By Masha V. Petrova, founder/CEO, MVP Modeling Solutions
Tools like CAD (Computer Aided Engineering), FE (Finite Element) and CFD (Computational Fluid Dynamics) save inordinate amounts of time and money for companies that use these tools in their Research and Development. Some theories simply can not be tested in a lab and can only be modeled. So if research can be done cheaper, faster, with more innovative products as a result of computer simulations, why are so many researchers not getting the funding from management needed to expand or simply keep in place computer modeling projects?
Having worked in both engineering R&D and sales, I believe I figured out what the problem might be. It has to do with the approach that engineers take when trying to implement a new computer model in their workflow. Being detail oriented, engineers tend to focus on things like getting a delta mue as close to 0.0001 percent as possible, or re-writing chunks of code to better represent a certain set of equations, or focusing on which turbulence model is more accurate. All these things do need attention, but not when it comes to getting more funding or resources for the modeling project.
When I went to work in software sales several years ago, just like many engineers I was under the impression that sales guys were, shall we say, somewhat of a lower life form, compared to us – smart and hard working engineers. I was wrong. Sales guys taught me to think about engineering research in a very different way – the kind of way that brings in money, closes deals, and allows research programs to expand.
If you are thinking about becoming more involved in engineering computer modeling, or are trying to figure out how to get funding to buy a needed software tool - read the 5 steps below and start applying them to your engineering problems. Do this, and the benefits of computer modeling will become blatantly obvious to you, your group, and you management.
Step 1: Ask What Is The Big Picture? One thing that sales guys are really good at doing, is figuring out what is the Big Picture underneath all of the equations, tolerances and input variables. They are able to make the sale to management because they relate the most technical engineering software or hardware to the Big Picture. Here are some questions that you need to ask yourself when figuring out what is that Big Picture:
- “What are my company’s products?”
- “How does my company get revenue?”
- “Is my company presenting itself as innovative, environmentally friendly, profitable, other?”
This step will get you thinking on a broader scope. It will get you to understand why this project is important to the overall goals of you company.
Step 2: Ask How Do I Fit Into The Big Picture? Now you have to relate the goals of your company to you, your team and your project.
Ask yourself:
- “How do I/my team contribute to company products / services?”
- “How does what I do help company image (my work is innovative, helps the environment, creates new products that bring in revenue,etc)?”
- “How does my work help the bottom line (saves money or brings in more revenue)?”
Step 3: Define Project In Terms Of Computer Simulation Now it’s time to get a bit more technical. A sales guy would not get too involved in this step, but you being an engineer, need to specify the following:
- What is the goal of your computer simulation? (e.g learn how emissions vary with input temperature, understand how the thickness of microchip coating depends on the inlet flow-rate, etc). Possibilities are endless. Just make sure that the goal of your simulation fits directly with Steps 1 and 2 above.
- Identify variables that you can control or cannot control but need to take into consideration (temperatures, pressures, heat releases, turbulence…) There are many options, make sure that you really examine the problem you are trying to model from ever angle and identify all possible variables. I can not emphasize enough how important this step is and yet about 90% of engineers choose to skip it before running a computer experiment!
- Pin-point assumptions that can safely be made in order to achieve your simulation goal.
- Pick the best software available.
Step 4: Create Specific Modeling Plan / Run Computer Experiments/ Analyze Data Finally, here is a step that a sales guy would not touch with a 10-foot pole. As engineers we thrive on this step, so it is relatively self-explanatory to any engineer. The only thing I would point out here is that setting up an experiment plan, running experiments, and analyzing results are interconnected. If after looking at modeling results you need to go back and adjust you modeling plan and then re-run the experiments, that is a very natural process.
You should NOT however have to go back to Step 1, 2 or 3 and wonder “What are my assumptions anyway?” or “I think I need a different software tool” or “Not sure how this is going to be useful to my company.” Most engineers do it anyway and that is why computer modeling is not expanding as fast as it should in the engineering industry.
Step 5: Presenting Modeling Results To Management Sales guys would be all over this step. In fact, if you are trying to get funding from your management to, for example, renew an expensive license for a software, here is my suggestion. Call up the software vendor that you purchased the tool from and let them know that you need to present the modeling results to management. Tell them that getting funding to renew the software license depends on this presentation. Then politely request if the sales guy would review your presentation and optimize it in a way that would get you funding from management (make sure to remove any proprietary information).
Most good sales people would be thrilled to help you with that. They would do it by tying all of your modeling results to the Big Picture. And if you have done some work on my Steps 1-3, you can do the same thing. Trust me, management would be much happier understanding how your results are helping accomplish company goals instead of how you re-wrote the deta mue function in C++.
Describing how modeling results fit into the Big Picture will get you project funding, and who knows, maybe even a raise.
Masha V. Petrova holds a Ph.D. in aerospace engineering is a founder and CEO of MVP Modeling Solutions. Her weekly blog on a variety of engineering topics, can be found on mvpmodelingsolutions.com/mvpblog.
For more information visit MVP Modeling Solutions.