Customer acquisition, retention and extension have become a fine art as product markets increasingly turn into buyers' markets. The cost of winning customers' is growing exponentially as numerous companies jostle for customers' attention. The barrage of junk mail that inundates every customer lowers the effectiveness of current methods of promotion. Even after companies successfully woo customers, they run a significant risk of losing them to competitors. The opportunity cost of losing customers is not only the promotional costs invested in them but also the potential revenue that could be earned from cross-selling opportunities. Companies, therefore, need to find innovative ways to cultivate their bonds with customers. Business Intelligence helps to mine customer data and uncover opportunities for building better relationships with clients.

The financial services industry scours for data that will help to improve the accuracy in the estimation of risk and the associated costs of managing it. Historically, the financial industry has been unable to use its information which lies scattered across several departments and companies find it hard to aggregate it as long as it is in its paper form or is stored in legacy systems.

Zurich North America specializes in providing property and casualty insurance to commercial enterprises in the US and Canada. While Zurich is among one of the more expensive insurance providers, corporate customers, mostly manufacturing companies, value it for its services. In the past, Zurich provided its customers with a CD-ROM which had information on claims filed, in each of their factories, and was useful in planning for the expenses of insurance coverage. Over time, customers became impatient with the delays in receiving the information. Zurich responded by creating an extranet, called Risk Intelligence, which allowed customers to access data in real time. The substantive benefits from the extranet were to come later when Zurich decided to collate the data for all customers, disaggregated by geographies, industries, etc, which allowed customers to benchmark their data with their industry and to find the underlying causes from comparisons.

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Supply Chain

The modern enterprise is no longer a self-contained institution onto itself; it has evolved into a complex web of collaborating companies. Outsourcing of business processes, supply sources and services creates a complex network of an extended enterprise. Business activity monitoring reaches beyond internal flows to external inflows sometimes spread across the world. Enterprises have to ensure that the manufacturing and transportation of supplies from its collaborating group of companies is so synchronized that consumers receive the products in quantities, types and time they need. Companies have to learn to optimally select their sources of supply and then co-ordinate with them till products reach their destination.

The management of supply from the extended enterprise entails several different challenges. Companies have to be able to place orders well ahead of the time so that they reach in time to be sold. Also, the company placing the order has to be able to communicate with to their vendors information on seasonal fluctuations of demand, changes in preference and geographical variations in demand so that they can plan their production schedules. Ideally, the purchasing company wants to minimize the time it has to stock the product.

Increasingly, companies are changing their strategy towards the management of their supply chain, hitherto seen as an adjunct function, to a more demand driven approach. They use forecasting tools available with business intelligence software to determine their needs and to place their orders with the vendors. The buyer shares information on a common business intelligence platform. Business intelligence tools help to monitor the replenishment needs of companies as they compare the flow of demand and supply. They are also able to manage their logistics in real time as they receive information from the vehicles bringing the supplies.

The magnitude of the benefits can be gauged from the experience of IBM which has one of the most complex supply chains in the world. It had expected cost savings of $2 billion when it set out to lower its supply chain management costs of $40 billion in 2002. By 2003, the company cut its supply chain costs by $7 billion from lower inventory costs alone. Additional benefits from efficient management of the supply chain are the higher turnover, stocks move faster so that outstanding sales have been reduced by an average of four days, reduction in overheads such as warehouses and trucks which IBM does not need to own any longer, contract negotiation takes less time as both parties have the same information and lower costs of managing account receivables and payables.

When companies are able to anticipate and communicate changes in demand, they can save the expense of procuring goods from higher cost vendors. TruServ, a member-owned hardware cooperative of 7,000 or so independent retail stores, found a wrought-iron park bench at a bargain from China. Initially, the stores placed orders for 17,000 of them while the buyer for the co-operative decided to buy 40,000 of them. Eventually, the sales touched 92,000 and Truserv had to procure many of them in the USA, at a high cost, to meet the entire demand. Despite the unexpected bonanza of sales growth, Truserv was able to just about break-even on the order.

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Demand Planning

When it comes to forecasting demand, individual stakeholders in business have conflicting interests. The retailers lose most from loss of sales opportunities and they would rather overestimate demand than face disappointed consumers. They have a vested interest in placing larger orders, especially when sales growth is brisk and vendors have limited capacity, than their needs warrant. The manufacturers, on the other hand, prefer to bunch orders so that per unit costs of transportation and administration remains low. Sales personnel make deals with customers to book orders, later returned, to ensure that they earn their annual bonuses. Academics call this the "bull whip" effect or swings in demand triggered by pressure rather than actual needs.

Business intelligence systems, specifically Collaborative Planning, Forecasting and Replenishment (CPFR), enable each party to share information about the entire business activity and estimate the demand more accurately. Wal-Mart took one of the first initiatives in this direction by involving Proctor and Gamble in such a project.

In the past, a lack of collaboration stymied the co-ordination of promotions and supply; vendors were unprepared for surges in demand caused by incentives. Nabisco increased visibility to variations in demand by letting Wegmans, a grocery, access to its information. Its Planters sales vaulted 40% while the fill rate for its warehouse increased from 93% to 97%, and inventory dropped by 18%. Cisco used to similar system to share information with the flexible manufactures who could then directly supply goods to customers eliminating the need for its own distribution system.

Demand forecasting failures are the bargain hunters dream; scarce space compels retailers to dispose inventory at a loss. Manufacturers' ability to estimate market size is confounded by a growing list of unknowns; competition and price changes, creative destruction by innovative new products, productivity growth besides the familiar factors like seasonal changes, quirky weather and misjudgment.

