Monday, November 5, 2018

Case Study: Empowering Leadership with Better Sales Reporting



Key Challenges

   Create a cloud-based unified business intelligence engine to consolidate sales data from disparate sources.
   Create a reporting system tracking sales performance across multiple sales programs.
   Create a report showing a unified overview of sales performance with key metrics tailored to the leadership team.

A Comprehensive View for Leadership

For growing companies, maintaining alignment between sales teams and leadership is a challenge. During growth, divisions tend to focus on individual products or specialized markets, and teams become segmented. Sales information then becomes increasingly disparate, and leadership often struggles to keep track of sales metrics.

Our client, the internal sales team of a large software provider, needed to re-engineer an aging sales metric tracking approach. The sales team consisted of specialists trained to sell an array of commercial software products. The company tracked sales metrics using multiple Excel worksheets. Due to customization, the worksheet data was often inconsistent. With the old approach, the leadership team could not track metrics to sales manager and seller levels. Worse yet, no unified view of operational performance existed, impairing the leadership team’s ability to accurately gauge sales performance.

Our Approach

The sales team initially contacted us to build a single Power BI report. When the sales team later decided to consolidate their ad hoc reports, they asked us to build a cloud-based unified business intelligence engine. We redesigned the system with Azure services to deliver eight easy to use reports. We created one report for each of the seven programs the sales team managed. The final report provided a unified overview of the programs. The final report allowed the client’s leadership team to evaluate sales performance at a glance.

We started brainstorming with the client to identify their specific needs. We met with the client’s leadership team to discuss industry-standard tracking metrics and KPIs. The client surveyed their user base to identify the top ten metrics and KPIs to track for each sales program.

To build the metrics, we used our expertise with client's sales databases. We also worked with the data platform teams to better understand the relationships within the databases. We then hosted several whiteboarding sessions, created visual mock-ups, and reviewed the mock-ups to determine the best way to present the data.


We created a powerful implementation intuitive enough to ensure widespread adoption. Our initial metrics and visualizations, though, were difficult to understand. To address the complexity, we worked closely with our client's sales team. We simplified the data visualizations, but still allowed advanced users to drill down to detailed views.

Our project lead later observed that ease of use is a visual's single most important quality. “I learned a lot about user experience and how to tune the UI complexity to the audience with this project. Complex visualizations offer many insights, but clean, straightforward visuals are more intuitive and help drive adoption.”

Another challenge arose when implementing the cloud-based business intelligence engine. Azure Analysis Services initially seemed far too expensive. A later optimization analysis of the existing tabular model design allowed our team to introduce cost efficiencies. These efficiencies led to lower space and processing needs, bringing the cost to acceptable levels.

Azure Data Factory presented a final technical hurdle. Azure Data Factory cannot directly connect to cube data sources. Our client's business intelligence engine needed to connect to multiple upstream data platforms with on-premise cubes. To resolve the issue, we set up a solution that created small virtual machines (VMs) used to pull data from the upstream cubes and process the data onto Azure Data Factory. Cube data was now utilized along with data from other sources.

Our Results

The completed BI engine and report suite provided a comprehensive view of sales performance and  KPIs that were critical to the leadership team’s needs. We consolidated our tabular model to integrate over 200 data points and reduced monthly Azure infrastructure costs by over $5,000. In addition, one of the reports from the suite was ranked in the top ten for usage among over 250,000 reports across the company.