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How Chemical Companies Benefit from Dynamics 365 Finance
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How Chemical Companies Benefit from Dynamics 365 Finance
How Chemical Companies Benefit from Dynamics 365 Finance 700 500 Xcelpros Team

Chemical companies always look for ways to optimize their operations and maximize profits. Today, one of the most effective ways to achieve these goals is by implementing a modern chemical ERP (Enterprise Resource Planning) system. Microsoft’s Dynamics 365 finance and operations (D365) software is part of an advanced, cloud-based platform that fits most chemical companies perfectly. This blog explores how most chemical companies benefit from Microsoft’s D365 for Finance.

According to a survey conducted by Forrester Consulting, chemical companies that have implemented Microsoft Dynamics 365 for Finance and Operations have experienced a 20% improvement in operational efficiency, a 15% increase in customer satisfaction, and a 10% reduction in supply chain costs. This highlights the significant impact that Dynamics 365 is having on chemical companies and their ability to streamline operations, improve customer service, and reduce costs.

What is Microsoft Dynamics 365

Microsoft’s D365 is an industry-favorite, integrated ERP solution providing a wide range of business functionality for finance, operations, sales, customer service, manufacturing, supply chain management, project service automation, and more.

The Dynamics platform is designed for use in any business environment, whether a large enterprise, SMB, or hybrid-remote blend. The current version of D365 focuses on helping organizations streamline processes, increase productivity, and gain greater visibility into their operations.

With advanced AI/ ML (Artificial Intelligence / Machine Learning)-powered analytics, deep integration, and cloud computing capabilities, D365 gives organizations real-time insights into their operations. The system also allows users to track and monitor performance, manage financials and accounts payable/receivable, and improve operational efficiency. Leveraging the power of the cloud and the efficiency of modern artificial intelligence (AI), D365 can help organizations reduce costs and create unmatched value across their enterprise.

How is D365 being used by chemical companies?

Today, Microsoft’s D365 is used by chemical companies to streamline every part of their operations. The platform has been refined over time to integrate seamlessly with existing business systems, making it easier for companies to take advantage of a growing list of powerful features quickly. D365 allows chemical companies to reduce costs and improve efficiency by automating key financial processes.

One of the biggest advantages for chemical companies after implementing Dynamics 365 is far better control over their inventory. With integrated inventory management functionality, these businesses can track their stock levels in real-time, allowing them to adjust their ordering and production schedules accordingly. This helps ensure that there are always enough materials to meet customer demands. In addition, integration with other systems gives businesses a more accurate view of their supply chain, enabling them to identify areas where they could save money or streamline processes.

Another major benefit of using Dynamics is better visibility into financial performance. With a clear, up-to-date picture of current financial health, businesses can make more informed decisions about optimizing their operations. This includes identifying cost savings opportunities, improving their cash flow, and gaining insights into areas marked for improvement.

Year after year, Microsoft D365 continues to prove itself as an invaluable tool for chemical companies. By helping businesses reduce costs, gain greater visibility into their operations, and more effectively manage their inventory, Dynamics 365 finance and operations software is helping these companies take their business to the next level.

What about the benefits?

Across the industry, we see an increasing chemical companies taking advantage of the powerful features included in Microsoft Dynamics 365 to optimize their business processes and operations.

This includes the ability to streamline operations with automated workflows, increase visibility and control with real-time data and analytics, and enhance customer service.

Figure 1:Benefits of Dynamics 365 Finance for Chemical Companies

Benefits of Dynamics 365 Finance for Chemical Companies

The ability to integrate D365 with other industry-specific solutions gives chemical companies more insight into their production and inventory management, along with their financials.

The ability to make more informed decisions helps these companies reduce their costs by reducing the number of materials that go unused, and through better planning of their production cycle. These companies end up improving their customer service with faster order processing, real-time tracking of orders, and automated notifications when an order is ready for delivery.

Overall, the use of D365 provides chemical companies with numerous benefits, from increased visibility and control over their operations to reduced costs and improved customer service. As the industry evolves, companies will continue to find new ways to capitalize on the features of D365 to stay competitive.

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What does the future hold?

Year after year, the future of D365 continues to look extremely promising. As the platform continues to evolve, chemical companies can leverage more advanced capabilities to streamline their operations further. This includes improved automation, data analytics, machine learning, and artificial intelligence designed to help optimize processes and uncover deeper insights. Cloud-based functionality will continue to be a major component of this platform, enabling companies to access their data from any device, anywhere in the world.

