SAP Lumira Sales Intelligence Solution for Trucks Dealers

SAP Lumira is software for visualization and data management. It allows analyzing data by creating and sharing graphical visualization of data from multiple sources without writing code. The main advantages over other analytic tools are: simple and intuitively understandable interface, the ability to retrieve information from multiple heterogeneous data sources (excel worksheets, the relational database tables), data sharing, and others. Skybuffer Business Intelligence experts used SAP Lumira to build sales analysis with SAP Lumira for Robust Trucks, Inc. and evaluated all the advantages of this tool.

BUSINESS CASE REQUIREMENTS

Trucks producer is Trucks, Inc.

Robust Trucks, Inc. is the official dealer of Trucks, Inc.

Trucks, Inc. defines the truck quota for countries annually. Customers can buy trucks directly from Robust Trucks, Inc. or can get them into international leasing without any participation of Robust Trucks, Inc. This transaction also affects Robust Trucks, Inc. annual quota.

It is necessary to make an analysis of sales activities, including:

  • Sales allocation by customers;
  • Sales allocation by trucks models;
  • The level of quota compliance;
  • The maximal revenue of sales transactions possible & completed in the context of sales managers. Purpose: to identify managers with weaknesses (low profitability of transactions),
  • The level of deals closing assessment for each Sales Manager. Purpose: to assess the level and equality of managers workload.
  • Evaluation of weighted deals income. Purpose: to track objects of deals with different levels of profitability in the context of sales managers.
  • Evaluation of the orders capacity in the context of customers and ordered trucks models. Purpose: to find out the reasons of a certain level of sales and to assess the sales for each customer in details.
  • Evaluation of the customers profitability. Purpose: to identify leaders and outsiders among customers in order to perform appropriate promotion activities.

MASTER AND TRANSACTION DATA

The basis for the analysis of the current situation of trucks sales for the specific time interval is represented by the data collected in the CSV file. The first spreadsheet reflects the list of sold trucks, characteristics, and the quota for each type of truck.

Fig. 1. Robust Trucks, Inc, Orders Data. Worksheet 01

The second CSV spreadsheet provides information about the potential deals and deals held with a Manager responsible for each transaction.

Fig. 2. Robust Trucks, Inc, Sales Opportunities Data. Worksheet 02

Data is loaded to SAP Lumira in the form it has been extracted from the data source system.

For analysis purposes the data can be post-processed directly in SAP Lumira. These transformations have no effect for the source data file. Moreover, an original file can be modified and these changes will be reflected in data visualizations reports created using SAP Lumira.

ROBUST TRUCKS, INC. SALES ANALYSIS

Sales assessment

Following charts can help to analyse the year according to date sales activities of the dealer company.

  • The distribution of orders by customers;
  • Trucks sales by models;
  • The level of quota compliance.
Fig. 3. Robust Trucks, Inc, sales assessment

To simplify the selection of values, there is an option of filtering . With the help of this tool there can be shown only values of the user’s interest.

In this example, the most relevant filter criteria for the graphics are in the slide: series of the trucks sold, engine & order type. When selecting a specific criterion, information corresponding to the selected characteristic is displayed in all graphs.

Let us take a look at the “Sales orders by customers”. It is convenient to use the function of Full Screen.

Using this chart we can conclude which customers are most active in making deals. Moving the mouse to the sectors of the pie chart you can see the exact number of deals with the client. In this case Optimal Waybills, Inc. is the leading customer.

Fig. 4. Sales orders by customers

Filtering functionality can also help to monitor customers who prefer trucks with a certain type of engine, for instance, in order to negotiate with the clients more effectively, to be aware of their preferences and to make appropriate proposals for further cooperation.

Fig. 5. Sales orders by customers filtered by Engine type

“Sales by truck models” chart helps to define which item is the most popular among the customers.

Moving the mouse to the sectors of the chart you can evaluate not only the quantity but also the percentage of goods sold.

The quota compliance is an indicator that requires perpetual control. The third chart “The level of quota compliance” represents the current situation of the quota compliance for each type of truck.

Fig. 7. The level of quota compliance

For the current example, it can be concluded that the truck model DAF_CF is being sold quite actively and perhaps a deficit of the annual quota may occur by the end of the year. Thus the increase in the quota should be provided for the next year.

Evaluation of the maximal revenue

The assessment of the potential sales is an important part of the sales analysis.

