BI software puts important business information in front of decision-makers when they need it, in a format they can understand and act upon quickly. This whitepaper introduces three majors capabilities of BI systems, the benefits of using these tools, and major trends in the industry.

1. Business.com Guide
to Business Intelligence
(BI) Systems

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3. Contents
The Basics of Business Intelligence Systems 4
Three Major Capabilities of BI Systems 7
The Benefits of Business Intelligence Systems 11
Trends in Business Intelligence Systems 14
Top Tips for Evaluating BI Systems 17
Business.com Checklist for Business Intelligence Systems 19
Glossary of Business Intelligence Terms 22

4. 4
The Basics of Business
Intelligence Systems
B
usiness Intelligence (BI) software comprises various application tools
to retrieve, analyze and report on raw historical and current data
in order to identify and develop business opportunities as part of a
competitive marketing strategy.
Another way of looking at it is that BI software puts important business information
in front of decision-makers when they need it, in a format they can understand
and act upon quickly. The information has to be shareable, yet secure.
Every day, large BI systems analyze the activities of millions of individual
customers making literally billions of transactions. Sophisticated software
is able to continuously track the profitability of specific customers and
products, and to detect fraudulent activities using algorithms that become
more accurate over time.
Something as simple as a spreadsheet is a business intelligence tool. On a
very basic level, you manually enter data into a spreadsheet so you have an
easy way to visualize relationships among the different data points and, in many
cases, draw conclusions about what these relationships mean.

5. 5
At this very basic level, if your sales spreadsheet showed gross sales doubled
in July and August, you might reasonably conclude your product is most
appealing to consumers in the summer or during hot weather. Based on this
information, you could decide to concentrate a larger portion of your marketing
spend in the summer, as that’s likely when people are most interested in your
product. Then again, you might also decide to move your marketing dollars
toward the cooler seasons to improve year-round awareness of your product
and boost off-season sales.
The moral here is that BI software doesn’t tell you what to do. It provides a
means to quantify and visualize data so you can make more informed decisions
based on the data you select. Some of the business problems that business
intelligence software helps with include:
ƒƒ Customer Satisfaction
ƒƒ Problem Resolution
ƒƒ Customer Loyalty/Value
ƒƒ Customer Segmentation
ƒƒ Customer Turnover
ƒƒ Product Upsell/Cross-Sell
ƒƒ Cost Control
ƒƒ Revenue/Profitability
ƒƒ Performance Management
ƒƒ Product Defects
ƒƒ Collections
ƒƒ Marketing Effectiveness

6. 6
Just as there is an enormous amount of data to sort and categorize, there is
a wide variety of BI tools that are both open-source (free) and commercial.
Generally, open-source software is good for people with IT experience whereas
commercial software usually comes with training and other useful customer
support useful for those with minimal technical training.
While there are more expensive tools that automatically do more sophisticated
processes than a spreadsheet can, almost all BI tools have an export to
spreadsheet function. There are also several other ways to display data,
including visualizations and infographics (i.e. charts and graphs), which most
BI tools also generate.
Generally, open-source software is good for people with
IT experience whereas commercial software usually
comes with training and other useful customer support
useful for those with minimal technical training.

7. 7
Three Major Capabilities
of BI Systems
J
ust as there are different spreadsheet providers, some free and some
not, there are various open-source and commercial software products
for each BI tool. These tools can be broadly categorized as:
1. Data Management. These are tools that Extract, Transform and Load
(ETL) data from various sources and place it into a central repository
(data warehouse). Not all BI tools require a data warehouse, although
data warehouses provide additional functionality and more seamless data
retrieval and reporting. Additional tools “clean up” the data to delete errors
and ensure usability.
2. Data Discovery. These tools refine the initial data extraction to make some
sense of what you’re looking at.
¾¾ Data Mining. Identifies patterns, trends and associations among
large quantities of data. Data mining is typically the first cut at
sorting through data that other tools further refine.

8. 8
¾¾ Online Analytical Processing (OLAP). Sorts data by different
“points-of-view” or “dimensions.” Example: You can request an
OLAP tool to display product sales by month or by geographic
region, and then compare it to last year’s sales by month and
geographic region. In order to do this, data has to be tagged with
certain attributes (e.g. month, region, year) or “dimensions,” and
stored in a multidimensional database.
¾¾ Predictive Analysis. Anticipates future trends and probabilities
by analyzing current and historical “predictors” - measureable
variables such as age, gender, credit score, etc.- to forecast likely
outcomes. Google used predictive analysis during the 2009 swine
flu pandemic to predict the spread of the disease two weeks
ahead of government reports and their predictions enabled local
healthcare officials in the forecasted areas to stock medicine and
prepare treatment response plans. Similarly, your business can
use predictive analysis to anticipate probable customer behavior,
product usage, and purchases.
¾¾ Text Analytics. Identifies patterns and trends among textual, as
opposed to numerical, data. Example: Search engines “look” for
certain word frequencies and associations to both refine results that
are more likely to be of interest to you and push advertisements you
are more likely to click on.

