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How Embracing IoT Enables Business Growth

How Embracing IoT Enables Business Growth

How Embracing IoT Enables Business Growth 700 500 Xcelpros Team

At a Glance

  • $5.5 – $12.6 trillion: The estimated dollar impact on the world economy from the Industrial Internet of Things by 2030
  • 26%: The impact of IoT in manufacturing, hospitals, and other areas
  • 10 – 14%: The impact of IoT in human health-related companies
  • 55%, down from 61% in 2020: The economic value potential of the developed world

Source: McKinsey Digital

IoT in Production

The Internet of Things is continuing to have a growing impact on all industries, including the production of medicines and other pharmaceuticals.

“The IoT enables devices to connect and exchange data. The IoT connects assets to processes, systems, and people in manufacturing. This enables better integration of plant processes, achieving higher productivity levels and taking manufacturing to the next level of transformation, Industry 4.0,” a blog post from IBM states.

“IoT for manufacturing can harness the data from machines and equipment to transform the processes and systems of the modern factory environment. By denying or ignoring the transformation that the IoT (internet of things) will inevitably bring, manufacturers risk falling behind competitors and losing clients that value speed and innovation,”

Today, the world is in the midst of the fourth Industrial Revolution following 1783’s use of water power and steam, 1870’s introduction of electricity and the 1960’s switch from analog to digital technology.

Industry 4.0 embraces cognitive manufacturing using a combination of connected sensors, big data, predictive analysis and robotics. With the industrial internet of things (IIoT) on the rise, human workers are moving away from repetitive, mundane tasks. Instead of people dipping thermometers into vats or manually counting products, sensors can monitor temperatures in real time. Barcode labels attached to everything from individual packages to pallets let handheld devices identify the contents and where they belong.

This information flows from sensors to device controllers for each machine. Each controller sends information into a plant’s internal computer network. From there, it’s passed into individual workstations that can be anywhere in the world.

Digital Controllers for IoT

Walk into any production plant anywhere in the world and regardless of what the plant produces, changes are high you’ll see controllers made by Siemens.

“Siemens is a pioneer in framework and energy arrangements, just as computerization and programming for the Industrial Control And Factory Automation Market. Being one of the world’s greatest makers of energy-effective, asset sparing advancements, this organization gives research center diagnostics, clinical imaging hardware, and clinical IT solutions,” Verified Market Research states.

VMR lists Siemens of Germany at the top of its seven industrial control and factory automation companies. The others are ABB of Sweden, Emerson Process Management of the U.S., Rockwell Automation of the U.S., Schneider Electric headquartered in France, Honeywell of the U.S. and Mitsubishi Electric of Japan.

Siemens markets the SIMATIC IOT ® gateways, which make it easy to, “implement forward-looking production concepts in your existing plant with SIMATIC IOT gateways – they’re open, versatile, and retrofittable,” the company states.

One of Siemen’s products is a controller aimed at cloud computing: the SIMATIC Cloud Connect 7. These types of controllers help companies with far-flung operations in multiple countries share information in real-time, letting workers know what’s going on in a machine a continent away. Industrial manufacturers sending this information through the Microsoft Azure cloud computing platform can easily access data from—or send commands to—devices using these controllers.

Siemens’ industrial robots “help manufacturers grow and develop new applications that were once unfeasible with previous robotics technology.” Combining different Siemens controllers and robots is one way small and medium businesses can boost their production and efficiency. By automating formerly repetitive steps, companies can run production lines longer with reduced errors. Fewer human interaction is required, allowing production runs without anyone in the building.

Information from these controllers produces what’s commonly referred to as “big data.” Terabytes of data can be routed through machine controllers into your network from individual sensors. Unfortunately, this information is almost worthless if you can’t make it work for you.

Figure: 1IoT Enterprise Spending Forecast

IoT Enterprise Spending Forecast

IoT Data

When it comes to IoT data, Enterprise Resource Planning (ERP) software is the next logical step in the flow of information. ERPs are designed to organize the data sent through your controllers and present it in useable forms such as graphical dashboards and reports.

“ERP systems bridge information gaps across different departments within a business allowing managers to see a more holistic view of a company’s finances and critical issues. With easy access to all company processes and data, managers can make quick and informed decisions to improve the productivity of the business,” according to Omniaccounts.

