Scaling an Internet of Things start-up: Can alliance strategy help?

2021 ◽  
pp. 204388692098616
Author(s):  
Dipankar Chakrabarti ◽  
Soumya Sarkar ◽  
Arindam Mukherjee
Keyword(s):  
Internet Of Things ◽  
Ad Hoc ◽  
Scale Up ◽  
High Tech ◽  
Industrial Internet Of Things ◽  
Start Up ◽  
Industrial Internet ◽  
Multiple Challenges ◽  
Proper Strategy

Owners of start-ups in the high-tech field face multiple challenges while scaling-up. The major challenge is to form a proper strategy that guides them to move from building products for point solutions to more industry-focused solutions, retaining skilled resources, efficient workforce management, and improving market reach. This case study is on Distronix, a start-up in the Industrial Internet of Things that could see steady revenue within 3 years of its operations. Distronix wanted to reach the next orbit fast. Distronix wanted to change the organizational blueprint with a proper strategy to scale-up. The young entrepreneurs owning Distronix brainstormed with their employees and the industry experts to strategize the next phase of growth. Market reach and coping with the changing demand of customers on Industrial Internet of Things were the two most important aspects of their strategy. After discussing with stakeholders and the mentors, the owners focused on alliances to increase their delivery and market reach capabilities. They could establish strong alliances, even with larger companies, with proper planning and sustained quality delivery. From the inception of Distronix, owners established alliance, but those were ad hoc and not as per the holistic plan, which provided them a better focus and guidance on alliancing. The alliance strategy seems successful from its revenue growth but needs regular review as the technology stack is getting refreshed fast. Regular monitoring of performance is also critical. The case study shows the importance of a well-thought and well-rounded alliance strategy for a start-up to scale-up confidently.

A case study: How did IoT start-up Distronix change its business model to sustain growth in the pay-per-use economy

2021 ◽  
pp. 204388692098158
Author(s):  
Dipankar Chakrabarti ◽  
Rohit Kumar ◽  
Soumya Sarkar ◽  
Arindam Mukherjee
Keyword(s):  
Internet Of Things ◽  
Business Model ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Project Delivery ◽  
Public Cloud ◽  
Industrial Internet Of Things ◽  
Start Up ◽  
Industrial Internet ◽  
Fixed Fee

Industrial Internet of Things emerged as one of the major technologies enabling Industry 4.0 for industries. Multiple start-ups started working in the Industrial Internet of Things field to support this new industrial revolution. Distronix, one such Industrial Internet of Things start-up of India, started operations in 2014, when companies were not even aware of Industrial Internet of Things. Distronix started executing fixed-fee projects for implementation of Industrial Internet of Things. They also started manufacturing sensors to support large customers end-to-end in their Industry 4.0 journey. With the advent of public cloud, companies started demanding pay-per-use model for the solution Distronix provided. This posed a major challenge to Distronix as they had developed technology skills focusing fixed-fee customized project delivery for their clients. The situation demanded that they change their business model from individual project delivery to creation of product sand-box with pre-registered sensors and pre-defined visualization layer to support use cases for Industrial Internet of Things implementation in multiple industry sectors. It forced Rohit Sarkar, the 26 years old entrepreneur and owner of Distronix, to upgrade capabilities of his employees and transform the business model to support pay-per-use economy popularized by public cloud providers. The case discusses the challenges Rohit faced to revamp their business model in such an emerging technology field, like, to develop new skills of the technical people to support such novel initiative, reorienting sales people towards pay as use model, developing new concept of plug and play modular product, devising innovative pricing, better alliance strategy and finding out a super early adopter.

How Can Industrial Internet of Things (IIoT) Improve Enterprise Productivity?

2020 ◽  
pp. 112-133
Author(s):  
Erdinç Koç
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Detailed Knowledge ◽  
Healthcare Industry ◽  
Industrial Internet Of Things ◽  
Time Consumption ◽  
Industrial Internet ◽  
Smart Cars ◽  
Industrial Part

This chapter gives brief information about internet of things (IoT) and then detailed knowledge of industrial internet of things (IIoT). Internet of things applications can be seen in different areas, such as smart cars, smart homes, smart cities, agriculture, healthcare, industry, etc. This study focuses on the industrial part. Industrial internet of things (IIoT) means internet of things (IoT) applications for industrial usage. IIoT give a chance to enterprise for tracking supply chains, monitoring production line operations, and real-time consumption of energy, managing stock, and transportation decisions. This study used case study method for developing theory about IIoT's contribution to enterprise productivity. IIoT applications can be adapted to which operations of the enterprise, and how it will contribute to enterprise productivity is explained in this chapter. The chapter discusses the projects that are within the vision of IIoT but not yet implemented and concludes with suggestions for future studies.

scholarly journals Industrial Internet of Things Based Efficient and Reliable Data Dissemination Solution for Vehicular Ad Hoc Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Shahid Latif ◽  
Saeed Mahfooz ◽  
Naveed Ahmad ◽  
Bilal Jan ◽  
Haleem Farman ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Data Dissemination ◽  
The Other ◽  
Message Delivery ◽  
Industrial Internet Of Things ◽  
Traffic Conditions ◽  
Industrial Internet ◽  
Transmission Region

