Business

Introduction to Business Control System Using Business Intelligence

In this post, I will discuss the methods and business control system using business intelligence, especially quantitative methods. See the individual problem areas in the below image. The action phases accordingly cover the management range from prediction to error tracing.

business control system using business intelligence
business control system using business intelligence

The operational, tactical and strategic level on corporate policy and corresponding actions.

Decision support systems make use of essentially two methods: simulation and linear optimization.

In addition to demonstrating the risk-management activities, and especially the global economic and financial crisis of risk awareness and risk management are becoming increasingly important in decision-making. It is due to political pressures, globalization, and economic and environmental needs.

While older information systems followed the same logic of fire-fighting (decision, then action, and then control). The new decision-support in business control systems are constantly monitoring the actions taken in order to achieve targets. This task is performed by monitoring, which can be understood as part of Controlling, and provides suitable procedures and corresponding software.

Businesses may still have such a sophisticated planning system, making the best possible decisions under uncertain expectations. And incomplete information and all work processes have well-structured and efficiently monitored by target actual deviations. However, they are not immune to Services and are defective or errors occur in the manufacture of products, which results in warranty claims of customers and reputation losses. The product recalls in the automotive industry is eloquent testimony that “the child fell into the well”.

In such situations, the troubleshooting is the appropriate approach, by abductively closing expert teams (task force) from the first indications or symptoms, such as errors in the circumstances and conditions with the highest possible confidence or security.

Forecasting and Scenario Technique In Business Control System

The term forecast comes from the Greek word and it means a prediction. Serious forecasts should at least be verifiable. It provides a short-term perspective of future developments, states, or events. Quantitative forecasting methods are based on time series as a series of temporally ordered, in the majority of cardinally scaled, observational or measured values. The forecast distance τ ∈ N depends on the granularity of the time axis and the extent of past data, such as the length of the time series. And is usually one day in the daytime terms, one month in the month values and fifteen years in the year values.

Examples include predictions of daily occupational accidents, development of beer consumption, passenger transit international air traffic, the brand value of long-lived luxury goods, the outcome of polling, and the rate of failure for bachelor examinations at a high school.

Scenario techniques also provide forward-looking statements. However, they are long-term (with periods between 5 and 25 years) and are predominantly qualitative, ie the data is based on nominal or at most ordinal scales. This makes sense in that such scaled, “soft” forward-looking statements inherent insecurity have proved to be more powerful.

On Scenario method produces alternative, hypothetical, plausible and self-consistent future pictures in a well-defined socio-economic context. It considers several qualitative factors of influence and their interactions (interdependencies). For example, in the scenario study “Mobility Europe 2020”, which was examined by an automobile manufacturer with regard to the role and development of private transport in Western Europe, influential variables (so-called descriptors) such as energy price, drive type, transport, spatial planning and environmental policy, economic situation, and species of the individual traffic (professional, leisure or purchase-related) of interest.

Forecasting Methods

Now we turn to the forecast of economic time series. The starting point is an analysis of the time series, followed by the selection of the prediction formula. One should not stick to the representation of the data in tabular form, but visualize it in a Cartesian coordinate system or in another form.

For the human visualization system much more suitable than a below table, which is a diagrammatic representation of time series. And is often able to show at a glance structure, such as trend, season, economy, etc. but also outliers. It can be easily visualized when the individual seasons are superimposed every first of the year. One recognizes “at a glance” that the seasonal figures are season-dependent and that the seasonal fluctuations increase from year to year. This increasing volatility of sales places increased demands on short-term and long-term production and capacity planning.

Business Control System Monthly tanker sales (khl) 1974-1989
Business Control System Monthly tanker sales (khl) 1974-1989

Scenario Planning

Due to the large uncertainties of data and forecasts over a long time horizon, ordinal or nominal scales are used to stabilize the predictions. The choice of a non-metric scale level means, for example, that the gasoline price (B) is not expressed quantitatively with the unit of measure Euro / l, but qualitatively. There are two specifications of the value range: range (B) = {low, medium, high} or range (B) = {falls, stagnates, rises}. In the first case, the (descriptor) of the data type Stock size, at the second of the type of flow size (flow)).

Scenario engineering detects uncertainty and uncertainty of current and inventory quantities as well as the “value per unit” (vpu), e.g. Gasoline price per liter or power consumption per hour, specifying the direction and strength of the interactions between the influenced variables. All risk assessments and potentials can only be determined purely subjectively because of the problematical “data deficiency” of future values. Roughly, the future perspective can be summarized in the scenario funnel. Note that in the “classical” scenario technique the present state itself is not modeled, but only the future end state is described.

Planning and Consolidation

Planning as preparation for entrepreneurial action can be formally reduced to setting the triple (Z, M, W). Thus, in individual cases, goal Z can be the annual profit improvement of bus operation in public transport, and M serves as an increase in the annual personnel budget in order to increase the service level of the workshop as a way (W), for example, and thereby reduce revenue-causing, unproductive workshop days of the buses , Planning has a double function in the company:

Control Function of The Planning

Following plans reduces ambiguity about the next steps and coordinates the activities of different people.

Selection Function of Planning

A plan involves a decision between possible plan alternatives. Here, the goal is to achieve the most effective and efficient possible achievement of the organizational goals.

Risk Management

Risk management is the identification and analysis of possible events that can negatively affect companies in terms of human, physical, financial and financial matters. Control, monitoring and possibly the removal of these ventures take place in such a way that a desired level of risk is almost certainly not exceeded.

Monitoring

While process control was originally used only in the manufacturing industry, it has also proved to be efficient in the service sector due to improved-especially mobile telecommunications. Just think about online health and environmental monitoring or traffic control systems.

A monitoring system warns if target-conforming limit values are exceeded. It triggers an interference in the process involved when it is recognized that the process is “out of control”, i.e. that the sequence of measured actual values deviates “significantly” from the predetermined target value.

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