One important ERP feature is resource allocation. Modern sensors and controllers might be able to tell you what each machine is doing, but not which sequence of machines is most efficient. That’s where your ERP comes in.

Omniaccounts states “When ERP systems are implemented correctly across a business, they transform the financial, operational, and human resource aspects of an organization. Companies at the forefront of innovation are implementing ERP software to improve the way data is shared across an organization, reduce internal costs, increase efficiency, and improve processes across their organizations. An ERP system fits in with any industry, be it retail, corporate, industrial, and even small businesses, assisting with the day-to-day operations of the company and the ever-changing industry needs.”

Effective ERP

Picking the right ERP for your business can make a big difference in functionality. Among the many benefits of modern ERP for manufacturing is improving supply chain efficiency by helping track raw materials from the supplier to your warehouse. Once the essential items arrive, an ERP designed with labeling makes it easy to efficiently store, trace and track products throughout production and on to customers.

The right ERP also boosts production by enabling more efficient resource allocation.

Imagine your factory is running a dozen different jobs and one of the orders is smaller than normal. When that job completes, the ERP can indicate that a machine is available. The remaining time can then be used for preventive maintenance, to run a low-volume order for one customer, or increase production for another.

On top of resource allocation, especially with IoT data, an ERP with predictive analysis helps companies.

  • It lets you know when a part is showing wear so you can replace it before having to shut down a production line
  • It helps predict where new markets will emerge through evaluating business intelligence
  • Supply chain information, coupled with business intelligence, can predict where the next Suez Canal-type fiasco might occur, giving you the option to route your shipments through other ports

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ERPs and Pharmaceutical

Today’s modern ERPs are a great way to boost the business of any small, medium or large business. ERP Research lists six ERP software makers whose products are especially good for pharmaceutical companies.

“Many pharmaceutical companies are exploring Microsoft Dynamics as their pharmaceutical ERP. The solution provides great flexibility plus a large partner ecosystem that has developed many pharmaceutical industry add-ons,” ERP Research states.

An important advantage of using Microsoft Dynamics 365 products is the company’s focus on security. Using Azure, Microsoft’s cloud computing platform provides an additional layer of data security as propriety information travels from one company site to another.

Labeling solutions that can print either barcodes or QR codes lets pharmaceutical companies embed any and every piece of required information in each label. A scan of an individual product’s label can then provide all data required in order to meet the regulations of each country or state that item moves through after leaving the factory. Even safety data sheet (SDS) information and instructions can be embedded in a label, quickly and easily.

Final Thoughts

IoT in the pharmaceutical industry is sure to be a defining factor as more use cases develop. Any company wanting to take advantage of modern technology and move to Industry 4.0 need to look at investing in at least three types of products:

  1. 1.IoT sensors to gather information at the machine level
  2. 2.Controllers to guide that data into your network
  3. 3.A modern, efficient and scalable Enterprise Resource Planning tool like Microsoft Dynamics 365 to turn that data into information for helping your company run more efficiently and profitably.

This combination gives your company an edge over competitors locked into older products and programs. Is your business IoT ready?

using AI ml-in the pharmaceutical industry key considerations banner

Using AI & ML in the Pharmaceutical Industry – Key Considerations

Using AI & ML in the Pharmaceutical Industry – Key Considerations 700 500 Xcelpros Team


Artificial intelligence is one of those science-fiction-sounding phrases, but what does it mean to people in the pharmaceutical industry? What is the difference between AI and its cousin, ML, which means machine learning? How can the two types of computer software make pharmaceutical companies more efficient and profitable?

The answers are in what they do and how AI and ML work together.

AI can be defined as using computer algorithms—math—to perform tasks requiring human intelligence. IBM defines AI as “leveraging computers and machines to mimic problem-solving and decision-making capabilities of the human mind.”

“It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable,” John McCarthy was quoted as saying in a 2004 paper.

So if AI acts like somewhat like a human mind to solve problems, how is machine learning different?

“Machine learning is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence,” Wikipedia states.

In essence, the two types of programs work together to analyze information.

For example, say the first 100 production runs of product XYZ1000 have a 70 percent success rate in terms of meeting basic quality standards. Analysis shows the difference between success and failure is one step. Every run where the temperature was kept within a 0.2-degree range succeeded. Every run where the temperature exceeded 0.5 degrees failed. Logic says that keeping the temperature within that narrow range boosts success which, in turn, improves productivity.

