CLOUD ANALYTICS SERVICES

There is valuable insight hidden in the volumes of structured and unstructured data produced by most organizations. When analyzed and presented clearly and visually, this data translated into information has the potential to:

  • Improve performance management
  • Identify opportunities
  • Achieve data-driven decision-making
  • Understand where current needs exist
  • Achieve an evidence-based policy-making standard
  • Identify ground-breaking discoveries from data visualization
  • Nurture an atmosphere of inquiry and investigation

Every organization today generates a huge amount of data. The different departments must harness this data and tap into its power for deeper insights. 

As a result, Business Intelligence, as a concept and as a tool, is in high demand by private sector firms as well as by government agencies seeking to gather insights and formulate strategies to achieve their goals and objectives.

Companies are driving better results with modern analytics by:

  • Utilizing data visualizations with metrics to measure programs and policies and make informed decisions
  • Collaborating across departments and reducing information silos
  • Sharing insights to promote transparency and accountability
  • Processing large volumes of data and using latest in-memory analysis technology to load and analyze data in short time frames
As the ability to access, analyze, and use data becomes easier, organizations are taking advantage of business intelligence analytics to facilitate the various tasks.

USE CASES:

24

USE CASE: IMPROVING HEALTHCARE OPERATIONS THROUGH ANALYTICS USING COGNOS ANALYTICS

Problem

Our client is a healthcare provider on the East Coast that needed help in improving their operations. This included factors such as wait-time in emergency, response time to patient calls, and other factors.

Solution

In order to improve healthcare operations, the task involved would include data collection, analysis of the data, finding out process gaps through analysis of the collected data, and finally improving the system based on the identified gaps. We felt that IBM Cognos Analytics would be the best solution to tackle the problem. We started the process by spending time in the facility and collecting data from the ground. We collected several types of data including response time to patient calls, wait time in the emergency rooms, accompanying factors during each individual waiting scenario, etc. Based on the collected data, we used the BI tool to analyze and visualize the data in forms that would help us and our clients understand gaps in the situation. We identified several areas that needed improvement. We also came up with ways to anticipate high footfall and demand based on surrounding conditions. This helped predict situations when our clients would need more manpower because of high volume. Operational improvement being a continuous process, it was important that our clients become experts with the adopted BI tool. We ensured that proper training was provided. We oversaw our client employees use the tool in the best possible manner, and only when the handover was successful, we marked the project as completed.

Outcome

The major benefits of this project were:

  • Rapid availability of relevant information
  • 15% Reduction in response time to patient calls
  • 35% Reduction in wait-time in emergency
  • Easy dissemination of best practices and relevant lessons
  • Multiple levels of access based on position and requirement
  • Online record and visual representation of all relevant information
  • Hassle-free experience for patients, doctors, and facility personnel
3

USE CASE: INCREASING SALES THROUGH CUSTOMIZED APPROACH USING INCORTA

Problem

Our client is an internet service provider who were facing challenges from their competitors. Business Intelligence plays a key role in ensuring that a sales lead converts to a closed deal. This comes from understanding the potential customer’s preferences from past transaction data in order to customize the sales for the particular customer in question. Another equally important factor is identifying which sales leads should be pursued by making intelligent selection of sales leads with the highest potential.

Solution

Pursuit studied the nature of the problem, and identified Incorta as the tool to be used to reach a solution. We used our data-analysis experience to analyze each sales lead in terms of multiple aspects and properties. We inspected several areas for both successful and unsuccessful past sales leads. Some of the areas that we investigated are:

  • Time spent on lead
  • Money spent on pursuing lead
  • Demographic information
  • Socio-economic aspects of the lead
  • Customer satisfaction
  • Correlation with other businesses
These exercises helped us in making sure that the sales leads could be separated into pools of highly possible, moderately possible, and highly improbable leads. Moreover, each sales action was then being customized for higher probability of conversion and better follow-ups.

Outcome

The exercise of data analysis increased the possibility of sales by a large margin. Some of the benefits were:

  • Identification of leads with maximum chances of conversion
  • Not following-up on leads that had very low history of conversion
  • Pinpointing specific issues that are highly relevant to the sale
  • Customizing sales procedures for each lead
  • Ensuring targeted follow-ups
  • Identifying leads with the possibility of repeat business
  • Overall sales increased by 35%