformation includes two primary stages: understanding and mapping the data; and transforming the data. | Transformation |
| Decisioning Algorithm | Decisioning Algorithms are singular purpose pieces of code which aren’t as advanced as AI however, given a known set of rules, are able to generate an output from some given inputs. | Transformation |
| Data Mapping | Defining how fields in different data sources connect together, and what types of data transformations they require. | Transformation |
| Extract Load Transform (ELT) | ELT is a process where data gets leveraged via a data warehouse in order to do basic transformations without the need for data staging. ELT uses cloud-based data warehousing solutions for all different types of data - including structured, unstructured, semi-structured, and even raw data types. | Transformation |
| Extract Transform Load (ETL) | ETL is a data integration process that combines data from multiple data sources into a single, consistent data store that is loaded into a data warehouse or other target system. | Transformation |
| Forecasting | Forecasting is the act of analyzing and mining data in order to predict what will happen in the future. Forecasting is typically accomplished using a BI application. | Transformation |
| Machine Learning | Machine learning is the study of computer algorithms that can improve automatically through experience and by the use of data. | Transformation |
| Machine learning (ML) Insights | Narrative add-ons that are based on evaluation of data on Quicksight | Transformation |
| Raw Data | Raw data is a set of information that was delivered from a certain data entity to the data provider and hasn't been processed yet by machine nor human. | Transformation |
| Project IOnize | Re-inventing IO’s processes using technology to allow the organization to keep ‘Creating Endless Opportunities for our Partners to realise their full potential’ | Transformation |
| Representational state transfer (REST) | Representational state transfer is a software architectural style that was created to guide the design and development of the architecture for the World Wide Web. | Transformation |
| REST / RESTful API | RESTful API is an architectural style for an application program interface (API) that uses HTTP requests to access and use data. | Transformation |
| Data Scrubbing | see Data Cleansing | Transformation |
| SPICE | Super-fast, Parallel, In-memory Calculation Engine in QuickSight. SPICE is engineered to rapidly perform advanced calculations and serve data. | Transformation |
| System Integration | System integration is a data management process that uses software to share information between various subsystems automatically. As every system is programmed with different coding, an integrator acts as a middleman that translates data from each software behind the scenes. | Transformation |
| Data Analysis | The basic workspace for creating data visualizations, which are graphical representations of your data. Each analysis contains a collection of visualizations that you arrange and customize. | Transformation |
| Data Cleansing | The careful analysis of datasets and data storage protocols to support the most accurate data possible by deleting out-of-date, inaccurate, or incomplete information. | Transformation |
| Chatbot Platform | The interface where the user interacts with a chatbot. | Transformation |
| Rule driven Chatbot | The most simplistic chatbot but often very effective in initial implementations. | Transformation |
| Statistics | The practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample. | Transformation |
| Data preparation | the process of transforming data for use in an analysis. | Transformation |
| Dashboard (on Quicksight) | The published version of an analysis on Quicksight | Transformation |
| Data Staging | The staging area is mainly used to quickly extract data from its data sources, minimizing the impact of the sources. After data has been loaded into the staging area, the staging area is used to combine data from multiple data sources, transformations, validations, data cleansing. | Transformation |
| Extract Load Transform Load (ELTL) | The supported data integration process at IO that is a combined approach between ELT and ETL. We leverage between both a Data Lake and Data Warehouse infrastructure in the IO Data Architecture affording us the flexibility of both. | Transformation |
| Structured Data | The term structured data refers to data that resides in a fixed field within a file or record. Structured data is typically stored in a relational database (RDBMS). It can consist of numbers and text, and sourcing can happen automatically or manually. Characteristics of Structured Data that differentiates it from Unstructured Data are:
| Transformation |
| Unstructured Data | Unstructured data is more or less all the data that is not structured. Even though unstructured data may have a native, internal structure, it's not structured in a predefined way. There is no data model; the data is stored in its native format. Typical examples of unstructured data are rich media, text, social media activity, surveillance imagery, and so on.