Machine learning tells operators, “keep the temperature within 0.2 degrees for this one step.” Artificial intelligence builds on machine learning. It says, “by keeping everything else the same and keeping the temperature in this single step within 0.2 degrees,” the company will see:

  • More efficient use of raw materials
  • Less waste
  • Greater profits
  • A host of other benefits

So how does a pharmaceutical manufacturing company benefit by using AI and ML? Let’s look at the numbers.

By the Numbers

  • $100 billion: The amount of money AI and ML can generate in the US health care industry alone.
  • $161 million – $2 billion: The estimated cost of getting a new drug through clinical trials and obtaining FDA approval.
  • 72 percent: The percentage of healthcare companies believing that AI will be crucial to how they do business in the future.
  • 62 percent: The percentage of healthcare companies considering investing in AI soon.
  • 61 percent: The percentage of companies believing that AI will help them identify opportunities they will otherwise miss.
  • 13.8 percent: A study from the Massachusetts Institute of Technology estimates the number of drugs successfully passing clinical trials.
  • 11 percent: The percentage of businesses who have not considered investing in AI.

Sources: Digital Authority Partners and PharmaNews Intel.

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How AI Helps the Pharmaceutical Industry

Add in a third element—large data sets created by Internet of Things (IoT) sensors wired into a company’s network—and the result is a technology-savvy, company that can see ways to improve efficiency. AI runs computations that estimate probabilities based on known numbers.

Going back to our earlier example, 30 percent of the production runs failed quality standards. That’s the new baseline. Having computers that can finely tune machines reduces tolerances.

Another way pharmaceutical companies are using AI is to speed up drug discovery. It sifts through large datasets from clinical studies and other sources to detect hidden patterns, performing tasks in seconds that once took months. Learning every time they perform a task, AIs run through millions of tasks.

“Drug discovery is being transformed through the use of AI, which is reducing the time it takes to mine the vast amounts of scientific data to enable a better understanding of disease mechanisms and identify new potential drug candidates,” says Karen Taylor, director of the Centre for Health Solutions at accounting and consultancy group Deloitte. “Traditional drug discovery has been very fragmentary, very hit and miss,” she adds in The Guardian article.

The rapid creation of effective Covid-19 vaccines is a direct result of AI and ML in the pharmaceutical industry, Taylor states.

Figure: 1 Funding in Artificial Intelligence in the Pharmaceutical Industry

Funding in Artificial Intelligence in the Pharmaceutical Industry

How valuable is AI to big pharma? Britain’s two largest drug makers—AstraZeneca and GSK—recently funded the Cambridge Center for AI in Medicine at the prestigious university. GSK already opened a £10 million (roughly $13.5 million) in central London. This lab is near Google’s DeepMind AI lab.

DeepMind founder Demis Hassabis recently unveiled Isomorphic Labs, which intends to use an AI-first approach to discovering new drugs. DeepMind’s AlphaFold2 AI system solved the 50-year-old challenge of protein folding. AlphaFold is capable of predicting the 3D structure of protein directly from its amino acid sequence to atomic-level accuracy, Hassabis said in a recent Isomorphic blog post.

“One of the most important applications of AI that I can think of is in the field of biological and medical research, and it is an area I have been passionate about addressing for many years,” he said.

Hassabis considers biology an extremely complex and dynamic information processing system, making it a perfect match for AI.

“But just as mathematics turned out to be the right description language for physics, biology may turn out to be the perfect type of regime for the application of AI,” he said.

The Guardian article also looks at the money: Using older methods, nine of every 10 drugs in development will fail. The average drug development time is 10-12 years. With AI, the success rate is expected to at least double and possibly boost success from 1:10 to as high as 1:2.

How Can SMBs Benefit from AI?

While having $13 million in labs devoted to research is a great idea, many companies don’t have that large of an R&D budget. At least one well-known company has enterprise resource planning modules that integrate AI: Microsoft.

