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Key Performance Indicators (KPIs)

Key performance indicators (KPIs) are metrics ‐ financial and non-financial ‐ used by executives, analysts, IT professionals and business users for business activity monitoring and corporate performance management. KPIs are aligned with the measurement of business performance against an organization's strategic goals and objectives.

Successful KPIs follow the SMART criteria:

  • Specific ‐ pertaining to the goal of the organization
  • Measurable ‐ for the organization to assess its progress
  • Achievable ‐ realistic in terms of the business environment
  • Relevant ‐ directly linking the business and metrics
  • Time-Bound ‐ placing goal achievement in a certain time frame.

Analyze KPIs using Dashboards and Scorecards

The MicroStrategy Business Intelligence Platform provides a wide range of capabilities to design KPIs and deliver and analyze them on visually appealing, interactive dashboards, scorecards, and reports. These rich graphical interfaces quickly convey company performance to executives and business users alike. KPI-rich dynamic dashboards can be proactively delivered to users online or via email. Dashboards can be customized at the user level, or formatted adhering to recognized performance measurement theories, such as Balanced Scorecard and Six Sigma. In addition to corporate KPIs, companies can build department-level and business unit-level KPIs with ease.

MicroStrategy provides out-of-the-box KPIs in pre-built BI applications in the BI Developer Kit of MicroStrategy Architect. Each pre-packaged application is designed for a different aspect of the business to help reduce application development time, for example:

  • The ‘Customer Analysis’ module includes KPIs to help the marketing function of a company measure the performance of its customer satisfaction scores or monitor the lifetime value of its customers.
  • The ’Financial Analysis’ module allows a company to utilize pre-packaged KPIs pertaining to Finance, e.g. accounts receivable and accounts payable.

In addition to providing pre-built Business Intelligence applications with KPIs, MicroStrategy has hundreds of pre-built functions to leverage in KPI creation.

Build KPIs and Metrics Easily Using Pre-packaged Functions

The MicroStrategy platform includes more than 300+ mathematical, OLAP, financial, and statistical functions. Users can apply these functions on the fly to any set of enterprise data without any administrative help. These functions range from simple database concepts such as running totals, to full mathematical functions such as sum, count, average, correlation, slope, and standard deviation; to OLAP functions such as rank, running sum, and exponential moving average; to financial functions such as internal rate of return and accrued interest; and to statistical functions such as chi-squared and exponential distributions, kurtosis, skew, and t-tests, among a host of others.

Basic Functions
Average
Count
Geometric Mean
Greatest
Maximum
Median
Minimum
Mode
Product
Standard Deviation
Variance

OLAP Functions
Exponential Weight Moving Average
Exponential Weight Running Average
First Value in Range
Last Value in Range
Moving Average
Moving Count
Moving Difference
Moving Maximum
Moving Minimum
Moving Standard Deviation of Population
Moving Standard Deviation of Sample
Moving Sum
Running Average
Running Count
Running Maximum
Running Minimum
Running Total
Running Standard Deviation of Population
Running Standard Deviation of Sample
Running Sum
Rank and NTile Functions
N-Tile
N-tile by Step
N-tile by Value
N-tile by Step and Value
Percentile
Rank
Mathematical Functions
Absolute
Arc cosine
Arc cosine hyperbolic
Arc sine
Arc sine hyperbolic
Arc tangent
Arc tangent2
Arc tangent hyperbolic
Ceiling
Combine
Cosine
Cosine hyperbolic
Degrees
Exponent
Factorial
Floor
Integer
Log
Log Base 10
Modulus
Natural Log
Power
Quotient
Radians
Random Number Between
Round
Round with Precision
Sine
Sine hyperbolic
Square Root
Tangent
Tangent hyperbolic
Truncate
Statistical Functions
Average Deviation
Beta Distribution
Binomial Distribution
Chi-Square Distribution
Chi-Square Test
Confidence Interval
Correlation Coefficient
Covariance
Criterion Binomial Distribution
Exponential Distribution
Fisher Transformation
F-Probability Distribution
F-Test
Gamma Distribution
Heteroscedastic Ttest
Homoscedastic Ttest
Hypergeometric Distribution
Intercept
Inverse of Beta Distribution
Inverse of Chi-Square Distribution
Inverse of F Probability Distribution
Inverse of Fisher Transformation
Inverse of Gamma Distribution
Inverse of Lognormal Cumulative Distribution
Inverse of the Normal Cumulative Distribution
Inverse of the Standard Normal Cumulative Standard
Inverse of T-Distribution
Kurtosis
Lognormal Cumulative Distribution
Mean
Mean T-Test
Negative Binomial Distribution
Normal Cumulative Distribution
Paired T-test
Pearson Product Moment Correlation Coefficient
Permutation
Poisson Distribution
RSquare
Skew
Slope of Linear Regression
Standardize
Standard Normal Cumulative Distribution
Standard Error of Estimates
T-Distribution
Variance Test
Weibull Distribution

Data Mining Functions
Clustering, Numeric
Clustering, Non-Numeric
General Regression, Numeric
General Regression, Non-Numeric
Mining Model, Numeric
Mining Model, Non-Numeric
Neural Network, Numeric
Neural Network, Non-Numeric
Regression, Numeric
Regression, Non-Numeric
Train Regression Model
Train Regression Model with Tree
Tree Model, Numeric
Tree Model, Non-Numeric