Table of Contents:

Definition and Overview

1. Introduction

2. Shifting Business Landscape

3. The Evolution

4. Business Intelligence Capabilities

5. Data Warehousing Fundamentals

6. Methodologies and Processes

7. Conclusion

Self-Test

Glossary

PDF of this tutorial

Strategic Decision Support

This is the cornerstone to business intelligence. In this model, end users are provided with intuitive tools to distill information about corporate assets and their performance. Corporate assets include customers, products and services, network infrastructure, and employees. Typical performance measurements include profitability, availability, usage, sales, and lifetime value. Companies can now track key performance measurements, refine customer segments and scores, and optimize campaign strategies. Some of the typical strategic decision-support capabilities in the telecommunications industry include the following:

1. Develop simple reporting capabilities that allow one to measure and trend key performance metrics; these metrics include the following:
• install and disconnect rates
• call-center average sales per hour
• call-center average talk time
• campaign performance
• customer segment lifetime value
• peak network volumes
• uncollected receivables
• customer satisfaction
2. Develop complex reporting capabilities that allow one to uncover problems and discover new opportunities; typical areas for analysis include the following:
• market assessment
• channel planning
• competition assessment
• strategy and pricing
• customer penetration and profitability
• customer segmentation
• program definition
• recognition of patterns relative to customer behavior and needs
3. Develop statistical models that predict customer needs and behaviors; for example, one can build models that predict a customer’s likelihood to do the following:
• buy a new product
• generate high profitability
• respond to contacts through specific channels (e.g., direct mail, telemarketing, e-mail, etc.)
• not pay their bill

In addition, models can be built that predict network growth and fraud based on traffic patterns in the network.

Scoring and Segmentation

These provide the mechanisms for deploying score and segmentation rules developed through strategic decision support. Scoring provides processes that apply statistical models to each customer (or prospect). A score from one to 100 is then assigned to indicate how well the customer fits the model. For example, suppose that a model predicted who was likely to be a high-usage customer. This model would be applied to each customer and a resulting score would be assigned. A score of 100 would indicate a near-perfect match to the model, as opposed to a score of one, which would indicate that the customer did not fit the model at all. Segmentation provides a means for grouping similar customers. For example, one may segment the customer base between residential and commercial markets. In addition, one may decide to provide further granularity by defining segmentation within these subsegments. Defining customer segments is the first key step toward defining a customer management strategy.

Campaign Assignment and Management

These start where strategic decision support and scoring and segmentation leave off. Now that we understand what products to deliver, to whom and how, it is time to set up a campaign to orchestrate the contact activity. Generally, campaigns contain six key elements:

1. the list of customers to be contacted as part of the campaign
2. the channel to be used in reaching the customer
3. the product, program, and service to be offered
4. the incentive to be used in selling
5. the relationship relative to other campaigns
6. the priority relative to other campaigns

Once the campaign has been defined, it is executed via the contact management capability.

Business intelligence—and subsequently the data warehouse—plays a key role in this process by providing capabilities to generate customer lists (element one). Elements two through six are handled as business management activities, as a result of different data, access, and availability requirements. Attempting to perform elements two through six as business intelligence activities (via the data warehouse) is likely to constrain one’s information architecture over time.

Putting the Capabilities to Work

Now that the tutorial has discussed business intelligence capabilities that will be crucial to surviving in tomorrow’s business landscape, it will examine how these capabilities align to the needs of the business. Customer retention will serve as an example.

1. Strategic decision support would be used to track key performance metrics relative to customer install and disconnect activity. This would provide early warning of increasing disconnect activity.
2. If disconnect activity began to grow outside of acceptable limits, strategic decision support would be used to analyze why customers were disconnecting and extrapolate impact to profitability.
3. If the profitability impacts were not acceptable, strategic decision support would be used to formulate strategies for retention.
4. Once strategies were formulated, strategic decision support would be used to develop predictive models that would align retention strategies to the appropriate customers.
5. Scoring would apply these predictive models to the entire base of customers, assigning a score value between one and 100.
6. Campaign assignment would use these scores and other relevant data to assign customer lists to the appropriate retention campaigns.
7. Business management would initiate these campaigns and manage their execution.
8. As feedback is being returned from business management, input would be used by strategic decision support to refine retention strategies.

As may be deduced, a number of capabilities are needed to support a single business need (e.g., retention), and these capabilities are integrated through the business process. What may not be quite as evident is that these capabilities can be reused to support other business needs, such as customer care or fraud. Capabilities are essential to providing telecommunications companies with the ability to respond to the changing needs of their customers and the marketplace quickly and cost effectively. The data warehouse is a fundamental enabler to delivering business intelligence capabilities.