Don't let growing software choices divert you from path to useful business analytics

Tread carefully to find holy grail of clear data for practical use


Tread carefully to find holy grail of clear data for practical use

Business intelligence is at a crossroads. Commentators are increasingly asking in what direction the softwareis heading and whether, amid all the consolidation and competition, its original purpose is being forgotten.

The basic reason for having business intelligence systems is to provide a single, consistent and robust view of an organisation. However, they have changed substantially in the past five years.

There used to be three basic categories of tool:

  • Online analytical processing (Olap) applications were used to build huge databases called "cubes". These were designed to answer a wide range of questions.
  • Management information systems (MIS) drew on the functionality of SQL Server to answer particular management questions.
  • Executive information systems (EIS) were dashboards that could pool information from various sources to aid executive decisions.

But the benefits and limitations of each of these approaches has led to a merging of the categories.

For example, Olap is powerful but not particularly user-friendly. If a cube of quarterly sales data is assembled, it may be out of date by the time it is ready. Should an executive want to ask a question of it that was not anticipated, this could cause problems. So Olap suppliers have developed more intuitive front-ends and geared the tools for the real-time enterprise.

Conversely, MIS and EIS applications have tried to capitalise on their flexibility by moving in the opposite direction: they have gained analytical substance by copying Olap characteristics. In the process, suppliers have been bought and sold, brands have disappeared and others have gained ground.

Jon Crews, a partner at PA Consulting Management Group, divides the growing number of products into three types. First is enterprise-wide business intelligence, from companies such as Cognos and Business Objects, which are substantial enough to provide a corporate-wide view, and robust enough to supply data feeds to the supply chain and customers.

Second, business intelligence is bundled in with other corporate applications, notably from SAP and Microsoft.

Third, there are niche applications for particular needs. "For example, Hyperion is often thought of as the business intelligence tool for accountants, and SAS has found niches in a variety of areas," said Crews. Other suppliers include Microstrategy, which is particularly strong in retail, and Applix for finance and insurance.

Overall, sales of business intelligence tools are growing. According to the annual Olap Report, the market continues to grow faster than most other enterprise software sectors, increasing by 16% in 2004.

IDC has predicted the global market for business intelligence products will grow to £3.1bn by 2009, with Business Objects the leading supplier. The analyst firm said the company is growing two and a half times faster than its nearest competitor.

However, it is hard to make comparisons between different products. Business Objects software may be regarded as the leading pure-play corporate business intelligence tool, but Microsoft products are widely found in smaller organisations.

"A continued maturation of this software market is leading to increasing adoption of business intelligence tools throughout organisations of varying sizes," said Dan Vesset, research director, analytics and datawarehousing at IDC.

It is a market replete with choices. There are premium products that, for the right price, will do everything. There are low-end products that satisfy the needs of specific business decision-makers. But analysts are concerned that the basic value of business intelligence systems is being clouded by market consolidation and competition.

Frank Buytendijk, research vice-president at Gartner, believes the central issue is whether business intelligence enables the chief information officer to present the chief executive with one version of the truth. He suspects that although business intelligence has come down from the top of the "hype cycle" (when supplier claims reach their peak), gaining one view of the organisation may be as difficult as ever.

The past few years have not been without progress, however. "What has happened is that corporate infrastructures have become much more centralised. Companies no longer have multiple business intelligence tools all over the organisation," said Buytendijk. "That business intelligence is now infrastructure- heavy and application-light is the right balance, but the functionality still needs to be pushed back to the users."

However, other commentators are not so sanguine about the centralisation of the infrastructure. They point out that if you put bad data in, you only pull bad information out. "The data layer is the biggest problem," said Royce Bell, a partner in Accenture's Technology Practice.

He said much has been spent at the functional level, orienting business intelligence to business needs - for example, in response to regulatory demands - and this has led to silos of information.

"People have put single enterprise-wide databases together in a few cases, but mostly companies create a warehouse to deal with financial analysis, compliance needs, and retail requests: multiple warehouses that then exist in silos," said Bell. "And the amount of data in the organisation is only going to grow, when you add new sources of data, such as RFID flows."

This has been referred to as information entropy, the idea that, left to its own devices, data becomes more and more chaotic. "What is required is an integration plan at the highest level," said Bell.

Bell's thoughts are echoed in research from IT services firm Unisys. According to a survey of 250 European IT directors, 60% believe their business intelligence investments have yet to significantly improve customer management; 27% of companies cannot cross-sell between divisions or products; and 32% of all customer data still requires manual analysis.

Steve Rawsthorn, Unisys vice-president of sales and marketing, systems and technology EMEA, said many companies think they have a business intelligence strategy once they purchase a business intelligence application.

"CIOs need to ensure that there is an infrastructure in place that can monitor a mass of data streams in real time, enable huge databases of information to be shared across departments, and provide sufficient storage capacity to analyse data quickly and effectively," he said.

"Inadequate systems specification means that, despite implementing the most sophisticated software, companies cannot even mount all their customer data simultaneously for analysis or to cross-sell."

Although organisations are using business intelligence products for a range of tasks and are keen to do more, questions remain about the direction suppliers are taking. Systems may generate useful corporate knowledge, but to exploit them further companies might have to get smarter in using them.


Case study: Software powers Powergen campaign strategy

Energy supplier Powergen is using business analytics from KXEN to fine tune the way it targets customers and prospects with the most appropriate energy packages for their needs. Even early on in its implementation the results are encouraging, according to Powergen's head of customer relationship management Mark Perrett.

"The first time we used a KXEN-generated model to support campaign activity we saw a 20% rise in sales and a direct £150,000 saving in mailing costs. Those figures represent an excellent and speedy return on a software investment. More importantly, we also retained 300,000 customer contact opportunities for future campaigns, having been told by KXEN that a successful sale was unlikely to result this time."

Only four analysts were needed to do the modelling. Perrett said he has heard of other organisations where many more analysts were needed to do similar work. Also, rather than taking several weeks to build one model, the software took minutes.

KXEN puts its flexibility and speed down to the use of mathematical rather than traditional statistical techniques when it comes to building models.

"We did get KXEN initially for a very specific purpose but on the strength of our early experiences we are going to invest some time in exploring its other capabilities," said Perrett.


Case study: Peacocks tackles till-based fraud

Clothing and homeware retailer Peacocks has installed Fraud Alerter software from Innovetra to help it tackle the problem of fraud at the point of sale.

Peacocks will use Fraud Alerter to analyse till data from 420 stores. The software will identify suspicious transactions and highlight excessive use of tills' training mode, which can be used to disguise fraud.

The increased speed and efficiency with which the firm's loss prevention team will be able to act based on the data is expected to cut losses from till-based fraud and provide a strong deterrent to staff.

"We are confident it will play a significant part in preventing fraud and stock loss," said Chris Miles, operations director at Peacocks.

"The data is mined overnight and the loss prevention team will have indicators of suspicious activity on their desktops first thing each morning, enabling them to start investigations immediately. Previously, such information was not available until two or three weeks after the event."

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