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BI in South Africa – a continuing evolution

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In South Africa, the implementation and use of Business Intelligence (BI) systems has come a long way over the last five years, reaching high levels of maturity in numerous organisations. As an ever-evolving system, the BI lessons learnt serve to inform those just starting out, while new ways of communicating and doing business point to new information management challenges on the horizon.

Says Carlo Gunter of e.com institute, a business solutions provider: "BI was previously regarded by business as a 'nice to have'. Now it is essential to global competitiveness. From mere delivery of departmental reports, BI is becoming an integral tool for the entire enterprise.
"Acknowledged as a key component within the Performance Management (PM) agenda and Business Process Management (BPM), the next frontier is where BI will be used to assist organisations to get a more accurate view of their future business landscape, utilising predictive analysis."
The foundations of information management were laid 20 years ago with the introduction of data warehousing, then little more than an accumulation of data from different systems to enable reporting from a single database. The development of BI systems followed. A 'visual enabler', BI provides the means to manipulated structured data easily, displaying it in a comprehensible visual format.
Says Gunter: "Today, BI is used at every level of the organisation to inform decision making, but it no longer only delivers reports. Gaining a competitive advantage in the current dynamic business realm means organisations must be able to plan better and manage the organisation better. BI has evolved to enable this.
"Components of the BI solution, which include scorecards, dashboards, reporting and analysis, are used for predictive analysis and planning, assisting organisations to gain a broader view of the businesses' performance (right down to process optimisation) and the risks to which it is subjected – and manage these."
The increased use of BI within an organisation often parallels its growing maturity with regards to the use of data.
Explains Gunter: "As organisations begin to structure their data better, it grows from a mere random collection of facts and figures (data) to become information.  With more information to hand, organisational knowledge grows. This knowledge can be applied in ways that provide a glimpse into the future. Predictive modelling, which falls into the realm of artificial intelligence, is a prime example.
"Artificial intelligence (AI) uses past experience and historical information to find predictable patterns that clarify the future – an accurate weather channel for data if you like. For example, if a company wishes to introduce a new product into the market, predictive modelling makes use of historical and current business performance data (such as sales figures, financial behaviour and customer profiles) to give the organisation a clear idea of which segment of its client base is most likely to purchase the product and how it will fare."
However, reaching this point takes more than the implementation of a data warehouse and BI solution. Says Gunter: "BI fails for a few very key reasons: when there is no executive buy-in; when BI is seen as an IT project; and when BI is considered a finite project.
"Where BI is seen only as an IT project it is usually doomed to failure. All successful BI projects are driven by business. There is also no such thing as a 'finished' BI project.
"Implementation is just the beginning. A BI system (which includes the data store) must grow and evolve with the business if it is to continue to deliver value. New business rules, such as those dictated by a change from a monthly payroll to weekly, daily or hourly payment will, for example, require a change in the BI system."
Successful BI is also dependant on accurately assessing the maturity of a businesses' data and determining its information needs.
"Organisations need to understand the level of maturity of their data and of data use within the business, and also understand the level of maturity they need to achieve. For example, if they want a report and don't have the system to generate the information or from which to extract it, it's a waste of time putting in a data warehouse," says Gunter.
Companies should also not fixate on best practices and methodologies but use what will best fit their business needs. The size of the data warehouse, for example, should be determined by the amount of data that needs to be analysed and the timeframes in which this needs to be done.
As business evolves and communication methods change, so too must information management. New legislation and the drive to AI has set the next big challenge. To date, structured data has been the sole focus area for data warehousing and BI. Now companies need to begin thinking about how, and if, they should store unstructured data like emails, telephone calls, faxes and drawings. A clear understanding of what information is critical to drive business competitiveness needs to be achieved.
This takes business intelligence to a new level but also reflects the need to ensure its continuing relevance to the business. BI is not a closed system. It relies on human intelligence to create and extract value.
Key questions organisations should ask themselves when defining their BI initiative include following:
* Will static reports do or are ad hoc reports created on the fly necessary?
* Will the business rely on IT to create the reports or does it have the necessary skills within the lines of business?
* What level of growth in terms of using the BI tool is expected across the organisation?
* Which areas of the business anticipate using the tool?
* Will the business only need reports or does it want to do performance monitoring and predictive analysis?