The 2022 Data Revolution continues: extending analysis with scenarios
In a previous article we talked about using data to grow your business in 2022, why data is important and potential items to start analysing in 2022.
Here we are going to talk about extending that analysis to look at scenarios. It is a bit more advanced, but gets to the core of better decision making and being able to learn from the analysis to help with this.
Most analysis helps us tell “what” has happened, but scenario analysis helps us to model what might happen if the inputs were changed (it is a fancier way of saying what-if analysis). The secret of scenario analysis lies in the underlying data model. That is, the way that the data is brought together, calculated and segmented. This is something the PT 2.0 team can help you build into your own data analysis reporting.
What we want to be able to do is model the relationship between data. Let’s take a simple example and work to a more complex example to see the power of scenario analysis. Oh, by the way, did I mention that if you do this right then you can automate the analysis so it takes seconds to change scenarios depending on what you are modelling? Exciting right?!
Example 1: If we were to reduce debtor days by 10 days, what effect would it have on cashflow?
Let’s keep this example simple. Suppose we currently have 30 debtor days; we would simply use that change to shrink the payment cycle of the debts being paid based on the seasonal sales volume.
What would show out of this kind of analysis is how much extra cash (or working capital) is now available to the business and what the long-term trend would be based on a sales budget. You would then change the number of days and get the new changes in working capital.
Now, this is a very simple example, but it could also be extended to include things like different payment times in different seasonal periods, different payment trends inside a period (e.g., more people paying upfront), but you get the gist, the kind of scenario analysis can make it easier to model what the impact of those decisions may be.
Example 2: Increasing sales revenue by 20%.
This is where it starts to get cool!
Something as simple as increasing revenue may have several different methods and several different impacts. Firstly, we need to determine are we increase the value of sales, volume of sales, or both. Or are only certain product categories increasing and others staying the same?
Next if volume is increasing, that extra revenue does not turn directly into profit. So, what does that look like in terms of increasing our costs?
We can then get the model to start looking at the impact on variable costs across and between product groups to reflect the impact of changing our sales targets. The more variables we analyse means the greater accuracy in the scenarios we can model, but note, there is a point of diminishing returns, so sometimes less is more!
OK, all the accountants have just read the above and said to themselves, “This is stupid, he is just doing a budget, we have been doing this for decades”. And you would be right, except for two little items:
1. Using a data model, we can get this to happen daily and automatically so we can do the analysis in fractions of the time with the latest data; and
2. we can extend this past the financial, to also look at operational effects and things like:
a. What is the impact on the sales team?
b. What would be the impact of inventory re-order points and timing?
c. Do we have the capacity to deliver the extra sales?
d. And more.
Scenario planning is not new. What is new is the ability to be able to analyse the data more quickly and be able to easily make faster and wider ranging decisions. Pretty darn cool if you ask me!
Watch this space for an article on using analysis to make recommendations (rather than decisions) in the near future.
Our team at PT 2.0 is always happy to talk about the virtues of using data in your business, reach out for a no-obligation chat now on (07) 4659 6700, or email us on email@example.com.