Predictive Analytics: the Future of Business Intelligence

MasterCard Incorporated is one of the world’s premier credit card processing and money transfer companies in the world. It is the second major payment company in the United States. They focus on making payment transactions safer and beneficial to the society while delivering value through their innovation and execution. MasterCard has three main competitors, Visa at the very top, American Express, and Discover. Visa Inc. has the largest market share of 13.7 percent in the United States with revenue of $12,702 million in 2014. In the same financial year, MasterCard Inc. has recorded total revenue of only $9,473 million and 7.3 percent of total market shares. MasterCard’s SWOT analysis revealed its strength of being the world’s second

Forecasting analytics will enable SYSCO to make appropriate upfront decisions and monitor customers as well as the industry. Extraction and data mining are also useful tools that will positively affect SYSCO’s decision-making process. Lastly, consulting support and employees’ training will facilitate the implementation of the new software in the company. For all these reasons, the use of BI at SYSCO can create a competitive advantage of the company in the industry. However, this competitive advantage depends on the competition – do the competitors use a similar software or by chance the same and do they already have a strong position in the market? Outperforming for example “U.S Food Service”, SYSCO’s main competitor, might be arduous if that company relies on a similar software and already has an eminent role in the

This report is an analysis of business intelligence systems currently available to our business. As an introduction, I will address in general terms why we need to purchase a business intelligence system and how it will aid our business. Then I will discuss several applications in detail, paying particular attention to the information and analysis capabilities of each, and the hardware and software required for each. Finally, I will conclude with a short evaluation of the products discussed and offer a recommendation as to the best application for our business. I will pay particular attention to IBM, Microsoft, SAP, and Oracle.

As we discuss the possibility of emerging into business intelligence software we must keep in mind the overall purpose of using any type of software is to reach strategic goals in order to increase market shares. I will discuss how business intelligence software will allow us to meet those strategic goals. We will establish what type of information and analysis capabilities will be available once this business intelligence software is implemented. We will discuss hardware and system software that will be required to run specific business intelligence software. Lastly, I will give a brief synopsis on three vendors (IBM, Microsoft Microsoft and Oracle) that are dominating the business information software industry today.

We cannot all help but notice the steady decline in our market share for the past consecutive 11 quarters. Annual revenue has shrunk by 40% since we last saw a sales growth. Despite all the cost cutting measures that we have implemented we still continue to see a steep decline in sales. To make matters worse we do not know why, we do not know how and do not have any insight on what the competition is doing and how they are doing it. I’m proposing that we adopt a business intelligence system. This will allow us to see the state of our overall processes, and pinpoint areas of improvement or elimination. In short, business intelligence will allow us to better analyze the organization’s plans and results. I will provide us with insight into what is working correctly at the same time identifying potential problem areas

How much will organizations spend on business intelligence (BI) in 2016? According to Gartner, organizations are projected to spend almost $16.9 billion in 2016. That is an increase of 5.2% over 2015 sales . Business Intelligence plays a big role in today’s business, it now used in every part of the organization from supply chain to human resources (www.gartner.com). This paper will compare two business intelligence software tools. First, I will define business intelligence (BI). Then, I will examine the features of each of the BI tools. Next, I will discuss the pros and cons of each software. This paper will focus on the capabilities and costs for each BI software. Lastly, this paper will indicates which choice was made and an explanation of that choice.