Figure: 2 AI Powered Insights by Microsoft

AI Powered Insights by Microsoft

AI Powered Insights by Microsoft

One example is Microsoft Dynamics 365’s Customer Insights is one of several modules that has AI built in. When pharmaceutical companies combine Dynamics’ Business Intelligence module with its Integrated Chemical Management (iCM), the two work together to mine your pharmaceutical data.

iCM is specifically designed to handle tasks like System of Record (SOR) for chemical and regulatory data plus compliance with cGMP regulations.

Add in Dynamics’ Supply Chain Management module and pharmaceutical manufacturers and suppliers can know to the second how much of any given product they have. Using AI and other information mined from a thorough inventory review, companies can accurately predict how much of any given precursor chemical they need to meet forecast demands. With this information, companies can place orders when costs are low or keep just enough on hand.

The Bottom Line

Pharmaceutical companies already create mountains of data. Instead of losing valuable nuggets of information such as trends and insights, artificial intelligence can sort through it. AI can:

  • Perform comparatively mundane tasks extremely fast
  • Provide your company with ways to create new products at lower costs
  • Produce new drugs much faster than before
  • Reduce the number of new drug failures

Using Microsoft Dynamics 365 modules equipped with the power of AI will ultimately help boost your bottom line.

Process and systems to support the bio-economy banner

Process and systems to support the Bioeconomy

Process and systems to support the Bioeconomy 700 500 Xcelpros Team

The public benefit gained through biological research can be seen through the eyes of a patient who receives a critical medication that did not exist a decade ago, a farmer whose higher-yield crops are turned into fuels, food, and intermediate chemicals, and a small-business owner whose innovative biobased products are breaking new ground in manufacturing. Increased societal needs for food and energy, combined with new knowledge/discoveries in biology and new methods for harnessing biological processes, have dramatically increased the economic potential of the bioeconomy.The National Bioeconomy Blueprint


Though written in 2012, The National Bioeconomy Blueprint contains some information valuable to any company wanting to explore the bioeconomy. Critical elements are investments in research and technology.

“… If we want the next big breakthrough, the next big industry to be an American breakthrough, an American industry, then we can’t sacrifice these investments in research and technology,” then-President Barack Obama says in the report. The White House authored the report.

Government agencies at the time were supporting the bioeconomy by:

  • Identifying research and development (R&D) methods
  • Developing foundational transformative technologies
  • Integrating approaches from engineering, physical sciences and computers
  • Improving predictions of vaccine and drug toxicity and efficacy
  • Identifying and characterizing any microbial organism, including purely synthetic versions
  • Creating “science enclaves” that allow analysis of large, complex datasets while maintaining proprietary information.

The report also wanted American industry to increase investment in and production of biofuels, replacing fossil fuels with biomass systems.

Other tasks cited in the report included converting carbon dioxide into liquid fuels, improving biofuel and energy crops, developing new agricultural research programs that drive job creation and transforming manufacturing through bioinnovation.

Some of these tasks have already shown results.

Recent Biotechnical Innovations

A 2020 post on the Klabtree Blog lists 10 biotech innovations.

One of them is CRISPR-based platforms. An acronym for clustered regularly interspaced short palindromic repeats, CRISPR technology was used to create the Pfizer-BioNtech and Moderna Covid-19 vaccines. Other medicines are also using the same technology.

The CRISPR tool, “is based on a system that bacteria use to fight viruses. Bacteria develop clustered repeated sequences in their DNA, known as CRISPRs, that can remember dangerous viruses and then deploy RNA-guided scissors to destroy them,” an article in Time magazine states.

Unlike a DNA-based product that targets a cell’s nucleus, messenger RNA (mRNA)-based vaccines just need to get into the more accessible outer regions of cells where proteins are built.

Using CRISPR technology to accomplish this task, both companies were able to produce Covid-19 vaccines that meet FDA emergency standards. The Pfizer-BioNTech vaccine, now known as Comirnaty, uses its regular, non-emergency procedures. The “regular” and “emergency” variations share the same formula, the FDA states.

Another technological innovation cited by KolabTree that is still being developed involves using DNA as a computer hard drive. The concept would turn cells into data storage chambers with the not-yet-realized ability to store information similar to current data storage.

A third innovation is using base pairings of DNA and RNA nucleotides in what is known as “DNA origami” after the Japanese paper folding art form. Nanovery is using this technology to create diagnostic nanorobots. The robots are inserted into a blood sample. When cancerous DNA is found, the robots light up.

