Definitely want to use revenue (and profit) generated from the product -- to calculate the return on R&D. However, what if you have a really poor sales & mktg. and very productive R&D organization? If revenue is low, it appears that the return on R&D is low. Although financial measures that use revenue and profit can be very valuable, they can give a distorted picture. Metrics that, to the greatest extent possible, directly reflect the output of a particular organization provide the most insight when analyzing a business. Thanks for your comment. Ron
I completely agree with you -- "lines of code" and "gates" or transistors, etc. are wholly inaccurate measures of output, and to use them invites misleading results and misguided behaviors. Thanks for your comment. Ron
One approach is to use a model that calculates the amount of effort the average development team in the particular industry segment would expend on that project. Then compare that effort value with the amount that your team actually spent. If you spent less, then you were more productive. If you spent more, then you were less productive. Since this isn't a forum for commercials, I'll direct you to www.numetrics.com where there is further info on this. Thanks for your comment. Ron
No doubt that value to the customer is the most important metric in business. And using a product's revenue (or profit) as a measure of Output is very useful. However, in most cases it yields an incomplete picture because revenue is the result of the Output of the entire enterprise, not just the R&D organization. For example, high revenue could be the result of powerful marketing and sales, as opposed to superior engineering. This actually is very common -- a strong sales/mktg. organization masks a weak R&D organization. Likewise, the revenue for a particular product line might be very low because of poor mktg/sales, but the productivity of the R&D organization could be very high. Thanks for your comment. Ron
attention grabbing title Ron! productivity is easier to define in manufacturing units as one need to simply check the end results but during research and development, i do not think the productivity is as simple. One way to check productivity can be through the return on investment as everything is about money in the end.
This reminds me of stupid management metrics like "lines of code per hour" for software engineers and "gates per hour" for hardware engineers. It also reminds me of an old Dilbert cartoon in which managment was paying bonuses for verification engineers to discover bugs -- which quickly lead to collaboration between design & verificaton and a cartoon panel in which one of Dilbert's colleagues was coding a minivan worth of bugs!
On schedule, within budget and less engineers.
That's simple isn't it?
But... we engineers like numbers so an equation is required for IC productivity.
To measure complexity... I bet there ought to be some efforts being done already trying to measure that. In some top rated university in the US.
Design complexity is less important than the value to the customer. Presumably, a more complex design will have greater value to the customer and fetch a higher initial price. Instead of trying to measure design complexity, use the market price for the result of that design as a proxy in the calculation of productivity.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.