Predictive Analytics

Advanced Analytics and Power BI in Chemical Manufacturing

Advanced Analytics with Power BI in Chemical Manufacturing Industry

Advanced Analytics with Power BI in Chemical Manufacturing Industry 700 500 Xcelpros Team

Chemical manufacturing is a complex process with several different variables to consider at any given moment. Staying ahead of the competition today means using technology to help drive productivity and profitability.

Advanced analytics features in Power BI supply valuable insights into the substantial amounts of data that enable chemical manufacturers to make more informed decisions and optimize their operations.

In this blog post, we’ll explore how advanced analytics in Power BI can help chemical manufacturers drive productivity and profitability, including how data-driven decisions can be used to improve performance, reduce costs, and create more value for the business.

Power BI and the benefits of Advanced Analytics

In the chemical industry, data-driven decisions are necessary for businesses looking to maintain a certain level of efficiency and profitability. This means that organizations need access to reliable analytics and insights from their data to make strategic decisions that lead to better outcomes. Advanced analytics in Power BI are powerful tools that can help chemical companies maximize their productivity and profitability.

Advanced analytics solutions offer various features designed to help chemical companies find trends, uncover hidden patterns, and predict future events. Using the latest AI-based algorithms, these advanced analytics solutions can uncover insights that would otherwise be impossible to discover, resulting in improved decision-making and more efficient operations.

Power BI is an analytics tool that provides an interactive platform for visualizing and slicing data. Included features like charts, graphs, and dashboards allow users to easily explore and analyze data from anywhere, making it easy to gain a comprehensive understanding of their data and make more informed decisions.

Figure 1:Benefits of Advanced Analytics in Power BI

Benefits of Advanced Analytics in Power BI


Power BI is a powerful business intelligence tool that can integrate with various systems, including enterprise resource planning (ERP), customer relationship management (CRM), financials, and more. These integrations make connecting data across different platforms easier, ensuring that all stakeholders have access to the information they need to make decisions quickly and accurately.

For businesses in the chemical industry, Power BI integrations can be incredibly useful for businesses in the chemical industry. They allow companies to make better use of their data and get insights from multiple sources. An ERP integration can help track inventory and orders, while a CRM integration can offer information about customer preferences and buying habits. By connecting these different systems, businesses can better understand their market and customers.

In addition, Power BI integrations can be used to improve operational efficiency. By integrating various systems, such as enterprise asset management (EAM) and predictive maintenance systems, businesses can get real-time insights into their equipment’s performance. This can help them find potential problems before they become major issues and ensure that their operations run smoothly.

Overall, Power BI integrations can be invaluable for businesses in the chemical industry. By connecting multiple systems, they can gain better insights into their operations and customers, improve operational efficiency, and ensure compliance with regulatory requirements. With Power BI, businesses can make better use of their data.

Automatic Reporting

Power BI supports automated reporting to help show trends and improve productivity. This automation allows companies to quickly find problems or opportunities within their processes and operations, which helps them make informed decisions quickly and efficiently.

With automated reporting capabilities, businesses in the chemical industry can save time by automating data collection and reporting processes. They can also receive help from the insights generated by this process, allowing them to make smarter decisions in less time. With accurate and up-to-date data, businesses can measure performance, compare trends, and optimize operations more effectively.

Overall, automatic reporting with Power BI helps businesses in the chemical industry achieve greater efficiency, profitability, and customer satisfaction.

Report Customization

Power BI gives businesses several ways to customize reports to meet the needs of any business, including those in the chemical industry. Businesses can quickly and easily customize their reports to streamline the entire process. This includes creating personalized visualizations, adjusting the format and layout of data, and adding new elements to existing reports.

Customized reports can give these businesses key data points to check progress, performance, and safety. Reports can be tailored to track specific aspects of a business’s operations and production, allowing for more efficient and effective decision-making. The customization process is highly intuitive and provides users with an interactive dashboard for creating and editing reports.

Overall, report customization provides businesses in the chemical industry with the tools they need to stay ahead of their competitors and maximize their value in the market. With custom reports, companies can easily identify trends and make better decisions faster, increasing productivity and profitability.

Simplified Collaboration

Power BI was designed from the start to promote collaboration and communication across teams in the chemical manufacturing industry, simplifying data sharing and streamlining how different departments and locations work together to achieve their objectives.

One of the main benefits of Power BI is that it helps users break down data silos. By allowing users to pull from multiple sources, such as cloud-based databases and on-premises sources, Power BI enables users to get a comprehensive view of their data. This helps decision-makers in the chemical manufacturing industry better understand the relationships between different pieces of data, which can then inform more informed decisions.

