KPISTEP

KPISTEP is a mutli-phased way for integrating The Decision Model into business transformation projects, requirements projects, or full systems development projects.

Its most innovative characteristics are:

• The Decision Model as a standard business deliverable
• ROI-driven approach to prioritizing
• The Decision Model with Business Process Modeling standards
• Iterative, fast-paced, and time-boxed deliverables
• Test  case generation and development
• Comprehensive training,  methods, and techniques for mining business decisions from legacy or  packaged code.

KPISTEP fits well within an existing software development lifecycle (SDLC)

KPISTEP is the first approach for delivering The Decision Model as a standard business asset or requirement.  KPISTEP leads business experts and business analysts through the inception, development, and validation of business rules and logic organized into a normalized Decision Model. After the first KPISTEP project, most organizations establish a Center of Excellence for The Decision Model projects or Business Decision Management Functions.It is common for organizations to certify employees as KPI Decision Modeler Practitioners.

KPISTEP is introduced to organizations in a two-phased approach:

• Pilot
• Project

The KPISTEP Pilot

The purpose of a pilot is to validate the KPISTEP approach, determine a quick scope, estimate resources and level of estimate, and determine tools for the models.A typical pilot lasts 2-5 weeks, working with business experts, Decision Modelers, and Process Modelers.

It consists of:

• 1-2 days of training 
• Scoping, aligning with Business Motivations 
• Development and validation of  Business Process Models, Decision Models, and glossary for pilot’s scope 
• Capture of productivity metrics 
• Development of high-level project plan 
• Presentation to management

The KPISTEP Project

• Additional 1-3 days of training
• Development and validation of Decision Models, Business Process Models,and Glossary
• Capture of productivity metrics
• Alignment of glossary with data models, data standards, data sources
• Presentation to I/T and Solving of miscellaneous technical issues
• Tool selection
• Presentation to Management