CFO Talk: Modeling Demand Beyond the Simple Financial Model: An Interview with Lance Rubin and Giles Male
Steve: When I think of models, I immediately picture forecasts, capital spending, some of the things you talked about earlier. Today, what type of models are in biggest demand?
LanceThere is one in particular that we have seen interest in. Social benefit bond modeling. We’ve seen quite a lot of this in Australia because our society is trying to tackle public private partnerships (PPPs). These are partnership between the public sector and the private sector, government and non for profit organizations. For example, toll roads and other infrastructure assets.
We have been doing this for the last two to three years and we’ve just closed one recently around disadvantaged youth that don’t attend school. Our model forecasts the impact that has on society and homelessness. Modeling is starting to be used more than just, as you say, for cashflow. I mean, cashflow is always important, but commercial profits and balance sheets and all the rest, now we are talking about social issues. It is incredibly empowering for myself and my staff who work on these projects because they know at the end of it our work could potentially save someone’s life. Our input may change the future direction of society and that is pretty empowering. When starting my financial modeling career, I would never have thought we could construct models that would have this type of impact.
Steve: That is eye opening, Lance. Using models in a way that have more than just a financial impact.
In the scenario you describe above, the results have a long tail. To make your model accurate enough for investors to consider the opportunity do you need a lot of data? Is this a cross between modeling and data analytics?
Lance: You hit the nail on the head. It plays a huge role. I think that’s part of the challenge around the data, because quite often there will be people saying certain things and certain metrics and key hurdles. So, what happens is there’s various trigger points that kick in at various measurement periods during the bond.
So, the point of the PPPs is to raise money to pay for the project. We issue a bond, a debt instrument that pays a coupon with principal repayment based on those measurement points. So, data is incredibly important at those measurement points to work out, is this program successful or not? If it’s successful, then the coupon ratchets up or ratchets down. Giles mentioned earlier the scenario analysis and sensitivities, which is pretty much or should be in most models. In this case, it is critical.
So, data is important. But you don’t need the data to build the model, but you absolutely need the data to run the program. You need specific measures at specific points in time, to determine if we are successful or not. You cannot necessarily measure everything so it’s a control group that you are putting through a program. There’s anecdotal evidence of what this will do for society, like not having to build more hospitals if people get sick or, you know, other infrastructure assets that you need to develop. All these aspects and the measuring of those data points become incredibly powerful, but also quite political. You end up in this really interesting debate between politics and data and modeling and society. It’s a really sort of nice little melting pot of complexity, which is a weird, but increasingly important, space to be in as a financial analyst.
Steve: That is quite an example, it opens the mind to what these models can do. I have been a practicing CFO my whole career with a mindset that is all about a financial outcome. PPPs have a whole different aspect to them that I didn’t expect. Thank you for sharing that.
Giles: I have a different anecdotal story for you from my experience. So the answer to your first question, What type of models are in biggest demand? The most common thing I see is people looking for ways to automate the exporting of actual results. We see a huge amount of manual copy paste work that we solve for small and medium sized enterprises (SMEs) with excel add-in tools. I’ve built some crazy models. One was trying to estimate the number of commercial washing machines a hotel group needed based on the size and weight of dirty laundry from hotel rooms and the number of vans being used in the number of deliveries to a commercial property. It was a nightmare to try and work out. I had to run scenarios for a mobile gin bar. So how many bottles of gin did they need? Scenarios where how many people at an event have got alcohol problems, which was an interesting one to build as well.
Steve: It sounds like we are trying to fix a social ills there to, Giles. I guess the sky’s the limit when it comes to modeling for decision making. If there is a decision to be made, there may be a model behind it.
That wraps up today’s CFO talk. Thank you for joining us Lance and Giles. I sure appreciate it.
Lance/Giles Pleasure. Thanks, Steve.
Steve CFO.University is a community of member scholars, companies and trusted advisers committed to the professional development of chief financial officers.
Next in our series with Lance and Giles - How is Modeling Changing and Why Should CFOs Care?
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