In the coming years, we will see more organizations leveraging Dynamics 365 to achieve their business goals. These companies should consider investing in this technology sooner than later to remain competitive. With various options available, businesses of all sizes should be able to find a solution that meets their specific needs. Not sure where to start? This is where most businesses look to their trusted Microsoft Partner to help understand what products suit the needs of their business, both now and in the future.

User stories

User stories are a fantastic way to show how other companies achieved success with Microsoft’s finance and operations software. User stories highlight the versatility of D365 and its ability to support a wide range of business functions, from sales and marketing to finance and operations.

Whether you are considering implementing D365 for the first time or looking to expand your current platform use, user stories provide insights into how other businesses have successfully navigated the implementation process and used D365 to drive their desired outcome.

Chemical Manufacturing

A well-known chemical manufacturing company produces and supplies various products to customers worldwide. As part of their mission to be more competitive and stay ahead of the industry curve, they decided to invest in Microsoft Dynamics 365.

The cloud-based solution allowed the company to quickly get up and running without needing a lengthy on-premises installation. The system immediately provided the company with real-time visibility into its financial performance and a comprehensive overview of its operations. As a bonus, the company could access data securely and easily connect to its existing systems.

After implementing D365, the company quickly realized increased efficiency, transparency, and accuracy across its financial and operational processes. The platform has enabled the company to streamline its supply chain, reduce inventory costs, and improve customer service by providing an accurate view of its inventory levels. They also found themselves better positioned to manage their production and procurement processes, allowing them to respond quickly to customer demands.

Conclusion

Microsoft Dynamics 365 for Finance is becoming invaluable for chemical companies looking to streamline their processes, increase efficiencies, and save time and money.

With robust capabilities and flexibility, D365 can provide the support needed to make more informed decisions and the ability to automate many complex manual tasks. The result is a more organized and efficient organization better equipped to serve customers and grow.

Deciding to go with Microsoft D365 allows chemical companies to benefit from streamlined processes, improved accuracy, increased visibility into their financial operations, and better customer service. In addition, they’ll have access to powerful insights that help them make better decisions leading to growth and success.

With Microsoft Dynamics 365, chemical companies can be assured that they are making the most of their resources and maximizing their growth potential. Not sure where to get started? Work with your partner to ensure you’re both on the same page. Need a push in the right direction? Our team is waiting to answer your questions. Get ahold of us today!

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

Introduction

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.

Artificial Intelligence (AI) in Customer Service Keys Benefits
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Artificial Intelligence (AI) in Customer Service: Keys Benefits
Artificial Intelligence (AI) in Customer Service: Keys Benefits 700 500 Xcelpros Team

At a Glance

  • Customer support professionals face constant challenges trying to understand customer requirements while making connections on an emotional level.
  • Emotional connections with customers has become an extremely important requirement for companies looking to boost their bottom-line.
  • Artificial intelligence (AI) for customer support coupled with machine learning (ML) helps analyze large volumes of customer data using tools like Natural Language Processing (NLP) and advanced voice recognition, to generate.

Introduction

Today’s customers want more affordable, convenient services that cater to their unique needs. Significantly more business is transacted seamlessly across both physical and digital channels. This is a result of increased trust in day-to-day technology which has led to increased sales, along with an easy way for customers to recommend products and services to other people, creating a whole new network of promoters. To take advantage of this change in behaviour, more companies are working harder than ever to deliver better services and provide great end-to-end customer experience.

67%

of customers are willing to switch brands looking for a better customer experience.

Source: Forbes

A lot of brands fail to create a positive emotional experience which directly impacts customer loyalty. This dissatisfaction results in customers switching between brands due to a poor customer experience.

Companies that excel in customer experience can uplift their revenues by 4%-8%.Source: Bain

Understanding this, more companies are beginning to come around to the benefits of investing in AI-automated technologies, with some choosing to focus on boosting their revenue, and others favoring customer experience over price and quality. This doesn’t ignore pricing, but let’s companies place more emphasis on the user experience. Additionally, most of these systems can be automated, further increasing the benefits.

