Another update from Decision Modeling. I’m really enjoying this class. Yes, it’s a lot of hard work. But the professor is really good, and I enjoy the topic. This week, we started learning about modeling “risk profiles” in your spreadsheets, and adjusting for risk in a way that’s more nuanced and robust than what is normally used.
See, most B-schools tout the praises of NPV-analysis and business decisions that have the highest EMV – and these are important and useful tools. But they are, in reality, pretty limited, because they make an assumption that we can afford to lose however much there’s a chance we might lose. It’s not very robust. Real people – and real businesses – may not be that tolerant of risk. Using Risk Profiles and another trick called Risk Utilities allows us to be more nuanced in the way we approach decisions in which risk plays a significant factor. We also learned a little about how to use a package called @Risk (an Excel add-on) to help with this analysis.
Finally, we learned more about general Excel modeling tips and tricks. As much as the former part of class was interesting, this was, for me, the best part. You see, I love writing. Writing is a deep-seated need, for me. I love drawing. And though it seems wholly unlike those creative activities, I love making models in Excel. In part, that’s because I’m a nerd. But more than that, it’s because I feel like making models in Excel is a creative challenge. It’s still a creative activity, bounded by logical constraints. Trying to solve a problem on how to do something in Excel is like trying to solve a puzzle. When I come up with a creative and elegant solution, it gives me a feeling of pride and pleasure. Learning more tricks of the trade only better equips me to tackle bigger, more mind-boggling problems. Put it another way, it’s like playing with Legos, but the Legos are numbers and Excel formulas (FYI, I’m a grown man, and I still love Legos; please send more).
Sometimes, I just wish I had the guts to ask permission, at work, to be in charge of building the budget and forecast models in Excel, from scratch. I’ve no doubt I could do it – it would be a long-term project, certainly, but I have the skills. And I’ve learned enough about good “modeling hygiene” (as the Decision Modeling professor likes to put it) to make it a really robust and flexible and reasonably realistic model. I can’t say for sure it would be terribly easy for non-excel jocks to use, but my experience building that character sheet for my modified D&D game system I mentioned last week suggests to me I have the ability to make components of the overall model easy for non-gurus to enter information. Ultimately, though, I realize such a model is really too much for Excel. I’d want something that works like Excel, but in reality it would have to be a database, and what individual departments would have, rather than an Excel spreadsheet, is some sort of application (that looks and works something like a well-modeled Excel spreadsheet might) that gives them access only to that part of the database that directly concerns what they can control.
My current company is trying to roll-out such a database application, using an Excel add-on that makes Excel act as the front-end of the database, called Hyperion. We’ve been using it in Finance for the last year, now, and we’ll soon be rolling this out across the company. The problem is, while Hyperion (with the add-ons to it that we’re using) does the interface and database part that is necessary, it has no inherent business model on the back-end. Which means that when we enter data into the database, it’s just numbers without meaningful context. There’s no part of it that says “if I spend money here, then this measurable result will happen here” (the sole exception to this being our Headcount model, and though I helped build parts of that model, I don’t get to be the guy on the team that does the ongoing management of the model). This lack of a connection between inputs and results means that when we make a decision on one aspect of our business, we have absolutely no basis for understanding what the ramifications of that decision will be on other measurable business metrics, aside from some heuristic models in the heads of various grand high muckity-mucks that may or may not be reflective of reality.
It’s exactly that kind of problem I’m learning to address in my Decision Modeling class. Now, somehow, I have to convince the grand high muckity-mucks that I’ve got the skills needed to make this thing work and make their jobs easier. The Decision Modeling prof calls these our ninja-skills and we, the students, are ninjas in training. I kind of like being a ninja, I just wish I wasn’t so stealthy.