Facing the Blank Sheet

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.

The blank sheet of paper

Confronting the dreaded blank canvas

4 thoughts on “Facing the Blank Sheet”

  1. Concrete and useful advice, Tom. Thanks.

    There’s another angle, a psychological one, akin to “writer’s block,” that I often have to confront. I (we?) often want things to be really good, if not perfect, from the beginning. And, we certainly don’t want to be embarrassed when showing an early product to someone else. But that’s not reality and it makes it really hard to start.

    My brother, a writer, starts with what he calls the “zeroth draft.” Even before the “first draft,” he’s willing to start with any kind of junk just to get things underway. And, that’s the “zeroth draft.” Even his wife doesn’t get to read it. But, it gets things started and is usually quickly discarded for the “first” of typically 30-35 versions.

    I try to keep that in mind when I’m struggling to start problem definition, modeling, and my own writing of a very different sort.

    1. 30 duds before things get real sounds about right to me.

      Sometimes there’s a risk to not being stuck, too. Sometimes I find it too easy to create the first draft, and the result is a clever model that’s good for showing off, but not on point for the problem. Best to keep those in the dark for a while, too.

  2. Two ends of an SD modeling spectrum are (1) Answer Machines built to generate output that answers questions and (2) Thinking Machines built to change or deepen mental models. At the thinking machine end of the spectrum, I find going through a loop diagram on the road to a simulation model is often useful. Lots of people suggest a version of the following steps :

    (1) List variables that seem like they might be important to the foggy idea we have of a problem
    (2) Draw reference modes for up to 6 variables (by hand and from memory)–these actually become “problem statement” with no words.
    (3) Create dynamic hypotheses (i.e. loops)
    (4) Create a simulation model(s) by
    (a) choosing a loop (or cohesive loop set)
    (b) quickly identifying which “molecules” can be used where and which areas are mysteries.
    (c) model the loop, starting with the molecules and finishing with the mysterious area(s).

    Notes: (i) Molecules of System Dynamics Structure are available from the Vensim site and on Stella Online. (ii) Molecule documentation is available at the website below.

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