Business Intelligence in a Corporate Environment
Business Intelligence in a Corporate Environment
The purpose of this literature review is to provide an overall perspective to the workings of business intelligence in a corporate environment. With the onset of massive technological gains in the past decade the implementation of business intelligence has grown accordingly. In the workplace the demand for business process improvement, responsive reporting, cutting edge forecasting, and internal business customer relations has triggered a need for a unit that understands the business needs as well as the impact on company technology. This review will focus on the various areas that business intelligence impacts in the workplace. There will also be an emphasis on understanding the longevity of these types of units. With these units in the workplace questions concerning departmental automation goals and the impact on the maturity stages that are involved with the creation of business intelligence units. Finally, with the growth of data collection and ease of use, the security and management of company information is intertwined with the operation of business intelligence.
The Age of Information
The Role of Shifting Technology
Throughout history technology has influenced the very fabric of business operations. The role of business intelligence in this shift is the implementation and continuous improvement of that technology. This role is ever changing because technology continues to improve. While to some the role of business intelligence seems new and upcoming the usage and practice goes back to the earliest days of industry. An example of this history would be in the automation industry. In years past large amounts of labor was done by hand. The role of the business analyst would be to collect and analyze the entire business process from start to finish. Once this was done the analyst would narrow their focus to the individual in an attempt to provide management with data to increase speed and efficiency. That role is now used to analyze the systems and machines that are responsible for making the products.
While the example above is simple the connection between the shift in technology and the role of business intelligence is clear. With any business the desire for information is strong. To be competitive a company needs to be aware of the business environment in which they operate. Business intelligence serves to meet the information and improvement goals that drive the company to greater success.
For this literature review there is an article written by Elliot King that exemplifies the shift of technology and the role of business intelligence on it. King focuses on the large amount of company resources that are spent on the implementation, development, and management of business intelligence technology in the workplace. This attention has been driven by the increasing demand for such software products and personnel to manage them. Understanding this current shift King focuses on the role business intelligence has and will continue to have on the business that use data en mass.
The article provides a brief look at the history of data storage and misconceptions about employee interest in accessing the data. This interest has largely been pushed down due to the complex nature of interacting with the information present within the data warehouse. With the explosion of the internet and user assimilation to it these technical barriers are slowing beginning to fall (King, 1998).
With the ease of use and understanding increasing employees are beginning to grasp the value of data. This is where the role of business intelligence has thrived. Business intelligence has been implemented to bridge the gap between the employee and the business data stored in the warehouse. This is done through a variety methods that have made data more and more useful to the companies that have and utilize their data.
King summarizes his article with the theory that as the internet was opened far and wide to all this should concept should be applied to the data warehousing. While King understands that the two pieces of technology are different he affirms that they are similar enough in nature that the same approach can be applied. Overall, the article provide a good look at how the shift of technology in business can affect the demand for systems and the personnel that maintain and operate them (King, 1998). The impact of Business growth
With the growth of business the world has begun to shrink. No longer are companies that employ a hundred or even a thousand considered to be impressive. In 2014 Bank of America was reported to have employed two hundred and eighty four thousand people to run its operations around the globe (“Bank of America,” 2014). The implications of companies of this size are astounding and have significantly impacted the demand for business intelligence.
To truly understand why a company would spend millions of dollars on business intelligence operations a simple example can be provided. For Bank of America each employee is assigned a unique number or code that distinguishes him or her from the rest of the employees within the organization. On the other side of the table each customer that has interacted with the bank is also assigned a unique identifier. If these are added together the quantity of unique entities starts to become astounding.
The example above shows why a business like Bank of America would be heavily interested in utilizing business intelligence assets to manage the data associated with its business units. While the example provided only touches on areas concerning employees and customers the amount of data associated with those people can be mind boggling. For employees this data could be anything from human resource forms to vacation day requests. For customers the data could be products purchased, recorded marketing calls, website interaction as well as a host of other areas.