80%

of the customer interactions will be handled by AI eliminating the presence of human agents by 20202

Source: A Gartner Study

Enhancing the customer experience with AI

In a digital world where every minute is important, it doesn’t make sense to have multiple virtual customer service agents set up to manage small issues. Using AI-based solutions to answer simple questions can help control costs to your company along with offering a host of additional benefits such as:

  • Providing faster issue resolution
  • Answering customer questions 24/7
  • Sorting and routing messages
  • Ability to transfer to live support as necessary
  • Freeing of asset availability to manage high value incidents

This is accomplished by analyzing large volumes of data much faster than a human. AI also uses high-level voice recognition to identify the voices of customers, understand the problem and provide the necessary responses. This all allows for faster prediction of market requirements with much higher accuracy.

Another tool born of AI, Natural Language Processing (NLP), analyses human language to understand context and determine outcomes seamlessly, and often undetected. NLP works in a union with voice recognition to ensure faster problem resolution for customers, reducing frustration. These solutions are deployed as bots and can even be set up to transfer to a human assistant in the event the system is unable to assist. This is important to remember as AI isn’t a replacement for human interaction, just a tool that facilitates an improved experience.

Using AI for enhancing customer experience helps organizations achieve a number of sought after benefits including minimizing pain points, and reducing the number of hours spent by customer agents on simple tasks. AI driven automation with advanced machine learning helps empower your support agents to do their job more efficiently, creating more opportunities for up-sell and cross-sell activities designed to increase sales.

In today’s Age of the Customer, personal, emotive customer interactions play a critical role in bridging the gap for what disruption and digital innovation alone cannot solve. For brands to compete – and win – in CX in 2018 and beyond, service leaders must ensure their teams optimize processes and communication in ways that create positive emotional experiences for customers.

Dennis Fois | CEO of NewVoiceMedia

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Exploring options – How Dynamics 365 can help

Microsoft’s Dynamics 365 Customer Service insights let’s businesses leverage AI-driven insights to improve their customer service experience. Microsoft has included the following innovative features designed to help track performance across various channels

  • Dashboard Reference
  • Data Subject Rights (DSR) requests under GDPR

The dashboard reference comprises of various dashboards such as –

1.KPI summary dashboard This offers a macro-view of customer service experiences in your company, displaying topics currently generating the highest volume along with emerging issues.

2.New cases dashboard This is an overview of all the newly added customer cases in your system.

New cases dashboard

3.Resolutions dashboard This is a company-wide view of all case resolutions. AI helps identify the issues that impact resolution time.

Resolutions dashboard

4.Customer satisfaction dashboard Offers an overview of all the customer satisfaction scores in your company using AI automation to track the topics which have the highest impact on CSAT scores.

Customer satisfaction dashboard

5.Topic details dashboard This is a detailed overview of key performance indicators(KPIs) for specific topics using AI automation to showcase the impact by product and channel on customer satisfaction scores and resolution time.

Topic details dashboard

Aside from built-in dashboards, visual filters, and interactive charts that give an overview of operational data across all channels, Dynamics 365 also offers actionable insights based on critical performance metrics and emerging trends from your customer service system, highlighting areas that could benefit from improvement and could significantly impact business growth.

Dynamics 365 AI for Customer Service Insights provides a number of valuable benefits including

Improving customer satisfactionBuild brand loyalty by resolving issues before in a timely fashion. Gain a comprehensive understanding of CSAT scores used to calculate customer satisfaction.

Increasing operational efficiencies Streamline operations with insights from case resolutions, historical comparisons, and backlog trends to evaluate customer service agent performance. Monitor case volumes and expected support topics to optimize efficiency.

Enhancing visibility Dynamics 365 helps with effective visualization of customer engagement patterns, customer service operations using various AI-automated dashboards, machine learning capabilities and agent performance, and more. Discover and share critical insights using interactive charts and filters with AI for customer service.

Key Takeaways

While things like sales, pricing and quantity is often the main focus of businesses, it’s important to understand that developing good experiences with customers is just as important, sometimes more. Satisfied customers become extremely effective promoters of the brand simply by recommending your products or services to people they know. This helps businesses expand as loyalty leads to an emotional connection.

As we continue to see newer, more advanced technologies designed to simplify and enhance customer service experiences emerge, understanding the simple fact that people never forget how you made them feel will be even more important. The future of AI in customer service is indeed very bright.

