LO1 Appraise scholarship and demonstrate a comprehensive understanding of the roles and the impact of different types of information systems that support the decision making process within businesses

Module Code:

BMD0003

Module Title:

Intelligent Business Information Systems

Assessment Type

Individual Report

Academic Year

2022/23

Assessment Task

 Part A Discussion Question

Discuss some of the trade-offs and the challenges of a move to an enterprise-level analytics solution for companies and their individual end users who might have grown accustomed to working with their own customised solutions for generating data.

Back your discussion with i) critical review of relevant literature, ii) the case of Nationwide Insurance (Support Case presented in the next section of this assessment brief).

(1,500 words), (60 marks)

Part B Discussion Question

Discuss the typical architecture of the master data and its components in SAP ERP and explain its importance in Sales and Distribution (S&D) module. Back your discussion with relevant literature available on SAP ERP.

1. Explain the Material Master specification in SAP ERP and discuss why it is one of the most complex types of data in SAP ERP system? (20 marks)

1. Discuss how SAP 4/HANNA is different from previous versions of SAP? Explain SAP 4/HANNA capabilities and its features, especially regarding SAP ERP. (20 marks)

(1,000 words), (40 marks)

Part A Support Case:

Nationwide Insurance Use of BI to Enhance Customer Service

Nationwide Mutual Insurance Company, one of the largest insurance and financial services companies in the United States, with $23 billion in revenues and more than $160 billion in statutory assets. It offers a comprehensive range of products through its family

of 100-plus companies with insurance products for auto, motorcycle, boat, life,

homeowners, and farms. It also offers financial products and services including annuities, mortgages, mutual funds, pensions, and investment management.

Nationwide strives to achieve greater efficiency in all operations by managing its expenses along with its ability to grow its revenue. It recognises the use of its strategic asset of information combined with analytics to outpace competitors in strategic and operational decision making even in complex and unpredictable environments.

Historically, Nationwide’s business units worked independently and with a lot of autonomy. This led to duplication of efforts, widely dissimilar data processing environments, and extreme data redundancy, resulting in higher expenses. The situation got complicated when the company pursued any mergers and acquisitions.

Nationwide, using enterprise data warehouse technology from Teradata, set out to create, from the ground up, a single authoritative environment for clean, consistent, and complete data that can be effectively used for best-practice analytics to make strategic and tactical business decision in the areas of customer growth, retention, product profitability, cost containment, and productivity improvement. The company transformed its siloed business units, which were supported by stove-pipped data environments, into integrated units by using cutting-edge analytics that work with clear consolidated data from all of its business units. The Teradata data warehouse at the insurance company has grown from 400 gigabytes to more than 100 terabytes and supports 85% of the company’s business with more than 2,500 users.

Integrated Customer Knowledge

Nationwide’s Customer Knowledge Store (CKS) initiative developed a customer-centric database that integrated customer, product, and externally acquired data from more than 48 sources into a single customer data mart to deliver a holistic view of customers. This data mart was coupled with Teradata’s customer relationship management application to create and manage effective customer marketing campaigns that use behavioural analysis of customer interactions to drive customer management actions (CMAs) for target segments. The insurance company added more sophisticated customer analytics that looked at customer portfolios and the effectiveness of various marketing campaigns. This data analysis helped the company to initiate proactive customer communications around customer lifetime events like marriage, birth of child, or home purchase and had significant impact on improving customer satisfaction. Also, by integrating customer contact history, product ownership, and payment information, the company’s behavioural analytics teams further created prioritised models that could identify which specific customer interaction was important for a customer at any given time. This resulted in one percentage point improvement in customer retention rates and significant improvement in customer enthusiasm scores. Nationwide also achieved 3% annual growth un incremental sales by using CKS. There are other uses of the customer database. In one of the initiatives, by integrating customer telephone data from multiple systems into CKS, the relationship managers at the company try to be proactive in contacting

customers in advance of possible weather catastrophe, such as a hurricane of flood, to

provide the primary policyholder information and explain the claims processes. These and other analytic insights now drive the insurance company to provide extremely personal customer care.

Financial Operations

A similar performance payoff from integrated information was also noted in financial operations. Nationwide’s decentralised management style resulted in a fragmented financial reporting environment that included more than 14 general ledgers, 20 charts of accounts, 17 separate data repositories, 12 different reporting tools, and hundreds of thousands of spreadsheets. There was no common central view of the business, which resulted in labour-intensive slow and inaccurate reporting.

About 75% of the effort was spent on acquiring, cleaning, and consolidating and validating the data, and very little time was spent on meaningful analysis of data.

The Financial Performance Management initiative implemented a new operating approach that worked on a single data and technology architecture with a common set of systems standardising the process of reporting. It enabled Nationwide to operate analytical centres of excellence with world-class planning, capital management, risk assessment, and other decision support capabilities that delivered timely, accurate, and efficient accounting, reporting, and analytical services.

The data from more than 200 operational systems was sent to the enterprise-wide data warehouse and then distributed to various applications and analytics. This resulted in a 50% improvement in the monthly closing process with closing intervals reduced from 14 days to 7 days.

