Essay On Analytics

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.

Data is a forever growing thing and is not looking to slow down anytime soon. With that be said, companies must be able to manage data for their day to day operations as well as for predicting future trend. Now there are many tools for managing data and extremely high cost for managing it as well. One of the costs for managing data is data security, but this paper will touch on that topic in, but not as much as other topics. Also, this paper will demonstrate various business cases to serve as testimonial for just how useful big data management it in to day society.

Competing on analytics is currently one of the most essential qualities for companies looking to gain a larger market share in their given industry. This is due to the fact that the easiest way for corporations to differentiate themselves from their direct competitors is to maximize efficiency through cohesive processes and decision making. Analytics is defined as, “The extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact based management to drive decisions and actions.” (Davenport, 2007, p.7) So in order for companies to compete on analytics they need to be willing to invest in the proper technologies that are able to compile all of this information and data into output that can be used

The analytic capability that is currently supported and trusted by decision makers and analysts are the business intelligence type of analytics with an enterprise reporting tool as illustrated in the figure 2. This technology is very reports and dashboards focused as this is the standard in governments. It does not have full coverage of data and there is no data exploration functionality. It also means that access to some of the data is limited which complexify the integration with other data to find potential emerging issues. However, there are business users that have tools which contain advanced analytics features but they are not formally used as an Enterprise analytics tool, but rather in silos. This can

As Harris and Davenport mention in “Competing on Analytics”, it is extremely necessary for management to support and commit to integrating analytics in order for a company to become an analytical competitor. (Davenport and Harris, 2007) Specific to Impax, there has been a lot of recent change in management and minimal push down to incorporate analytics for better decision making. While we are capable and do utilize a fair degree of analytics in our day to day operations, unfortunately, I find its use tends to be more retroactive in nature than proactive.

Research shows that “49% of companies who champion the use of customer analytics are likely to have profit well above their competitors.” It’s one of the best ways to differentiate your business in the market.

In this highly competitive business environment, businesses are constantly seeking ways to gain traction and understand what is on the minds of current customers and potential customers in order to increase business efficiency. Many companies, such as American Express have turned to business intelligence (BI) and data analytics to maintain a competitive edge over the competition.

The company I am with is beginning to use analytics more and more. We are on step 1 of the five step process, so we still have a lot to learn and set goals on. We have just started using them so that we can compete with the “top dogs” of the bank data processors. I believe that if we didn’t use analytics one of the big competitors would come in and try to buy out the company. We are looking into ways to help use analytics so that we can strengthen our position in the service and show that we can handle any size community bank. We have created a Business Intelligence department to look into ways that we can improve products, forecast what a bank may buy when signing a contract, and to see how to pitch our regulatory compliance products to other companies to help them with their compliance.

Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis.  Business analytics is used by companies committed to data-driven decision making.

Analytics is in the top ten of upcoming technology trends at the moment. Analytics is going to be a game changer for all aspects of modern life and it is something everyone should know about. Nowadays analytics are used for everything, business data, marketing, government even healthcare and sports. There are some basic areas within analytics such us web analytics, business analytics, marketing analytics, behavioural analytics and predictive analytics. Analytics is growing so fast that in the near future is will be hard to think of any aspect of business that will not be affected by analytics. The main customers of analytics are business people, marketers, and sales people and in general all people that need analytical tools in order to improve their businesses profit, success and value.

In the era of 2007-10 where most of the economies of the world slowed down and companies restrained themselves from making new investments there were others that were gearing up to reverse this trend. Viewing this as an opportunity lot of new companies entered into the consulting and business advisory domains. This phenomenon lead to an inception of once such company named “Analytics Quotient”. Analytics is once such field, which is not only making a mark upon the business of the companies but also changing the business trends by focusing on data utilization across functions and optimizing the available information that the company has.

Whereas, Analytics is a subset of BI, a step ahead in the evolution of Business intelligence. It about getting answers to further questions like “Why did it occur”, “When and what will it occur next (in future)”, “What can be the best option to solution”. Analytics contains tools and techniques to detect patterns, predict future occurrences or events and prescribe the most optimal solution. It is about the cleaning, processing and analyzing data to detect problems and optimal solutions from trends, patterns and relationships eventually leading to better data driven decision making.

According to1Gartner (2013) „Business analyticsis comprised of solutions used to build analysis models and simulations to create scenarios, understand realities and predict future states.”

Most of the time analytics software generates value through aggregation, processing, and visualization of data. But the real magic comes from people, and if a new business is just kick-starting the analytics program and have a tight budget then it can probably get more value out of a good analyst over an

Analytics and business intelligence (BI) are not new concepts in the market place, but the exponential growth of offerings, lower total cost of ownership (TCO), and simplified deployment options have made these solutions a necessity for modern businesses. Some customers continue to use a comprehensive stack of a database, extract-transfer-load (ETL) tools, an analytics engine, and a reporting interface from a single vendor, placing much of the burden on IT to keep operations running and produce reports. However, many businesses are finding success with a different model based on smaller-scale deployments of self-service or embedded analytics and data discovery tools directly to end users.