Also Read: Artificial Intelligence in Insurtech : Reshaping the Insurance Industry

Artificial Intelligence in Sales Performance
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How Artificial Intelligence Helps in Boosting Sales Performance
How Artificial Intelligence Helps in Boosting Sales Performance 700 500 Xcelpros Team

At a Glance

  • In today’s hyper-connected digital world, customers expect personalization, convenience, and targeted sales experiences. Sales professionals are continuously striving to provide an enhanced and integrated customer experience.
  • Sales Professionals face many challenges every day – a better understanding of buyers’ needs, value communication, demand prediction and most importantly, staying connected with the customer.
  • Low customer engagement hinders companies’ brand image, forcing them to switch to other brands that better cater to customer requirements. Availability of market data and customer behavior is driving sales professionals to understand customer needs better. Enhanced customer experience ensures business outcomes.
  • Sales powered by Artificial Intelligence is the differentiator that can build better customer relationships as AI helps to understand customer behavior, enhances your ability to forecast, and enables you to focus on sales that matter. AI in sales also helps you in effective demand forecasting to stay in line with the market demands.

The Age of Distraction

Your sales departments play a pivotal role in your organization. They face numerous challenges in increasing customer satisfaction. The significant consequence of living in a digital era is that sales reps get defocussed as they cannot accurately read the customer information. Sellers need appropriate tools to instill a focused effort on sales.

These distractions reduce sales efficiencies by 14%

59%Sales people claim to have too many tools

64% Sales reps’ time is spent on non-selling activities

50%Sales reps’ have no idea about what is expected of them

In addition to distractions, sellers face increasing complexity in today’s sales environment. They work with an average of 10 stakeholders for every purchase decision to be made, resulting in buying decisions to take 97%¹ (Gartner) longer than expected.

Yet, 60% of companies lack a well-defined sales process, further contributing to the long sales cycles. The need to work with different functions and people requires more collaboration, adding to its complexity.

Using Artificial intelligence in sales helps you streamline your sales process by automating various functions like – sales execution, tracking sales performance, connecting with prospects helping you increase your conversion and win rates.

For instance, AI automation in sales has helped automate purchasing using bots decreasing 15 to 20% of expenditure sourced through e-platforms.

Gartner predicts that 30% of all B2B companies will employ some type of AI to augment at least one of their primary sales processes by 2020. Your competitors are experimenting with artificial intelligence, looking at the benefits it offers from automating their sales processes. Per McKinsey, companies using artificial intelligence in sales have seen –

  • 50% increase in leads and appointments
  • 40-60% decrease in overall costs
  • 60-70% decrease in call time

While staying at par with competition makes automation a must, clarifying the software’s personalized capabilities and limitations is paramount.

85%

of customers will manage their relationships with different enterprises using bots or virtual assistants by 2020.

Source: Gartner

Smart CRM Solutions Can

  • Transform decision-making across many functional areas
  • Unite key functional areas on organizational goals
  • Improve efficiency, accuracy, profitability
  • Allow staffers to do more creative & strategic work

How can AI help your sales department?

There remains a misconception that AI automation can replace humans. Instead, AI helps humans to increase accuracy and perform their jobs better than before. Incorporating artificial intelligence in your sales departments enables you to automate various tasks done by humans and reduces the scope for human error increasing efficiency. Your sales department can benefit from AI by –

AI for increased price optimization: To decide the discount to be given to a client is always a tricky question for companies. As important as winning the deal is, leaving money on the table is a loss for you. Adopting artificial intelligence in sales departments helps you estimate the ideal discount rate for a proposal by viewing the specific features of a past deal closed. These features also include Features could include: the size of the deal in dollars, product specification compliance, number of competitors, company size, territory/region, client’s industry, client’s annual revenues, a public or private company, and level of decision-makers (influencers) involved.

AI for Better Forecasting: Forbes estimates that 74% of large B2B firms engage in sales forecasting every week. They also estimate that 69% of companies, regardless of their size, consider their sales forecasting methods to be ineffective. Sales managers face a daunting challenge in tracking where their team’s total revenue falls short each revenue cycle. Using AI in sales can help you effectively estimate and predict your revenue, reducing your operational challenges to manage your inventory and resources better.

Companies boasting accurate sales forecasts are 10% more likely to grow their revenue and 7% more likely to meet their targets.Source: Aberdeen Group

Cross-selling and up-selling: The most effective and economical way to increase profits is to sell more to your existing client base. But how do you understand which audience to target? You can spend your revenue marketing your product to the wrong audience or use AI algorithms to identify which clients would be willing to update their product (up-selling) and/or buy a completely different product that you offer (cross-selling).

