Measuring the benefit
Measuring the financial return on BIM is not easy.
Many of the promoted benefits are vague and can’t be isolated or pinpointed.
Furthermore, it can be difficult to separate costs from other expenditure (such as CAD, IT & training) & many benefits are equally challenging to isolate.
For instance, savings due to documentation quality improvements, or in downstream use (such as reduced construction errors or delays) can be hard to ascribe directly to BIM.
Therefore, the challenge is in identifying metrics, hard & soft that can be attributed directly to BIM. Since most design and construction projects are quite different (if not unique) a project-project comparison is also tricky.
Even defining meaningful metrics just for design can be a challenge. I once worked in an organisation that measured productivity by ‘person-hours per drawing’ i.e the less work per drawing, the better. On first impression this might appear reasonable, however:
- The quality of each drawing was not considered.
- The metrics could be quickly improved by duplicating one (AutoCAD) drawing and turning it into an additional drawing with minor change. For example, an extra building section, or new detail plan (change the scale, add a few notes and some extra dimensions)
In other words, the value of the drawings decreased.
As I explained in ‘BIM: Less is More‘ model quality is much more important than quantity. But how do you measure quality ?
- A design consultancy might measure design & documentation quality by the number of drawings that need to be revised & reissued, the number of requests for information from the contractor, or even the number of professional indemnity claims.
- A contractor might measure design & documentation quality by the number of delays or the cost of rework (higher quality documentation might reduce construction profit margins through reduced variations, but that is another story)
- A client might measure design & documentation quality by the number of variations or delay, or by aesthetic evaluation of the end result, or a subjective view on how smoothly the project ran.
There are publications which use surveys to quantify benefits such as construction cost reduction or work acceleration .
However, the metrics are generally subjective rather than objective i.e ‘I feel we had a reduction of more than 5% in construction cost’. It depends who you are asking- if the respondents are design consultants or contractors who have have BIM expertise or advocated BIM, then they possibly have a biased view or be more likely to respond to a survey.
In simple terms- ask a bunch of BIM aficionados if BIM is good- then the natural answer is ‘yes’. I believe this is called ‘confirmation bias’.
A BIM sceptic ?
I’m not saying that I don’t think BIM can provide these benefits (it can) but just that some publications (often vendor-sponsored) have flimsy evidence and don’t stand much scrutiny.
I should note that there are academic papers which do take a rigorous scientific approach to determining BIM performance, but these have limited value in terms of readability and practicality.
Some benefits of BIM are not tangible or quantifiable. For example:
- an accident is prevented by better understanding and construction methodology
- construction acceleration opportunities are identified
- more competitive pricing due to better definition of scope
- a building is more energy efficient due to the model-based analysis
- reduction of risk
and so on.
Tips for evaluating the return of BIM
- Define objective metrics (hard metrics) across a number of projects
- Include subjective evaluation (soft metrics), but ensure that it is balanced with independent or negative input.
- Don’t rely on reported metrics from others.
- Don’t think that ROI of BIM can be boiled down to a simple number
- Consider that BIM done badly can be worse than no BIM at all
(refer my posts BIM: Success is not guaranteed & BIM: Talk the talk. Walk the walk?
Despite what I’ve said above, my view is that the difficulties in measuring the ROI of BIM means that you could probably manipulate the numbers to justify both for and against arguments.
After all, success stories like the reborn Apple or Tesla came down to gut instinct and commitment of Jobs/Musk rather than allowing the accountants to make the decision.