MGT 560M Business Modeling and Decision Analysis Lecture 2

1. MGT 560MBusiness Modeling and Decision AnalysisLecture 2 N. Bert Loosmore, PhD 10/08/14 bert.loosmore@pinchot.edu

2. What are we doing today? • Learning Objectives • Talk about influence diagrams • Discuss the 11 point case analysis • Introduce the decision matrix • Desired Outcomes • That you’re ready to do the Southside Restaurant case

3. Check in and/or Any questions? • (about screencasts, readings or last week’s hw?) • How to enter text in Excel • Text box • Merge cells

4. Framing and depicting decisions • We are considering introducing a new product: Introduce Product? Price? Fixed Costs Units sold COGS Company Profit

5. The graphics of influence diagrams • Types of nodes • What the arrows represent: • Can represent either ‘relevance’ or ‘sequence’ • An arrow pointing into an uncertainty or chance node designates relevance • An arrow pointing into decision nodes indicate that the information is available before the decision is made Decision Uncertain Event Outcome

6. Let’s do an example… • You’re thinking about installing solar panels on your building. Your goals are to reduce emissions, while not spending too much money. You don’t know exactly the installation will cost or what happen with energy prices. You also aren’t sure if you’ll be able to charge a rent premium if you have solar panels installed. • First, let’s brainstorm the different types of nodes: decisions, uncertain events and outcomes Now, take a few minutes and sketch out what an influence diagram might look like. (There’s not just one right answer!)

7. Let’s do an example… • You’re thinking about installing solar panels on your building. Your goals are to reduce emissions, while not spending too much money. You don’t know exactly the installation will cost or what happen with energy prices. You also aren’t sure if you’ll be able to charge a rent premium if you have solar panels installed. • First, let’s brainstorm the different types of nodes: decisions, uncertain events and outcomes • Now, take a few minutes and sketch out what an influence diagram might look like. (There’s not just one right answer!)

8. What did you come up with?

9. My Solution Energy Prices Solar Radiation Installation Costs Company Profit Install Solar Panels? Emissions Reductions

10. More thoughts on influence diagrams • Don’t get overly complicated - Simpler is better • You’ll get the chance to practice on this week’s case • Again, there’s no right answer. What I’m looking for is that it holds together and captures the essence of the decision, as you see it

11. The 11-point Case Analysis • Decision Maker • Stakeholders • Decision Context • Values and Objectives • Uncertainty and Risk • Influence Diagram • Alternatives • Quantitative Model and Analysis • Sensitivity Analysis • Decision • Disclosure See course page week 2 for more details

12. Sample Decision Matrix • As part of #8, you should include a decision matrix: • 4 parts to figure out (alternatives, criteria, weights and scores), then the rest is determined for you • Typically the quantitative analysis is used to help figure out the scores • Hint: You’ll want something similar for Southside There’s a sample Excel version on the course page

13. Southside Restaurant Case What is this case about? • Laura Silverton is the manager of South Side and she is interested in selecting a new wine for their wine list • One of the criteria she uses to make her decision is CO2 footprint of the bottle of wine. However, instead of being given this by the wineries under consideration, she’s given much of the low level detail • She needs to make sense of this data as well as other information and figure out which wine to select

14. Two parts to this case • What are the CO2 emissions for each of the three possible wines? • What other information might go into our decision? • A crucial part of our class is the idea that quantitative methods help inform our decisions, AND we should use whatever information is available and important to us. • Emissions matter, but what else? (As the decision maker, you’ll get to decide)

15. Calculating per bottle emissions • We’ve got a whole mess of data, and we need to figure out how to make sense of it. • How does the data we’re given fit within the supply chain? • How do we convert the data we’re given into its portion of the CO2 emissions per bottle?

16. 9 Steps in the Supply Chain • Grape Production • Agrichemicals (production, transport and N2O release) • Production Fuel • Water irrigation • Land Use • Wine Production and Materials • Winery Energy • Barrel Transport • Sugar and Fermentation • Bottle production (& recycling) • Transportation • Wine Transport

17. “Carbon Inputs Associated with Wine” • Pause here to read from the case… (see page 6)

18. It’s a puzzle! • For each step of the supply chain, we want kg C02 per bottle, but that’s not the form we have the data in. • So, we need to look at what data we have, what conversions exist, and then map out how we would get from where we are to where we want to be

19. Let’s look at agrichemicals • We’re given kg of agrichemical input per ton of grapes that a winery uses. We want kg of CO2 emissions per bottle. How do we do this conversion? • We know 2 important things: • The number of bottles produced (bottles/ton) • The CO2 emissions per kg of agrichemical inputs (kg CO2/kg agr) • (and remember, for each winery, we are given their specific usage of agrichemicals in kg agr/ton) ??? kg agr/ton kg CO2/bottle

20. Putting the puzzle together • We can write this as (without the values): • Using: • The winery specific input (kg agr/ton) • The reciprocal of bottles per ton of wine • The relationship between agrichemical inputs and CO2emissions kg CO2 kg agr ton kg CO2 bottle ton bottle kg agr

21. Putting the puzzle together • We can write this as (without the values): • And, make sure the unwanted units cancel and you’re left with the desired units in the right place! kg CO2 kg agr ton kg CO2 bottle ton bottle kg agr

22. Plugging in values • If a winery uses 100 kg of agrichemicals per ton of grapes produced, what is their associated per bottle CO2 emissions? 100 kg agr 1 ton (150+30+55) kg CO2 ton kg agr 700 bottle 0.448 kg CO2 bottle

23. Emissions from Westry Winery • Note: These data are estimated (not given in the case) to fit the Westry total emissions value. Details of the calculations are in the Westry Winery LCA file

24. What I’ve done for you… On the course page: • Westry Winery LCA (*.pdf file) • Westry Winery Analysis (*.xlsx file) • And, for those of you who want the challenge, you don’t have to use what I’ve given you. Feel free to recreate from scratch.

25. Things to consider… • Who should be responsible for getting this data? Is it reasonable for a store owner to go to this level of analysis? What role should the distributor play? • How might the store owner help push for change? • For a given bottle, what are the biggest contributors to its carbon footprint? How did this vary across the bottles? • Given she’s signing a 10 year contract, which places in the supply chain have the potential for reductions from where they currently are? How would we figure this out? Should this weigh into her decision? • Is she or someone else auditing this data? • What do you think about this approach? Is there anything material missing from the analysis? • Do you think having and publishing this data helps drive meaningful consumer change?

26. Questions? • And remember to see the additional case specific questions on the course page

27. For those who are presenting: • What to show: • (We’ve all read the case so keep the intro to a minimum) • Influence diagram • Decision matrix and decision • A short discussion about your quantitative model • Plus anything else you found interesting

28. The next two weeks • The rough plan…

29. What did we cover today? • Learning Objectives • Talk about influence diagrams • Discuss the 11 point case analysis • Introduce the decision matrix • Desired Outcomes • That you’re ready to do the Southside Restaurant case