A Real-World Look at How BI Empowers Employees

Joay SinghalOctober 14, 2014

It can come as a surprise to see that even in today’s technologically advanced world, employees still juggle numerous spreadsheets to make sense of their business. This way of operating not only consumes precious resources but also results in delayed, misinformed decisions.

Business intelligence (BI) can help by providing an up-to-date, eagle-eye view of business performance, plus the flexibility to quickly analyze and identify outliers at an individual unit level. It’s important to realize, though, that BI only works when it’s tailored to the people who use it — your company decision-makers and employees.

How, exactly, can BI empower your employees? What does successful implementation look like in a range of industry settings? Here, we share real-world examples of how BI, done well, helps both power users and decision-makers consume organizational and third-party data, and to share this information at the click of a button or even automatically. Thus, the need for information flow from top to bottom or bottom to top becomes obsolete, expediting decisions that improve the bottom line of businesses and give them a competitive advantage over others.

 

Scenario 1: A VP of business operations monitors market performance

A leading contract sales organization has just launched a new product in the market. The vice president of business operations would like to monitor the market performance and marketing effectiveness on a weekly basis. However, it requires up to 50 different spreadsheets to arrive at a measure as simple as the market share of the newly-launched product. Consider maintaining this large volume of analyses on a weekly basis and consolidating it to arrive at the Key Performance Indicators (KPIs) — an incredibly daunting, error-prone, and time-consuming task.

In contrast, BI offers an automated alternative that churns the weekly data load overnight and presents the KPIs to anyone who needs access to this critical business information anytime, anywhere, along with the option to dig deeper into the performance metrics for a top-down analysis.

 

Scenario 2: A CEO analyzes daily store performance

The United States retail industry typically operates on razor-thin margins. To keep improving the bottom line, the CEO of a giant retailer needs to analyze daily store performance across the entire country. Reviewing thousands of spreadsheets every day can prove to be a nightmare and a performance drag, and conducting video conferences every morning can already be too late to make an immediate impact on the business.

A smart BI solution consolidates data from all of the retailer’s stores and publishes an executive reporting package within just a couple of hours of the day’s closing. Imagine the productivity boost BI provides to this efficient, focused, early-riser CEO who now doesn’t have to wait for the office to open at eight a.m. to begin taking inventory of the operations of the day prior.

 

Scenario 3: A data scientist conducts predictive analytics

A data scientist has been positioned to employ trend and predictive analytics for a renowned consumer goods retailer that undergoes seasonal business cycles. However, the organizational data is scattered across the various business units and corresponding databases. It has been this way for ages, with individual units maintaining their own spreadsheets for corporate reporting.

Not surprisingly, it is monumentally difficult for the data scientist to do his or her job effectively and efficiently. By deploying BI solutions, however, all of the data stored in silos is virtually or physically brought together and made available to authorized personnel for analyses, while keeping the existing reporting mechanism intact to minimize organizational change and possible resistance to adopting BI. This helps employees develop a more data-supported understanding of the business cycle, followed by a more efficient supply chain management through timely business decisions.In each of the three scenarios, employees struggled to obtain the information needed to make decisions and do their jobs. They faced silos of data that took infinite time to coordinate and sift through, and they needed answers on the spot that they could share with other team members. Once they implemented BI, they received the information they needed — in the time span they needed it. And the entire company benefited as a result.