Defining BI Requirements - Measures
Defining BI Program outcomes relates directly to the roles of
the users in the functional area.
There are two aspects to this step:
- Determining the base data required to measure outcomes - this
data will be used in terms of dimensions to add context to the
data, and thus transform the data into information.
- Determining the level of data required - based on the business
Define the Dimensions
Dimensions are used to describe the measures, and give them context.
For instance, sales by customer group. 'Sales'
is the base measure, and 'customer group' is the dimension. At a
higher levels, calculated measures such as profitability by customer
When deciding on measures, consider how they interrelate and are
calculated before defining dimensions such as time, product group,
Consider where the data is derived, how available it is based on
current systems, and what data transformation will be required to
access it to provide these measures.
Dont just think on each dimension alone, consider how multiple
dimensions can describe a particular measure. Analysis across multiple
dimensions simultaneously makes the data useful for analysiss
Dimensions typcially found in BI applications for each functional
- Sales and Marketingproducts, customers,
demographics (age group, gender), sales channel, geography, promotions,
campaigns, sales force, order status, sales type, time
- Human Resourcesorganizational chart,
employees, time, business unit, department
- Operationsshift, time, assembly line,
product, manufacturer, warehouse, suppliers
- Financecurrency, account, scenario, time,
business unit, department
Define the Level of Detail
For each combination of dimensions and measures, decide how much
detail is desired. This is defined as the lowest level of information
for each dimension that must be available across different user
groups. This is important, because all summarized data can be easily
derived from the lowest level of detail.
The level of detail required is driven by the business requirements,
yet it must remain practicable. Consider the relative cost and benefits
of summarized vs. detailed data.
- Summarized or high-level data tends to minimize
the number of data points that you have to analyze, but it does
not allow you to see trends at lower levels of detail.
- Detailed, low-level data means that you will
need to analyze more data points to identify trends.
This is required to meet the needs of both transactional level
users who require detailed data to monitor activity performance,
and managers who require summarized data to identify trends.
The key to finding the right balance is by first determining a
reasonable level of detail for the lowest level of data required
across all users, and then using the BI system to create hierarchical
Detailed data may also be used for more advanced analytical techniques,
such as data mining.
Once the level of data detail is determined from a business requirements
perspective, it will still need to be evaluated in terms of the
feasibility of accessing the data.
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