The Role of Operational Business Intelligence - Essay Example

Exam 4 Lecturer: Question what do various terms mean Operational BI, Analytics, OLAP? Operational BI (Business Intelligence) involves a combination of analytical processes within operating business structure in order to trigger real-time decision-making and collaboration in the business. This is increasingly essential as businesses rely on the capability to manipulate and analyze data for their survival, in return this propel the demand for operational business intelligence (Turban, Sharda, Delen & King, 2010). Operational analytics refer to the high availability of database computing environment made up of redundant components and automation software. These components are applied in operational management allowing the management to access up-to-date data in real-time. Therefore, operational analytics offer an insight of the data within a data warehouse because it allows greater visibility of the various forms of data at a great speed (Turban, Sharda, Delen & King, 2010). OLAP (Online Analytic Processing) is the commonly used technique in data analysis employed within data warehouses driven by the increase in data volumes and the value of data-driven analytics in business. OLAP is also referred to as the capability to effectively manipulate and analyze data from various perspectives using its operational structure that relies in the concept known as cube. This concept has a multidimensional data structure that allows fast analysis of data because arrangement of data into cubes overcomes the limitations associated with relational databases (Turban, Sharda, Delen & King, 2010). Question 2 what is a KPI, and what are its distinguishing characteristics KPI (Key Performance Indicator) represents a strategic objective and measures performance against a goal. KPIs are multidimensional and upon translation, this indicates that KPIs encompass various unique features. One of the distinguishing features includes strategy because KPIs embody a strategic objective. Moreover, KPIs measure performance against specific targets that are defined within the strategy, planning, or budget allowing the targets to take different forms like achievement targets, reduction targets and absolute targets among others. KPIs also have ranges because objectives have performance measures like above, on or below the target. Encoding in KPIs allow ranges to be encoded in software enabling the display of performance through colours like green, yellow and red based on percentages or other complex rules. Time frames in KPI mean that targets are assigned time frames within which they have to be accomplished; as well, the time frames are often divided into small intervals to allow monitoring of performance mileposts. KPI has benchmarks or baselines against which targets are measured with mostly previous year’s results functioning as the baseline even though arbitrary or external benchmarks may be used (Turban, Sharda, Delen & King, 2010). Moreover, there are distinctions between outcome KPIs and Driver KPIs. Outcome KPIs also referred to as lagging indicators that measure the output of the past activity like revenue because they are often financial in nature but not always. Driver KPIs also known as leading indicators or even value drivers measure activities that have significant influence on outcome KPIs like sales leads. In other areas, driver KPIs are referred to as operational KPIs, which implies that organizations collect operational metrics that deal with operational activities and the performance of the company. These metrics include customer performance, service performance, sales operations, and sales plan. For the operational metric to be strategic, it relies on the organization’s use of the measure and in many cases these metrics are essential drivers of strategic outcomes (Turban, Sharda, Delen & King, 2010). Question 3 what are some of the drawbacks of relying solely on financial metrics for measuring performance? Although calendar-driven financial reports remain a significant component in many performance measurement systems, there are drawbacks of using financial data as the main feature in performance measurement. One of the drawbacks is financial measures are normally produced by organizational structures like research and development expenses and never by the processes that generate them. Moreover financial measures are lagging indicators that show what happened instead of why it happened and fails to offer a prospect of what may happen in future. Financial measures like administrative overhead are usually products of allocation that do not relate to the underlying processes that produced them. As well, financial measures focus on the short-term, which allows provision of little information regarding the long-term aspects (Turban, Sharda, Delen & King, 2010). Question 4 what are the Legal, Privacy and Ethical issues related to "BI"? The introduction of BI compounds a host of legal issues that are already relevant in computer systems especially those associated with automated activities. There are concerns regarding liability for actions through advice offered by automated intelligent systems; moreover, there is the issue of using of computerized analysis as an unfair form of competition. Apart from resolving the unexpected and possibly damaging results associated with some BI systems, various complex issues surface. For instance, there are concerns of liability regarding an organization if the organization finds itself bankrupt because of using advice offered by the BI system. The legal concerns arise from the value of opinions offered by experts within a court of law since the expertise is encoded within the BI analytical system. More legal concerns arise regarding the owner of the knowledge in a BI system, the effects of entering incorrect judgment value into the BI system that consequently results in enormous damage to people and companies and the possibility of forcing managers to use BI systems (Turban, Sharda, Delen & King, 2010). Privacy issues arise from the fact that in the past, the complexity of manually accessing information meant that it was a built-in protection against misuse of private information. However, the internet through a combination of large-scale databases, a data warehouse, and social networks create a new dimension for accessing and using personal data. This raises concerns on the price one has to pay in order for an organization to fight fraud. Although private information may be necessary in helping an organization make decision, concerns about employee privacy arise. As well, similar issues also arise from information regarding customers (Turban, Sharda, Delen & King, 2010). Ethical issues associated with BI and computerized support arises from personal values. These issues include electronic surveillance, invasion of an individual’s privacy, use of corporate computer for non-work-related purposes and the amount of decision-making delegated to computers. Moreover, employees are tempted to use sites and other infrastructures for non-work-related purposes and in some companies; the use is tremendously out of proportion to the work-related use (Turban, Sharda, Delen & King, 2010). References Turban, E, Sharda R, Delen D & King D. (2010). Business intelligence: A managerial approach. Boston: Prentice Hall. Read More