In 2000 Deborah Rowe an article that centered on business trends pushing database management systems to greater growth. Rowe focuses on the data warehousing concept that has proved to meet a large majority of business needs in terms of information management. The focus of the article is to explain how progress is pushing for better and better systems for managing data. The article talks about how increasing competition has created a lean environment for data management. Companies that are complacent with their data are either failing or catching on to the need for better interaction and usage of their data. Rowe delves into the process of choosing these systems from a corporate perspective.
The challenges presented by this type of implementation are rather glaring. These challenges include upfront cost, long term cost, and mismanagement of data. If a company chooses to implement a product that its employees don’t understand correctly the effects can be devastating on the business. Hiring knowledgeable employees to manage and implement the product is essential to long term success. With all of these hurdles of implementing a DBMS system the task can be daunting.
Rowe discusses how the task of purchasing and implanting a DBMS needs to be done with great caution and a clear focus. If a business isn’t able to look further down the road and consider how the DBMS can be used in the future it will fail completely. Having a perspective that encompasses as much of the companies goals and visions is critical. This is why companies are constantly looking for individuals that are able to focus on a detailed system but be able to at the same time look at the broader scope of the company’s needs (Rowe , 2000).
In summation the article leaves the reader with an interesting perspective on the increasing demand for these systems. Rowe concludes that the ERP industry will grow and tremendous pace in the future. With that growth the need for knowledgeable employees that understand the systems use and can translate the data to affect business needs will continuing to increase.
The increasing corporate demand. At its very core business is driven by two simple concepts. These are the laws of revenue and expenses. In business these two laws drive companies on a daily basis. Popular opinion about these concepts can sometimes sway in either direction. Proponents may put all of their support into revenue generation while others will focus on creating the perfect lean business model.
Whatever the theory or opinion is the law of revenues and expenses will remain the same. As discussed in this review the expenses of implementing DBMS systems and employing highly skilled individuals can be massive. To a company that purely focuses on the expense side of the equation these systems may seem like a waste of precious assets. To others who understand the future and current impact of these systems the decision to utilize them is an easy one.
Like the concepts of revenues and expenses the goals of a company can dictate the perspective of business intelligence units. The reason demand has begun to steadily increase over the past decade is the potential to affect both the expense and revenue side of the business structure. Business intelligence units are designed to support departments in ways that can amplify their current revenue production and decrease their expense habits.
An article written by Ken Rudin explains how corporate demand for business intelligence in their companies is steadily increasing. Rudin talks about how business intelligence has become a very high priority for business executives who understand the values they can derive from business improvement. This demand has grown to the point where corporate leaders are focusing on moving past the traditional business intelligence processes (Rudin , 2007) .
Rudin explains the implications of this progressive thought process by paralleling the impact of software applications that software products have had on industry to business intelligence services. The discussion is focused on how executives are looking into custom company specific solution provided on an instant. This type business process software is highly intuitive and seeks to provide all of the necessary tools needed to make an informed business decision.
Examples of these on-demand solutions are software’s likes SQL Server Reporting Services by Microsoft. This software allows for not only the display of information but the real time interaction with the data that the web services are pulling their content from. Rudin discusses how these types of solutions are not only catching fire they are exploding all over the business world. This explosion of demand is driven by the complexity of the data being pulled as well as the cost associated with the data being collected and stored.
This cost and complexity equation is what Rudin believes is the key piece to business intelligence demand. Like the example of revenues and expenses the idea surrounding on-demand solutions is the same. The question asked is, “What can these solutions do that allow a normal employee to do their job at a higher level which in turns into a higher rate of return for their employer?”
Concluding Rudin’s article he discusses that a key factor associated with on demand business intelligence solutions is the usability of the product. Having solutions created that users do not understand or lose trust in can be a major drain on process improvement. Rudin emphasizes that the development of these processes needs to be done in such a way that they take into account the users that are interacting with them. This is essential to developing a trust relationship between the users and the product (Rudin , 2007). Business Intelligence Tools
The Role of Reporting
Reporting is one the most essential pieces of and type of business process. If a company sells laundry detergent it needs to know how much product it has, how much product it has sold, and how much it should produce. These three simple questions speak to the ramifications of good reporting data within a business.