Power BI also makes it easier to access and share data with others within the organization. Through built-in visualizations, users can easily create a dashboard of all the data they need to review, making it easier to collaborate on data-driven decisions. Power BI also offers custom security settings, allowing users to control who can view, edit, and access the data. This ensures that sensitive data stays secure and private while allowing users to collaborate on projects.

Power BI’s collaborative features make it an invaluable tool for the chemical manufacturing industry. By eliminating data silos, users can access a single source of truth that can be shared with anyone in the organization. Additionally, its ability to restrict access to certain data and its customizable security settings help keep confidential information safe. Finally, its built-in visualizations help make it easier for everyone involved in a project to collaborate on data-driven decisions.

Predictive Maintenance, Throughput Analytics, and Maximizing Value

Chemical manufacturing is an incredibly complex industry with many operations and processes. Fortunately, advanced analytics and Power BI can help chemical producers make data-driven decisions and optimize their production, maintenance, and supply chain operations. Three advanced key analytics–based tools can help chemical producers improve their performance: predictive maintenance, throughput analytics, and maximizing Value.

Predictive maintenance is one of the most effective ways to ensure the best performance of chemical manufacturing assets. This tool uses machine learning algorithms to identify patterns in equipment behavior and predict potential failures before they occur. Predictive maintenance also helps to minimize downtime by enabling initiative-taking maintenance actions. This approach can increase operational efficiency and reduce costs associated with unexpected equipment breakdowns.

Throughput analytics are essential for optimizing production operations in chemical manufacturing. By analyzing production data, chemical producers can gain insights into their processes’ efficiency, find improvement opportunities, and reduce waste and inefficiency. Yield analytics can decide how effectively raw materials are being converted into finished products, while energy analytics helps producers identify areas of excessive energy consumption. Finally, throughput analytics enables chemical producers to optimize their production schedules by tracking the performance of each stage of the process.

Maximizing Value is important for enhancing the profitability of chemical producers’ supply chains. Power BI uses advanced tools to analyze customer data and uncover valuable insights that can be used to create new products and services that meet customer needs. Value maximization can also help chemical producers find opportunities to reduce costs in their supply chains by streamlining processes, finding more cost-effective sources of raw materials, and improving planning operations.

Next Steps

As with any technology solution, getting the most out of Power BI for your chemical manufacturing business requires a solid implementation plan. To ensure success, best practices for implementing Power BI at a chemical company should include these steps:

  • Gathering requirements from key stakeholders to find specific data needs and business goals.
  • Designing an analytics solution tailored to the organization’s unique business and data environment.
  • Developing an end-user interface that is intuitive and easy to use.
  • Training users on how to get the most out of their Power BI data.
  • Testing and refining the system to ensure it meets the needs of all stakeholders.

If you are ready to take the next step in using advanced analytics and Power BI to improve productivity and profitability in your chemical manufacturing business, contact us to learn more.

Schedule a call, our experienced team can help you design, implement, and support a custom solution tailored to your requirements. With the right analytics solutions, you can drive performance while getting the insights you need to stay competitive in today’s changing markets.

Pharmaceutical analytics and business intelligence using power bi banner

Pharmaceutical Analytics and Business Intelligence using Power BI

Pharmaceutical Analytics and Business Intelligence using Power BI 700 500 Xcelpros Team


Modern pharmaceutical companies are undergoing a significant transformation with new opportunities from digitization, big data, and analytics. In response to COVID-19, businesses are seeing an increased need for an agile enterprise Business Intelligence (BI) architecture to leverage these opportunities in order to grow. Successful Pharmaceutical companies are looking beyond standard operational and statutory reports to implement more powerful Analytics and AI-driven solutions. These new solutions provide actionable insights and useful KPIs to help make better decisions. This leads to more empowered teams and new engagement that drives additional revenue.

Pharmaceutical companies generate massive information every day through their day to day operations. But the data is not always being put to the right use. Some companies tend to look at reports with a traditional eye that doesn’t drive a ‘call to action’ to grow the business.

The strength of any analytics software lies in its ability to help users easily create quick insights, especially for an agile business like pharmaceutical manufacturing. Creating reports in days instead of months frees up hundreds of hours in unnecessary spend to gather these hidden insights. This allows business leaders to repurpose cost savings towards other operational improvements and growth.