Secondly, predictive analytics not only use statistical algorithms and forecasts on historical data but also anticipate likely situations to plan ahead. The means of these predictive models differs depending on their behaviour and future events but the aim is to go beyond reporting what has happened in providing the best assessment of what will happen. Data mining is an important component that tends to identify trends, patterns and relationship. They largely depend on statistical models and multivariate analysis techniques. Thereby decision making can be streamlined and new insights can be revealed leading to better decision making. Organisations are adapting to predictive analytics for competitive advantage. They are used in identifying trends, understanding customers, enhance business performance, predict behaviour and drive decision making. (SAS and Nyce)

The advantages of credit cards have revolutionized the way society pays for bills, goods and services. Credit cards allow individuals to receive goods and services today in exchange for the “promise of future payment” (Rommann). Credit cards are extremely quick and convenient, sometimes

There is a lot of hype recently around big data and its potential. When leveraged correctly big data can provide many great benefits for organizations in almost any industry. Some organizations currently have a lot of big data they have gathered throughout their life but have no current way of leveraging this data. One of the ways companies are able to leverage all of their big data is through predictive analytics.

SmartCard LLC is a company that possesses expertise smart cards as well as magnetic strip technology. SmartCard LLC intends to develop applications and solutions to address the rapidly growing demand for marketing frequency or loyalty programs. SmartCard LLC asserts that as competition increases in the retail sector and other industries that companies will be searching for new ways to understand their customers and techniques to retain their customers. SmartCard LLC’s smart card solutions are a proposed solution to this market problem. The SmartCard LLC strategy is focused on using smart cards for their clients’ frequency or customer loyalty programs and bringing end

Data is being produced at a huge rate and 90% of the data which exists today were produced in the last two years. Thus, it is difficult to manage big data which are extremely large, structured/ unstructured data sets analyzed to find trends, associations, reports, etc. The biggest challenge today is to find the quickest and the most inexpensive tool to analyze the big data which consists of emails, videos, pdf, audio files, and tweets. Predicting future with being able to access and store real time data is the future of BI and big data analytics (Jamack, 2012). When BI reports are run using the data and queries, information is retrieved and it is called Descriptive Analytics. When the dataset is further analyzed and drawn inferences using statistical methods like correlation or regression then it is called Diagnostic Analysis. Based on this information when the possible outcomes are predicted it is called Predictive Analytics. Finally, Predictive analytics uses previously tested or predicted models which are put into a reiterated process to produce an anticipated outcome. Big data technology combines all of these analytics, along with being fast and efficient in handling real time data (Payandeh, 2013). Business Intelligence consists of different tools to make better informed decisions with the data they have. Traditional BI were focused on the OO of the OODA loop (Observe, Orient, Decide, Act) but the modern BI needs to directly integrate the Decide and Act since there is a

Credit cards became a severely important and reliable method of payment. Not only is it is extremely convenient but building good credit became a necessity. In 2011, credit cards were being used for over 22 billion transactions that consisted on living an average lifestyle valued at a projected 2.1 trillion dollars. Consumer involvements and outlooks toward credit cards, as revealed in user surveys, may be subjective by overall lucrative circumstances, clients who own monetary conditions; the involvements of friends, family members, and colleagues; enclose broad knowledge conveyed by media reports about the credit card market. Customers with a stable occupation and growing salaries, for example, may have

This case study reviews the strategy followed by Union Investment Group (UIG) to analyze customer behavior patterns using predictive analytics (Union Investment GmbH, 2015). With the business objective of boosting profitability and staying ahead of the competition while facing a customer base that demanded individualized product offerings, UIG teamed with IBM to determine the problem at hand. After describing the problem, this case study next considers the stakeholders involved, other expert opinions, recommendations, and caveats.

Chase Cardmember Services (CCS), the credit card-issuing business within financial services conglomerate J.P. Morgan-Chase, found itself at a critical juncture at the dawn of the 21st century. Faced with an array of converging forces, both internal and external, CCS would have to redefine itself if was to survive going forward. The prior fifty years had seen the emergence and growth of the of credit card industry. The concept began as an issuance of a deferred payment plan (a line of credit) by retailers to their favored customers for purchases on those retailers' goods and services--to be tracked on an imprinted card, each with unique information on it (per customer). Banks got hold of this concept, began issuing credit

Predictive analytics is a technology that makes use of the current and existing database to produce a trend and predict future outcomes. In short, it does not tell you what will happen in the future.