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Business intelligence (BI) is a business management
term which refers to applications and technologies which are used to
gather, provide access to, and analyze data and information
about company operations. Business intelligence systems can help
companies have a more comprehensive knowledge of the factors affecting
their business, such as metrics
on sales, production, internal operations, and they can help companies
to make better business decisions. Business Intelligence should not be
confused with competitive
intelligence, which is a separate management concept.
A few examples of everyday business intelligence:
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Inbound phone call count drops below X; where X is
the average necessary to maintain sales....
An email is sent to a key manager in charge of
marketing operations. The manager determines if there are
marketing actions that changed the inbound call count. This
notification sets in place an investigation that may have never been
noticed or best.... noticed after sales dropped 25%.
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Warranty Expiration occurrence:
This example company has 5000 warranties to monitor, what are the
chances that anyone is looking ahead enough to catch expiring
warranties?
This defined operation will perform multiple tasks such as sending a
friendly reminder to the customer/owner explaining the expiration
date and how that could affect them; direct the customer to a
re-registration/purchase renewal site, etc. But, in addition a
call will be put on a customer service persons calendar.
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The regional sales manager wishes to receive sales
forecast reports on a weekly basis.
Task Centre can be set to gather the sales forecasts from the CRM
system, format the data into an organized pre-defined format and
distributed to each sales person, the regional sales manager and any
others who have need to know.
Imagine how this "automatic" distribution can save costs,
increase database usage by the team and instill urgency of timely
and accurate forecasts.
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Web site customer inquiries.....
Sure many businesses have website inquiry forms but how many respond
within 24 hours or for that matter ever?
Task Centre can be setup to parse ("look at the content")
inbound E-mail and determine if there is content which needs to be
acted upon. Not only does it look at the content, it reacts
intelligently and promptly.
As an example: Jon Doe fills in a form asking for literature
to be sent about a widget - it's Saturday morning by the way!
When Jon presses the submit an email is formatted and sent by the
website code to a predetermined "person" or department at
ABC Company.
Manual system response: Wait two days? Hope
"person" checks email on Monday morning and notices that
it is a website request. And, hope that "person"
values those requests more than the morning coffee.
Task Centre response: Within seconds Task Centre receives the
email, sees that it deserves a response, finds the reference to the
widget literature, locates the response literature on the ABC
corporate network, prepares the response to Jon Doe, e-mails it and
a "how did we do" link. Not to leave the human out
of the loop, Task Centre schedules a follow up activity in a CRM
system for the "person" in the office. Just to
ensure that "person" doesn't fail or drop the ball, Task
Centre sets itself a reminder to look and ensure that
"person" did his/her piece. If he/she fails or
delays, Task Centre can react and handle as defined.
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There are many tools used to gather, format, and analyze
business intelligence. These tools come in various languages,
versions, formats and costs. There are general purpose tools and
industry specific tools.
We recommend only a few tools to start with. A
spreadsheet package such as Microsoft Excel is the laymans analysis
package. Although somewhat automated, Excel requires that the user
know when to look, what to analyze and who to distribute such
information or analysis to -- Too much human input needed, doomed to
failure!
The primary tool we recommend is a self running software
that will "Tell you when your benchmarks are reached".
Our premier package is a product called Task
Centre. Another optional product we offer is
KnowledgeSync where Task Centre may not be appropriate.
With Task Centre, one defines the queries, triggers,
data conditions, important points, key performance indicators (KPI's)
and other benchmarks that are meaningful. Once defined, the system
watches on a constant or scheduled basis. When a benchmark is
recognized a number of resulting operations can be set into motion.
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Business intelligence (BI) is one of the many tools we
need to know how to operate within our business paradigm. Let's look at
a bit of BI history.
Sun
Tzu's The
Art of War highlighted the importance of collecting and
analyzing information. Sun Tzu claimed that to succeed in war, a general
should have full knowledge of his own strengths and weaknesses and full
knowledge of the enemy's strengths and weaknesses. Lack of either one
might result in defeat.
Prior to the start of the Information
Age in the late 20th
century, businesses had to collect data from non-automated sources.
Businesses then lacked the computing resources to properly analyze the
data, and as a result, companies often made business decisions primarily
on the basis of intuition.
