The Rock N’ Roll Of Project Management: Getting Your Facts Straight
By Carl M. Manello
Facts are simple and facts are straight/ Facts are lazy and facts are late/ Facts all come with points of view/ Facts don’t do what I want them to. “Cross-eyed and Painless,” Talking Heads
Music, when composed and played well, is a joy. As I’m trying to teach myself how to play guitar, I’m learning that there is more to it than simply learning some chords and strumming patterns. Music theory, progressions, complex patterns, scales, and technique all come into play. Project management is similar. When a plan is well-defined and executed by a professional, experienced PM, the results can be a joy. But there is more to project management than creating a plan and managing due dates. Project management theory, base-lining, dependency management, resource loading, and soft skills also come into play.
I think the parallels between music and project management are interesting. For example, we can explore the importance of metrics with the help of David Byrne and Talking Heads. I’ve always been struck by Byrne’s lyric noted above. Whether doing financial analysis in my corporate roles or guiding projects as a consultant, the manipulation of information has always provided an opportunity to make data tell the right story. Mark Twain has great insight on this as well, stating, “Get your facts first, and then you can distort them as much as you please.”
I’ve seen skilled practitioners take Twain’s words to heart. Sometimes this is done on purpose (e.g., in the creation of a business case to justify a new venture) and in some cases the manipulation is simply a lack of understanding or the selection of the wrong facts. And that is one of the biggest problems. When we use facts (metrics), especially those founded on complex math (which tends to lend them credibility), we feel more comfortable with quantitative measures as opposed to qualitative ones. But often, the measures we choose are not representative at all.
For example, I worked to support a financial systems replacement project for a global corporation. As part of the project planning effort, the leadership chose to implement the sophisticated earned value measures of Schedule Performance Index (SPI) and Cost Performance Index (CPI). Each week, more than a dozen project schedulers would update plans and calculate variances to demonstrate progress. The metrics were presented to management and everyone felt comfortable about the initiatives progress. However, the facts were somewhat misleading. Here’s an example:
Facts used to show progress
|Duration||8 Days||6 Days||75%|
Facts that represented true progress
|# of Screens Designed||22 Days||5 Days||23%|
Seventy-five percent of the way into the task, the team was only 25% complete with the effort. So as the project progressed, the company used misleading facts (time) to represent progress. In addition to not differentiating between duration and effort, or building in a measure of “stuff,” there was no metric for quality. Therefore, we found instances where the time had elapsed, but the deliverables were either incomplete or of poor quality. But the mis-representation was almost unnoticed since the cost and schedule metrics were right in line. And those cost and schedule metrics we maintained by a huge work force and project plan that was extensive. How could the facts be wrong?
Making it better
In my current role – advising companies how to design and implement frameworks to increase their delivery effectiveness – I help clients understand the importance of selecting appropriate facts (metrics). The approach that we advocate at Slalom is to select metrics that represent work products. For example, if the project is rolling out new computers with the latest software to a global team of 60,000 associates, the measure should be the number of computers delivered. Simply measuring project schedule and project costs may provide a sense of false confidence. By using a “wigit-ized” metric and associating it with schedule dates, one can assess current status, protract velocity, and better predict the ability to complete the project on time.
Combination of facts used to show progress
|Duration||8 months||2 months||25%|
|Number of computers||60,000||4,000||7%|
From this example, we can see that the expected velocity of change (7,500 machines per month) needs to be adjusted closer to reality (2,000 machines per month), thereby extending the schedule. With representative measures, we can get a sense of true progress… and we can make adjustments to our plans.
It is important to select the right facts, measure them often, report on progress and make adjustments accordingly. As Byrne concludes, “Facts continue to change their shape.” Therefore, we must continue to watch and report our status appropriately to make the facts “sing” the way we want them to.
Carl Manello is a Solution Lead for Slalom‘s Program & Project Management practice based in Chicago who enjoys exploring how to tightly couple the art and science of project delivery with business operations. You can read from Carl on his blog.