Most people work in an environment where their department has special forms or procedures that affect the operations of another department within the organization. For example a receiving clerk may receive products and fill out the required paperwork they need to pass the billing up to the finance department. Then the finance department would do what they need to do to pass their information along to the next level in the organization.
Well today many businesses are turning to "Enterprise-wide Analytic Technology" to help streamline the processes and steps that an organization goes through when conducting business. Enterprise analytics is quite simply put a way for enterprise sized companies to capture business-critical information and make it visible across the entire organization. Informatica (2001)
In many businesses today the internal operations of the company run in a manner where the internal departments are treated as individual businesses somewhat like that of a silo or tower standing on its own and operating under its own controls and processes. Enterprise analytics is a way for the enterprise to link the separate business towers and make the critical business information available to all. In many cases the information being tracked is related to the transactions taking place. The transaction is the life blood of any company therefore it is critical to make sure that not only is it processed in as timely a manner as possible but that the information relating to the transaction be accurate across the entire organization.
In addition enterprise analytics must allow for the information to be easily viewed and readable to the persons that must make the critical business decisions that can lead to the success or failure of an organization. Enterprise analytics gives executives a way to see what is happening across the organization at any time. This is the kind of real time knowledge that executives need to keep their companies competitive in the work place.
However, in a utopian business the business intelligence tool deployed would provide all the features and meet the needs perfectly. Today's businesses are anything but utopian. When an organization looks at deploying a business intelligence tool there can be many factors that will complicate its deployment. Often times challenges such as whether or not the application is intuitive or not will play the largest role in deployment.
Traditional business intelligence tools are being replaced by data discovery software. The data discovery software has numerous capabilities that are dominating purchase requirements for larger distribution. A challenge remaining is the ability to meet the dual demands of enterprise IT and business users.
The statistical inferences I have observed are mostly in one dimension. The use of Dash Boards (unfulfilled orders, open tickets, etc.) the creation of Fusion Center used in many occasions as past performance but not to try to anticipate future behaviors or to capture changes in demand on the spot. The spreadsheets, and graphs that are displayed are at most per supply chain and not as a metric compared to the standard metrics decided by senior leadership. The intention of senior leadership is to go in the direction of enterprise analytics but I see it is relatively in its
Companies have transformed technology from a supporting tool into a strategic weapon. ”(Davenport, 2006) In business research, technology has become an essential means that many organizations use in their daily operations. According to the article, Analytics is a major technological tool used. It is described as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.
Most of studies have proved that a lot of companies are doing great job in using web analytics in order to do investments , but they still have problems on how they can make the right business decisions and recommendations. Most of the employees are complaining about the tera bytes of data and giga bytes of data that comes from the reports for Excel and power points files that have no actionable insights . Avinash Kaushik had found the solution for this issue , he created the “10/90” rule. This rule suggests that for every $10 you spend on your analytics tool and implementation, you should spend $90 on intelligent digital analysts that can convert your data into actionable insights. Avinash Kaushik mention an example in order to clarify his
Using successful delegation benefits management and subordinates within the organization. Possibly the most significant advantage for the company is a higher quality of work. At my workplace, delegation can improve quality of work by permitting the employees who have direct knowledge of the laws, regulations and procedures governing the administration of public assistance grants and programs and of interviewing and record keeping techniques to make decisions and complete tasks. Additionally, administrators and supervisors gradually gives more responsibility to eligibility staff for making independent determination of initial and continuing eligibility for applicants and program participants receiving public assistance within established guidelines and procedures so that eligibility staff has the ability to effectively search and gather records of various incomes or eligibility related information from multiple sources including computer databases, and apply the rules and regulations pertaining to eligibility for various categories of aid programs, makes mathematical computations, evaluate financial data, and interact effectively with the public in the process of public assistance program evaluation. Employees may do their work better because they may feel a personal liability for the ending result, even though responsibility ultimately rests with the person who made the delegation. Motivation should also be enhanced as delegation enriches the worker's job by expanding the types of tasks that are involved in it (Camp 2006).
