The Value of Statistical Analytics for Capital Project Management
July 01, 2019
Consider the following questions for your organization:
- What is the value of a 3% improvement in cost performance for your organization?
- How would you benefit from knowing the top 3 reasons your projects succeed or fail?
- How valuable would it be to know exactly how to improve your estimating assumptions?
- How would your management practices and forecasting change if you knew which variables were leading indicators of project performance?
- Would you be surprised if you were shown new KPIs that better predicted performance?
- How would you use the knowledge that specific contractors, vendors, PMs, etc., were reliably linked to desired or undesired project performance?
Answers to these types of fundamental project management performance questions are realistic expectations when data science experts analyze your organization’s existing data using Statistical Analytics (“Analytics”). And through a combination of industry and project management expertise with data science best practices, results are proven to be reliable, beyond coincidence, and relevant for your management teams. Single proof-of-concept projects or turnkey entry packages are both smart entry points for organizations new to Analytics, and the resulting model results typically reveal additional high-value analyses that organizations should seriously consider. If your organization is new to Analytics or unsure how to take the next step, start by asking the questions “How do we improve performance of …” or “How can we predict the result of …” and then enlist an Analytics professional to build and interpret the statistical models that answer your questions.