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Pharma
This industry has very unique challenges. Pharma companies have complex sales processes that change depending on the type of product, long production cycles, with lead times that can easily reach 180 days, and a distinctive requirement for quality; it all comes with an excellent opportunity to get large benefits from applied analytics.
One of the most common challenges they face is that a real increase on market share is highly dependable of medical recommendations and prescriptions and other health care providers influences and decisions. Analytical recommendation models can generate a lot of value for the relationships with doctors and patients. Lead scoring models is also great tool to maintain a strong pipeline.
The product formulation, especially in solid deployed medication, and the packaging process, both represent a singular challenge for manufacturing sequencing and schedule. In addition to that, the complexity of package MRP and constant component changes and improvements only increase the potential value to be captured by the use of analytics.
One of the most common challenges they face is that a real increase on market share is highly dependable of medical recommendations and prescriptions and other health care providers influences and decisions. Analytical recommendation models can generate a lot of value for the relationships with doctors and patients. Lead scoring models is also great tool to maintain a strong pipeline.
The product formulation, especially in solid deployed medication, and the packaging process, both represent a singular challenge for manufacturing sequencing and schedule. In addition to that, the complexity of package MRP and constant component changes and improvements only increase the potential value to be captured by the use of analytics.
DHAUZ can help
DHAUZ has extensive experience in exploring publicly available and privately captured data to leverage data science modeling in combination with process transformation that creates a high performance environment for health care. Here are some areas that we can actively help:
R&D and Clinical Trials
- Big Data and AI can improve discovery and the results interpretation from research and also, during development, it can define which molecules have higher propensity for success
- Identification of eligible patients for clinical trials outside of medical office visits, leveraging, for example, social media and genetic variables
- Real time signal processing during trials to enhance and allow for clinical adjustments, risk mitigation and high efficiency
Manufacturing
- Predictive analytics enables the evaluation and tracking od equipment sensor signals, such as temperature and vibration, to identify potential risks and maintenance needs, which decreases stops and costs
- AI applied to understanding loss of quality root-causes and video analytics that can evaluate the visual quality of components and recommend the required changes or repairs
Supply Chain and Planning
- Process design to support a more modern approach to integrated planning, aligning the strategic, tactical and operational plan cycles and assuring visibility and information flow among them
- Development of tools to learn the best sequencing and exceptions so that planners can best control production flows and reduce risks
Marketing and Sales
- Identification of prescription drivers and segments and the volume of utilization in each segment
- Pricing algorithms, root-cause analyses for lost sales, sales target redefinition during the current month
- Sales force routing
- Attribute based AI and forecast are techniques that work really well for prevention and for calibration of algorithms used to anticipate sales with high levels of accuracy
Where can you get the most impact?
Demand Generation
1. Learn client needs
2. Understand demand drivers
3. Pricing and CTRM
4. Marketing and Sales Execution
Supply Chain & Operations
1. Understand productivity drivers
2. Intelligent planning
3. Optimize manufacturing and operations
4. Distribution speed and resilience
NPS & Business Outcomes
1. Net Promoter Score (NPS)
2. Environmental Goals
3. Top Line
4. Bottom Line
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