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.

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Ramamurthy Venkatesh 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, Mulshi, Lavale, Pune District – 412115, Maharashtra, IN

Abstract

Objective: Business Model Innovation approaches in service business model context are not adequately studied in the extant literature and there is a clear need for extension of different business model typologies for innovating service business models. Principal aim of this study is to explore how service business model archetypes can be explained as a business model representation such as Business Model Canvas, particularly what the term managed services really mean. Also, it is intended to add clarity to current business model innovation approaches in providing managed services, especially business process services in a service value chain. This will prompt further research to address related implications of networked business model setup and information technology as an enabler in managed services context. Methods/Statistical Analysis: Established framework of Business Model Canvas from extant literature and recent trends in business model representations that cover digitally enabled service business models are compared and contrasted. In line with service dominant logic, approaches for management and optimization of key resources and key activities are used as basis of stacking up different service business model archetypes. Service value chain and network business model implications are emphasized for further differentiating the innovation approaches in managed services business models. Findings: Among various business model design tools and representations, service business models can be better represented as a business model canvas with special emphasis on how key resources and key activities are managed and optimized in a service value chain. Digital enablement with the use of IT and/or cloud infrastructure shall act as accelerators for effective business model innovation in service context. Service business models shall be categorized as a stack of service offerings such as outsourced services, resource outsourcing, professional services, BPO/ITeS, managed services and Business Process As A service (BPaaS). Managed services currently mean to only manage IT services but there is new paradigm of "Managed Business Services" which is emerging. Applications/Improvements: Suggested findings of this paper and the identification of broad types of service offerings, which clearly differentiate managed services from other service models, can be applied in practice. This approach shall bring in more consensuses about understanding of managed services business models among practitioners and researchers.

Keywords

Business Model Innovation, Business Process as a Service (BPaaS), BPO/ITeS Managed Services, Managed Business Services, MSP (Managed Services Providers), Service Business Models.

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