Modeling projects usually start with the dreaded blank sheet of paper (or blank screen). How to get started? Just do it. Write stuff down, and see what organization emerges.
Here are some concrete approaches that I’ve often used:
- Start with the question. Inventory is unstable? OK, put inventory on the diagram. It’s a stock, so what are the flows? Put them on the diagram. Are the inflows and outflows unstable, or just one? Follow the unstable direction….
- Start with the data. We get this a lot in marketing science projects. There’s typically a big pile of Nielsen or IMS data on price, promotion and distribution. How does that drive sales? You can do a little data mining for insight, but typically the data describes less than half of what’s going on, so more importantly, what else drives sales? How do brand equity, supply chain performance, and other dynamics introduce feedback into the picture?
- Start with a spreadsheet. There’s always a spreadsheet. It’s probably open loop and static, but it captures features that someone thought were important. Audit the spreadsheet to discover its structure, then make it dynamic.
- Start with the goal. You want to maximize profit? Write down a P&L, then trace each item. Where does revenue come from? What drives costs? When you answer these questions, look for the key strategic stocks that govern the behavior – people, capital, perceptions, etc.
- Start with the physics. What are the key stocks of scarce resources in the system? Equipment, people, money, knowledge? What makes them change, and where are the decisions?
- Start with the stakeholders. What are the major constituencies in the problem domain. What do they want, and what stocks are they looking at to guide how they get it?
The key thing is to remember that modeling is an iterative process at every level. The data might be wrong. The equations will be wrong. The equations might be in the wrong structure. The structure might describe the wrong problem. This is normal. Don’t be afraid to back up and start over.