There is so much information that is gathered by companies with the singular intent of providing reports for business decisions. This gathering is done in a way that the information collected in stored in some type of server which houses a virtual warehouse. Like a physical warehouse it is critical to understand how and where something is stored so that it can be retrieved for future use.
When it comes to reporting the challenge presented to businesses is the quantity and placement of their data. If a business is unable to utilize their data efficiently they are sacrificing business opportunities every second the data is left idle. This quandary has been analyzed and the solution has been to purchase and employee people and products to provide this data in a useful format for business use.
In a business intelligence unit a data analyst will focus on first understanding the overall goal of a report request. This is important because the impact of creating something purely based on the request can lead to disastrous results. These can range from customers not understanding the terminology used within the reporting system to not grasping the capability or usage of the system being used to provide the report.
To make sure these requests are understand correctly a business intelligence unit is commonly found implemented within a specific area of the business. This cultivates a cross knowledge between the highly technical nature of the reporting systems to the broad scope goals of a particular business department. This type of side by side interaction can be a major benefit to not only getting more precise and accurate reporting it also serves as educating tool to the department through exposure.
An article written in 2005 by Harry Debes explains this process in detail. The author of the article begins the discussion by emphasizing the importance of timely and accurate data. These two pieces are the bread and butter of business intelligence. The reason for this is that both factors are highly dependent on each other.
Debes explains this concept by focusing on the energy market and the application of business reports in this area of industry. He shows that there various daily functions that are conducted that are in need of constant monitoring to allow for efficient operation. Some of the examples include repair requests, credit collections, meter usage, demand fluctuations, and most important customers (Debes , 2005).
All of the examples cited by Debes are common sense in nature but they require an entire business process to effectively report on. Using the example of meter usage by having daily reports energy companies can identify issues based on real time data and not be forced to swallow a catastrophe because of something as simple as mechanical fault. The problem could easily be identified by a simple reporting tool that was programmed to expect a specific range of usage. If the range was violated the system would send an alert with a level of priority based on the disparity of the ranges.
The article written by Debes is a good example of how business intelligence reporting can be implemented in ways that benefit the company at levels of the corporate ladder. From interactive financial data and forecasting to specific customer energy consumption and history reliable and accurate reporting in the energy industry is a very powerful tool that has been used and is being continuously improved upon for future endeavors (Debes , 2005). Impact of data driven Forecasting
Forecasting is an important an element of any business. At its most basic level it is simply looking to the future and making guesses to a specific result based on past and present data. This is where the role of business intelligence arrives. Data analysts like their namesake are paid to look at data and decipher how that data works and relates to the business.
Once a data analyst is able to firmly grasp company data they can provide constructive advice based on the knowledge of that data. In addition to providing advice the data analyst can create reports that take past data and make estimations programmatically based on definable trends. These reports can be provided through an assortment of software’s and displayed in formats that best fit the target audience.
Having a system in place that looks to past data and provides useful forecasts can not only give a company an idea of where they are going they can also give an idea where their competition is going as well. This ability to compare company performance to the market and project where the company is headed is critical. With timely and reliable forecasting a company can discern opportunities and threats within the marketplace before they even occur.
With market competition becoming more and more intense the role of forecasting has been prioritized highly by most companies that operate on a large scale. This is clearly supported by an article written by Susana Schwartz about the greater need for more robust forecasting technologies. The concept of the article focuses on the next level of forecasting that business intelligence units are seeking to achieve.
The author talks about how the next set of tools utilized by business intelligence units will be integrated into the business processes that have already been laid down. The key factors that are emphasized are the broad categories that these tools can influence. Examples of these are products such as SSRS by Microsoft, ARGOS by Ellucian, and APEX by Oracle.
Each of these tools provide granular interaction with business process data while still being able to be applied to other categories. These tools are used to be the developing platforms that take the business process driven data and formulates it into reportable information used for forecasting. In the article these are the types of tools that Schwartz describes when talking about integrated and real time driven tools (Schwartz, 2007).