There is a right and wrong way of reporting – one provides overwhelming numbers, while the other means to understand those numbers and make them actionable.

As the pharmaceutical industry continues to undergo significant adjustments to new opportunities presented by digitization, big data, and analytics, more enterprises continue to see the need for an agile enterprise Business Intelligence (BI) architecture to leverage these opportunities & seamlessly deliver business-critical insights to executives.

The Strength of PowerBI

Power BI, Microsoft’s business analytics solution, lets you visualize your data and make it accessible to your Organization. Insights can be easily shared through various platforms of your Organization by embedding them in your app, portals, or website, collaborating on Teams, and integrating them into your ERP or CRM applications. Microsoft’s Power BI makes it easy to combine these numbers from different sources, streamline analytics onto a single dashboard, act on newfound insights, and enhance visibility to other teams in your organization.

Leveraging PowerBI interactive reports in a few quick and easy steps

  • Onboard
    • Access PowerBI either from or any of the Microsoft ERP/ CRM applications.
    • Connect to your data wherever it lives.
    • Explore your data with interactive visuals.
  • Collaborate & Share
    • Publish reports and dashboards.
    • Collaborate with your team.
    • Share insights inside and outside of your Organization.
  • Access insights from anywhere
    • Act with seamless access to data insights from your desk or home.
    • Access on the go with Power BI visual reports built rapidly.

Book a demo to learn how Power BI can boost your pharmaceutical analytics.

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Turning Industry Data into Smart Decisions

Leading Pharmaceutical companies who are transforming into agile organizations need 360-degree insights for business-critical functions such as manufacturing execution, sales productivity, financial management, purchasing raw materials from approved suppliers, quality assurance & quality control.

Today’s pharmaceutical organizations collaborate, monitor, and communicate on available live data to achieve operational excellence. Pharmaceutical business intelligence enables these organizations to monitor real-time data from multiple sources and combine them into one pharmaceutical dashboard with the ability to drill-down into the report to identify issues, as necessary.

Figure 1: Pharmaceutical Analysis using Power BI

Pharmaceutical Analysis using Power BI

Usage in the Pharmaceutical Industry

01.Interactive Reports

Power BI is an analytics software that brings to the table a strong background in delivering end-to-end BI analytics to modern Pharmaceutical companies such as

  • Efficiency Reports On Lot Production
  • Trending And Analysis Of Quality Control Data
  • Recommendations Based Clinical Trial Reporting
  • And Financials Per Batch Produced For Each Product
  • Product Go to market assessments (how much spend and types of activity is involved, expected and actual results)

02. KPI Reporting

Accurate decision making occurs when reporting provides clarity on both good and bad data points on prime KPIs. With business analytics in the pharmaceutical industry, companies can acquire intelligence in real time and can track key performance indicators like:

  • Machine utilization
  • Process efficiency
  • Cost of Sales
  • Inventory levels
  • Batch Losses and cycle times
  • Quality standards of a product line
  • Customer engagement and customer experience

03.Real-Time Analytics

One of the essential requirements for agile Pharmaceutical companies is to have real-time analytics of overall operations, and to be able to make quick corrections and proactively handle situations before they turn into risks. Especially for manufacturing execution and pharmaceutical inventory management, knowing the work is progressing and inventory is turning around helps production supervisors to manage batch production processes much faster and make on the fly corrections. This real-time reporting on screens throughout a production plant gives needed visibility to both the managers and operators who can be alerted and fully aware of any issues.

Figure 2:Real-Time Data Tracking with Power BI

Real-Time Data Tracking with Power BI

Benefits of PowerBI enabling business improvements

  1. 1. This information gives the ability to make changes to processes based on how well resources are functioning to increase productivity, and how each product lot produced is performing in the market.
  2. 2. Getting real-time alerts with Power BI mobile apps makes your operations more efficient, allowing you to achieve a higher level of organizational agility and minimize response times.
  3. 3. Power BI enables monitoring of your supply chain end-to-end, letting you identify problems and potential bottlenecks before they can affect critical processes.
  4. 4. Monitoring quality inputs and outputs from all sources, including your customers, allows you to make quick and meaningful decisions that will improve the quality of batches that are manufactured.
  5. 5. The ability to share your dashboards with suppliers and partners is a plus and accommodates adjustments to the latest information available to work towards making your processes leaner and smarter.
  6. 6. Microsoft’s Power BI is a full-featured BI solution that offers a number of benefits to many different organizations on their path to success such as –
    • Global Scale – Local Speed
    • Agile Business Processes
    • Predictive Analytics
    • Machine-to-Machine
    • Employee Onboarding

