Apoteket is a state-owned pharmaceutical retailer in Sweden, employing 3,200 staff across its 390 physical stores and online operations. To encourage company-wide collaboration, Apoteket adopted Tableau as its analytics platform. Today, the sales organisation can take a more accurate, strategic approach to retail strategy and marketing teams can analyse and share sales data with different departments. As a result of this self-service approach, Apoteket increased sales effectiveness and prevented costly mistakes.
As the largest pharmacy retailer in Sweden, Apoteket has a wide range of data involving partners, promotional activities, and sales analysis. But the company didn’t have a standard platform for data analysis—leading to missed opportunities and insights.
“The more we looked, the more we found instances of important data being stored at a local level, rendering it useless to the wider company,” explains Mats Malhammer, Business Intelligence Architect. “Not only was this hindering the day-to-day activity of numerous teams within the company, it meant important decisions were being made without all of the pertinent information to hand.”
Mats started to investigate the issue and determined the need for a analytic self-service business intelligence (BI) tool.
For example, Mats witnessed that several members of Apoteket’s business control team kept research data on their individual desktops or in local networks, which was only accessible to a handful of individuals—leading to siloed information and potential for costly errors, such as not being able to compare and group data according to business requirements.
Apoteket works closely with a wide network of pharmaceutical manufacturers and retail partners, selling their products both in-store and online, and conducting regular promotional activities.
Before Tableau, Apoteket’s marketing team found it increasingly difficult to track each partner’s promotion success. As a result, the team struggled to determine which promotions were worthy of repetition and which partners it should be working with more frequently.
Today with Tableau, data is now readily available to employees—increasing collaboration between key business groups including sales, marketing, business intelligence and business control.
The marketing team now uses Tableau dashboards to analyse promotional data. The team can determine effective promotions and flag stand-out campaign strategy for repetition, allowing the team to cut costs and focus resources appropriately. With automated reporting, the team can track online orders performance in almost real time—a competitive differentiator in the fast-moving pharmaceutical industry.
Mats’ team can now quickly gather intelligence from across the company and be much more precise with their analysis. Leadership are impressed by the interactivity of Tableau dashboards and the ability to effectively track key performance indicators.
“With Tableau, real insight is never more than a few hours away,” says Mats. “It has transformed the way the BI team uses data for the good of the whole company, while encouraging other teams to be much more proactive with their data analysis needs as well.”
The previous lack of a business intelligence tool for analytics had a hindering effect on the productivity of Apoteket’s business intelligence department.
Since some key stakeholders within internal teams couldn’t extract and analyse data on their own, many of them were leaning on Mats and his colleagues for help. Not only was this taking up a large proportion of the team’s time, it was affecting their ability to conduct more business-critical tasks in a timely fashion.
The upsurge in self-service analytics within Apoteket has quickly led to more creative uses of data and encouraged cross-departmental analysis.
“Tableau has fundamentally changed the way we view and use data as part of our day-to-day activities,” concludes Mats. “Analysis is now so quick and easy there’s no excuse for anyone not to do it, while the information gained is often invaluable.”
This shift has reduced the reliance on the business intelligence team as a reporting factory for the whole company, saving many hours each day that can now be spent working on business-critical tasks and challenging assumptions with hard analysis.