Concluding the article by Schwartz she emphasizes the value of report generation. She talks about how even if the emphasis might be redundant the need to focus on this factor is critical to accurate forecasting. This is because all of the past data collected is contained within the reports. Schwartz’s realizes that for business units to understand any of the forecast data they need to be familiar with the data that has been collected and displayed within the provided reports (Schwartz , 2007). Data analysis and Improvement
The core of what business intelligence does is data analysis and improvement. Both of these factors contribute to each other in a never ending spiral of push and pull. When data is analyzed it is used to improve a process which in turn is analyzed. With this concept firmly in place understanding the role of business intelligence becomes clearer.
As the facilitator of analysis and improvement business intelligence units are responsible for the flow between the two actions. When a department senses a need for analysis or improvement the business intelligence unit is used to facilitate that action. This responsibility to facilitate these actions is what drives the demand by corporate leadership. As expressed earlier in this review having units that are constantly looking at moving the expense line down and the revenue line up is very beneficial a corporate entity.
An article that was created in response to a seminar on business data analysis describes how this process is essential to the strategy development and future readiness of company’s based on data analysis. The article provide insight into a couple areas within the sphere of data analysis. One of these is building the foundations and structure of the culture within the company to respect the data and make decisions off of it (Computer software .., 2012).
This whole concept of creating a decision based culture is driven by the need for action in the market. If a company fails to take action on its corporate strategy it will fall behind its competition fairly quickly. The article discusses how through data analysis an attitude of decision making individuals can be created to promote action.
The key of this data driven culture is the analysis that goes into making the data credible. Without credible data the ability to make decisions quickly and effectively is crippled. If employees can’t trust the data they are working with they will begin to question the entire infrastructure based on a single data set. In addition to data analysis the article talks about improving recruitment through data analysis tools. Being able to create a clear picture of who a person is before the expense of bringing them in for an interview can be a great time and money saver. This is done through internal and external data analysis (Computer software .., 2012) .
Once research is done on an individual the business intelligence units can categorize potential recruits and provide reports based on recruiters specifications. If an office manager needs someone with three years of experience and a knowledge of a specific software system a tool can be created to provide that data in real time to the inquiring party.
When it comes to data analysis and improvement making sure that they are used in conjunction is essential for seamless implementation and continued success. An example of poor usage is providing a complicated and detailed report within a system that can’t handle the data correctly. Even though the data itself is good the system used for improvement is poor. This can create animosity towards certain products and mistrust in data (Computer software .., 2012). Data management
The term data management is something that has been thrown around industry the past few years. When this happens the real meaning of the terminology begins to take on a life of its own based on the perception of those trying to comprehend its true meaning. A clear way to explain what the definition of data management is to show the similarities between an industries accepted practice. Like employee management data management requires a certain style to correctly guide the direction of the data. In a department setting a manager may spend time developing a plan that their employees will play specific roles in. The same is true with data management. Depending on the setting and usage data is set aside in specific formats to meet highly granular needs. A good example is list of information that is associated with a company’s employees. The data will stay the same but it requires a level of management to break into specific formats to meet different needs. The human recourse department might need the list as a reference sheet to pull information about quickly and efficiently. That same information could also be used by the employee development department to conduct surveys and gauge employee satisfaction.
These examples are very simply but they do provide a good idea of how managing data in a succinct and efficient way can broaden its usage and usability immensely. There is an article written in the Journal of Digital Asset Management that describes the role of business intelligence on data management. This article provide a brief look into how the emergence of big data has pushed an emphasis on utilizing business intelligence units to provide levels of data management. The article talks about how business intelligence is beginning to play critical role in the storage, maintenance, and usability of the data. These three factors are critical in guaranteeing the reliability of information collected and scrubbed for company use. The first of these factors briefly mentioned is the storage factor. Arguably the most important of the three storage is the bucket where all unstructured and structured data is stored (Jordan & Ellen , 2009) . Within the context of the article the authors describe how storage is the first step that business intelligence units have to consider when managing data. The tasks associated with this piece range from creating feeds to port information from various databases to creating tables and views within specific schemas.