Basic analytics used by the Pharmaceutical Industry

  • Products & Inventory
    • Full Track & Trace Functionality
    • Enhanced Global Marketability
    • Customer Requirements
    • Product Quality
    • Product Recalls
  • Sales
    • Quotes & Order analysis
    • Pricing and Cost reporting
    • Available-to-Promise reporting
    • Order Profitability
  • Supply Chain Management
    • Match demand and supply
    • Improved Supply Chain Responsiveness
    • Updated and efficient Logistic analysis
  • Financial
    • Product Profitability reports
    • Batch costs
    • A full audit of transactions
  • Manufacturing
    • Safety and sustainability analysis
    • Realtime production data reports
    • Equipment failure predictions
    • Production rescheduling

Final Thoughts

A big step towards change today comes from enhancing visibility across all operations including manufacturing execution, sales force productivity, procurement, and financials. Power BI brings to the table a strong background in end-to-end BI services for modern pharmaceutical companies – covering BI strategy, managed services, implementation & support, and even more. From the moment you start considering a BI solution for your growing Pharmaceutical company, the benefits of Microsoft’s Power BI become evident very quickly. Microsoft’s Power BI will continue to be a must-have product for leading Pharmaceutical companies by delivering a 360-degree insight of operations.

References: Advantages of Using Power Bi

Predictive analytics in the pharmaceutical industry key use cases banner

Predictive Analytics in the Pharmaceutical Industry: Key Use Cases

Predictive Analytics in the Pharmaceutical Industry: Key Use Cases 700 500 Xcelpros Team

At a Glance

  • The digital era has given companies various tools and techniques to help pharmaceutical manufacturers optimize and streamline their operations, and predictive analysis is one such highly advanced method.
  • There are different ways with which predictive analytics can integrate with existing software setup and forecast plausible technical glitches and predict future trends, thus helping in enhancing operational efficiency.
  • Predictive analysis can help planning to execution, aftermarket services level to develop better products/ services, improve their response time, and stay ahead of the curve for delivering better customer experience.

The Role of Robust Infrastructure

Database management has become one of the topmost priorities for companies across the globe. This database is used to fabricate trends and patterns for a particular time-frame or a process or a product. Data historians have been around for quite some time now, but manufacturers have recently started to look at them as more than software that stores and retrieves data. Application of predictive analytics is turning out to be a game-changer in terms of predicting the future with maximum accuracy and helping manufacturers make the right calls across various functions- purchase, operations, consumer demands, marketing, and more.

Any business operates with the ultimate motive – to enhance productivity and profits. Optimizing operations thus becomes a must for manufacturers. Companies are riding the digital wave with cutting-edge technologies and tools such as Cloud, Internet of Things (IoT), Machine Learning, and Digital Analytics. By making the most of this digital disruption and using predictive analysis to their advantage, companies can achieve better operational efficiency and higher productivity.

Increased and better predictability for both structured and unstructured data helps companies in planning their operations accordingly for enhanced productivity and a faster pace of work.

Predictive Analytics in Pharmaceutical Operations

Predictive analytics is creating a buzz in the Pharma industry for quite some time now. Different pharmaceutical manufacturing companies are looking to model their business processes by gauging the future requirements. The predictive analysis makes use of data historians to accurately make predictions about future trends, possible glitches, and diversions along the road. While technology has come a long way when it comes to predictive analysis, at an enterprise level, there are many things you can do to make the most of this technique.


of healthcare executives stated that predictive analytics is important to their business’ future.


As major companies are competing to stay ahead, product sales and consumer acceptance of a specific drug are a few contributing factors that help decide on advancing to Predictive analytics.

Here are a few ways that predictive analytics helps Pharmaceutical operations become more streamlined and agile:

01.Predictive analytics assets help in understanding patient needs ahead of time

For years Pharma companies have invested heavily in market research and insight experts to understand various geographies and patient domains. This included research to understand and forecast patient needs and medicine usage compliance to help both R&D and manufacturing teams prepare them ahead, thus catering to the requirements of the patient base. Predictive analysis plays a vital role in this domain by taking historian data and mining it to populate trends and patterns that can be used by Pharma companies to decide upon the demand for their product. Advanced digital analytics is also capable of generating models based on consumption density for a particular geography, demographic, and health index of the patient base. A pharmaceutical company, thus, would automatically be empowered by knowing its end customer base better and learn the composition of drugs and approximate quantities to produce. You can, therefore, produce the medicines as per the forecast and restructure your supply chain as per the demand. All this will optimize your operations by streamlining both the production department and your supply chain. This will result in enhanced productivity and reduced risks of stock-outs or inventory influxes.

