SPAR Framework

SPAR – Framework

Navigating complexity in today’s interconnected business landscape

Step One:

Understanding Modern Project Myths

In other words, there is unseen risks in complex projects

Myth #1

The defined Solution is the “Real” Need

Myth #2

The Problem will solve the “Needed” Solution

Myth #3

The Problem can be solved with the available Resources

Myth #4

The resourcing is approved by a person with Authority

Step Two:

Realizing the Solution is only as good as its weakest foundational constraint.

There is more at play than a good scope of work. So, your ability to understand the problem, access resources, and have the appropriate authority to execute will determine whether your solution meets the “Real” need. Or it might just miss expectations and waste effort

Step Three:

Managing constraints and expectations

Solutions are constrained by the three supporting triangles (Problem, Authority, and Resources). Therefore, the solution can only be as large as the smallest underlying supporting triangle.

Depending on your role and level of experience, you will have varying degrees of influence over the problem space, the resources required to solve it, and the authority to allocate those resources.

Understanding the supporting foundational triangles in a project will allow you to “Right Size” your efforts and focus on the areas you can control and influence.

The Resources

  • Do we have people who know and understand the problem?
  • Are the people available?
  • If not, when will they be available?
  • How long will it take to get up to speed to learn about the problem?
  • What is the expected timeline for completion?
  • Has the team done this before?

The Authority

  • What do we gain by providing resources?
  • What do we give up by allocating resources?
  • Is this a make-or-buy decision?
  • Do we have a budget of hours or dollars?
  • Can I rationalize the allocation given my competing resourcing?
  • Will the solution provide value for the allocated resources?

The Problem

  • Ask Questions: What problem are you trying to solve?
  • Collect Data: What do we know, and who can we ask?
  • Root Cause vs Symptom: Are we simply making something bad more efficient
  • Find a similar Cohort: Who has done something similar, and how long did it take?