9. 9
3. Reports. Reports are easy-to-understand displays of information for the
technically challenged in the form of spreadsheets, graphs and infographics
that literally draw you a picture.
¾¾ Visualizations. Process information from databases and present it
in graphical form. You can enter new data and immediately see the
effects. An example is seeing a street map when you enter a new
travel destination in a GPS system.
¾¾ Report Writers. Create customized, ad hoc reports from a wide
range of data sources in response to specific queries. For example,
you can create “what-if scenarios,” such as how changing variable
cost per unit affects net profit.
¾¾ Dashboards. Browser-based displays of Key Performance
Indicators (KPIs) linked to target values. These metrics determine
whether a business unit or product line is meeting expectations.
Example: What is the expected average time to repair a given
product and what is the actual average time achieved?

10. 10
¾¾ Scorecards. Much like recording runs, hits and errors for
a baseball game, scorecards attach a numerical value to
performance achievements. For example, the scorecard might
compare stores by the increase in quarterly revenues for stores
open at least 12 months.
Much like recording runs, hits and errors for a baseball
game, scorecards attach a numerical value to
performance achievements

11. 11
The Benefits of Business
Intelligence Systems
¾¾ No more guesswork. Without totally discounting your gut feelings, the
problem in going with your gut is that too many times the results end up
looking like something your actual gut produces. BI software presents
you with the cold hard facts, historical trends and real-time updates,
sliced and diced by just about any parameter you choose. It can even
answer those “what if” questions that keep you up at night. You still make
the decisions, but you’ve got better data to do it with than you would if
you just used your gut feeling.
¾¾ Better understanding of your customers. What are they buying? What
are they not buying? What type of customer (sorted by age, gender,
geography, previous purchase, etc.) is purchasing particular products?
Get key metrics such as these almost immediately simply by defining
what you’re looking for and creating a customer report.

12. 12
¾¾ Identify new opportunities. BI data not only tells you where you’ve
been, but where you’re going and, moreover, where you could be going.
Predictive models point to where you can best focus your marketing
efforts, suggest prospects for upgrades and cross-sales, and detect
trends for product development.
¾¾ Improve manufacturing and operational efficiency. BI software can
analyze your business to pinpoint excessive expenses and identify areas
in need of improvement. For example, BI software can help you order
the right amount of inventory at the right time so capital isn’t tied up in
excessive inventory.
¾¾ Get the data you need when you need to get it, in a readily
understandable format. One problem plaguing large organizations is
getting information from different departments in a consistent format and
conglomerating it in a way that retains intelligence. Data often needs to
be discovered, then converted, merged, and tweaked before it can be
put into a report. BI software helps centralize all that data and makes it
viewable in dashboards that can generate reports. When implemented
properly, it can save enormous amounts of time and increase efficiency.

13. 13
¾¾ Improve business negotiations. If you expect to negotiate prices
and terms with your suppliers, business intelligence software can help
give you a negotiating advantage. You can easily examine your entire
relationship with a vendor or supplier and generate facts and figures
that can be used in negotiations. For example, BI software might report
the percentage of deliveries that are on-time, the percentage of defects
noted, trends in pricing, or even what competing vendors charge for
similar services. This information can be invaluable in negotiating
contracts and discounts.
BI software might report the percentage of deliveries
that are on-time, the percentage of defects noted,
trends in pricing, or even what competing vendors
charge for similar services. This information can be
invaluable in negotiating contracts and discounts.

14. 14
Trends in Business
Intelligence Systems
¾¾ Moving to the cloud. Storing data and software in the cloud - essentially
a series of large servers shared by a multitude of users - is increasingly
popular increased convenience and cost-effectiveness. Instead of
hosting and maintaining a server and associated software on-site, a
Software as a Service (SaaS) vendor does it for you.
¾¾ Going mobile. Just as everyone is looking up to the cloud, they’re
increasingly doing so via a mobile device. Consequently, BI software
vendors are emphasizing “on-the-go” access. With more and more
people outside the IT department needing to access these tools, there is
a parallel need to optimize ease-of-use and intuitive operation.

15. 15
¾¾ Open-source vs. commercial. You may be tempted to go the open-
source route because the code is free. But, BI software could be
virtually running your business and BI data could be valuable enough
to warrant the kind of security found in closed-code commercial BI
packages. Ask your IT team if they feel comfortable supporting an
open-source package. Don’t have any IT staff or do you have limited
resources? Then the answer is probably to look for a commercial
service rather than open-source software.
¾¾ Improved usability for the non-geek. Initially, BI tools were for
programmers and similar technical specialists. But, just as most
people don’t need to know how to build and program a computer
to use it, businesses want tools with low implementation costs that
all the necessary employees can easily use and understand. Look
for BI software vendors that emphasize their interactive visualization
capabilities. The automation of data analysis and visualization has made
it easier to access and manage data. While there is a counterargument
that increased ease-of-use comes at the expense of more complex
analyses, there’s little point in having a tool no one fully understands
without expert guidance, sorting and decoding.

