A Fortune 50 healthcare company needed an efficient way for managers and executives to track personnel and manufacturing metrics across sites and regions. bipp’s data modeling capability made this possible, and scorecards developed using bipp are live at 130+ facilities worldwide.

Vital Company Data Points

  • Fortune 50 healthcare company
  • Operations in 60 countries
  • Products sold in 175+ countries
  • 125,000+ employees
  • $80B annual revenue
  • One of the world’s top 5 healthcare innovators
  • Four divisions: Pharmaceuticals, Medical Devices, Consumer Products, Delivery


Visibility is a perennial challenge for global manufacturers. Our client, a F50 healthcare company, needed to gain greater visibility into its international manufacturing locations. They used Tableau and other BI products to develop dashboards at the site level, and all locations used their own BI solution. But managers and executives wanted a single platform to view consolidated KPI data associated with all global manufacturing plants.

To provide this visibility, bipp developed a plant scorecard that could onboard new global manufacturing locations and track personnel and manufacturing KPIs such as ‘Headcount’ or ‘Total Spending’ for that plant. Previously, adding a new site scorecard could take up to six months, but bipp’s data modeling capabilities typically reduced that to less than two days. The project began with bipp building a single reusable scorecard for ten locations, and the solution now displays KPIs for more than 130 plants.


Large manufacturing companies struggle to maintain comprehensive views of their operations. Their two priorities are typically ensuring end-to-end supply chain visibility and clarifying what’s happening at a micro-level within each plant.

For bipp’s F50 healthcare client, plant-level visibility was the critical challenge that brought them to consider bipp’s modern BI solution. They needed a way to display information related to each location in their drug manufacturing and medical devices divisions, including human resources metrics, manufacturing rates, cost metrics, attendance, and other KPIs.

Each plant had developed dashboards using Tableau, Qlik, or other BI platforms. These gave managers visibility at the manufacturing site level, but the dashboards fell short regarding regional or global visibility. As a result, location owners and higher-level executives had no way to see aggregated KPIs such as ‘Cost Per Finished Device’ and ‘Training Adherence’ from multiple plants. There was also no consistency in dashboards between sites, so it wasn’t possible to benchmark performance. Furthermore, they couldn’t visualize how metrics had changed over time.

This ad hoc approach made it difficult to create consistent dashboards for new locations. Each facility had to develop its solution, which meant there was no ability to scale design and data set management nor achieve a consistent regional or global view.


To meet the client’s local and regional reporting and analyzing needs, bipp’s analysts used the platform’s advanced data modeling functionality to build a manufacturing and personnel scorecard. This scorecard established a single web-based source of truth at a single URL. It could automatically be replicated across plants, and rolled up KPIs such as ‘Productivity’ and ‘Schedule Attainment’ into an aggregated view.

Single Model, Multiple Sites

The key ingredient for this single scorecard was the underlying data model. bipp created a single data model in a predefined format, so the healthcare company’s managers didn’t need to change the underlying model to onboard a location. To bring on a new location, plant analysts only had to format the data to conform to the predefined schema and specify the data source. This approach made it easy to scale, as each time they wanted to onboard a new site to the platform, the client’s analysts could leverage the underlying model. KPIs fell into four broad categories — cost, quality, safety/people, and reliability — but varied at each location to suit local reporting needs. bipp’s data modeling approach made it possible to display each plant’s KPIs without having to write a new model each time analysts added a site.

Since the scorecard was consistent, data could be aggregated across location or area levels so regional or global executives could analyze trends. It was easy for executives to view specific information across plants by applying filters, which allowed them to either deep dive or zoom outwards for a broader view. They could track products that were manufactured at different sites in a way that was previously impossible.

Furthermore, since the same data model and scorecard were used across locations, they saved hundreds of hours of human effort per plant. Analysts no longer needed to create individual data models and dashboards to meet their reporting needs.

Autoscaling Replaces Manual Visualization Creation

What enabled this was a bipp feature called TileRepeater, which made autoscaling visualizations possible. For example, to create a report for a new site with a traditional BI approach, BI analysts would manually define the report. Since the client’s visualizations were shaded line graphs which showed a change in KPIs over time, this manual process was inefficient and unnecessary. TileRepeater allowed them to replace this manual process with a filter that automatically rendered new shaded line graph visualizations when new facilities (and associated KPIs) were added to the platform.

Furthermore, TileRepeater made it possible to automatically update these visualizations as the database updated, eliminating the need to create or update visualizations any time a new plant was onboarded. Adding a new site required no effort beyond building a data pipeline between the locations and the scorecard.

Automated Pipelines Allow You to Plug-and-Play

The data itself lived in an Excel sheet on the cloud or could automatically be added when source systems fed into databases on the cloud. For example, one client site had a machine that produced needles, with production data feeding into SAP. This data was automatically pulled into the bipp scorecard within ten to 15 minutes. The KPIs were then automatically calculated and visualized.

To be successful, bipp’s analysts had to understand the client’s KPIs, learn how they formatted data, and then train the client’s analysts and end-users to connect their locations to the scorecard. bipp created a training manual, so client employees didn’t have to reach out for help. With bipp’s scalable scorecards, they simply needed to format the data then plug it in to onboard a new plant.


This personnel and manufacturing scorecard started with ten sites. However, when executives at other facilities learned about the project and noticed the operational efficiency of adopting this new solution, they asked to be onboarded to this new reporting method.

Adding new plants was a matter of formatting the database and connecting it, so what took several months in Tableau could be done in less than a few days with bipp. There was no change in the underlying data model. The client could keep adding sites, and the scorecard was live within days.

Today, with an average of 10 KPIs per plant, bipp is managing more than 2,200 visualizations across the plants. Each visualization would take four hours on competitive platforms, so the bipp solution represents a time savings of more than 8,700 hours since the relationship began.

The scorecard now serves as a reporting tool for location owners and higher-level executives. They can look at the scorecard, monitor how KPIs are performing, and if they notice something underperforming, can zoom in to investigate.

The project began with the client’s pharmaceuticals division but expanded to the company’s medical devices division as well. bipp now supports more than 220 locations in Asia, Europe, North America, and South America.

Over the next year, new plants will continually be on-boarded to the scorecard. bipp is also rolling out support for non-English languages and mobile devices in 2022.

The Last Word

Data modeling is a powerful way for manufacturing companies to gain visibility into their operations by building consistent scorecards across sites. It allows them to quickly onboard new locations while aggregating KPIs so regional or global executives can monitor trends and dive deep as needed.

bipp's modern business intelligence platform is an easy and affordable way for analysts to leverage data modeling. bipp is designed for data analysts using best practices of modern software development and allows full customization that transcends what's possible in other BI platforms.

Interested in seeing bipp’s data modeling functionality for yourself? Contact us for a complimentary demo, or sign up for your free trial here.