Pursuing an MBD initiative is much like any strategic effort: it requires executive buy-in. Leadership is often presented with the potential benefits in terms of hard monies and organizational productivity gains balanced against monetary investments and changes to processes and practices. As shown in this research report, adopting an MBD initiative is worth the effort, but it must be done the right way. In this context, it becomes imperative to set the proper expectations. Unfortunately, a number of cohorts surveyed for this research report have underestimated or overestimated the benefits of such MBD initiatives to an extreme.

Comparing Against Projected Estimates

To start, consider how organizations that are currently releasing drawings and models view the transition from fully annotated drawings to fully annotated models. To consider how much benefit an engineering organization would realize from such a transition, remember that findings previously shared in this research report show that all respondents estimate that it will take 8.8 hours on average to create the fully annotated drawing dataset.

To understand how much benefit an organization expects from a change, consider their estimate of how long it would take to develop the fully annotated model dataset. These organizations that are currently releasing drawings and models estimated that such work would take 6.9 hours, on average. Given that, we can assume that these types of organizations expect to realize a 22% reduction in the amount of time to create engineering documentation. That is the expectation that these organizations would likely set with their executives.

Finding: Overestimating the Benefit of MBD

Finding: Overestimating the Benefit of MBD

On the left is the average of the estimate to create the fully annotated drawing dataset by All Respondents cohort. In the middle is the average of the estimate to create the fully annotated model dataset by the Model-Reliant cohort. On the right is the average of the estimate to create the fully annotated model dataset by the Model-Based cohort. Details on all of these estimates and cohorts can be found in the ROI of MBD study page.

Comparing Against Real Performance

Now, let’s look at what is likely a more accurate estimate. The study identified a number of organizations that are currently releasing MBD deliverables as part of their day-to-day development process. Because they have experience in creating annotated models, they are likely to most accurately estimate how long it would take to create the datasets defined in this survey. They estimated it would take 11.7 hours, on average. These organizations realize that transitioning from a fully annotated drawing to a fully annotated model will actually result in a 33% increase in the amount of time it takes to create engineering documentation.

Imagine how the transition would go for the organizations currently releasing drawings and models. They pursue the MBD initiative expecting to see a 22% decrease in time spent on engineering documentation, but instead, they realize a 33% increase. Obviously, experiencing such a drastic shortfall in improvement would be catastrophic. Why do these organizations overestimate the advantages of MBD? Perhaps it is their familiarity with model-based approaches given they currently release models alongside drawings. Regardless, this overestimation of MBD benefits can clearly stop any MBD initiative.

Of course, these organizations can experience these kinds of gains in productivity if they develop minimally annotated models instead of fully annotated models. Organizations currently developing MBD deliverable estimated it would take 6.7 hours, on average, to develop the minimally annotated dataset, equating to a 24% gain in engineering productivity.

The Takeaway

Therein lies the first cautionary tale: organizations releasing drawings and models need to carefully and conservatively assess the benefit that they can reasonably expect from such engineering documentation initiatives. Don’t let your familiarity with models cloud your judgment.