When Traditional BI is Not Enough: Advanced Methods to Improve Decision-Making

6 November 2014

In order to achieve the set goals, decisions are made by heads of companies and managers on a daily basis. Long-term business success depends on the quality of decisions made. From the perspective of operations management, correct decision making is considered to be one of the most important factors for a company to function efficiently.

 So what can be considered a good decision?

Surely it is a decision made on time, at minimum cost, which allows for the achievement of the best results. Constant practice of making effective decisions enables a company to move at a faster pace ahead of the competition, becoming the leader of the field at the same time as maximising the return of investment for the company shareholders.

The actions of a person making decisions in the management process cannot be spontaneous. It is necessary to organize, coordinate and control decision making in a centralised manner and constantly evaluate the results.

Since decisions are made based on the available information on the situation, it is important to make sure the decision maker gets the properly prepared information at the right place and on time.

Traditional BI tools fail to provide real-time insights

The Business Intelligence (BI) systems, which are widely available and have been used in major companies up until now seem to cope with the task of providing information. The data is collected from various internal systems and analysed, then reports and future projections are made.

However, the global, dynamic and competitive business environment demands faster solutions. Processing and presenting data streams which are growing at an ever increasing rate is proving to be more difficult each time, and the decisions made based on data of the past period cannot be always effective.

BI – step or two removed from business operations

BI systems are built to support the strategic and tactical decisions of managers based on historical experience (and not on correlation with the present day). Meanwhile the decision makers managing everyday business operations refer to methods or practices set from above, or intuition, having no access to analytics, which would allow them to choose the best solution alternative.

Such a divide between the strategic and operational levels creates a medium for appearance of unfavourable situations, which can cause damage if left unsolved for a long time.

Decision pyramids

Intelligent Business Operations: analytics, decision making and control in one platform

Connection of business information systems into a common environment, in which data is analysed and made available for operation managers in real time is a task addressed by Intelligent Business Operations (IBO). IBO are also known as a work method, which involves the integration of real-time analytic and decision management technologies into operational activities and processes of the company.

IBO and BI should not be compared, since these methods do not perform the same function, but rather complement one another. The main aim of Business Intelligence (BI) systems is to gather and analyse the historical data of the past period. Meanwhile the IBO platform compares historical data with the data of the real-time period, determines trends, links between actions and makes forecasts for future periods.

Another important IBO function – automated making of optimal decisions, where the forecasted demand, existing and planned limitations, and results are used in real-time to automatically choose the most cost efficient combination of quantity, delivery time, route, size of package, etc.

Graphical dashboards, customization of user interface in accordance with the performed functions, alerts and decision simulation tools give full visibility of the situation to the decision maker, as well as the ability to rapidly and flexibly respond to real-time changes. In the meantime, managers can perform real-time monitoring and evaluations of the Key Performance Indicators (KPIs), monitor implementation of strategic goals in the company, stay informed on the system suggested tactical actions.

Artificial Intelligence powered cash management solution

The FOBISS CM™ IBO platform for cash supply chain management uses integrated artificial intelligence algorithms to carry out the complex tasks of cash-demand forecasting and optimization. These algorithms are capable of processing large amounts of information in real time, evaluating patterns, relationships, trends and projections, and then choosing the optimum actions from millions of possible combinations — something the human brain and standard analytical tools simply cannot accomplish.

However, it is important not to underestimate the importance of human input in the process of algorithm training. The system does not answer the question “why”; it simply evaluates causes based on insights provided by expert staff.

For example, while analyzing an error in system forecasting, an employee notices that this might have been influenced by an unusual or anomalous event that occurred in a particular region.

The algorithm receives this information and re-evaluates the relationships, thereby learning to make even more precise projections. Such a work method can eliminate the risk of losing know-how in a staffing change. It can also prevent an "information gap" should an employee in Region A be called upon to fill in for an employee in Region B, due to a vacation, sick leave or other unexpected absence.

The precision of these complex algorithms can be demonstrated and quantified. In studies and pilot projects, Fobiss found that a network of six thousand ATMs can save 22 percent in logistics costs, 17 percent in money-handling costs and up to 55 percent of interest-related costs. Expressed in monetary terms, the ATM deployer saves 11 million euros ($14.5 million) per year.

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