When faced with an important decision, there are a variety of informal methods you can use to visualize various outcomes and choose an action — perhaps you talk it out with a colleague, make a pros and cons list, or investigate what other leaders have done in similar situations.
Particularly when it comes to marketing, this can feel risky — what if my colleague is so attached to a new product, she doesnâ€™t want to mention any of its shortcomings? What if my marketing team doesnâ€™t mind office growth, but they havenâ€™t considered how it will affect our strategy long-term?
Sometimes, you canâ€™t make a decision properly without introducing a formal decision-making method. In cases like those, you might need a decision tree.
What is a decision tree?
A decision tree is a flowchart-style diagram to help you analyze various courses of action you might take for any given obstacle, and the consequences for each. There are three parts to a decision tree: the root node, leaf nodes, and branches. This method can help you weigh risk versus reward, and map out a course of action to follow.
The visual element of a decision tree helps you include more potential actions and outcomes than you mightâ€™ve if you just talked about it, mitigating risks of unforeseen consequences. Plus, the diagram allows you to include smaller details and create a step-by-step plan, so once you choose your path, itâ€™s already laid out for you to follow.
Here, weâ€™ll show you how to create a decision tree and analyze risk versus reward. Weâ€™ll also look at a few examples so you can see how other marketers have used decision trees to become better decision makers.
Decision Tree Analysis
Letâ€™s say youâ€™re deciding whether to advertise your new campaign on Facebook, using paid ads, or on Instagram, using influencer sponsorships.
For the sake of simplicity, weâ€™ll assume both options appeal to your ideal demographic and make sense for your brand.
Hereâ€™s a preliminary decision tree youâ€™d draw for your advertising campaign:
As you can see, you want to put your ultimate objective at the top — in this case, Advertising Campaign is the decision you need to make.
Next, youâ€™ll need to draw arrows (your branches) to each potential action you could take (your leaves).
For our example, you only have two initial actions to take: Facebook Paid Ads, or Instagram Sponsorships. However, your tree might include multiple alternative options depending on the objective.
Now, youâ€™ll want to draw branches and leaves to compare costs. If this were the final step, the decision would be obvious: Instagram costs $10 less, so youâ€™d likely choose that.
However, that isn’t the final step. You need to figure out the odds for success versus failure. Depending on the complexity of your objective, you might examine existing data in the industry or from prior projects at your company, your teamâ€™s capabilities, budget, time-requirements, and predicted outcomes. You might also consider external circumstances that could affect success.
In the Advertising Campaign example, thereâ€™s a 50% chance of success or failure for both Facebook and Instagram. If you succeed with Facebook, your ROI is around $1,000. If you fail, you risk losing $200.
Instagram, on the other hand, has an ROI of $900. If you fail, you risk losing $50.
To evaluate risk versus reward, you need to find out Expected Value for both avenues. Hereâ€™s how youâ€™d figure out your Expected Value: take your predicted success (50%) and multiply it by the potential amount of money earned ($1000 for Facebook). Thatâ€™s 500.
Then, take your predicted chance of failure (50%) and multiply it by the amount of money lost (-$200 for Facebook). Thatâ€™s -100.
Add those two numbers together. Using this formula, youâ€™ll see Facebookâ€™s Expected Value is 400, while Instagramâ€™s Expected Value is 425.
With this predictive information, you should be able to make a better, more confident decision — in this case, it looks like Instagram is a better option. Even though Facebook has a higher ROI, Instagram has a higher Expected Value, and you risk losing less money.
How to create a decision tree in Excel
- Put your base decision under column A, and format cell with a bold border
- Put potential actions in column B in two different cells, diagonal to your base decision
- In column C, include potential costs or consequences of the actions you put in column B
- Go to shape tool, and draw arrow from initial decision, through action and consequence
While the Advertising Campaign example had qualitative numbers to use as indicators of risk versus reward, your decision tree might be more subjective. For instance, perhaps youâ€™re deciding whether your small startup should merge with a bigger company. In this case, there could be math involved, but your decision tree might also include more quantitative questions, like: Does this company represent our brand values? Yes/No. Do our customers benefit from the merge? Yes/No.
To clarify this point, letâ€™s take a look at some diverse decision tree examples.
Decision Tree Examples
The following example is from SmartDraw, a free flowchart maker:
Example One: Project Development
Hereâ€™s another example from Become a Certified Project Manager blog:
Example 2: Office Growth
Hereâ€™s an example from Statistics How To:
Example 3: Develop a New Product
To see more examples or use software to build your own decision tree, check out some of these resources:
- IBM SPSS Decision Trees
- LucidChart Decision Tree Software
- Zingtree Interactive Decision Tree Template
Remember, one of the best perks of a decision tree is its flexibility. By visualizing different paths you might take, you might find a course of action you hadnâ€™t considered before, or decide to merge paths to optimize your results.
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