Post-merger Data Integration

Nationwide’s Goal State Rate Management initiative enabled the company to merge Allied Insurance’s automobile policy system into its existing system. Both Nationwide an Allied source systems were custom-built applications that did not share any common values or processes data in the same manner. Nationwide’s IT department decided to bring all the data from source systems into a centralised data warehouse, organised in an integrated fashion that resulted in standard dimensional reporting and helped Nationwide in performing what-if analyses. The data analysis team could identify previously unknown potential differences in the data environment where premiums rates were calculated differently between Nationwide and Allied sides. Correcting all of those benefited Nationwide’s policyholders because they were safeguarded from experiencing wide premium rate swings.

Enhanced Reporting

Nationwide’s legacy reporting system, which catered to the needs of property and casualty business units, took weeks to compile and deliver the needed reports to the agents. Nationwide determined that it needed better access to sales and policy information to reach its sales targets. It chose a single data warehouse approach and, after

careful assessment of the needs of sales management and individual agents, selected a

business intelligence platform that would integrate dynamic enterprise dashboard into its reporting systems, making it easy for the agents and associates to view policy information at a glance. The new reporting system, dubbed Revenue Connection, also enabled users to analyse the information with lots of interactive and drill-down-to-detail capabilities at various levels that eliminated the need to generate custom ad hoc reports. Revenue Connection virtually eliminated results for manual policy audits, resulting in huge savings in time and money for the business and technology teams. The reports were produced in 4 to 45 seconds, rather than days or weeks, and productivity in some units improved by 20% to 30%.

Task specific guidance:

- Your answers should be well referenced, following the instruction provided in the next section of this assessment brief.

- Make sure your answer to each part is well highlighted and separated.

- You are advised to devise a table of content.

- Abstract, or executive summary is not necessary.

Part A

You are expected to:

- Review and address relevant literature on the adoption of enterprise-level analytics solution, highlight their advantages, disadvantages, and implementation challenges,

- Refer to the case study provided to form an argument and make a point,

- Consider reviewing few solutions in more detail, conducting comparative analysis, or case analysis to strengthen your argument.

Part B

To answer both questions and to form your argument and make your point:

1. Consider explaining and highlighting the general architecture/structure of master data in SAP ERP, the specific architecture/structure of data in Sales and Distribution module in SAP ERP, the functions of master data in S&D module.
2. Compare SAP S/4 HANA, highlight its capabilities and compare them with those of previous version of SAP, specifically with regards to SAP ERP.

General study guidance:

Cite all information used in your work which is clearly from a source. Try to ensure that all sources in your reference list are seen as citations in your work, and all names cited in the work appear in your reference list.

• Reference and cite your work in accordance with the APA 7th system – the University’s chosen referencing style. For specific advice, you can talk

to your Business librarians or go to the library help desk, or you can access library guidance via the following link:

• APA 7th referencing: https://library.hud.ac.uk/pages/apareferencing/

 The University has regulations relating to academic misconduct, including plagiarism. The Learning Innovation and Development Centre can advise and help you with how to avoid ‘poor scholarship’ and potential academic misconduct. You can contact them at busstudenthub@hud.ac.uk.

• If you have any concerns about your writing, referencing, research or presentation skills, you are welcome to consult the Learning Innovation Development Centre team busstudenthub@hud.ac.uk. It is possible to arrange 1:1 consultation with a LIDC tutor once you have planned or written a section of your work, so that they can advise you on areas to develop.
• Do not exceed the word / time / other limit.

Assessment criteria

• The Assessment Criteria are shown the end of this document. Your tutor will discuss how your work will be assessed/marked and will explain how the assessment criteria apply to this piece of work. These criteria have been designed for your level of study.
• These criteria will be used to mark your work and will be used to support the electronic feedback you receive on your marked assignment. Before submission, check that you have tried to meet the requirements of

the higher-grade bands to the best of your ability. Please note that the marking process involves academic judgement and interpretation within the marking criteria.

• The Learning Innovation Development Centre can help you to understand and use the assessment criteria. To book an appointment, either visit them on The Street in the Charles Sikes Building or email them on busstudenthub@hud.ac.uk

Learning Outcomes

This section is for information only.

The assessment task outlined above has been designed to address specific validated learning outcomes for this module. It is useful to keep in mind that these are the things you need to show in this piece of work. 

On completion of this module, students will need to demonstrate:

1. Appraise scholarship and demonstrate a comprehensive understanding of the roles and the impact of different types of information systems that support the decision making process within businesses
2. Demonstrate a critical understanding of relevant theories and techniques of intelligent business information systems to analyse contemporary issues and devise solutions

1. Critically analyse issues in relation to business information systems and the role of intelligence in these systems
2. Critically evaluate and demonstrate the role of ERP systems in businesses

Please note these learning outcomes are not additional questions.

Submission information

Word Limit:

2,500

Submission Date:

26/05/2023

Feedback Date:

19/06/2023

Submission Time:

15.00

Submission Method:

Electronically via module site in Brightspace. Paper/hard copy submissions are not required. For technical support, please contact: busvle@hud.ac.uk