First of all, business intelligence analysis requires the capturing of information and storing in a single location for effective data analysis. Currently, data analysis is supported by transactional systems, business specific data marts, and other ad-hoc processes. Information is distributed making it difficult and time-consuming to access. Business teams have adapted to this environment by creating user maintained databases and manual “work-arounds” to support new types of reporting and analysis. This has resulted in inconsistent data, redundant data storage, significant resource use for maintenance, and inefficient response to changing business needs.
All companies obtain information on their customers or on their product. All these information may help a business to develop new strategies. They can also forge ahead by treating these big data. All companies have in their possession those information, so use it can be very useful. A company can identify for example their weaknesses and can improve their strategy to become the best on the market. It will help to create more opportunities for the company and maybe create a real competitive advantage.
Decision making refers to the process of finding and selecting options according to the priorities and values of the person making the decision. Since there are many choices involved, it is important to identify as many options as possible so as to pick the option that best fits a company’s target, goals, values and vision. Due to the integral role of decision making in company growth and financial progress, many firms such as Amazon.com and EBay are pumping in huge investments in business intelligence systems, which are made up of certain technological tools and technological applications that are created for the purpose of facilitating improved decision making process in business. In this paper, I take a critical look at Decision Support Systems and how they affect organizational Decision making.
Government: personal relationships with people at all levels across multiple departments (Public Works is example, where San Fabian employee used to be at the DPW and so can drive the sale and collection process)
The ERP system allows a strategic flow of information between all areas within an enterprise in a consistently productive manner. The purpose of implementing an ERP system in a company is when the company isn’t operating efficiently. Look at it like this, when your body is sick, you know you need to take medicine, you just can’t stand the taste. And in the same way, when your company isn’t operating efficiently, you’ve got to take steps to correct it. Most companies just fear the disruption, the learning, and the cost, and the inconvenience of it all.
Analytics means using data and performing statistical analysis on it, applying quantitative and predictive models, in order to arrive at a certain decision. Analytics can be the first step in a process or can rather be an intermediate step as well. Analysis can be done using different set of tools that are available in the market or it can done manually using different concept and formulas. Business intelligence firms like Cognos, SAS and BusinessObjects have developed different tools that are readily available in market that assist in analysis and decision making. Analytics is used in order to find solutions to the problems and the solutions provided enables us to be successful and in the business world allow us to compete with our contenders.
In order to be more productive and accurate, most of the companies depend on use of technology, with the help of enterprise resource planning (ERP) systems. (Olsen, and Saetre, 2007).
...at to expect from our society and consumers is very key in the business world. With business intelligence and Data Mining strategies and skills, companies can have that extra competitive edge which will in turn increase profits and market share. The skills gained by those employees who specialize in the BI and DM fields will continue to be top-notch assets to companies and based on the salary trends, they will continue to have increasing compensation. Businesses that implement BI and DM effectively will dominate their markets and stay ahead of the curve.
For the past couple of decades the majority of businesses have wanted to construct a data-driven organization or company. Furthermore, companies around the world are considering harnessing data as a basis of competitive advantage over other companies. As a result, business intelligence and data science use are popular in many organizations today. The increase in adoption of these data systems is in response to the heavy rise in communications abilities the world over. Which, in turn ,has increased the need for data products. Indeed, the Data Scientist profession is emerging to be one of the better-paying professions due to the urgent need of their labor. This paper is going to discuss what business intelligence is all about and explain data science that is usually confused to be similar to business intelligence. I will tackle a brief overview of data scientists and their role in organizations.
It is closely related to the field of management science. Business intelligence can be querying, reporting, OLAP. In other words, querying, reporting, OLAP, and alert tools can help in answering questions such as what happened, how many, how often the problem occurred, where the problem is coming from, and what actions are needed to resolve the problem. Business analytics helps in answering questions like why a certain thing is happening; what if these trends continue in the future and what is the best that can happen in the current scenario etc.