16. 16
¾¾ Everything is bigger. You’ll hear the term “big data” a lot because there
is a lot of it and more of it every day, thanks in large part to the Internet.
And as the amount of data available becomes larger and larger, it
becomes all that more difficult to sort through and make sense of what
you’re looking at.
The ability to analyze large data sets is a competitive advantage. It
will make waves of growth in productivity, innovation, and abundant
production possible. The rise of big data will challenge the capabilities
of all leaders, not just information officers. The exploding volume of
data collected by organizations, combined with the rise of multimedia
and social media, will generate enormous troves of data that we will
be learning from for decades. The challenge to business intelligence
software vendors is to continually improve their capabilities to bring “big
data” down to a manageable size.
The exploding volume of data collected by
organizations, combined with the rise of multimedia and
social media, will generate enormous troves of data that
we will be learning from for decades.

17. 17
Top Tips for Evaluating
BI Systems
¾¾ Avoid BI BS. You don’t always need a Ferrari to get to your destination.
Don’t focus exclusively on brand names as that can easily lead to buying
more than you necessarily need. Your BI software needs to fit what you
are looking to discover about your business. Before you go shopping, use
the Business.com Checklist for Business Intelligence Systems to match
your needs with software that best accommodates them.
¾¾ Plan for your infrastructure. What’s your server and network capacity?
What about the capacity of your vendor? This is particularly important for
mobile applications, where users expect information to be available to them
in real time. Equally important, of course, is that any business intelligence
software you select should work with your existing infrastructure.

18. 18
¾¾ Don’t get technical. If a system requires a technical background to
learn or use it, adoption will be limited to those with the technical know-
how. Any system that requires contacting a technical support person to
generate reports is going to lead to end-user frustration and low adoption
rates. Many BI systems started out as something hacked together by
IT people for IT people. If the intended users of your system are not IT
people, look for a system that is easier to use.
¾¾ Get a timeline. BI systems are complicated by nature, since they usually
involve the integration of information that used to be sectioned off, such
as human resources and sales. It can take more time than you might
imagine installing an infrastructure that can integrate these different
components. Inquire about timelines from business intelligence vendors.
In an open bidding process, look for a vendor who has a reputation
of completing installations in three months or less as it might be worth
paying more to get the job done on schedule.
¾¾ Don’t try to do everything at once. Focus on one key area, get used
to how the BI tool works (or doesn’t work), and then gradually expand
implementation based on evolving needs and what you’ve learned.

19. 19
Business.com Checklist for
Business Intelligence Systems
My Needs Vendor 1 Vendor 2
Capabilities Desired
Customer Satisfaction
Problem Resolution
Customer Loyalty/Value
Customer Segmentation
Customer Turnover
Product Upsell/Cross-Sell
Cost Control
Revenue/Profitability
Performance Management
Product Defects
Collections
Marketing Effectiveness
Other

20. 20
My Needs Vendor 1 Vendor 2
IT Integration
Data Warehouse Required
IT Platform
Integrates With Existing IT infrastructure
Mobile
Cloud- or Server-Based
Pricing
Installation
User-Based or Server-Based?
Software Upgrades
Maintenance
Technical Support
Add-Ons
Implementation Schedule
Proof-of-concept demo
Time to convert a prototype into a tool
Time to deploy a tool as a finished app
Modifiable

21. 21
My Needs Vendor 1 Vendor 2
Usability
Learning curve; how many days of
training (and/or days use) required for
the following level of employees to gain
a basic understanding and proficient
use of tool:
IT/Business Analyst
Mid-Level Manager
Senior Executive
General Support Staff
Visualization Tools
Maintenance/Support Contract
User Community Support

22. 22
Glossary of Business
Intelligence Terms
Ad Hoc Report: A custom report created in the moment by sending a query for
specific information that is displayed as a report in the specified format.
Analytic Application: A turnkey software program for specific data needs, e.g.
customer intelligence or market research.
Balanced Scorecard: Summarizes business performance measurements from
multiple perspectives (e.g. financial, customer knowledge, internal business
processes, learning and growth) on a single page or view.
Business Performance Management (BPM): A kind of internal BI application,
BPM focuses on the effectiveness and efficiency of business units (e.g. finance,
sales, human resources) as well as processes, such as planning and forecasting.
Data Dictionary: A list of all data elements and databases by name, structure,
function, and other information about their usage.
Data Mart (DM): A specialized data warehouse with a predefined grouping of
select data.

23. 23
Data Warehouse: A raw database created by integrating data from a variety
of sources.
Drill Down/Up: The process to create summaries of data either more detailed
(drill down) or less detailed (drill up).
Enterprise Portal: Access to BI software and reports via a password-
protected website.
Executive Information Systems (EIS): Turnkey software with targeted level of
detail for use by senior executives.
Granularity: Level of detail. The less detail, the lower the level of granularity.
Conversely, the more detail, the higher the level of granularity.
Metadata: Describes the content, structure and processes of a data warehouse.
Relational Database System (RDBMS): Data organized by relations. In the
broadest (and somewhat imprecise) terms, relations are defined as a series of
yes/no propositions. Data queries sort according to what information is or is not
contained in these relationships.
Structured Query Language (SQL): A standard programming language used
to access and manipulate data in a relational database.