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Yours, mine and ours

Integrating data from multiple business areas improves decision making.

by Randy Lea and Imad Birouty

Every day, countless decisions are made by every person at every level of an organization. Success depends heavily upon how well those decisions are made.

Organizations go to great lengths to provide information to their employees to help them make the best choices. In fact, companies that build decision support systems to accomplish that goal tend to stand out as leaders. These organizations leverage their data in a way that gives them greater insight into their business. Accordingly, they can consistently make smarter, faster decisions that yield streamlined operations, effective customer service, improved revenue and market growth.

Getting to intelligent conclusions often requires information from different areas of the business, including inventory, sales, marketing and financial data. Bringing this data together in a timely and meaningful manner is the key to getting the right information on which to make choices. Companies that do this will enable differentiated decisions solidly based on all available facts, which gives them a competitive advantage.

Cross-functional analysis of data is essential to making differentiated business decisions. Consider the retail scenario described in the images to the right. In this situation, a certain style of sunglasses was selling at 50% of the normal rate. Through a step-by-step analysis you can see how new insights are gained by leveraging cross-functional data, producing a complete view of the business conditions and yielding the best conclusion for the company:
Situation: Sales of the sunglasses were low but were not affecting sales of other products, nor were they driving market baskets that were more or less profitable than average.
Decision—Put sunglasses on sale to reduce inventory.
New insight: The company's best customers were not purchasing the sunglasses.
Decision—Put sunglasses on sale to reduce inventory.
New insight: Product profitability was average compared with similar sunglasses.
Decision—Put sunglasses on sale to reduce inventory.
New insight: The supplier only shipped 60% of requested inventory, and sales were actually 83% of available inventory.
Informed decision—Check alternative suppliers, order more sunglasses and consider raising the price, as demand seems higher than supply.

In each step of the analysis, additional data is leveraged, leading to new insights as well as a better understanding of the surrounding conditions. At any given stage, a different conclusion might be drawn and the course of action altered. However, with a 360-degree view of business conditions, the best course of action emerges—simply increasing inventory will return sales to their normal level.

A complete picture
The quality of information provided by analytical environments can be described in terms of how well-integrated the data is within them. When data is not integrated, it usually means that the user will make a decision based on information from a subset of total data available within the organization. Consequently, the user will have limited information with limited scope. This in turn reduces the breadth and sophistication of the questions the user can ask.


When data from multiple subject areas is brought together and integrated, the number and sophistication of the questions users can ask grow. Having integrated data provides users with access to all relevant information within an organization. Thus users can ask cross-functional questions whose answers provide a complete picture of the business conditions. This enables them to make a fully informed decision.

When data isn't integrated, decision makers can only answer a limited number of questions in various subject areas. For instance, questions that can be answered based on product sales data alone would be narrow in scope. Using the retail example, these would include: What are my top-selling sunglasses by store and region? Questions based on market basket data alone would include: What products are purchased with the sunglasses? While these are important questions, they are undifferentiated from what competitors are answering.

However, when the subject areas are combined, new cross-functional questions can be addressed: Which brand of sunglasses is present in my most profitable market baskets? If I promote the sunglasses, which other products are likely to be sold? These questions carry more business impact and could not be answered by one subject area alone.

Integrating more subject areas yields evermore sophisticated questions: Based on current promotions, which sunglasses are forecast to be out of stock at which locations, and how will that affect my best customers and other products I sell? These new cross-functional questions are much more relevant to the business and provide insight that enables differentiated decisions.

Having integrated data significantly increases the number of questions that can be answered. In the figure, each subject area can enable a certain number of questions when taken alone. Product sales data can enable 26 questions, market basket data 32 questions, and so on. The total number of subject-specific questions enabled is 164 (26+32+45+23+38). However, when the subject areas are integrated and new cross-functional questions are enabled, an additional 158 questions can now be answered, yielding a total of 322 (164+158).

Improved vision
The pattern evolving is clear: The more subject areas that are integrated from across the company and available when a decision is made, the more sophisticated and relevant the decisions become. There's a double win. Integrated data enables more questions to be answered with greater business impact.

Imagine making a business decision without knowing how it affects your customers, the sale of other products or the bottom line. Organizations that lack integrated data will be challenged to make decisions with only partial data or in a potentially untimely manner. Those companies with integrated data will enjoy the ability to make rapid, informed and differentiated decisions. As a result, they will emerge as leaders among their competitors. T

Randy Lea is vice president of Teradata's global product and services marketing.

Imad Birouty is program marketing manager for Teradata's high-availability solutions and data mart consolidation program.

Teradata Magazine-December 2008

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