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What is Smart Discovery?

Smart Discovery is a set of capabilities in SAP Analytics Cloud that is powered by the SAP Cloud Platform predictive services. The guided analysis is designed for Business Users and features the power of Exploratory Analytics by leveraging SAP’s proprietary predictive technology. Smart Discovery allows business users to take advantage of predictive analytics without the need for any Data Science or Machine Learning expertise.  It enables business users to interact with insights, in form of intuitive charts and natural language, to make faster decisions and share newfound valuable insights with their organization. Let’s have a look at a concrete scenario.

Scenario: Analyzing Contractor Data to meet Budget

To demonstrate the feature, we use a scenario where an organization regularly hires contract workers. They would like to know which factors have a positive and which ones have a negative impact on a contractor completing their assignment with their given budget. Through Smart Discovery, this organization is able to discover the influencing factors and then they can take action to ensure contractors finish within their budget.

Setting Up

  • Create a “New Story” and import your data
  • Create a “New Smart Discovery”

 

For this scenario, the Percent_of_Budget_Consumed column in the data shows how much of a contractor’s given budget was used for their project. We are interested in finding out, what data is influencing the Percent_of_Budget_Consumed field. Smart Discovery’s interface allows us to easily exclude measures and dimensions from the analysis. In this case, we are excluding Budget_On_Track from our analysis in this scenario.

  • Let’s select Percent_of_Budget_Consumed as the measure we are looking at
  • Uncheck the box next to Budget_on_Track to exclude it from our analysis
  • Click “Run”

 

 

Interpreting Smart Discovery Results

In the background, Smart Discovery is running predictive technologies going over different algorithmic models to help us find the one that fits our data best. Here is what we see for this scenario:

 

So what did we learn? Well, we know that the Insight Quality is rated 4/5 which is great. In addition, 10 of the columns we provided for analysis have come back as Key Influencers. We can also see the column we chose to exclude and filters applied if there are any. Now as business users, we can take a closer look at what these influencers are to see what further insights we can gain from them.

The bar chart on the left displays the top influencers of the Percent_of_budget_consumed. By clicking into them, we can gain further insights about specific influencers’ impact. It turns out Supervisors have the highest influence on whether or not contractors finish with their Budget. On average, Eric and Yuru’s contractors collectively exceed the budget, especially when compared to the overage average of 96%. This is definitely something the organization should take action on!

Understanding Unexpected Values

Next, we can analyze the unexpected values in the dataset to understand the differences between predicted and existing values of the Budget_Consumed. Here, there are 14 outliers that vary significantly from the predicted results.

Simulation Analysis

To see how much we can expect in Percent_of_Budget_Consumed, the simulation feature can be used. Based on selected criteria, we can see the contribution by influencer on the possible Percent_of_Budget_Consumed. Seen below, under the selected Supervisor along with all the remaining fields, we can see an expected budget consumption of 93.89%.

Further Analysis

Now we want to know if there is a correlation between the Supervisor and Contractors’ Ratings. The heatmap visualizes the analysis and compares different Key Influencers combinations. These metrics can provide interesting combinations of fields and insights.

When comparing the Supervisor to the Rating, through this heatmap we can see that Eric and Yuru’s contractors tend to finish above average Budget_Consumed despite the type of Rating the contractors had. We can now use this information to keep an eye on this supervisor and look into why their contractors are finishing way over budget.

Sharing Insights

Lastly, after gaining and gathering all these new insights through our analysis, we would want to share this information with our colleagues. We can simply select any of the charts we looked at and pin them to any of pages for sharing.

  • Click on any chart you want to share
  • Click “Copy to Page”
  • Select the desired page to pin the chart for sharing

 

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