02.Digital analytics plays an imperative role in predicting plausible manufacturing equipment glitches

Anyone working on a production line can vouch for the fact that faulty equipment can cost fortunes by becoming the reason for slowed down or altogether stopped production for days. What predictive analysis does is that it uses the stored equipment data and runs the algorithms to understand the working patterns of any equipment. This, in turn, helps in generating reports for plausible scenarios of equipment malfunction. The production team can get forewarned and can work on the said equipment beforehand to prevent any glitches. Apart from helping in enhancing the operational efficacy, this can also help in preventing loss due to stalled production.

One can take the predictive analysis a step further and use the trends generated to get into a proactive maintenance mode, rather than a more cumbersome and costlier reactive maintenance option.


uptime improvement can be achieved by ensuring predictive maintenance in factories.

Source: A Report by PWC

03.Predictive analytics enhances operational efficiency by enabling risk assessment

Predicting the actions and production outcome of a batch record has become integral to measuring the performance of a Pharma product line. Predictive analytics helps in this assessment with maximum accuracy. It also helps in proactively foretelling issues risks related to product line performance, which allows Production Managers to mitigate these risks to raise product quality standards, and hence become a key driver in increasing product performance in the market. This could apply to both software and hardware in a production line. The cumulative phenomenon results in better risk assessment. This helps the operations team to proactively plan the course of their actions for a better outcome. The advanced predictive analytics tools integrate with different software used by the manufacturers to recognize patterns, share information with other machines and apply the principles of machine learning to automatically gauge risks and alert the users on a timely basis. For optimized operations, risk aversion plays an important role.

Figure 1Use Cases of Predictive Analytics in Pharma


Deriving 360 degree patient journey insightsDeriving 360 degree patient journey insights


Influencing patient adherenceInfluencing patient adherence


Capturing genomics data to accelerate discovery of precision medicineCapturing genomics data to accelerate discovery of precision medicine


Speeding up drug discovery and developmentSpeeding up drug discovery and development


Improving the efficiency in clinical trialsImproving the efficiency in clinical trials


Identifying gaps in compliance to streamline regulationsIdentifying gaps in compliance to streamline regulations


Reducing cost and speeding up time-to-marketReducing cost and speeding up time-to-market


Improving safety and risk managementImproving safety and risk management


Managing operations and employee trainingManaging operations and employee training


Taking effective sales and marketing initiativesTaking effective sales and marketing initiatives

04.Advanced analytics is essential in accelerating operations

The ways mentioned above with which advanced predictive analysis helps in operational efficiency have all resulted in more agility in the overall operations. Rapidly delivering medicines to the end customer, is becoming a primary responsibility for Pharma companies within the Pharma Value Chain. Companies see a rapid generation of patterns, demands met with more ease, lower risks in manufacturing processes – advancing production lines, and related functions to be more agile.

Business Scenario

Meridian Medical Technologies, a Pfizer company, continues to experience manufacturing challenges in the production of EpiPen® (epinephrine injection, USP) 0.3 mg and EpiPen Jr® (epinephrine injection, USP) 0.15 mg Auto-Injectors, and the authorized generic versions of these strengths. These challenges are expected to result in tighter supplies and greater variability in pharmacy-level access at this time.

Added to the shortage of EpiPens due to tighter supplies, the U.S. Food and Drug Administration provided additional information on lots that are about to expire creating further risk in Epipen availability for the patient base.

A good model of predictive analytics in the Pharma supply chain that provides a gauge of stock requirements based on patient demand, in-store inventory, and expiration dates would have mitigated this risk of Epipen outage before it is too late. Time to market is an essential factor in deciding the success of a product. Accelerating pharma manufacturing processes will thus help companies stay ahead in the competition.

Key Takeaways

  • Predictive analytics is highly effective in risk assessment, equipment analysis, trend forecasting, and data mining.
  • Every industry has their specific criterion to make use of predictive analysis to boost sales and with better use of such tools, enterprises will be better prepared to serve their customer base.
  • Manufacturers can benefit highly from this advanced digital technology by optimizing their operations and enhancing the speed of production.
  • Speeding up the medicine to the market process by predicting demand based on patient demographic enables Pharma companies to be prepared for the increase in end-customer demand and manage stock outages without compromising patient needs.

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