Use case #5: Forecast Analysis vs. Actual Performance
Category: Performance | Solution: DataMa Compare | Type: Recurring | Client: Travel & Leisure | Extension: Tableau
Tags: #Controlling #Performance #Budget
DataMa helps us to manage and understand on a monthly basis the drivers of our growth vs what was forecasted. It enables us to make quick and adequate decisions regarding Marketing actions or operational effort.
Click & Boat is a major web C2C marketplace matching private boat supply with customer rental demand.
The data team helps all business teams find insights and make decisions with first party data. Among other tools, they are regularly working with Tableau, based on a Snowflake database. They have been using DataMa within that stack for more than a year.
Among their tasks, one key challenge is to define and monitor the forecast of income, and regularly explain gaps between actual and forecasted revenues throughout the year. This analysis is critical to discuss with investors and make business decisions.
One of the complexities of the C2C marketplace is that the company income consists of the demand performance on one side, and the supply performance on the other side.
The match between supply and demand is not always the same, and for our client, some important demands are “Followed”, which means that they are handled by phone through a customer agent, and some other demands are “Unfollowed” which means that the owner alone is responsible for accepting the demand through the web platform. Obviously, the share of demand followed by customer agents is critical to explaining performance.
As such, they ended up with the following market equation:
This equation, which seems slightly more complex than the usual analysis in DataMa, has the important advantage of making the share of followed demand appear explicitly, which will allow the team to clearly monitor the impact of that KPI on the total revenue vs. forecasted.
Below is the technical translation in DataMa’s interface for that market equation:
In DataMa, you can set up the market equation using the “=**(*+(1-)*)*” annotation
Forecast/budget data is usually in an Excel spreadsheet which is used to build models and play with hypotheses. Once this exercise has been done for the year, the client brings it to Snowflake to join with the actual numbers for reporting purposes.
In this case, the data is then accessible directly in Tableau, and then DataMa is added as a Tableau extension, so that final users can have access to DataMa’s insights directly in their usual Tableau dashboard.
Obviously, the type of data (forecast version and actual) is the main dimension, which will be used for comparison. The data is also broken down by market and brand.
Here is an example (anonymized) dataset
We ingest the data using the DataMa Tableau dashboard extension
In DataMa Compare, the use case provides a quick view of the key drivers between actual and forecast date, and between baseline and target data to explain why the client is straying from the target, and to understand the value of each initiative and where to focus.
The whole use case in set up in Tableau and published in Tableau server so that users have seamless access and can interact with filters and hypotheses
In the example above, we see that the actual revenue is below the forecast (or targeted revenue), mainly due to the lack of traffic, particularly in the US, likely due to the pandemic. As a side effect, the Online Conversion (CVR) is down, because US users convert well, but they have decreased in the mix.
Thankfully, this decrease of traffic allowed the customer service to handle a larger share of demand than expected, which had a positive impact on revenue, and the acceptance rate of “Unfollowed” has also been higher than expected, limiting the impact on total revenue.
The report has been published and shared on Click & Boat’s Tableau server, so that final users can access DataMa’s waterfall easily and interact with filters and hypotheses.
The fact that DataMa was used in Tableau made adoption and regular updates easy and seamless.
DataMa’s waterfall allowed Click & Boat to align all stakeholders on the main focus required for performance improvement and clearly explained the financial impact of complex effects such as mix effects or changes in customer service efforts.