Welcome finance pro!
The UK clearly stands out as the source of the negative profitability variance.
Using Oracle Autonomous Data Warehouse and Oracle Analytics you will complete 4 objectives:
- Discover how the CFO came to her conclusions
- Load your Autonomous Database and prepare data for analysis
- Analyze UK data to understand the situation
- Dig deeper to discover the why behind the issues
You are now Autonomous. Let’s go!
Pulling out her tablet, the CFO quickly studies financial intelligence dashboards powered by Autonomous Data Warehouse using Oracle Analytics Cloud. Let’s look at revenue first.
Revenue KPIs show the business will end the year below plan.
Operating expenses also look like they’re trending up. Let’s zoom in.
Definitely looks like this is a big factor in the negative impact on profitability.
The system recommends reviewing the end of year sales forecast to see if the business can close some of the upside deals and thereby meet the revenue target.
Let’s take a look.
Objective 1 Complete
Now that you understand the high level insights, let’s prepare all the data we need for further insights by combining multiple data sources in one place for fast and easy analysis.
Let’s start by loading all appropriate data spreadsheets that might help in our analysis.
First, let’s load financial data.
Objective 2 Complete
You’ve successfully uploaded a new dataset to Autonomous Data Warehouse and joined it with two others to create a new multi-dimensional dataset for your analysis.
Next, let’s analyze British data to understand the situation.
The UK finance dashboard reveals rising troublesome trends in “OPEX by Account Group”. Let’s examine this trend further.
The graph reveals “Salary & Wages” and “Travel and Expense (T&E)” as key culprits.
Let’s investigate if “OPEX Planning” reveals further details.
Investigating “Out of Policy T&E” , hotel expenses spike around July/August and it continues to be a problem. Better make a note to alert the sales managers.
Objective 3 Complete
Now that you have a better understanding of the situation, let’s dive deeper to discover the why behind the issues.
Simultaneously, the call center had a huge staff turnover in July and has had a hard time filling the open job positions.
Combined data from various sources in the HCM system reveals many young, low salary employees have left the business around that same timeframe. But why are they leaving?
A word cloud, using data collected from an employee survey, sheds light on why employees may be leaving.
Well done! Oracle Analytics Cloud has enabled us to understand the problem with operating profits from all angles. By loading and combining multiple data sources, you’ve diagnosed the root cause and you’re well prepared for a successful board room meeting to share a powerful storyboard of your analysis.