The chart represented in the second slide allows you to compare the work of sales managers on the base of criteria set. The location of the bubble on the chart reflects the weighted income made by each manager to the date taking into consideration the number of processed orders. The width of the bubble indicates the maximal income of the manager’s deals. The height represents the probability of obtaining maximal income based on the average percentage of bringing the transaction to the point of sale by the Manager.

Fig. 8. Evaluation of the maximal revenue

Observing the chart for this example, it is already possible to make some conclusions. It is evident that in spite of a greater number of transactions for Manager Tommson that are in process, the average income from his activities is less than that of Manager Peterson. The size of the bubble also confirms the fact that Manager Peterson works more effectively, bringing his transactions to the point of sale. At the same time Manager Timberman is in the outsiders’ group, despite the fact that he has more processed transactions than Manager Johnson does. It is easy to notice that the small size of the bubble indicates low probability of receiving income from transactions processed by Manager Timberman.

Trends that have just been determined should be analysed from the different view. To do this, let us go to the evaluation of deals potential.

Evaluation of the deals potential

With the help of the next chart you can assess potential deals of each sales manager more accurately.

Fig. 9. Evaluation of the deals potential

It should be mentioned that Manager Peterson brought the most of the income. Thus, his activities are more productive. At the same time Manager Tommson and Manager Stevens are processing deals with quite large potential income, but due to certain circumstances the probability of bringing deals to the sales point is less than that with managers Peterson & Johnson.

For making a correct decision about redistribution of orders between managers, the parameters of deals closing for each Manager should be assessed. To do this let us go to the evaluation of the deals closure.

Evaluation of the deals completing

The next slide allows monitoring the deals closing by each Manager. The slide shows a chart with a quantitative comparative assessment of completed deals and orders in process for each Manager. The allocation of completed and processed deals among customers is represented in the table.

Fig. 10. Evaluation of the deals completing

Thus, it is possible to evaluate the workload of each Manager. Also a chart allows to conduct a comparative analysis of each Manager’s work.

It is confirmed again that the workload of managers Tommson and Stevens is the highest at the moment and requires redistribution of potential orders between less busy managers. The most rational decision is to pass part of Tommson’s deals to Peterson, and redistribute some Stevens’ deals among Johnson and Timberman.

The table represented in the slide allows explaining quantitative indicator in details. With its help it is possible to track which companies are being processed by every Manager, what is the probability of bringing the deal to the sales stage and what is the weighted income of the deal at the moment.

Fig. 11. Detailed evaluation of the deals completing

The filter panel in the slide allows you to monitor the information about deals with a defined probability of completing.

The status of a potential client, his motivation in buying and other factors often affect the probability of the deal completing. In order to highlight the transactions with the greatest risk of fail let us choose deals with a small probability of closing using the filtering tool.

Fig. 12. Evaluation of the deals completing. Filtering by sales probability

This deals requires greatest attention. Making redistribution, it is advised to involve more experienced sales managers in the work over such deals.

Capacity evaluation of the customers orders

The following chart shows the distribution of orders among customers. The graph allows evaluating the quantity of each customer’s orders in the context of truck models.

Fig. 13. Capacity evaluation of the customers orders

Particular emphasis should be put on the companies with the greatest risk of deals failure highlighted in the previous slide in order to evaluate the capacity of their orders in the past and present, to make a conclusion about the causes of the low probability of completing deals on this basis and to take appropriate actions. To do this, we should mark the companies with a small probability of completing the deals in appropriate filtering box.

Fig. 14. Capacity evaluation of the customers orders. Filtering by the customers with risk of a deal failure

It also makes sense to highlight the sales status: Completed, in order to determine which of the selected customers have already made orders which in its turn increases the probability of sale, despite its little chance at the moment.

Fig. 15. Capacity evaluation of the customers orders. Filtering by the customers with risk of a deal failure. Sales status: completed

According to the chart it is clear that more attention should be given to the organizations of Opportunity Services, Inc, Easy Way Logistics LLC and InTime, Inc. because these organizations are making an order for the first time.

Assessment of the customers profitability

The visualization of the customers profitability is of high importance. It is necessary, for instance, to divide customers into groups for events of various types.

This decision is easy to make based on the chart below.

Fig. 16. Assessment of the customers profitability

A more intensive color and a larger area indicates customers with highest revenue. They should be included in the VIP-clients group.

Customers marked with less intensive color require actions focused on the product promotion.

Conclusion

SAP Lumira is a fantastic easy-to-understand and easy-to-use data visualization and data maintenance tool. Even having a small dataset but using SAP Lumira, you can get comprehensive visualizations of data and make right management decisions.

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