Running numbers is crucial to understanding where you are with a new technology, especially if it is a physical product or tied to heavy industry. Even if you’ve only got three numbers in that initial .xls sheet, your ability to follow those assumptions over time and measure performance is important. Further, you’ll get better at your forecasting if you keep a record of what your past estimates were.
I’ve been reading / listening to three books that deal a lot with estimates of munition sizes, payloads and other constraints from World War II; The Making of the Atomic Bomb by Rhodes, Dam Busters (14 hours), by Holland, and To Kingdom Come by Mrazek. The math that went in to planning the equipment and raids was similar to what would go into current manufacturing planning.
- Scope: What was the size of the target
- Munition size: How big were the munitions needed to destroy the target
- Delivery mechanism: What size aircraft was needed to deliver the payload
- Probability: How many attempts would be required
Throughout these three texts there are multiple examples of the right engineers, scientists and operations personnel sitting together to talk through how they achieve their common goal. Often times their early math wasn’t right. Often, their goal in engineering and R&D was to enable the math to occur. However, in all of these examples, having done the math they were able to work towards the needed goals.
Production and Plant Capacity
Working with a typical filter maker or nonwovens manufacturer benefits from working similar math. Often times we know a target unit cost, but we are working with a customer through a long and complex product development cycle. Penciling out some rough numbers early on in the development cycle can help put any known issues on the table sooner rather than later.
- Unit cost – this is a great place to begin and usually helps flush out a lot of issues. By looking at the costs of the benchmark material, making some margin assumptions and cost estimates, you can understand a lot about what you’ll need.
- Line speed – line speed is often an area of importance, it obviously feeds into your unit cost assumptions, and depending on the geography different buyers may run in different shift configurations. Not everyone has 24x7x365 capabilities, which is good to know early.
- Volume – For nonwovens and rolled goods, this is easy; take my line speed, my usuable width, my operating time less downtime and you’ve got your annual volume capacity for a given line.
- Capex – Spend more money and you can get a line that makes more. This is especially true in electrospinning where it is always possible to go faster (our current fastest installation is 50 m/min – we could take that recipe faster with a more expensive line).
- Market demand – This is the greatest sanity check to apply and one we are always quick to look for. We once had a customer that was requesting a line speed we thought was very aggressive. In the meeting I couldn’t figure out why it made me so uncomfortable – looking at industry reports later that evening I realized that at that speed they would be making 7x current market demand. That was an important sanity check!
- Others – there’s no shortage of metrics that are valuable. The earlier you take a look and use them in a conversation with a customer, the easier it is to understand what it takes to succeed.
There’s another reason it is a good idea to have the math available earlier rather than later. Learning the potential red flags early in an engagement is helpful for everyone. If there are unrealistic expectations or if a production partner doesn’t know an answer to an important question, or isn’t willing to share, then being able to put those issues out front leads to a healthier long term relationship.
Reblogged this on Nicolas Umiastowski – Internet – Agile – Books.