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
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
New insight: The company's best customers were not purchasing the sunglasses.
on sale to reduce inventory.
New insight: Product profitability was average compared with similar sunglasses.
on sale to reduce inventory.
New insight: The supplier only shipped 60% of requested inventory, and sales were actually 83% of available
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
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).
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