BI smarts that let you ‘up’ your game

Greg Bogiages, Director at Cortell Corporate Performance Management
After two decades, demand for Business Intelligence remains high. What has changed is that data volumes have exploded and markets are increasingly volatile, emphasising demand for faster, more accurate, and deeper insight into business performance. and the potential impact of market forces on operations and earnings. Analytics provides a competitive advantage – and unlike the solutions of yesteryear, these systems are today within reach of most and take hardly any time at all to implement and show a return.

With an extraordinarily difficult global economic cycle barely behind us, the need for BI to make more informed decisions, enhance customer loyalty, better tailor products and services and improve business performance can hardly be understated. It is something the entire organisation is aware of, which has to a large extent influenced the democratisation of data – where the whole organisation, not just management, has access to BI reports.

Analytics, along with fast integration of BI to multiple layers and systems within the organisation, takes this step further, providing organisations with a competitive edge -in terms of understanding current business outcomes, in terms of prediction or projection of outcomes, and in terms of planning.

These benefits are available to a much broader segment of business as many of the BI truisms of yesterday are today myths. Open standards have taken care of most of the integration challenges, allowing any number of BI tools to be combined. And there’s no need, and often no advantage, to standardising on a single BI platform. A SAP financial and Oracle HR module today integrate with ease to deliver tailored BI reports. Or, to use a very relevant example, SARS may require its reports in a particular format, one that is easily facilitated by BI and accounting packages using XBRL

And when it comes to the time required to implement BI, Cortell’s view is that if you don’t have a quick win within three months, alarm bells should be ringing.

BI tools and solutions are now hugely more sophisticated than five and 10 years ago. Faster processing of data and richer visual outputs are a necessary essential and even entry level tools enable trend identification and present reports in a graphic format that can be easily manipulated by the user for deeper insight.

The single greatest challenge for BI in any organisation, however, is that it must be reliable. The death knell of any BI solution is sounded when users stop trusting the data. This is a matter of ensuring the underlying data used by the BI solution is accurate and up to date, and that the whole organisation uses a single layer of data for decision-making.

The challenges of complexity also seem to work in cycles. The evolution of analytics has led to BI becoming more complex. This has led to some resistance in terms of BI tool adoption by enterprise users. Many BI vendors are thus currently using ‘simplicity’ as a differentiator. And simplicity is of the essence – it is what has made Google what it is today. The clutter is thus being removed from BI interfaces and navigation is being simplified.

In terms of analytics, however, it is often difficult to strike a balance. Analytics was previously considered an elite division within an
organisation. Today, no-one wants to stand in a queue, so analytics is becoming the domain of everyman within the organisation. Yet identifying a trend may require expertise and insight, and like any system the quality of the query will determine the usefulness and accuracy of results. Thus, if important KPIs are excluded, results may be skewed.

The value of analytics can be considerable. A typical example is fraud detection. Credit card companies and banks are focused in on unusual transactions or anomalies in terms of account management. By recognising these triggers they can act quickly to stop fraud.

Similarly, analytics can be used to lower the risk of cell phone or loan companies. Using basic data, credit scoring will identify the probable propensity of an individual to default and then predict the right product/pricing to suit the individual. Analysis of customer history similarly enables greater cross- and up-selling of products to the individual.

There are three easy rules to follow when implementing BI: understand where you can achieve quick wins; always take a modular or phased approach; and just because the tool can do something doesn’t mean it needs to be done – the investment needs to provide a suitable return.

The future of BI is already being played out. BI systems have more users and the budget for BI is back with the business, and not with IT. Web services are also seeing BI being offered as a hosted service. As bandwidth and the reliability of connectivity improves in Africa, BI software as a service will see greater adoption.

Greg Bogiages, Director at Cortell Corporate Performance Management