Welcome Back!!! In part 1 we saw an example of analytics being used on a mobile platform - tablet - to realize the retail store objectives and gain advantage of real time data updates. In part 2 let us take a look at more case studies across similar leading products...
Case Study 2:
Scenario - The client is a US based fortune 500 energy and utilities company with approximately 10 million customers. Their integrated business model provides a strong foundation for success in this vertical which is experiencing dramatic changes. They strongly believe in capitalizing on emerging trends and technologies to provide insight into operations that will drive value for their end customers
Background - The organization uses Oracle - one of the top ERP applications for their myriad business processes. As part of this PoC the Infosys team setup custom analytics solutions for the client. Oracle's business tool OBIEE 12c is used here to showcase the length and breadth of the analytics tool available as part of the wide array of modules in Oracle.
Problem Statement - The client needed to do a comparative evaluation between two mobile analytics applications as part of their PoC to be reviewed by their senior management.
POC details - The PoC was aimed at the OBIEE module's ability to work on a mobile platform. The PoC also aimed to do a comparative demo of features between Microstrategy (another analytics tool) and Oracle tools (apps). A set of commonly identified features was expected to be compared and in most cases, the feature was available within these tools but the enablement of the feature was different between OBIEE and Microstrategy.
Pilot & Feedback - For the pilot, the app was shared only among the senior management in the organization. The focus group was impressed to see that OBIEE could provide the features needed and appreciated the way it is achieved in OBIEE, which was different from their current applications. Further using OBIEE on mobile presented a very unique but scalable scenario as it proved to be a seamless extension to the existing suite of oracle products and which meant lesser chance of data integrity issues. Post the successful demo, client is now evaluating an option of a complete migration to OBIEE with preference to the analytics app as it aligns successfully with their established principles.
Being an energy and utilities company, it is always essential for the organization to possess the latest status and forecasts in a rapidly changing environment with unpredictable trends. With the analytics tool on mobile, it has brought the leadership very close to data and trends that were hitherto not feasible. Management can now make an informed decision much faster and just as easily track the results through OBIEE. Also, the time and effort saving is huge since it allows the stakeholders to pull their own graphs and data analysis, first hand and without chances of error. As the gap between technology, user and data/solution is greatly reduced leadership is also now very keen on applying this model to other areas of analytics.
Case Study 3:
Scenario - The client is a global tool manufacturing corporation with interests in construction, heavy equipment and technological solutions. They excel through outstanding innovation, top quality, direct customer relations and effective marketing. Client also has their own production plants as well as research and development centers in Europe and Asia. They pride in integrating the interests of all their partners, customers, suppliers and employees - into their growth and sustenance strategies.
Background - The client uses SAP package and tools for running their analytics platform integrating the various aspects of their business from planning to customer feedback & support. Combining areas like technology, design, real time feedback and automated order processing and metrics like quantity, geographical location, customer database, the analytics tool (SAP's BI system), provides the necessary inputs to the stakeholders to catchup on the latest available information/trend.
Problem Statement - The client needs an on-the-go platform to deploy their analytics solution to enable salesforce and service personnel to meet client demands as and when they arise in an automated fashion.
Introduction of Mobile Analytics - The organization has about two-thirds of its workforce employed directly for their customers in sales organizations and in engineering. They average about 200,000 customer contacts every day. This entails a constant need to be up to speed with the latest and greatest as regards the end customer data (or detail). A ready reckoner for this situation is the SAP mobile analytics (ROAMBI as it is known otherwise), that most employees in the organization use on a daily basis. Further, the entire solution is a cloud based model, so they have the best of both cases - cloud computing and mobile application. This has proved to be very advantageous to their on the job salesmen, technicians, customer support or even the top executives discussing an org-level strategy.
A critical time bound customer order is not received at site on time.
However, the automated tracking tool, looking for the delivery report, has sensed it and raised an alert to the support center of the tools manufacturer.
This triggers the next set of established workflows in order to compensate for the delay in delivery.
Alerts sent to the nearest customer support personnel through a geo fencing feature enables the employee to locate the nearest outlet/warehouse/distribution center for the right part.
The support person raises a request under the right priority and is able to head over to the site to personally supervise the final delivery
All this has actually taken place on-the-go using the mobile device loaded with the BI tools and supporting applications to augment the corrective actions.
In this particular scenario, even the customer delight can be captured on the same mobile as feedback and, back at the corporate HQ, the top management will be able to gauge a real time heat map/graph showing customer satisfaction survey results that have been processed seamlessly through cloud.
End of part 2... in part 3 we will review the inferences and conclusion.
Part1 : http://www.infosysblogs.com/oracle/2017/09/analytics_and_the_app_1.html
Part3 : http://www.infosysblogs.com/oracle/2017/10/analytics_and_the_app_3.html