The assignment gives students the possibility to demonstrate their ability to evaluate and analyse a business problem. They apply data visualisation and data analytics to provide business intelligence to a fictional company.
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Description
Assignment brief
The rational
The assignment gives students the possibility to
demonstrate their ability to evaluate and analyse a business problem. They
apply data visualisation and data analytics to provide business intelligence to
a fictional company.
The learning outcomes being
assessed
This assessment assesses the
learning outcomes 1 - 3.
Overview of assignment
As a business analyst, you are commissioned to
provide intelligence to the senior management to evaluate the current pattern
of individual and team-level performance. You are asked to analyse the current
performance pattern using business intelligence to provide recommendations for
the company to improve its performance. Moreover, you should propose
performance dashboards calibrated based on historic data to enable the firm to
monitor its future performance.
SUBMISSION DETAILS
You submit two documents the first should comprise the following four elements:
An
executive summary (about one page)
A
non-technical report of 2.000 words (+/- 10%)
A technical appendix summarising your
methodology A performance dashboard (about one page)
The second document is the R code that enables me to
replicate your analysis.
Please also keep in mind:
Electronic copy must be tidy, and not show any
history of track changes. If
you use includes graphics, please ensure these are of a high quality.
The first page (slide) should include the title, all
names, and students’ numbers.
Use the Harvard reference style and provide a
reference list at the end of your slides.
You must
acknowledge your source every time you refer to others’ work, using the Harvard
Referencing system NO PLAGIARISM
DEADLINE
12 Noon, Friday 20th of May 2020.
Please note that this is the final time you can submit – not the time to
submit! Your feedback and mark for this assignment will be provided via return
of the assignment.
ASSESSMENT CRITERIA
1.
Effective summary of key
results in the executive summary and performance dashboards; stating the key
findings/ key recommendations and presenting an easy
|
to grasp visualisation that enables an informed decision
making .............................................. |
(25%) |
2.
Subject knowledge,
application of skills and communication skills in the report (non-technical and
technical): evidence of factual and conceptual understanding of the subject and
evidence of analysis and evaluation, ability to collate, categorise and apply
ideas and information and to develop and sustain a coherent argument; quality
of the recommendations; structure and organisation of the text content,
|
layout
and formatting, use of visuals, command of syntax, language and grammar, |
|
|
in-text
and end-of-text referencing (if applicable) ..................................................................... |
(60%) |
3.
Replicability of the analysis – a programme code
that allows an expert to replicate,
|
understand
and amend the analysis ........................................................................................ |
(15%) |
Description
of the call centre data
The union agreed to release aggregated data that link
the employee (call centre agent) to his or her individual performance. The
performance data including the ID for each agent is the call centre data. It is
available for the last couple of weeks. In addition, you have some personal
information about each agent in the HRM data.
Variable definition in the
call centre data
time
time of the day when the call has been recorded (in hours)
length
duration of the call with the call centre agent (in seconds)
waiting time
duration, the costumer spent waiting to be
connected to an agent (in seconds)
Customer satisfaction
each costumer has been asked to rate their satisfaction with the service
after the call via a 10 point Likert scale on the app, 1 is very unsatisfied
and 10 is very satisfied
Problem description
each caller chooses one of four options before connected to an agent,
the options are technical support, delivery problem, return problem and
complaint
Forwarded
if the call centre agent could not resolve the
problem, the agent could forward the call to an expert (for technical problems
only)
Agent
anonymous number for the call centre agent
Variables in the HRM data
Gender
indicating if male of female employee
Age
age of the respondent at the beginning of the period (in years)
Tenure
number of months working in the call centre
Qualification
three broad categories of education degree
including apprenticeship, some college and university
Ethnicity
four categories describing the employee’s likely ethnic origin including
British, Black, Asian and other