Within these tasks the question that is constantly asked is the question of available space. This question permeates each of the three factors but is most prevalent at the initial of data management. The second piece is the maintenance portion. This factor is most prevalent once data has been stored and refined into a usable manner. The article shows how this responsibility is what keeps business intelligence units in a critical role to companies data management needs. The tasks that occur with data maintenance can range from eliminating old data, archiving, inputting new systems, and creating methods to encourage more efficient data retrieval and reporting. The final factor addressed in the article is the factor of usability. This concept is what non-IT personnel will focus most of their attention on when looking at data resources. Business intelligence plays critical role in getting the data into an understandable and usable format at the customer level. This is the defining piece of business intelligence focus. Employers look specifically for individuals who are able to translate the technical data from a database perspective and be able to make that information as clear as possible for non-information technology users (Jordan & Ellen , 2009). Internal communications
When considering things that business intelligence employees should do well is internal communications. In many companies business intelligence units will be the ambassador between the data and the customer. These individuals are responsible for understating the customers’ needs from an IT perspective. Once the needs have been determined the customer needs to be made aware of how close or far away from their original needs are to the ones seen by the business intelligence personnel. Being able to discern what a customer needs is extremely important. The emphasis placed on cultivating effective communications between all parties is absolutely critical to getting the information needed to create or improve business processes. There are so many adverse situations that occur within corporate setting that could have been avoided by simply establishing channels of communications with involved parties. A good way to do this is to provide updates on the progress of the project. This can done by collaboration software, email, phone calls, and face to face interaction.
By establishing a working and efficient internal communication structure customers are more at ease with the progress and process being developed. This is essentially a status gauge that shows that all parties are involved and have a say in what is happening. An article released by press wire gives a good example of how companies are understanding the importance of internal communications and the role of business intelligence in it. Based on the trends within industry the article shows how the shift of technology has affected the way internal communications are done between IT and the various corporate departments. What has occurred in recent years is the need for new strategy development with business intelligence as key factors in these strategies (Business intelligence..,2001). From a corporate standpoint these new strategies have ushered in a different perspective of IT individuals in the workplace. No longer are individuals that work with databases left out of conference calls and meetings that determine company direction.
The article clearly explains that the need for individuals with technical and corporate goal understanding need to have an opinion in new processes and strategies. These individuals are becoming more and more important because of their perspective on how technology is being used in the marketplace. The final portion of the article by press wire addresses an important decision the transitioning companies have to make. The authors emphasize that decisions makers need to reshape their perspective of units like business intelligence and truly value the opinions that are being shared. If this perception of the average IT worker from the 1970’s continues to permeate a company’s upper level management the likelihood of less opportunities and more threats to occur is much more likely than competitors who are understand the shift (Business intelligence..,2001). Business Intelligence Outlook
From a sustainable field outlook the question has been raised is whether business intelligence as a field is here to stay. In any profession this question has been and will be asked as the world changes. No profession is one hundred percent guaranteed that the field will continue to be useful to the society in which operates. This simple truth puts into perspective the fragility of any profession.
In regards to business intelligence determining whether the field is going to progress for years to come is difficult. Currently, the demand for business intelligence employees and or software is currently high. With many top competitors in various industries searching for ways to cut cost and improve efficiency the current market outlook is good.
On the flip side of this equation the risk for business intelligence to improve itself out of a job is a definite possibility. With new software’s being created the technical barrier created by big data is beginning to slowly fall. The threat to the field is that companies will purchase a customer based software that provides cookie cutter reports that can be used by non-IT users to make business decisions.
An article by the journal of Journal of International Technology and Information Management touches on this topic and describes how measuring the effectiveness of business intelligence on a company can determine its future market outlook. The authors take a detailed look at how in some situations a business intelligence department has been effective for some companies while for others the effectiveness has been limited (Vinekar,Teng, & Chennamaneni , 2009).