| Transformation |
| Department | The team or account where a team member is assigned | Transformation |
| Events | The trigger to begin an automation process in such a way that the remainder of the automation runs as expected with the required information | Transformation |
| Ionize | Undergo a change; become different in essence; losing one's or its original nature | Transformation |
| Internal Digital Transformation | An index to measure how efficient we are with our internal digital transformation initiatives. Composed of 5 components: Admin-to-employee ratio Admin Cost Per FTE Admin Cost to Revenue Ratio Efficiency gains Investment to Efficiency gains Ratio | Transformation |
| Dropped Calls | Answered calls with no recording. | Transformation/Seated |
| Average Handling Time | Average length of interaction including talk time, hold time and wrap up or after call work | Transformation/Seated |
| Number of Missed Calls | counts the number of calls missed with a missed call reason indicated | Transformation/Seated |
| Number of Calls Received/Made | counts the number of calls routed to or made by an agent | Transformation/Seated |
| Number of Dropped Calls | counts the number of calls where recording is not available but call answered is 'Yes' | Transformation/Seated |
| Number of Calls Handled | counts the number of calls with a recording available and where call answered is 'Yes' | Transformation/Seated |
| Number of Voicemails | counts the number of calls with a voicemail | Transformation/Seated |
| Number of Unanswered Calls | counts the number of of calls where call answered is 'No' | Transformation/Seated |
| Number of Answered Calls | counts the number of of calls where call answered is 'Yes' | Transformation/Seated |
| Volume Percentage | gets the percentage based on the 'Number of Calls Handled' | Transformation/Seated |
| Inbound calling | Means incoming calls taken by agents for customer support or inquiries. | Transformation/Seated |
| Outbound calling | Means outgoing calls made by agents (or sales representatives) for sales, follow-ups, renewal reminders, or updates. | Transformation/Seated |
| Calls Handled | Number of calls not including dropped calls and unanswered calls. | Transformation/Seated |
| Total Call Duration (in Mins) | sum of all minutes taken per call | Transformation/Seated |
| Total Call Duration (in Sec) | sum of all seconds taken per call | Transformation/Seated |
| Average Number of Calls Made (per Hour) | takes the 'Average Number of Calls Made (per day) and divides it by 8 (where a work day is assumed to be made up of 8 hours) | Transformation/Seated |
| Calls Answered Percentage | takes the 'Number of Calls Answered' over the 'Number of Calls Received/Made' | Transformation/Seated |
| Average Number of Calls Made (per Day) | takes the 'Number of Calls Handled' over the 'Number of Business Days Spent' | Transformation/Seated |
| Average Number of Calls Made (per Week) | takes the 'Number of Calls Handled' over the 'Number of Business Days Spent' in a week (7 days) | Transformation/Seated |
| Percentage Distribution Calls Received/Made | Takes the 'Number of Calls Received/Made over the 'Total Number of Calls per Day' | Transformation/Seated |
| Number of Business Days Spent | takes the individual dates based on the provided records | Transformation/Seated |
| Total Number of Calls per Day | takes the sum every weekday for all 'Number of Calls Handled' over the 'Number of Business Days Spent' | Transformation/Seated |
| Average Handling Time per Agent | Total Call Duration (in Mins)' over the 'Number of Calls Handled' | Transformation/Seated |
Employee ID | Current IO Employee ID | Transformation |
Vertical | Current Vertical the Team Member is assigned:
| Transformation |
Department | Current Department the Team Member is assigned (equates to the team) | Transformation |
| Position | Current Position of the Team Member | Transformation |
| First Name | First Name of the Team Member | Transformation |
| Last Name | Last Name of the Team Member | Transformation |
| Basic Salary | Latest Basic Salary of the Team Member | Transformation |
| Allowance | Latest Allowances included in the compensation for the Team Member | Transformation |
| De Minimis | De Minimis amount included in the compensation for the Team Member (standard is Php 2,133.00) | Transformation |
| Total Salary | This is calculated as the Basic Salary + Allowance + De Minimis | Transformation |
Hire Date | Date when the Team Member was hired | Transformation |
| PH Positivity Rate | is the number of positive individuals as a percentage of the total individuals tested for the week. (Based on DOH) | Transformation/Covid |
| IO Positivity Rate | is the number of positive IO employees as a percentage of the total IO employees. | Transformation/Covid |
| Gender Wage Gap | is a measure of what women are paid relative to men. The ratio is often expressed as a percent, or in peso terms. This tells us how much a woman is paid for each peso paid to a man. | |
| Age Group | IO groups by age according to the following:
| |
| EAC | Employee Awareness Check | Transformation/EAC |
| Status - Done | employees who take the quiz | Transformation/EAC |
| Status - Exempted | employees who are exempted to take the quiz based on CPP-LC-0101_Employee Awareness Check 6.6 | Transformation/EAC |
| Status - Not Started | employees who did not take the quiz | Transformation/EAC |
| Status - Terminated | employees who are already separated | Transformation/EAC |
| Status - Other Status | Includes the following: Floating, Forced Leave, On Leave, RTWO | Transformation/EAC |
| Passing - Passed | score at least 80% | Transformation/EAC |
| Passing - Failed | score below 80% and those who failed to take the quiz | Transformation/EAC |
| Passing - Not Taken the Quiz | employees under exempted, floating or not started status | Transformation/EAC |
| Passing - Exempted | employees under done, exempted or not started status | Transformation/EAC |
| Passing - Terminated | employees with terminated status | Transformation/EAC |
| Passing - Other | under other status | Transformation/EAC |
| Month | date the quiz is conducted | Transformation/EAC |
| Policy | questions policy category | Transformation/EAC |