Samir Yerpude ¹, Tarun Kumar Singhal ²

Affiliations
1 Faculty of Management, Symbiosis International University, Lavale, Mulshi Taluk, Pune - 412115, Maharashtra, IN
2 Symbiosis Institute of Telecom Management, Constituent of Symbiosis International University, Lavale, Mulshi Taluk, Pune - 412115, Maharashtra, IN

Abstract

Objectives: To study the Impact of IoT data on Business Analytics. Methods/Statistical Analysis: An exploratory research to study the Impact of IoT data on Business Analytics was conducted. Through the Literature review process, various preliminary information on IoT and Business Analytics including the Advanced Analytics was gathered. Research papers, Journals, Internet Sites and books were used to collate the relevant content on the subject. Analysis of all the relevant examples was done. The gaps in the area of research were identified to arrive at the problem statement and its impact on Organizations. Findings: World is moving very rapidly towards the Industry 4.0, where the most impactful position in almost all the areas would be of IoT (Internet of Things). Profoundly IoT allows the connection between people and things at any point and any given place with devices that can transmit data over the network. Thus, the Smart environment evolves which consists of Smart devices transmitting the real time data over Smart networks. Business Decision Making is facilitated with a greater accuracy with real time data transmitted coupled with the relevant information. IoT and Business Analytics based on IoT data is gaining a lot of significance and importance in larger organizations. Right decision making at the right time and at the right place is the key to successful businesses in today’s dynamic environment. Application: The real time analytics becomes a reality with IoT data transmitted over the Internet and consumed by the Business Analytics. Use of Past data is to analyze and identify the hidden trends so that future predictability is built. Current data helps validate the relevancy of the Business Analytics Model. It also helps in taking some course corrections as and when required.

Keywords

Advanced Analytics, Big Data, Business Analytics, Industry 4.0., Internet of Things.

Full Text

   

Samir Yerpude ¹, Tarun Kumar Singhal ²

Affiliations
1 Symbiosis International University, Pune – 412115, Maharashtra, IN
2 Symbiosis Institute of Telecom Management, Constituent of Symbiosis International University, Pune – 412115, Maharashtra, IN

Abstract

Objectives: To study the Impact of Data generated from Internet of Things (IoT) on Demand Forecasting. Methods/ Statistical Analysis: An exploratory research to study the Impact of IoT data on demand forecasting was conducted. Preliminary information on IoT and Demand Forecasting including the different types of forecasting and data collection methods which was gathered through various available sources. Research papers, journals, Internet sites and books were used to collate the relevant content on the subject. Analysis of almost all the relevant examples was completed as a part of this study. The advantages of Real – Time data i.e. data generated by IoT systems were identified to arrive at the impact on organizations through deductive reasoning. Findings: Industrial revolution 4.0 has begun where IoT systems will play a vital role. The population of devices that can transmit data over the network will increase exponentially. Data from such smart devices will get collated, analysed and used in various forecasting models. Since the managerial decision- making is enabled by the forecast, efforts are being put in to align the forecasting model to respond proactively to the market dynamics. Application: The IoT data gathered is used in different forecasting models to arrive at the most accurate forecast. Accuracy of the forecast gets verified by the calculated error value and relevancy of the forecasting model is established. This helps the system to be agile and enable corrections on the go in case required.

Keywords

Demand, Forecasting, Impact of Internet of Things, Supply Chain.

Full Text