Business intelligence and forecasting tools has brought about a paradigm shift in the management of demand. Analysts find in the data early indicators of the demand for their products; game producers, for example, have learned to anticipate the demand from the early reservations of their products.

Forecasting tools, to be sure, are imperfect or make predictions with unacceptable margins of error. The availability of real time data allows analysts to continually modify their models and reduce the margin of error by taking into account the impact of events as they happen.

Sara Lee's household division needed to considerably improve its forecasting accuracies as it increasingly it sought to introduce its European brands into the USA. The lead time for importing goods from Europe is 12 to 14 weeks; the company had to increase its safety stocks to ensure that it had enough to meet unexpected changes in demand. Its software tool was able to generate forecasts at the brand and SKU level; the detailed forecasts elicited interest from sales staff and their commitment to feed data to the system. The accuracy of the forecasts increased from 51 percent in 1998 to 73 percent in 2002. The order fill rate is as high as 93 percent considerably lowering the need to hold inventories.

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Operational Risk: Enterprise Wide Risk Management

The daily activity of an enterprise is fraught with risk at several different operational levels. At any given point of time, the employees of a company are likely to be injured as a result of improper functioning of equipment. The inventory in the premises of a factory is prone to fire. Fraud is among the better known operational risks and widespread. According to Association of Certified Fraud Examiners (ACFE), losses from fraud and white collar hacks account for 6 percent of an enterprises' annual revenue. Gratuitous behavior, such as overly risky positions by a trader in an investment bank, could jeopardize the financial viability and entire institution. Stormy weather could delay the delivery of goods and could lead to loss in sales. Political turmoil could cause disruptions and unexpected surges in commodity prices. Consumers, employees or others could unexpectedly file law suits. Companies can also be overwhelmed by catastrophic events such as a terrorist attack or a storm.

In the past, companies have sought to monitor, control and lower these risks by bureaucratic methods such as forming committees to oversee fraud. These committees institute policies that slow down business processes and add to costs and discourage individual employees from taking initiative. Business activity monitoring software, a type of business intelligence software, on the other hand, achieves the same objective by monitoring individual transactions and raises an alarm whenever an unusual behavior is noticed. The software for detection of fraud in credit card transactions, for example, looks for patterns in purchases of a customer and investigates any abnormal change prompts verification from a financial institution.

Operational risk are typically unnoticed till the compounded effect of a lapse in one corner of an enterprise snowballs into a catastrophe. This happened to the Barings Bank when one of its traders in Singapore engaged in egregiously risky trading behavior. Similarly, a steady neglect in the maintenance of equipment could eventually lead to a major accident and a liability suite against a company. Dashboards empower companies to constantly monitor operational parameters against benchmarks, anticipate a problem and preempt it.

The traditional approach to risk management is to transfer risk to financial institutions by buying insurance or by purchasing futures and options. However, this kind of risk management is appropriate for measurable and known risks. Companies have to be able to manage unexpected adversities which can significantly impair their businesses. Business intelligence brings transparency in businesses and enables prediction of future risks. It provides data quickly for companies to mitigate risk.

The airlines industry is one industry where time schedules change frequently as airport authorities respond to events such as weather changes. Any one change in schedule affects all successive flights as well as the timing of supplies required for serving passengers and baggage movements besides the work plan for the employees. The risk of disruption of flights exists all the time when plans employees have to be instructed on the fly. Delta Airlines has installed business activity monitoring software to manage the logistics in real time including all the alerts to employees to ensure all goes according to plan.

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Regulatory Compliance

Sarbanes-Oxley, the corporate governance legislation implemented after the disclosure of a raft of accounting scandals in 2001, has substantially increased the reporting requirements for American corporations. The burden of compliance has increased to an extent where several companies now prefer private limited company legal status. According to the Corporate Executive Board (CEB), the audit fees for KPMG fees increased by an average of 109 percent, Ernst & Young's, an average of 96 percent and Deloitte's by 78 percent following the implementation of the Sarbanes-Oxley Act. In 2004, a sample of 43 companies investigated by CEB increased their expense on compliance with Sarbanes-Oxley by $5 million to $8 million. The primary reason for the increase in the costs is the detailed documentation and reporting required by especially Section 404.

Sarbanes-Oxley legislation holds chief executives responsible for any malfeasance in any activity in the enterprise. It would not any longer be possible for them to feign ignorance when an accounting lapse or poor management leads to an erosion of shareholder value. In addition, companies have to inform shareholders about any material change in the company within 48 hours. The implementation of Sarbanes-Oxley requires detailed transaction level monitoring of enterprises and rapid reporting of an adverse turn of events which is only possible with business intelligence software.

Companies can lower the costs of compliance if they use their systems for business activity monitoring for regulatory reporting as well.

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Basel II

Basel II norms make a departure from past practices of administrative monitoring of capital adequacy requirements for financial institutions. Basel I required financial institutions to maintain a minimum level of reserve capital, as a share of their total lending, to meet contingencies regardless of their risk exposure. In the future, financial institutions will be granted greater autonomy, as laid down by Basel II, in determining their capital reserves which can vary depending on the risk management needs of an individual financial institution. Hereon, financial institutions will be required to take into account all their risks including credit risk, market risk, liquidity risk, operational risk, etc. They will be expected to disclose all the information required to assess the total risk and adequacy of the capital reserves. Consequently, financial institutions will need to gather detailed information and report it in real time which they can do with business intelligence systems.

Regulatory compliance has turned out to be a blessing in disguise where business intelligence software has been implemented. Banks like Harris Bank and Dresdner are now able to compare the risks of lending against the profitability for each of their customers and optimize their portfolios.

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