Bioeconomy Business Strategies

Having the technology to turn biological products such as corn husks into fuel does not generate money. Having people who can see profits in the bioeconomy does.

“Entrepreneurs can contribute to the (bioeconomy transformation) by commercializing innovative technologies through startups and new business models,” Andreas Kuckertz writes in a white paper published through MDPI.com.

Figue: 1Bioeconomy Business Strategies

Bioeconomy Business Strategies

Using his research, key strategies for the United States mentioned by the author include:

  • Regulatory framework: Creation of tax breaks, reducing regulatory barriers and helping entrepreneurs obtain and defend patents
  • Market Conditions: Use the public procurement process to speed market adoption
  • Access to Finance: Support the bioeconomy by using venture capital for startups
  • Knowledge Creation and Diffusion: Educate entrepreneurs, connect them to mentors and educate government agencies about entrepreneurship
  • Entrepreneurial Capabilities: Enhance university entrepreneurship
  • Culture: Create an overview of available prizes and awards (mentioned in the National Bioeconomy Blueprint)

Kuckertz suggests modifying these strategies to include those that are:

  • Holistic and based on a clear, causal rationale
  • Include policies with measures tied to clear key performance indicators (KPIs) that can measure progress
  • Have, “dedicated innovation programs accounting for the specifics of bioeconomic innovation will be required to recognize the potential of many promising and possibly game-changing entrepreneurial initiatives.”

While Kuckertz’s comments are oriented at new business development, these same strategies can be used by existing companies. One way is by taking advantage of current cutting-edge business technology: Enterprise Resource Planning (ERP) software.

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Common Themes in Bioeconomy Products

Each of the previous technological innovations has at least three common themes:

  1. 1.Collecting massive quantities of data, also known as “big data.”
  2. 2.Analyzing it and making sense of what is found. Researchers can pour over spreadsheets and try to understand the data or they can use software. Machine learning (ML) and artificial intelligence software helps find the nuggets. These are the test samples that show a formula’s promise while also listing all of the others that don’t.
  3. 3.Safely storing this information away from prying eyes and competitors.

The good news for many companies is the technology to accomplish these three tasks exists today.

The industrial internet of things (IIoT) lets companies gather big data. ERP software is adept at many tasks, one of which is using artificial intelligence (AI) to provide business insights.

Cloud data storage is generally considered to be more secure than that on many small and medium business (SMB) internal networks, using the Microsoft Azure platform to run Windows-based products, adding extra layers of security and reliability.

Microsoft Dynamics 365 AI is designed to help businesses gather insights into customer needs and experiences. It helps companies accelerate a single process and lets groups solve problems and make decisions based on the data.

Microsoft Azure’s cloud computing service provides a stronger, safer and much more resilient computing platform than the average SMB network. It also has the advantage of making data easily accessible from anywhere in the world, all without compromising data security.

The Bottom Line

The bioeconomy is slowly making inroads into various industries. The chemical and pharmaceutical fields are perfectly set-up to take advantage of reusable biological materials such as corn husks for fuel. Other materials can be used to produce less toxic plant-based solvents.

Making money from the bioeconomy requires not only forward-thinking investors who care about the environment, but also advanced technology like Microsoft Dynamics 365 to make sense of it all.

The Road to Success Implementing Microsoft Dynamics 365

Jump-starting resilient and reimagined operations

Jump-starting resilient and reimagined operations 700 500 Xcelpros Team

Jump-starting resilient and reimagined operations

Based on a wonderful piece from our friends at McKinsey, describing the effort needed by businesses moving forward after COVID disruptions. A reminder that businesses able to maintain a certain level of speed during the transition can create a significant long-term advantage.

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The future of the chemical industry involves technology

The future of the chemical industry involves technology

The future of the chemical industry involves technology 700 500 Xcelpros Team

At a Glance

Technology is becoming a driving force in many industries and the chemical industry is no different. It’s easy to say the future of the chemical industry will continue to involve new and emerging technologies. Among the most cost-effective ways is through enterprise resource planning (ERP) software.

Among the industries benefiting the most from ERP systems’ integration of supply chain management are:

  • Manufacturing
  • Healthcare
  • Pharmaceuticals
  • Plastics


Tech will spur innovation in the chemical industry, a global management consulting firm, states.

