How Engineers Solve Problems in Real Life

As a group known for a “measure twice, cut once” mentality, this discipline of engineering has become a sort of pop-culture cliché due to how meticulous its practitioners tend to be. Engineers often rigidly adhere to on process discipline and create a new process when they perceive one should exist. This process-focused stance produces reliable, precise solutions that stakeholders can trust.

However, during the current season, when business seems averse to investing in new technology in favor of securing and improving profit margin, is the engineering approach outdated? Is it a waste of time to chase down the details, when budget and schedule pressures employing an 80/20 Pareto solution over a more “complete” engineered one?

You can guess my thoughts on the matter. First of all, it’s a complete misconception that engineers can’t deliver an on-budget, on-time solution. They strive to perfect their ability to balance the right amount of technical rigor with delivering their customers helpful and actionable solutions.

The proof, though, can be seen in the example of a project I worked on several years ago. My task was to develop a chemical formulation for a consumer product to address a severe consumer misuse failure mode. Several options existed on the market when I received the project, but each was an order of magnitude more expensive than the blend I sought to replace. This cost bloat was due mainly to processing and lack of sales volume. These pressures resulted in the firm nearly resigning themselves to the fact that the safer formulation would amount to no more than a niche product.

To tackle this, I reviewed the success criteria. The new formulation had to perform the same or better than the existing product, provide a more efficient reaction when used, and address the critical consumer misuse (oral consumption in this case). Rather than accept the commercially-available forms of the chemical, I approached the problem this way:

  1. Learn the marketing must-haves, and consider the rest excess cost adders
  2. Identify similar products to the existing production options and engage the manufacturer to learn all the options in total
  3. Pick the [3, 5, 7] best available feedstocks, and study their supply chains to learn how the base chemical gets from its feedstock to finished product
  4. Procure samples of the product at each stage along the process. This step uncovered an unexpected (but very favorable) outcome.
  5. Define a Design of Experiment (DOE) and conduct product testing to verify assumptions at each step of formula refinement
  6. Analyze the test results to conclude which thermophysical properties and product blend constituents produced the desired performance characteristics (magic)
  7. Immediately file patents to protect the magic

I approached all constraints as part of the same comprehensive analytical problem. There exists an optimal solution among potential solutions (not a perfect one!) that delivers the best product performance at the most efficient cost position with palatable availability/delivery time.

Through a pragmatic look at the marketing constraints, I knew how to craft the validation testing to ensure each formulation that was chosen over another delivered or exceeded the consumer-pleasing features. With the test plan in mind, I needed to isolate which facet of the product provided the best product performance and strip away the rest. In this case the formulation supplier further processed my winning blend for other end-use applications. I could remove those from the manufacturing process and not hinder the marketing requirements.

Once I found the specific chemistry and feedstock for the application, I looked at alternative sources to reduce the risk of single-source supply, and to confirm the robustness of the performance given inherent variance in the safer, more natural product.

The engineering mindset considers factors on multiple planes. This key group of buying-decision influencers takes pride in offering a complete recommendation. Knowing how they think and what they value positions you to break through their inherently skeptical nature. Engineers trust data, expertise, and quality. If you give them those three attributes, they’ll be some of your most vocal supporters with the buying authority.

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