BIDM Case Executive Summary

The ability to compete on analytics is made possible by certain qualities some companies possess which allows them to collect and use immense amounts of data in a way that differentiates the success and practices of those companies amongst any other businesses. Davenport and Harris (2007) define analytics as “extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions” (p. 7). Therefore, to be able to compete on analytics, a firm must not only use the data to extrapolate and execute strategies and models in order to drive business, but also to use that data better and smarter than their competitors. This requires forward thinking and continual developments of current analyses and practices. With regard to Davenport and Harris’s criteria and concepts on the ability to compete on analytics, Old Navy LLC’s practices will be analyzed to find whether the company is able to compete, is a competitor, and how it competes, if at all.

Accenture Analytics believes that refining the metrics used to measure analytic impact typically will yield an invaluable prize—greater and more credible clarity around ROI. Companies need to focus on getting the data that is relevant to business decisions and to business strategy, including big-data gathering in areas such as geometrics, telemetries and other unstructured data. Once businesses start using analytics for strategic decision making, they are more likely to get a better read on ROI.

When considering the IT management portfolio triangle consisting of infrastructural, transactional, informational, and strategic systems in regards to the Nicholas Carr’s viewpoint on information technology, I do not believe that his thoughts apply equally to all types of IT investments. Consider most Transactional System IT investments undertaken today. These systems are designed to help streamline and standardize the collection, modification, and retrieval of transactional data within a business. These systems typically perform well, and maintain consistency and reliability. When observing only transactional systems, I would agree with Nicholas Carr and say that this type of IT investment

Sumangla Rathore, Avinash Panwar, Prakriti Soral (2014). Critical Factors for Successful Implementation of Business Analytics: Exploratory Findings from Select Cases. International Journal of Business Analytics and Intelligence, 2(2), 14-15.

As a large, multi-national financial institution, BAC / ML is at the forefront of the analytical revolution. In an interview with PriceWaterhouseCoopers (PWC) , Brian Moynihan discusses how technology can improve operational efficiency. This is a point that Davenport & Harris make in “Competing on Analytics” - that in today’s market, efficient and effective execution are one of the strategies that can pay off in separating a company from its competition. Mr. Moynihan further speaks to how big data analysis is one of the tools that can provide the intelligence needed to achieve some of their strategic goals. As one of the world’s largest banks, BAC/ML certainly has the funds and resources to bring this intelligence to bear - provided that

I was working as an intern at a company called Project Management Institute (PMI) for six months and have learned some useful and interesting knowledge about analytics. Taking this class and doing this assignment help me understand more about how productive and effective PMI is to compete on analytics. PMI is the world’s largest not-for-profit membership association for the project management profession. PMI’s worldwide support for project management is supported by globally recognized standards and certification program, extensive academic and marker research programs, chapters and communities of practice, and professional development opportunities.

In the "Business Intelligence Software at SYSCO" case, SYSCO plans to use the BI software supplied by Business Objects to improve the ability of manage and analyze the data of whole company including all the operating companies. With the advanced way of data analysis, it’s easier for

The Business Intelligence dashboard is a streamlined, easily accessible, and more accurate and significant reporting process. It presents the ability to gauge performance, understand the impact of

Two related articles (Baller & Alan 2009, Galit & Otto 2010) demonstrate that “Business Analytics (BA) refers to the skills, technologies, practices

Stage 2 - These organizations have implemented localized analytic solutions with some data elements and reporting, but they lack the big picture view of implementing enterprise-wide analytics activities. There are department specific silos of data and reports to meet functional needs.

To help sifting through and combining the right data in the right ways, businesses must develop analytical capabilities that far surpass today’s standards. The sheer volume of data impressive, that same volume can lead to confusion, or plain bad direction for decision makers. A great rule to live by in analytics is that “numbers tell THE story, ANY story can be told by the numbers.” What this means is that managers must be certain that they are using the right data set, and designing their analysis to provide an output that solves the business problem they are trying to solve, rather than just providing the answer they are hoping to provide. This is done through the deployment of analysis tools, those that are becoming more and more prevalent, and easier to use, along with building or hiring the capability into the organization. The skills needed for this work include, but are not limited to, a deep understanding of the business, and ability to communicate complex concepts in a way that is easily understood, and a mastery of statistical and analytical methods. While the first two capabilities ensure that the right data is used, and it is analyzed to yield a sound outcome, the final capabilities is often the most important, and biggest stumbling block for organizations.

Business intelligence (BI) and business analytics (BA) (sometimes used interchangeably) has revolutionized the way businesses use data and can be contrasted, for the purpose of this essay, in the following way: BI is raw data that has been transformed into meaningful information that provides historical, current, and predictive views of business operations and environment, and BA uses data and statistical methods to provide actionable information for decision makers. BI explains what is happening, identifies the issue, and provides decisions to be made and BA explains why an issue is occurring, what will occur, and what actions need to be taken. At the forefront of BI/BA technology is International Business Machines (IBM) with a very broad array of related products and services. Among the more popular products are its flagship analytics product IBM Cognos and its Predictive Customer Analytics. IBM’s Cognos Analytics allows business and IT professionals to prepare and distribute all types of business reports from all departments with an organization and access pertinent information such as financial reports, sales trends, production yields, and inventory on any device on an hourly basis. IBM also offers a Predictive Customer Intelligence solution, an integrated software which uses automation to acquire customer information such as buying behavior, web activity, and social media presence to model and “score” costumer behavior and provide customized actions so that a business

However, turning over the data analytics keys to business users is not necessarily a “turn-key” event. It will require a philosophical buy-in on the part of those users. Specifically, they will have to adopt a true do-it-yourself philosophy.

The survey may contain several questions as follows: “How much do you think the company is an analytics-oriented company”,

Business Analytics refers to the skills, advancements practices for continuous iterative investigation and examination of past business execution to pick up knowledge and drive business planning. Business analytics concentrates on growing new bits of knowledge and comprehension of business execution taking into account data and statistical methods. Conversely, business intelligence generally concentrates on utilizing a predictable arrangement of measurements to both measure past execution and guide business planning, which is also based on data and statistical methods