“Historically, the chemical industry has generally been a slow adopter of new digital or analytics technology,” a McKinsey & Company report on the state of the chemical industry asserts. “Still, new digital approaches can provide incremental and relevant benefits (mostly around asset and commercial productivity).”

Among the chemical industry trends highlighted in the report are:

  • Productivity gains from using artificial intelligence (AI) in production, marketing and sales plus research and development.
  • Competitive advantages from having robust real-time information on sales, costs and inventories.
  • Increasing performance transparency around chemical products, management teams, individual activities and business lines.
  • Using process automation to change the way chemical companies think about complexity, scale and sourcing of administrative activities.

“While it continues to be unlikely that the chemical industry at large will experience a revolution, the evolution it faces will be continuously accelerating in speed and eventually significantly change the way things are done,” McKinsey states.

Other Ways Tech Boosts Chemicals

In addition to the business advantages cited by McKinsey, six other reasons why chemical companies are boosting their investment in technology are:

  • Cloud storage and information sharing
  • Advanced maintenance analytics
  • Reduce, reuse and regenerate
  • Yield, Energy and Throughput (YET) analysis
  • Globalization
  • Value Maximization

Cloud storage and information sharing lets wide-spread companies keep their divisions informed. For example, Sales in the U.S. can tell Procurement in India what to expect. That way Procurement has time to manage inventory.

Advanced maintenance analytics lets production facilities predict when a machine will break, Europe-based AG Chemi Group reports. By monitoring wear points, employees can replace worn components before they break. This reduces machine downtime by 30% – 50% and boosts machine life by 20% -40%.

Connected sensors, which are used by the Industrial Internet of Things (IIoT) to send data to company networks. Company engineers can evaluate the data to pinpoint the components most likely to wear, order replacements and have them ready to install.

Managing and reducing chemical waste , reusing products and materials and regenerating natural systems is part of the circular economy, which the Ellen MacArthur Foundation states, helps companies redefine growth by focusing on positive society-wide benefits. The circular economy model builds economic, natural and social capital, the foundation claims. AG goes further and states that chemical companies can take advantage of current trends in chemical engineering and process technology to increase efficiency, lower raw materials consumption and reduce manufacturing costs by reducing chemical waste.

YET analysis focuses on improving efficiency by reducing bottlenecks. Using information from literally millions of data points, companies can model the production process and identify areas for improvement.

Globalization is part of how the world now operates. Suppliers and customers are literally spread all over the globe. As a recent example, a ship stuck in the Suez Canal delayed 12 percent of global trade for more than six days. U.S-based companies depending on pre-production materials from Europe were stuck waiting, delaying production.

Value maximization refers to the idea that, “The economics of specialties production (such as chemical manufacturing) may demand maximizing output of a high-value product, while commodities production may prioritize holding down costs, but the former is typically built on the latter. Put simply, the businesses may have two separate profit and loss accounts, but they are connected to the same pipes,” AG Chemi quotes Valerio Dilda from the Polytechnic University of Milan as saying.

This method helps maximize profit generation in complex production systems and supply chains.

Figure: 1New Technologies in Chemical Industry

New Technologies in Chemical Industry

One Way To Update

A fast, easy method for chemical production companies to update their technology is by investing in ERP software. The integrated suite of programs allows chemical companies to access massive volumes of information, control it, massage it and use the insights for planning, inventory control and other business tasks.

One such product is Microsoft Dynamics 365’s family of programs.

Running on Microsoft Azure in a distributed, cloud-based environment, Dynamics offers secure computing, versatility and customization capabilities. Cloud computing offers greater security, meaning that patented chemical products and formulas are more secure than on a company’s own network.

The Supply Chain Management program includes these core concepts:

  • Asset management
  • Cost accounting
  • Cost management
  • Inventory management
  • IoT Intelligence
  • Master planning
  • Procurement and sourcing
  • Product information management
  • Production control
  • Sales and marketing
  • Service management
  • Transportation management
  • Warehouse management


The chemical industry tends to lag behind other segments in terms of modernizing its operations. Failing to keep with technology can cost companies through missed opportunities and poor inventory management. ERP software like Microsoft Dynamics 365 for Supply Chain Management or Finance are two of many options.

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