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OLAP Applications

Published
  • June 01 1999, 1:00am EDT

Over the last 15 years, we've seen corporations shift their strategic initiatives in an effort to reduce costs. Most recently, as products have become commodities and companies compete in a global economy, emphasis has changed to increasing revenue ­ getting higher margins from products and customers. Software industries emerge and flourish with each strategic initiative. Along the way we've also seen a growing need and market for data analysis tools to help companies take the raw data tracked in the transaction systems and generate information that drives decision making. Starting in the early 1980s, the primary goal of many companies was automation of business processes. This involved an investment in hardware and software to validate and capture data to support these processes. The most common of these were mainframe-based transaction systems supporting finance, manufacturing and human resources.

Once automated, companies turned their focus to process improvement (late 1980s). This started with an emphasis on total quality management standards (TQMS). It involved instituting business practices that guaranteed quality in many or all activities of the enterprise. After TQMS, came business process reengineering (early 1990s). This was an often-painful process designed to streamline business practices to eliminate nonessential activities, procedures and, in many cases, people. We were introduced to the term "downsizing" through these efforts.

Increasing the Top Line

These initiatives all had one goal in common: to reduce costs. Now that costs have been cut, how can companies continue to add value for their shareholders? The answer: increase the top line ­ increase revenues. Extensive studies have shown that improved customer acquisition, customer retention and growth can have a significant positive impact on revenues.

The latest corporate strategic initiative is customer management driving the development of customer relationship management (CRM) software solutions.

A successful implementation of a CRM solution will benefit nearly every department in a company. The obvious areas of impact are sales and marketing and customer support. But also consider the ramification on departments that do not traditionally interact with the customer ­ for example, product development and finance.

CRM solutions impact product development through improved tracking of product defects as well as enhancement requests. Also consider that if analyzed properly, this type of data can be used as input to drive product development decisions.

There are also benefits for the traditional "back- office" side of business (e.g., finance). As a customer's needs and wants are catered to more efficiently, the departments that track and administer related tasks such as billing, purchasing, contract administration, etc., will see benefits. As data is proactively forwarded to each department, request for information from finance regarding contracts, receivables and maintenance will be reduced. More accurate information will also lead to fewer customer inquiries.

Thus the impact of a CRM implementation can have wide- reaching effects. Often the implementation of a CRM system provides additional accountability relating to customer satisfaction. Thus, the aspect of measurement becomes critical to each of these areas.

Emergence of Data Warehouse/ Analytical Solutions

With the emergence of transaction systems throughout the years, we have seen a subsequent emergence of data warehouses and analytical solutions. Standard two- dimensional reports of transactional data proved inadequate to drive effective business decisions. It became obvious that analytical solutions ­ such as executive information systems (EIS), decision support systems (DSS), on-line analytical processing (OLAP) and data mining ­ were required to make business sense out of the increasing volume of transaction-level data.

The same cycle that drives business decisions has driven the need for DSS during the last 14 years. The first step is to analyze, the second is to discover and the third is to take action. Figure 1 shows this cycle with examples focusing on the customer management process.


Figure 1: Decision-Making Cycle

Consider This

A company has been tracking the products and services that its customers have purchased after an initial contract is signed. Instead of listing the customers and the associated products, they analyze the data in a multidimensional business model to answer the following questions:

  • How long after a sale do customers usually purchase product x?
  • What type of customer is purchasing what type of product/service by geography, by product line, by sales rep?
  • What is the context of transaction relative to the sale: which products sell well by phone versus by letter, including the ability to review all by time of year, geographic region, etc.?

The analysis of information in a business context will lead to discovery of valuable knowledge regarding customer growth. This, in turn, will drive action (e.g., putting into place cross-selling marketing campaigns, new support procedures, etc.)

This process can only be supported by an intuitive DSS solution that supports the aggregation of data in a business context using OLAP (multidimensional) technology. The benefits of implementing a CRM solution are tremendous in terms of optimizing the process surrounding the customer. However, without the implementation of DSS solutions, many organizations find that they simply are not getting the information they need to drive decisions across the enterprise ­ even after directing significant funds toward licensing, implementing and maintaining CRM systems. The reason: information is locked in the transaction system.

