CASE STUDY - 1
IVA for Power Trade Application
This document will give an insight into a USE case scenario and the operations conducted for one of the biggest power trading and distribution organizations of the public sector.
Key Note/Remark
The organization required a web-based application for monitoring real-time prices of Power trade market.
Pain points
A list of 12 different commodities was provided by the client, which he wanted to have in the customized dashboard. In addition to the prices, he wanted all the latest news about the trends and predictions about the prices.
Solution
A dashboard was created keeping in mind the client’s need, and we provided him with 28 more commodities fetched from live data sources. For predictive analysis, we used our AI-powered tools to forecast market trends. A tab for news ticker was also created for live updates. Continuous R&D in collaboration with stakeholders is being done for further development in the present application.
Result
Enables efficient price discovery and offers participants the opportunity to trade in a variety of energy products. Our platform increases the accessibility and transparency of the power market in India and enhances the speed and efficiency of trade execution.
CASE STUDY - 2
IVA for Airports Recruitment Portal
This document will give an insight of a USE case scenario, covering the operations conducted for one of the biggest Airports of leading Asian countries for the predictive analysis regarding the number of applicants and mitigation as per the Demographic/Geographic imbalance in the organization.
Key Note/Remark
Predictive analysis was done on the Airports data for Demographic/ Geographic imbalances, their root causes and subsequent mitigation steps.
Pain points
The organization was concerned about its Demographic imbalance as people from a few states were willing to apply for the recruitment, while some states’ participation was negligible. Thus, the organisation wanted to balance the number of applicants and ultimately recruitment as per the geographical locations.
Solution
To resolve this issue, the team ingested the data in our unified integrated secure platform having IVA (Instant Visual Analyzer) Module that helped in understanding the reasons for less number of applicants. For example, less or no advertisement in local languages/newspapers, family background and lack of awareness regarding the growth in Airports.
Result
The Platform deduced and predicted patterns along with the reasons for less or no recruitment and started to publish the advertisements in local languages/newspapers and recruitment rallies, thereby increasing the participation by 20 to 30%. However, the way we carried out the project for the Airports, the same technology can be utilized for any of the organizations facing recruitment participation issues based on the demographic/Geographic participation.
CASE STUDY - 3
IVA for Airports Human Resource Management Portal
This document will give an insight of a USE case scenario, covering the operations conducted for one of the biggest Airports of leading Asian countries to carry out the predictive analysis for analyzing the reason behind the shortage of manpower and how to manage the promotion of their officers in the organization.
Key Note/Remark
Predictive analysis was done on the Airports data for professional Health credit data and their planning for future inductions.
Pain points
The organization was concerned about the shortage of skilled manpower and wanted to analyse and understand the reason for the Professional Health Credit report.
Solution
To resolve the issue, the team ingested the data in our unified integrated secure platform having IVA Module which helped the organization to understand the reason behind the problem of high rate of voluntary retirement for a specific sensitive trade/position. Moreover, it proved costly to train the manpower in sensitive areas while it was not the case with other less sensitive “trades” in Air force. The team determined that there was a direct connection with the “outstation/overseas training stay and the rate of application for VRS. It was deuced that 8 out of 10 people applied for VRS, who undertook training for more than 6 months in comparison to 3 out of 10 people who were trained for less than 6 months.
Result
The IVA software predicted the patterns and helped the authorities in understanding the reasons for their pain points. Based on them, the organization changed its training schedule from 3 months to 6 months, and also motivated for more Peace time posting tenure reductions, and the rate of VRS has been cut down to 5 out of 10 which was earlier 8 out of 10.
CASE STUDY - 4
IVA for Railways Locomotives Maintenance Application
In this document, we will give an insight into a USE case scenario and the operations conducted for one of the biggest railways organizations to give out the predictive analyses regarding their equipment and infrastructure.
Key Note/Remark
The predictive analysis was done on Locomotives failure and maintenance needs.
Pain points
The organization was concerned about the performances of their Locomotives as they wanted to predict and analyze the future scope of performance from a particular hardware. They maintained data from the signals of sensors working for those hardware.
Solution
To resolve this issue, we ingested the data in our visual analytical software which helped the stakeholders to visualize and monitor the performance of their equipment through various kinds of charts and graphs. It also helped them generate timely alerts before the actual failure. The visualization software is designed in such a way that it can analyze any kind of data format and provide the results. A specific algorithm was designed considering the factors responsible for the performance of Locomotives. With the help of an algorithm, we were able to provide them with forecast charts and probabilities for future events.
Result
On-time alerts: Now the organization gets the alerts well before complete damage. Ease of operations: A person without any knowledge of a particular mechanical signal value can understand the condition of hardware.
CASE STUDY - 5
IVA for Customer Service & Feedback Portal
This document will give an insight into a USE case scenario, covering the operations conducted for one of the biggest Marine Companies of Asia to give out the predictive analysis regarding its customer experience.
Key Note/Remark
Instant Visualization Analysis was used to get an insight into the huge data of the organization.
Pain points
The organization was concerned about the performances of its client service team as they wanted to minimize the number of negative feedback they were getting for the logistics department services. In order to become more responsive to customer needs, the organization needed a new technology platform and a new approach to develop a new method which would help it deliver digital self-service tools and customer value rapidly.
Solution
To resolve this issue, we ingested on the fly data in our visual analytical software which helped the stakeholders to visualize and monitor the performance of their different teams responsible for their respective grievances from customers. The data analytics and predictive analysis highlighted the gaps between service and delivery processes.
Result
It improved the operational reliability and end customer response time for the organization. Timely alerts from the visualization helped the organization to make changes in their processes which were causing delays.
CASE STUDY - 6
IVA for Accidents & Road Safety Data management Portal
This document gives an insight into a USE case scenario of the operations conducted for one of the biggest Roadways networks for the predictive analyses regarding their incident management.
Key Note/Remark
Predictive analysis was done on the data of the number of road accidents which occurred in the past.
Pain points
The organization was concerned about the increasing number of road accidents; they wanted an analysis of the reasons responsible for these accidents. As by identifying the causes, they can take the corrective measures to resolve the problems. Data maintained by them was segregated in 18 different categories mentioning the number of accidents falling in respective categories.
Solution
To develop a solution for their problem, we ingested the data in our visual analytics software. Applying various methods, we came up with several categorizations possibly responsible for road accidents. The categorization and visualization of data helped the organization to figure out the hidden causes of accidents. We were also able to generate alerts by analysing the vulnerabilities.
Result
The organization was able to categorize the data in 16 new categories. It provided several reports highlighting the areas where they could plan the implementation of the solution and undertake preventive measures.