As businesses started automating more and more systems,
more and more data became available. However, collection remained a
challenge due to a lack of infrastructure for data exchange or to
incompatibilities between systems. Analysis of the data that was
gathered and reports on the data sometimes took months to generate. Such
reports allowed informed long-term strategic decision-making. However,
short-term tactical decision-making continued to rely on intuition.
In modern businesses, increasing standards, automation,
and technologies have led to vast amounts of data becoming available. Data
warehouse technologies have set up repositories to store this data.
Improved Extract,
transform, load (ETL) and even recently Enterprise
Application Integration tools have increased the speed of collecting
the data. OLAP
reporting technologies have allowed faster generation of new reports
which analyze the data. Business intelligence has now become the art of
sifting through large amounts of data, extracting pertinent information,
and turning that information into knowledge upon which actions can be
taken.
Business intelligence software incorporates the ability
to mine data, analyze, and report. Some modern BI software allow users
to cross-analyze and perform deep data research rapidly for better
analysis of sales or performance on an individual, department, or
company level. In modern applications of business intelligence software,
managers are able to quickly compile reports from data for forecasting,
analysis, and business decision making.
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Business intelligence often uses Key
performance indicators (KPIs) to assess the present state of
business and to prescribe a course of action. Prior to the widespread
adoption of computer and web applications, when information had to be
manually inputted and calculated, performance data was often not
available for weeks or months. Recently, banks have tried to make data
available at shorter intervals and have reduced delays. The KPI
methodology was further expanded with the Chief
Performance Officer methodology which incorporated KPIs and root
cause analysis into a single methodology.
Businesses that face higher operational/credit
risk loading,
such as credit
card companies and "wealth management" services often make
KPI-related data available weekly. In some cases, companies may even
offer a daily analysis of data. This fast pace requires analysts to use IT
systems
to process this large volume of data.
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When implementing a BI program one might like to pose a
number of questions and take a number of resultant decisions, such as:
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Goal Alignment queries: The first step
determines the short and medium-term purposes of the program. What
strategic goal(s) of the organization will the program address? What
organizational mission/vision does it relate to? A crafted
hypothesis needs to detail how this initiative will eventually
improve results / performance (i.e. a strategy map).
-
Baseline queries: Current
information-gathering competency needs assessing. Does the
organization have the capability of monitoring important sources of
information? What data does the organization collect and how does it
store that data? What are the statistical parameters of this data,
e.g. how much random variation does it contain? Does the
organization measure this?
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Cost and risk queries: The financial
consequences of a new BI initiative should be estimated. It is
necessary to assess the cost of the present operations and the
increase in costs associated with the BI initiative? What is the
risk that the initiative will fail? This risk assessment should be
converted into a financial metric and included in the planning.
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Customer and Stakeholder queries: Determine
who will benefit from the initiative and who will pay. Who has a
stake in the current procedure? What kinds of customers/stakeholders
will benefit directly from this initiative? Who will benefit
indirectly? What are the quantitative / qualitative benefits? Is the
specified initiative the best way to increase satisfaction for all
kinds of customers, or is there a better way? How will customers'
benefits be monitored? What about employees,... shareholders,...
distribution channel members?
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Metrics-related queries: These information
requirements must be operationalized into clearly defined metrics.
One must decide what metrics to use for each piece of information
being gathered. Are these the best metrics? How do we know that? How
many metrics need to be tracked? If this is a large number (it
usually is), what kind of system can be used to track them? Are the
metrics standardized, so they can be benchmarked
against performance in other organizations? What are the industry
standard metrics available?
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Measurement Methodology-related queries: One
should establish a methodology or a procedure to determine the best
(or acceptable) way of measuring the required metrics. What methods
will be used, and how frequently will the organization collect data?
Do industry standards exist for this? Is this the best way to do the
measurements? How do we know that?
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Results-related queries: Someone should
monitor the BI program to ensure that objectives are being met.
Adjustments in the program may be necessary. The program should be
tested for accuracy, reliability,
and validity.
How can one demonstrate that the BI initiative (rather than other
factors) contributed to a change in results? How much of the change
was probably random?
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Major portions of this article is licensed
under the GNU
Free Documentation License. It uses material from the Wikipedia
article Business_intelligence.
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