How project managers can measure a cloud project’s success

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Years ago, I had the opportunity to lead a project management office (PMO). In this job, I learned to appreciate the difficult role project managers play: keeping people focused and working, managing changing schedules, a myriad of business and technical issues, and keeping everyone moving in the right direction.

As project managers take on cloud projects, we’re seeing metrics play a large role in evaluating success. Project managers live and die by metrics, and understanding the key metrics to track—especially in cloud-based projects—is critical. In fact, every effective IT leader today relies on metrics to make decisions and gauge how things are going.

Personally, I’ve always had a fascination (obsession perhaps) with metrics (ask me about my fantasy football league if you want to see my obsession in action).  One challenge I’ve faced with metrics is information overload. In many cases, there are too many metrics and not all the metrics are necessarily important for the task at hand. In today’s climate, and considering the amount of information available, it’s important to “reduce the noise” and find the metrics that really matter toour job.

Over the last year or so, I’ve had numerous conversations with clients on their cloud adoption strategy that led me to an epiphany related to metrics, and it is this: Many of the key metrics I’ve come to value over the years are 100 percent applicable in cloud as well.

One way we can categorize metrics is using the “Project Management Triangle” as shown below:

The classic thought behind the triangle is that we need to optimize a project based on these three opposing forces of cost, time, and quality. The belief is that you can optimize to two of these points but not all three (e.g. I can optimize on cost and time but at the sacrifice of quality). This triangle accurately represents a project manager’s role—to optimize across cost, time, and quality for a particular project in order to reach an end goal.

The classic Project Management Triangle is a very useful way to categorize and discuss metrics related to cloud. In my client conversations, we use the categories Cost (Budget), Time (Speed), and Quality (Reliability) to group the metrics we want to measure. And in these cloud discussions, these are metrics that typically surface to the top that really matter:

Metric Category: Cost/Budget
Key Metric: Innovation Ratio
Comments: How much are we spending on reducing technical debt vs. adding new capabilities.

Metric Category: Cost/Budget
Key Metric: Budget underage/overage
Comments: How good are we at predicting costs and estimating?  How well do we manage our budget?

Metric Category: Time/Speed
Key Metric: On-time delivery percentage
Comments: Number of projects delivered on time/total number of projects

Metric Category: Time/Speed
Key Metric: Velocity
Comments: What is the velocity of our team?  What is our historical velocity?

Metric Category: Quality/Reliability
Key Metric: Uptime/MTBF
Comments: What is our mean time between failures?

Metric Category: Quality/Reliability
Key Metric: Test Escapes
Comments: How many defects to we have that were not found during testing?

Metric Category: Quality/Reliability
Key Metric: System Utilization
Comments: What is our resource utilization during stress (performance, number of users, etc.)?

In discussing inherent challenges with clients, it was interesting to map how cloud could potentially address many of the root issues. For example, deploying a simple Dev/Test cloud and offering an “on-demand, self-service” portal for testers and developers can dramatically reduce wait times and improve the time and quality metrics above. Using a production cloud to dynamically add compute capacity or support high availability and disaster recovery procedures will positively impact quality and speed. In the end, these were the metrics that “mattered.”

The other insight I had about cloud and metrics is whether we can take the classic Project Management Triangle and break the notions around optimization.  What if we were able to optimize across all three dimensions instead of two? I believe cloud can be a significant game changer and we can optimize across cost, time, and quality.  I’ll share some of my ideas on how this might be possible in my next post.

Cloud Advisor

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