How Arterium uses data-driven approach to improve decision making
Arterium creates and distributes in Ukraine and international markets high-quality and effective medicines to ensure a healthy, longer and more productive life.
Industry: Production and distribution of medicines
Company size: Corporation, more than 3,000 employees
Arterium Corporation is one of the largest pharmaceutical companies in Ukraine, founded in 2005. The company’s portfolio includes 147 human health products and 17 veterinary drugs.
The corporation includes PJSC Kyivmedpreparat, the Ukrainian leader in the production of antibacterial drugs, and PJSC Halychpharm, the leading Ukrainian manufacturer of herbal medicines.
Software and Services
Microsoft Power BI
The corporation not only carries out all production processes in accordance with Good Manufacturing Practice (GMP), but also actively modernizes and improves all business processes at enterprises and Research centers. By introducing innovations and actively developing, Arterium strives to ensure that every patient and every doctor constantly feels cared for and is confident in the high quality of the company’s products.
Employees of the Arterium’s production team
Why was there a need to implement a data-driven approach?
The company’s product portfolio includes more than 150 drugs. They are produced at two factories in Kyiv and Lviv. In order to make effective management decisions, as well as to predict the release of products, the company’s management needs the correct initial data: on the number of medicines produced, compliance with plans, the volume of defects and consumer complaints.
In 2021, Arterium set itself two goals: to be able to monitor the KPIs of plants in real time and, as a result of this data-driven approach, make timely decisions to prevent any deviations in the activities of plants.
Arterium strives to build consumer confidence and provide the highest quality product. It is to support this goal that corporations continue to introduce changes in production processes.
Workers of finished goods warehouse
How were the critical production indicators analyzed before Power BI was implemented?
In Arterium, a management reporting model was in place, which was maintained in Excel spreadsheets. All important data from two productions were stored in IFS/SCADA and 1C. Due to the lack of a single tool for obtaining information about production, analysts had to import different reporting formats from different systems and manually consolidate the indicators into a single document.
Reporting with the use of Excel spreadsheets posed numerous risks:
- Probable errors due to the human factor,
- Potential loss of information,
- The same data could be interpreted differently by different people.
Therefore, the main goal of cooperation between SMART business and Arterium was to systematize the process of collecting data and compiling indicators from different sources. As well as a visual display of analytics in the form of interactive dashboards.
Selection of critical production indicators and their display in Microsoft Power BI in real time
To streamline the process of building reports, Arterium, together with the SMART business team, reviewed KPIs and decided on a list of the most important reports that needed to be implemented as part of the project in the first place, namely:
- Fulfillment of orders in production at the specified time,
- Implementation of the strategic plan,
- Productivity in nominal units for the previous period,
- Recalculation and selection by units of measurement,
- Actual defect,
- Defect of the future period,
- Level of order fulfillment,
- Fulfillment of the sales plan,
- Display of the quality of input materials,
- Index of critical defects for write-off,
- Consumer complaints.
Improved decision making with a new reporting model
Thanks to changing the reporting model and implementing Microsoft Power BI, Arterium managers have received a flexible and mobile tool to help them make informed decisions based on the confirmed input data in the reporting.
Analytical reports in Arterium (with model data)
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