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Self-service BI tools increase efficiency, revenue

Self-service BI is able to increase business productivity and profit margins, says PBT Group's Armand`e Kruger.

Self-service BI is able to increase business productivity and profit margins, says PBT Group's Armand`e Kruger.

In the advent of technological evolution and the subsequent advancement of data, the wider adoption of self-service business intelligence (BI) tools and advanced analytical outcomes in business processes will continue to be the core focus for many organisations in 2016.

So says Armandè Kruger, Regional Sales director of business intelligence solutions company PBT Group. Kruger says one of the reasons businesses would turn to self-service BI tools to prepare data for analysis is to allow them the opportunity to effectively analyse collected data while increasing productivity and profit margins – to the benefit of the business.

He points out self-service BI tools, such as Chartio, Clearify WebFocus, Looker, Microsoft Power BI, Tibco Spotfire and more, can address a wide variety of questions within a business such as "What caused the dip in first-quarter profits?," "When did our market for this product really take off and what was the reason for it?"

Through these tools, business executives and managers are now able to generate their own queries against corporate data sets without requiring IT as a middleman.

"Self-service tools are by no means new and have been key in some BI businesses for the past five to 10 years, previously used to take monotonous and repetitive work out of the hands of the technologists and leave them with the more complex queries and reporting requirements.

"What has changed in recent times is that through these tools companies are not only able to produce quick analytical results but they will also increase efficiencies or revenue within a business," explains Kruger.

Discussing how these processes ensure a business remains relevant and competitive, he explains in today's age the end user is educated and hungry for data that will contribute to business productivity. As a result of this, organisations need access to the data and they will use these self-service tools to analyse the data without having to wait for a report that has to be subjected to normal processes and controls such as standards, redundancy, recovery, validation etc.

"Important to note is that these self-service tools tend to create "throwaways" – i e. a report or query to answer a specific question or analyse a specific trend without necessarily the need to re-use it," he adds.

According to a report published by Gartner in 2015 focusing on BI and analytic tools in business, Gartner predicted that by 2017, most business users and analysts in organisations will have access to self-service tools to prepare data for analysis.

The report revealed software developers will likely focus their efforts on developing algorithms for data that will automate up to 80% of all decisions people have to make on a daily basis.

It further found self-service data integration will do for traditional IT-centric data integration what data discovery platforms have done for traditional IT-centric BI: reducing the significant time and complexity users face in preparing their data for analysis and shift much of the activity from IT to the business user to better support governed data discovery.

Kruger advises if algorithms (a computer formula for solving a problem) are being used to reduce one's workload, one may find that a substantial percentage of work tasks can be automated because the worker may have acted in a consistent way to information most of the time.

In simple terms, he clarifies, data analytics take information within the business and when ‘mined' correctly, this information can be used to predict future outcomes for an organisation.

Data analytics can add a huge amount of value to an organisation wanting to increase effective decision-making, especially if it is applied and incorporated within various areas of the business – like sales, marketing and the call centre, he says.

"The biggest benefit of self-service data integration is time. Self-service allows for quick analysis and quick responses. The other benefit is that it allows the analysts to analyse and the technologists to attend to complex technological challenges. Each one doing what he or she does best".

Talking about the cons of self-service, he says: "The downside is really a mindset change of transparency. We were schooled in a siloed environment where data was separated by barbed wire and sharing it outside of a department would have been unthinkable and outside of a company, absolutely ludicrous."

Kruger concludes by sharing three laws of nature: "Data is an asset", "Businesses have to be data-driven" and "without analysis there can be no strategy or future".

He adds the BI industry has passed the point of educating and needs to move to a role of active participation where the value of BI becomes tangible and undeniable.


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