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Business analytics can offer empirical validation of strategic decisions

CAREL BADENHORST
Business analysis tools remove the emotional component of decision-making to enable rational and empirical decisions based on a company’s performance data

CAREL BADENHORST Business analysis tools remove the emotional component of decision-making to enable rational and empirical decisions based on a company’s performance data

18th April 2014

By: Schalk Burger

Creamer Media Senior Deputy Editor

  

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Business analysis systems expose the true performance of a business to enable daily operations to be cognisant of business performance and conditions, and executives to test and validate their strategic concepts using real performance data, says business intelligence company SAS Middle East, Africa, Turkey & Pakistan technology practice head Carel Badenhorst.

Experience and instinct can be tested against the true performance data of a company, enabling rational and robust decisions to be taken on all aspects of business performance.

SAS promotes a business intelligence method to ensure that business analytics systems are implemented, supported and used correctly. This is achieved by focusing on the entire business analytics life cycle to ensure that all the components of an effective business analysis system are in place and support decisions in the company.

“While one facet of a business analytics system is to generate visual graphs and reports, the objective of such a system is to expose the true performance of the business to users, especially executive officers, to inform decisions.

“This interpretation aspect of business analysis is crucial and can be used to generate forecasts and scenario planning that, in turn, can support or invalidate corporate strategies by determining the effects of changes, based on the real data of a company’s performance,” says Badenhorst.

The mathematical algorithms used in analyses and model forecasts draw on the historical performance data of the business.

“SAS has a vast library of proven mathematical algorithms and formulae to apply to any business. SAS is a mathematical company at heart and mathematical algorithms remove the emotional component of decision-making to enable rational and empirical decisions,” he explains.

Once executives have a good understanding of the historical performance of the business, hypotheses can then be formulated and problematic areas identified. This enables companies to manage by exception, identifying and focusing on the problematic and underperforming parts of the business.

The analytics tool can also be used to forecast various strategies to recover distressed parts of the business and to enable rational and evidence-based decisions to correct or close underperforming or unprofitable parts of the business.

The tool can thus provide relevant information for a business, based on the information relevant to a specific department or division and on the complete performance of the company.

“Another hurdle to unlocking value from business analysis is for executives to use and trust the tool. A proven mathematical algorithm cannot generate numbers inconsistent with input, which is the actual historical performance of the business.

“Further, the analysis tool provides weight to scenario planning and determining the probable effect of strategic changes, enabling a board to identify risks, such as falling profitability or rising costs, and operational improvement opportunities.”

A business analysis system that operates on the whole business-analysis life-cycle method means that all analyses take into account all the operations of a company, improving performance and risk management, concludes Badenhorst.

Edited by Martin Zhuwakinyu
Creamer Media Senior Deputy Editor

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