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Data Analytics Assignment: Issues Relating To Business Process Analysis

Task: Data Analytics Assignment Task 01: Business Process Re-engineering (BPR) for safety and operational excellence Michael Hammer and James Champy (1993), define business process reengineering as “the fundamental rethinking and radical redesign of business processes to bring about dramatic improvements in critical, contemporary measures of performance, such as cost, quality, service, and speed.” In the wake of the COVID-19 crisis many businesses and public institutions around the globe were forced to rethink of their operational processes, not least for the concern of safety for their customers and employees but also for adjusting and even improving on other important operational performance measures such as scalability, speed, costs etc to cope with and excel in the new reality. In this backdrop, you are expected to facilitate a significant BPR effort at your workplace (or *any other suitably large enough public/private institution) to re-engineer its existing operational process(es). Assume the organization is not just for striving for coping up with the present (or future) pandemic situation(s) but also aimed at excelling during and post-pandemic times. 1.a) Map the organizations present (or pre-reengineered) operational processes with the aid of a high-level Use Case Diagram/ Top Level DFD in order to provide an overview model of organization’s key operational processes in context. Also provide a very brief description of each process and discuss their alignment to organization’s mission & strategy, identify any lapses and/or opportunities for improvement. 1.b) Choose one process with sufficient scope that could greatly benefit from or warrants a BPR (Business Process Reengineering) intervention. Provide justification for the basis of selection. 1.c) Prepare separate stakeholder management plans for Sponsor and one another High Power /High Interest (either or both) stakeholder of this BPR project 1.d) Conduct elicitation on the selected process and Produce the ‘as-is model’ and the ‘process description’ of the existing (prior to reengineering) process Produce the ‘to-be model’ and the ‘process description’ for the (proposed) reengineered process Discuss both processes clearly highlighting process lapses, measured limitations and opportunities for significant improvement and innovation with expected benefits. 1.e) Produce a detail specification for the reengineered process that covers process values, KPIs, symptoms of noncompliance, methods of improvement and any other important details and underlying assumptions. Sri Lanka Railways (SLR): Business Process Reengineering (BPR) and Change Management Prior to the COVI-19 outbreak Government of Sri Lanka with the financial assistance of Asian Development Bank (ADB) had envisioned a program to modernize Sri Lanka Railways (SLR). The program would consist of a series of high impact subprojects to modernize the railways by improving the operational efficiency, maintenance capacity, safety, skills development, and implementation capacity of SLR. As with the current SLR operations, automation is very limited, and most planning, operating, and recording activities are carried out manually. For Example; SLR Ticket Issuance: Paper tickets are printed at SLR headquarters, and typesetters must manually arrange the letterpress blocks for the 60,000 ticket combinations frequently requested. Physical tickets are then sent by train to each station. Once purchased by passengers, daily ticket sales are then manually logged (handwritten) by ticket type and destination at each station, and revenues and records are sent by train back to the headquarters. Revenues are then coded in a database, and summary reports are generated on a monthly basis. The overall process requires a very significant workforce for printing, dispatching, writing, and coding, and is therefore prone to error. (adopted from ADB Technical Assistance Report (July 2019): Project Number 49111-005) Having faced up to a pandemic situation, assume the GOSL want to expedite the task of reengineering the whole ticket issuing process with the objectives of improving passenger and staff safety while achieving significant gains in other applicable operational performance measures. Assuming you are requested to provide consultancy to the SLR on a viable reengineered operational model for the whole Ticket issuing process, answer tasks 1.f and 1.g. 1.f) Produce a schematic diagram [i.e. Swimlane diagram or DFD] of the “reengineered operational model” for SLR ticket issuance. Discuss and compare the new operational model with the present operations, in terms of its strengths, technical implementation aspects, operational feasibility, and cost implications with respect to main stakeholders such as SLR, Staff and Passengers. Clearly state any assumptions made. 1.g) BPR projects often bring along significant change to the current status quo of how things are being done. In spite of the urgency created by the pandemic situation the envisioned change at SLR still need to be carefully planned out and executed for it to be a complete success. With the aid of suitable change management models/ techniques propose how the transition from the current system of ticket issuance to the new approach could be implemented successfully by the SLR. Task 02: Numeric prediction with linear regression Given is a sample data set (medExpense.csv) which contains 1,340 examples of beneficiaries currently enrolled to a health insurance plan, with features indicating characteristics of the insured individual as well as the total medical expenses charged to the plan for the calendar year. Preform the following tasks and provide evidence through well commented code snippets, results/output, and visualizations accompanied with your interpretation/discussion as appropriate in the assignment report itself 2.a Load the medExpense.csv file in to R (RStudio) and explore the given data set. 2.b Check for the existence of any relationships among features. 2.c *Partition the given dataset as 75% for Training data and 25% for Test data, make sure you set the seed value to 123. 2.d Build a model (multiple linear regression) to predict medical expenses with all other features and train it on the Training data. Evaluate model performance on Training data. 2.e Modify and improve you model further for optimal performance, clearly state any assumptions or steps taken in this regard. re-evaluate your optimal model against the Training data. 2.f Use the optimal model to predict medical expenses on the Test data, plot predicted versus actual expenses and report the correlation between them. 2.g Suppose you are required to suggest alterative machine learning algorithms for the same problem, recommend any two suitable algorithms, provide appropriate justification for their selection. Task 03: Emerging trends From a ‘Business Analyst’ perspective discuss the following concepts Process Mining Intelligent Process Automation Sentiment Analysis Your discussion should provide a definition of the concept, its potential business application area(s), benefits and any limitations/risks with suitable real-world implementation examples.


Subject Name: Information Technology

Level: Postgraduate


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