Industrial Internet of Things (IIoT) is the other name of industrial Internet. It integrates a variety of existing industrial automation technologies with computing, machine learning, and communication technologies. Vehicular ad hoc network, an application of IIoT, is a self-organized network of vehicles which tends to provide improved road safety, diminished traffic congestion, and ultimate comfort to the travellers. In VANETs, vehicles exchange data with each other directly or through roadside units (RSUs). Data dissemination in VANETs experiences numerous challenging issues including broadcast storm, network partitions, intermittent connectivity between vehicles, and limited bandwidth. In literature, various data dissemination schemes are proposed. However, most of these schemes are designed for either urban or highway VANET scenarios and evaluated under sparse or dense traffic conditions. Moreover, these schemes do not effectively overcome the aforementioned issues simultaneously. In this paper, we present a new data dissemination protocol for VANETs, which disseminates the emergency messages in different scenarios under varying traffic conditions. During dense traffic conditions, DDP4V employs the segmentation of transmission region of a vehicle in order to select the most appropriate next forwarding vehicle (NFV). Accordingly, it divides the transmission region of a vehicle in three distinct segments and selects vehicle(s) inside the highest priority segment to forward the message to all neighbour vehicles, whereas it also uses implicit acknowledgements for guaranteed message delivery during sparse traffic Conditions. Simulation results show that DDP4V protocol outperforms the other existing related protocols in terms of coverage, network overhead, collision, and end-to-end delay.

Mass personalization strategy under Industrial Internet of Things: A case study on furniture production

2021 ◽  
Vol 50 ◽  
pp. 101439
Author(s):  
Jia Ding ◽  
Maolin Wang ◽  
Xiong Zeng ◽  
Wenjie Qu ◽  
Vassilios S. Vassiliadis
Keyword(s):  
Internet Of Things ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Mass Personalization

scholarly journals Key role and potential of Industrial Internet of Things (IIoT) in modern production monitoring applications

2019 ◽  
Vol 252 ◽  
pp. 09003
Author(s):  
Jakub Pizoń ◽  
Grzegorz Kłosowski ◽  
Jerzy Lipski
Keyword(s):  
Internet Of Things ◽  
Production Management ◽  
Industrial Applications ◽  
Production Environment ◽  
Industrial Internet Of Things ◽  
Time Production ◽  
Industrial Internet ◽  
Monitoring Applications ◽  
Production Monitoring

The following paper presents a key role and potential of Industrial Internet of Things (IIoT) in industrial applications as a solution for monitoring and maintaining manufacturing assets. IIoT is particularly important due to progressing computerisation of hardware resources leading to development of a virtualised model of autonomous real-time production management. Adequately article presents case study of IIoT use in production environment – both methodical and analytic approach is presented.

Semantically-enhanced rule-based diagnostics for industrial Internet of Things: The SDRL language and case study for Siemens trains and turbines

2019 ◽  
Vol 56 ◽  
pp. 11-29 ◽  
Author(s):  
Evgeny Kharlamov ◽  
Gulnar Mehdi ◽  
Ognjen Savković ◽  
Guohui Xiao ◽  
Elem Güzel Kalaycı ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Industrial Internet Of Things ◽  
Rule Based ◽  
Industrial Internet ◽  
Semantically Enhanced

Industrial Internet of things at work: a case study analysis in robotic-aided environmental monitoring

2017 ◽  
Vol 7 (5) ◽  
pp. 155-162 ◽  
Author(s):  
Vito Scilimati ◽  
Antonio Petitti ◽  
Pietro Boccadoro ◽  
Roberto Colella ◽  
Donato Di Paola ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Environmental Monitoring ◽  
Study Analysis ◽  
Industrial Internet Of Things ◽  
Case Study Analysis ◽  
Industrial Internet

Order Fulfilment Progress Estimation for Collaborative Manufacturing Enabled by Industrial Internet of Things

2020 ◽  
Author(s):  
Chen Peng ◽  
Zheng Zhang ◽  
Tao Peng ◽  
Renzhong Tang ◽  
Xiaoliang Zhao
Keyword(s):  
Internet Of Things ◽  
Order Fulfillment ◽  
Manufacturing Companies ◽  
Industrial Internet Of Things ◽  
Production Chain ◽  
Collaborative Manufacturing ◽  
Make To Order ◽  
Industrial Internet ◽  
Order Fulfilment

Abstract It has been recognized by manufacturing companies that working collaboratively is the way to advance their competiveness. Order fulfillment estimation addresses the issue of uncertainty from vendors. It is significant for collaborative manufacturing, which enhances companies’ responsiveness to market dynamics. In a data-rich scenario, order fulfillment estimation can be performed based on information extracted from data acquisition devices, such as smart sensors. The analysis result should serve the decisions-making of the production planning, and an indicator should be passed along the production chain even to its end customer for collaborative purpose. In the meanwhile, the manufacturer’s sensitive or confidential information is excluded to avoid risks. This article studies a method to effectively evaluate the order fulfillment process in an Industrial Internet of Things (IIoT) facilitated make-to-order production system. An order fulfilment progress (OFP) indicator is proposed to dynamically represent the fulfillment progress, and its estimation mathematical models are proposed. To improve the practicability of the OFP indicator in production, the influence of abnormal event scenarios are discussed to modify the OFP. A case study presented in this research demonstrates the proposed indicator with consideration of job in process (JIP) is promising comparing to conventional indicators that are represented by the proportion of finished over total products.

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