The important factors that the authors cite for effectiveness center on corporate understanding of the role of business intelligence, implementation, defined goals, and perceived value opinion. Each of these factors are cited because of they are all touched at the inception of the business intelligence unit within the company. Without these factors being addressed correctly the ability for a business intelligence unit to operate effectively is severely hampered.
The first of these factor is the identity of the department. Just like meeting a person for the first time the impression created on the meeting is what defines the perception of the relationship. The article talks about how it is the responsibility of those implementing the unit to clearly lay out the benefit that the department will bring to the company as a whole. These individuals include directors and manager.
This push stage is the first step in gauging whether business intelligence will be effective within a company. If corporate leaders understand the benefit of the unit and put their support behind it the initial reaction is more likely to be positive than negative. The caution that is applied to this phase is that if there isn’t top down approval the unit will not succeed. The authors strongly emphasize the need for an executive push at the inception of the business intelligence unit (Vinekar,Teng, & Chennamaneni , 2009).
The second factor discussed by the authors is the implementation phase of a business intelligence unit. This is the first step to making a concerted effort for a business intelligence impact on a company. The authors talk about how this phase needs to be handled in a way that allows for immediate impact. The rational for this approach is that if the business intelligence unit can prove its value at inception the perceived value of the unit will be cemented in its early success.
With this approach the authors also caution at the risks involved. If the unit is not prepared the likelihood of error is high. Just like the perceived value of the unit based on a positive rollout the same can occur for a negative one. The authors are adamant in their idea that to make a good impact the unit needs to be prepared and aware of the tentative situation in which the unit is placed on the onset.
The third factor is defined goals. The unit needs be able to clearly express their goals for improving the company’s internal and external business processes. The article describes how the focus of the department needs to be grounded in the goals and direction set at the onset. This allows for an immediate understanding of what the unit hopes to achieve. The authors caution that without clear goals for the department the unit will not be able to work succinctly.
The final and most important factor discussed in the article is the perceived value opinion of the business intelligence unit from the rest of the company. This perceived value is critical for unit to be able to provide opinions and trusted data. The reason cited by the authors why this value opinion is most important is because the opinion can be had by every employee within the company. The simple truth is that with more eyes watching the unit there is a higher level of critique applied to the actions done by the business intelligence unit (Vinekar,Teng, & Chennamaneni , 2009). Departmental Goal Impact
In most businesses the unit structure is broken out into various departments that meet company specific needs. Examples of these include accounting, budgeting, marketing, human resources, R&D, and many more. These departments all do things that are subject specific but require a certain level of overlap with the rest of the company. For example the budgeting and accounting departments are joined at various stages of the financials that the company uses.
Having an understanding of these departments is very important from the perspective of the business intelligence unit. The reason business intelligence units need to grasp the subject impact as well as overall impact of departments is because the processes built usually touch more than
one specific department. What this means is that a data analyst needs to be able to determine what is best for not just one department but for all parties involved.
With a macro perspective of the company the business intelligence units are able to impact broad groupings of departments. This in itself is a big benefit to the company as a whole. The reason for this is because the improved processes help promote better interaction between departments. This is like connecting various standalone silos to each other with an agreed on process.
An article that addresses this departmental impact comes straight from the Business Intelligence Journal. The whole premise of the article is the authors argue that by assimilating business intelligence units into departments these units can change the departments core business practices. This can be done by embedding individuals from the business intelligence department into other departments through the company (Elbashir & Williams , 2007).
The authors lay out a plan for making sure the company gets the best benefit when the embed business intelligence personnel in a different department. The authors talk about how it is important to make sure an understanding of the units function is clearly laid down before the unit is implemented. The importance of this is that the departments understand the business intelligence units are not directly under the units they are embedded in.
The article makes it clear that to make the relationship work between the BI unit and the department the BI unit cannot be under the department they are servicing. The rational for this is that if the BI unit is under their own department they will be less inclined to favor a department when building a business process for multiple departments. This is important because it allows the business intelligence employees to say no to things that might be requested out of ignorance or selfishness.
