FSN: Why Business Analytics rather than Business Intelligence (BI) is key to competitive advantage.

Why Business Analytics rather than Business Intelligence (BI) is key to competitive advantage.

20th November 2006
Business intelligence (BI) as a genre of software is either dead or mortally wounded. One only has to consider the rapid consolidation of the BI industry as tools providers transform themselves into performance management vendors to see that this is the case. For example, Business Objects last month completed its acquisition of ALG Software, Cognos acquired Adaytum and Frango some time ago and Brio the BI software house was snapped up by Hyperion.

This teaches us that there is little future in simply being able to ‘slice and dice' data or present it in ever more inventive ways. Historic data has limited business value and rarely provides competitive advantage. On the other analytical applications that enable management to model trends and predict future outcomes can yield a step change in performance. But recent research by Professor Tom Davenport, the management guru, reveals that not all businesses are capable of delivering such competitive advantage.

Davenport , the President's Distinguished Professor of Information Technology and Management at Babson College , Massachusetts , was in London last month at a SAS sponsored roundtable discussion to present his findings following a research tour of 32 multinational businesses. He readily acknowledges that the use of analytics, statistics and fact based decisions in business is not new and most readers will be familiar with terminology such as Business Intelligence, Decision Support and more recently performance management. “What is new is that for an increasing number of companies, these activities have moved from the margins to the mainstream. For many, the use of analytics has become a primary activity used to support the overall business strategy,” he told FSN.

Davenport says that more companies are now choosing to compete based on analytics because analytical decisions are more often correct than decisions derived from intuition.

“That's not to say that there isn't a place for intuition,” he told FSN. “Some decision makers worry that an analytical approach removes the need for intuition but information systems are not perfect and it is not possible to test every possibility before committing to a decision. Even Amazon, which is highly analytical in its approach, will take decisions without underlying data.”

But with only 11 out of Davenport's sample of 32 businesses “clearly competing on the basis of analytical capabilities” there is some way to go before business analytics becomes commonplace. So what are the barriers to the successful deployment of analytics?

Companies in the top tier included Amazon, Yahoo, Harrah's, Capital One, Barclays and Marriott. Referring to these firms as “full-bore” analytics competitors they are characterised by top level management involvement and multiple initiatives under way involving complex data and statistical analysis. Furthermore, deployment of analytical activity in these showcase organisations is at the enterprise, i.e. non-departmental level.

The notion that top level management should be heavily involved should come as no surprise to readers of FSN since this has always been critical to the success of strategic projects no matter what they are. But CXO level executives still seem reluctant to get involved - really involved - rather than paying lip service to an initiative.

The importance of top management involvement is also underlined by another recent study carried out by Dr Bill Snaith and Professor Ian Stone of the Durham Business School . They say that, “Competence to mobilise resources, rather than resources per se , create value and personal relationships engender this mobilisation. Top management attitudes, senior management involvement in the implementation of IT and technical competence in the firm are key factors of success.”

Business analytics also involves sophisticated use of data. In an article published in the Harvard Business Review earlier this year, Davenport suggests that any company can generate simple statistics such as revenue per employee or average order size, but the ‘full bore' competitors look well beyond basic statistics. For example, Marriott International, the hotels group and an SAS user, which Davenport says is at the top of its game, uses predictive modelling to compare actual revenues as a percentage of the optimal ‘rack' or room rates that could have been charged. Using this measure, performance has steadily improved from 83% to 91% and is used enterprise wide to manage performance.

Winners in competitive analytics also use carefully constructed experiments to provide more data and improve decision making, says Davenport . For example, Capital One, conducts more than 30,000 experiments a year with different interest rates and incentive packages to see how customers respond. These experiments improve subsequent analyses and enable better decision making. They can also help reengineer certain processes by, for example, cutting out tasks that do not add value.

Davenport 's research suggests that successful companies focus their analytical effort around aspects of their business that give them their distinctive capability. For example, a web based company such as Yahoo or Amazon should concentrate on web based statistics whereas Barclays should concentrate on credit card statistics, for example, identifying customers with the greatest profit potential or the factors that will retain their loyalty.

“Understanding what drives customer profitability is the Holy Grail in retail banking,” said Eugene McCarthy, head of profitability measurement in Bank of Ireland's retail division. Bank of Ireland uses products from Cognos another vendor in the Business Intelligence space. “With the help of Cognos, we have been able to increase our understanding of our customer base, across all product businesses, as well as provide our customer relationship managers with meaningful, actionable information that impacts their decision-making process. Customer data is much more consumable and therefore, much more strategic to our organisation.”

“Knowing which customers are making and losing money, and why, at the net profit level, is an essential foundation of any customer segmentation strategy that includes improving profitability as one of it's goals,” said Chris D. Fraga, chief strategy officer at Acorn Systems Inc. “Armed with this insight, companies are increasing the profitability of their existing customer portfolio by aligning customer service levels to profit contributions, increasing business velocity with profitable segments, and re-negotiating favourable terms and pricing to maintain these profitable customers. Companies are also growing net new revenue profitably by proactively targeting profitable customer segments with marketing campaigns focused on profitable products and services.

Underlying the success of these ventures is a commitment to sizeable data stores, infrastructure and analytical tools but there is a danger that if all one's close competitors are using the same capability that any competitive advantage slips away. Speaking to FSN, Davenport acknowledges this possibility and recalls how one airline in the US set up a consultancy to advise other airlines, with the unsurprising result that they lost competitive advantage! “You have to be constantly moving and trying new things,” says Davenport .

Enterprise wide capability is the last part of the picture that characterises the ‘full bore' competitors. “Firms that compete on analytics don't manage it locally. They eliminate fiefdoms of data, centralise the data and expertise and manage analytics at the enterprise level,” says Davenport . This means that companies with patchy IT capability, based on multiple BI vendors are at a disadvantage. As a result, vendors such as SAS expect customers increasingly to standardise on a single BI platform and with the market for business analytics growing at around 10 percent per year there is everything to play for.

According to IDC' the worldwide market for business analytics software, which includes both application development tools and packaged analytic applications, reached $16.6 billion in 2005.

At first sight the fact that only 11 of Davenport 's sample were in the top category, i.e. “full bore” looks a little disappointing. But they were closely followed by another 6 organisations that had clear intent and were “almost there”. So just over half of the sample was either making good use of predictive analytics or on the brink of doing so.

On reflection it is a sizeable foundation and it seems that more organisations are switching their attention to the need for more capable analytics. As always top management involvement is crucial – “everything else flows from there”, says Davenport .

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