Analyzing through DSS

Knowledge gained via DSS capabilities through the process is valuable to all departments within an organization.

The analysis of the CRM data helps each department focus on the key aspects of customer management that they impact, from acquisition to retention. The analysis will allow users to track financial and operational performance for a specific customer or across all customers. In the end, the more informed each department is regarding the customer acquisition, retention and growth processes, the more effective decisions they will make resulting in improved customer satisfaction.

Too Many Tools

Over the last few years, we have seen companies spend significant dollars on data warehousing and decision support projects relating to the customer as well as the sales process. Too many OLAP offerings provide only the potential to solve business problems but don't deliver analytical solutions "out of the box." To fully empower CRM solutions, there must be out-of-the-box OLAP solutions available to analyze information.

Investing in an application gives the benefit of delivered functionality and frees the development staff from worrying about upgrades or keeping current with the technology and infrastructure (e.g., releases of operating systems and Web browsers).

Microsoft's Impact

Microsoft's OLAP Services has begun to shake up the market. More organizations are likely to discover OLAP as soon as they install Microsoft SQL Server 7.0, which includes Plato. But as a "free" product, users can't expect sophisticated functionality. Nor does Plato include "out-of-the-box" applications that answer questions such as:

  • Which products contribute the most to profitability?
  • What organizations have exceeded their spending limits by more than 10 percent over the last quarter?
  • What color packaging sells best in the central region in summer?

That's the rub. These are the types of ROI- resulting questions that decision-makers want answered quickly ­ not when IT has time to build an application.
Common applications, such as ranking, exception alerts and 80/20 analysis, apply to all types of enterprise information including sales, customer or operational data and are the bases for significant analysis done in the enterprise. By leveraging delivered "out-of- the-box" applications, business intelligence solutions can be deployed rapidly to a broader numbers of users for maximum return on investment. With these applications also available on the Web, everyone in the organization can partake in swift, intuitive access to key information.

An Example

To understand the power of OLAP applications combined with CRM systems, consider the following example. A large multinational pharmaceutical company was looking for ways to provide valuable information to its sales reps and sales managers. The company deployed a sales force automation system to help automate the day-to-day tasks and reduce their time on administration work, but it still lacked an aggregated view of its productivity and target customers.

In addition to creating the information for the sales reps, it faced an additional problem of deployment. Thousands of sales reps and sales managers were spread across the globe, and real-world experience shows that field sales forces simply don't or won't use valuable data and information unless it is succinct and easily available to them. Thus, providing analysis over the Internet was the obvious choice, but it required a solution to provide an intuitive interface to thousands of reps, without creating thousands of copies of the analysis.

By implementing a business intelligence solution through the Internet that focused on both transactional and industry-provided data, the sales reps were able to easily analyze information about their prospects ­ the products they were prescribing, their buying patterns and their overall practice. The architecture of the Web- based solution allowed the deployment to thousands of reps accessing a common multidimensional model.

Additionally a business intelligence solution focusing on sales performance relative to the metrics the managers put in place was made available to the district managers around the world. With the support of a highly scalable Web solution and the ability to handle a very large database, the solution provided efficient analysis of large amounts of detail.

The result: Through targeting analysis the sales reps were able to focus on the right prospects and sales managers were able to uncover successes and weaknesses, leading to overall improvements in the customer acquisition process (more revenue!).

Bottom Line

Business and IT professionals will increase their demand for delivered business intelligence solutions that answer questions about what drives their enterprise ­ not just the "ability" to address those questions. The OLAP marketplace is in swift transition from a tools approach to a solutions approach. The faster that key information can be used by large numbers of users to answer their questions and sustain competitive advantage, the more successful the initiative. Through these delivered applications, companies obtain the complete picture of their customer interaction to effectively drive decisions to improve customer acquisition, empowerment, retention and growth. The result is increased revenue and stronger profitability.

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