The second step for success when embedding a BI unit is to establish the relationship. The authors describe how important it is to set up the way communication is supposed to occur. In most situations it is important to have the directors of the department as the individuals responsible for setting up the proper channels. The benefit of this is that it forces employees to acknowledge the support of the department’s directors. This means the BI unit will be able to get the information they need from department employees to formulate effective business process improvements (Elbashir & Williams , 2007).
The final piece that the article discusses is how much leeway the BI unit has to make departmental decisions. In some cases the BI unit make most improvement decisions based on technology understanding and departmental trust. In others the unit has little leeway and requires approvals from the department to enact improvements. Whichever way the process is set up it is important to have that clearly explained and understood by all parties involved to avoid confusion (Elbashir & Williams , 2007). Tiers of maturity. In the business intelligence community there are various levels of maturity associated based on the length of time the unit has been in service to the company. Each of these levels are determined based on the progress the unit has made. These level begin at inception and end at forecasting. It is important to recognize these levels to determine the progress the department is making in the company that it is being utilized in.
These levels are broken out into three specific categories. These are the inception phase, the break even stage, and the forecasting stage. Each of these stages is unique and presents its own set of challenges to the business intelligence unit. The most critical phase is the inception phase. Since this phase is what spawns the impact that the BI unit makes it is critical that it goes well.
During the inception phase of the unit the challenges presented center on assimilation to the company. The unit must be able to find their place within the work environment if they are going to effective in the company. By analyzing company needs prior to actually meeting and planning with departments the unit can have a head start on how to make an immediate impact on their departmental customers.
The second tier is thoroughly described in an article by a group of authors writing for Information Technology and Management. This group of authors describes how the second phase of maturity is centered on getting to a point of break even. This term refers to the business intelligence unit being able to complete/automate enough critical tasks that they are able to look begin forecasting (Zeng & Duan, 2012).
During this second phase the authors stress the importance of consistency and performance. These two ideas are what the authors believe drive the unit towards a proactive mindset and away from a reactive mindset. This transition of thought processes is what make this phase important. Once a unit can break though to a state of mind that is forward looking they can begin to develop ideas that will prevent problems before they happen and predict future opportunities before they occur (Zeng & Duan, 2012).
The final phase is briefly addressed in the article and deals with the forecasting and future opportunities phase. This is tier of maturity that each business intelligence unit strives to get to at some point in its existence. With this phase the unit is able to think more creatively and follow leads and trails into data that could provide beneficial to the company (Zeng & Duan, 2012).
The conclusion makes a final point in regards to the level of maturity. The point made is that these levels once attained are not concrete. With the ever changing needs of the company as well as the creation of new technologies the department can easily waver between different tiers. The authors suggest that having a proactive approach is the best way to stay at the highest level of maturity for the longest periods of time (Zeng & Duan, 2012). Marketplace perspective
The final point of this literature review centers on the industries perception of business intelligence as a whole. This perception is what drives the demand for business intelligence within the workforce. If industry believe the benefit of a business intelligence department is greater than the cost then demand for these units will be high. If the value garnered is perceived as minimal then the field will falter. The real question that the marketplace has been asking falls on longevity. There has been speculation the technology will eventually push this field out into the cold. This would be done by platforms that mimic the various functions and responsibilities that are currently being held by business intelligence employees. If this happens the need for large quantities of analysts would no longer be needed. An article written by Chen talks about the perspective of business intelligence by outside entities. He looks at how a business intelligence unit can provide a competitive advantage to a company based on the agility it affords.
He argues that by having units that can provide data quickly the competitive advantage created is enough to sway popular opinion into the positive (Chen, 2012). Chen talks about the need for business intelligence units and his belief that the agility of these units will continue to drive demand. His entire argument is based on the unit’s ability to adapt to new technology and processes quickly enough to afford decision makers consistent windows of opportunity. Chen’s belief is that no matter how advanced technology gets the need for individuals to understand and communicate it to decision makers will always be needed. Chen concludes by describing how business intelligence units need to maintain a high level of flexibility. He addresses the issue of complacency and warns that if laziness creeps into the department then shifting technology will engulf the department. The real value is the ability to quickly analyze and develop a well thought out process that improves the current one using the existing resources at their disposal (Chen, 2012).
Business intelligence at its very core is business process improvement. This can be done through many different ways but the concept never changes. An individual working in a business intelligence department always ask the question, “How can I make this process better?” This simple phrase is the core of what business intelligence is and what it will always be. There are many companies that understand the importance of business intelligence. These companies have realized how important it is to strive for a lean work environment. This is achieved by isolating areas of work that can be automated or improved through the efforts of business intelligence units. The impact that can be made by tasking a unit to think through a process from every perspective and redesign it to meet current needs can be a massive benefit.
In conclusion, there are many areas in which business intelligence can be utilized to benefit a company. From data management to data security business intelligence departments are meeting the needs of companies as today’s technology moves faster and faster into the future. It remains to be seen whether these units will become a staple of the workplace but their current impact has been instrumental to the information technology industry as a whole.
Bank of america company statistics. (2014, March 3). Retrieved from http://www.statisticbrain.com/bank-of-america-company-statistics/ BUSINESS INTELLIGENCE: Internal communication excellence is critical to business success. (2001, Jun 29). M2 PresswireRetrieved from http://search.proquest.com/docview/444695082?accountid=12085 Chen, X. (2012). Impact of business intelligence and IT infrastructure flexibility on competitive advantage: An organizational agility perspective. (Order No. 3522073, The University of Nebraska – Lincoln). ProQuest Dissertations and Theses, , 124. Retrieved from http://search.proquest.com/docview/1035336826?accountid=12085. (1035336826). Computer software; business data analysis provides key to delivering successful workforce planning strategies. (2012).Marketing Weekly News, , 286. Retrieved from http://search.proquest.com/docview/926791455?accountid=12085 Debes, H. (2005). Business intelligence for the bottom line. Energy Markets, 10(4), 36-38. Retrieved from http://search.proquest.com/docview/228760265?accountid=12085 Elbashir, M., & Williams, S. (2007, Fourth). BI impact: The assimilation of business intelligence into core business processes.Business Intelligence Journal, 12, 45-54. Retrieved from
http://search.proquest.com/docview/222617043?accountid=12085 Jordan, J., & Ellen, C. (2009). Business need, data and business intelligence. Journal of Digital Asset Management, 5(1), 10-20. doi:http://dx.doi.org/10.1057/dam.2008.53 King, E. (1998, October). The business intelligence technology shift. Enterprise Systems Journal, 13(10), 17+. Retrieved from http://go.galegroup.com/ps/i.do?id=GALE%7CA21260167&v=2.1&u=vic_liberty&it=r&p=CDB&sw=w&asid=6f3bfaa58245586c92ea5fb6ad499092 Rowe, D. (2000). Business intelligence trend leads DBMS growth. Technology in Government, 7(4), 17. Retrieved from http://search.proquest.com/docview/206108771?accountid=12085 Rudin, K. (2007). On-demand business intelligence. DM Review, 17(8), 26. Retrieved from http://search.proquest.com/docview/214676633?accountid=12085 Schwartz, S. (2007). BI 2.0 — the next generation of business intelligence tools will be integrated within business processes themselves, enabling improved forecasting and real-time data analysis. Insurance & Technology, 32(4), 41-44. Retrieved from http://search.proquest.com/docview/229300747?accountid=12085 Vinekar, V., Teng, J. T. C., & Chennamaneni, A. (2009). The interaction of business intelligence and knowledge management in organizational decision-making. Journal of International Technology and Information Management, 18(2), 143-159. Retrieved from http://search.proquest.com/docview/205859311?accountid=12085
Zeng, L., Li, L., & Duan, L. (2012). Business intelligence in enterprise computing environment. Information Technology and Management, 13(4), 297-310. doi:http://dx.doi.org/10.1007/s10799-012-0123-z