Enhanced lead scoring: 61% of companies say misleading buying signals are a huge barrier to effective lead scoring. They claim to fall prey to customers’ gut impulses and inaccurate information, which significantly hurts their lead scoring or bottom line. Per Forbes, 68% of respondents reported implementing lead scoring strategies, whereas 40% believe in the value associated with lead scoring.

Effective performance management: Sales managers are expected to eagerly track their team performance and look out for barriers in meeting their revenue targets. With AI, they can now use dashboards that showcase employee performance and help managers predict which salespeople are likely to hit their quotas and which deals have a higher chance of being closed.

Empowering your sales force with AI technology

Before investing in a pilot project, you need to meet your sales managers and understand the potential use cases to determine the suited requirement. Three types of AI technology promises results for B2B sales organizations. They are –

  • AI in Sales Predictions – Analytics like AI in sales forecasting find correlations between various data points. Such tools automatically create the insights that are essential to managers and sales reps. For example, they can determine a prospect’s likelihood to become your client and help in sales forecasting.
  • Prescriptive – Such analytics supports guided selling. AI suggests activities based on all the sales methodologies adopted by the firm. This is a step forward to move a deal to the next sales stage or develop a pricing model based on a prospect’s general preferences.
  • AI for Text and sentiment analysis with Natural Language Processing – understands and analyzes the context of customers’ questions and their behavior. Using sentiment analysis, sales reps are alerted if signs of dissatisfaction are discovered.

What Microsoft Dynamics has to offer: Exclusive Features

Dynamics 365 AI for Sales enables salespeople to build stronger functional relationships with their customers to increase customer satisfaction. It helps them take actions based on helpful insights helping them close sales faster.

Dynamics 365 AI for Sales offers the following capabilities for sellers:

  • Relationship analytics: This feature helps you assemble relevant information from the entire database to create a graphical representation of all the KPIs and activity histories. Such a visual display showcases KPIs and activity histories for any contact, opportunity, lead or account.
  • Predictive lead scoring: This feature helps you generate scores for all your leads in the pipeline. It assigns a score between 0 to 100 to leads based on signals from them and related entities such as contact and account. This helps you identify and prioritize leads with more chances of converting into opportunities.
  • Predictive opportunity scoring: This feature provides a scoring model to generate scores for opportunities in your pipeline. It assigns a score between 0 and 100 to all the opportunities based on the signals they give out and other related entities such as contact and account. This helps identify and prioritize opportunities that have more chances of converting into sales.
  • Notes analysis: Notes give you intelligent suggestions to help you save time and effort by taking actions such as creating a meeting request and adding a contact. The text in the note is highlighted and when selected, suggestions are displayed.
  • Talking points: This feature is useful to help you start conversations with customers based on emails. The conservation starters include topics that are related to Health, sports, vacation, family, and entertainment. These topics help you start a conversation with your customer, as you can choose your customer’s area of interest. Talking points will display only the latest communication for each topic in hand.
  • Who knows whom: This feature provides you details such as your contact’s name and email address who knows the lead. Using these details, you can reach out to your contact and get introduced to a lead and increase the chances of a positive outcome during the interaction.

Key Takeaways

  • Good sales professionals advance their sales processes by leveraging the right skills at the right time. They become agile in their approach to numerous stakeholders who represent a host of opinions and interests.
  • Sales managers will require their workforce to have skills and tools to help customers build the case for change by understanding how factors like desired outcomes and solution options influence decisions.
  • Companies can benefit from seeing tangible rep to customer conversion analytics and identify different ways to improve deal closure rate.

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Artificial Intelligence in the Biotechnology – 5 Key Trends
Artificial Intelligence in the Biotechnology – 5 Key Trends 700 500 Xcelpros Team

At a Glance

  • The biotech industry is witnessing unprecedented demand on many fronts. Companies are looking to invest in fast-paced innovation, systematic storage of massive research data, analysis of humongous databases, and meticulous management of the business processes. AI-enabled applications play a crucial role in meeting these demands.
  • Machine learning, robotics, informatics, and AI branches can help in expanding the horizons of the biotechnology industry and move towards newer possibilities.

AI-led Transformation of the Biotech Industry and Its Positive Effects

The Biotechnology industry is currently relying heavily on storage, filtration, analysis, and the exchange of data. Massive databases are maintained by biotechnology companies and various health organizations worldwide. Drug manufacturing, chemical analysis of different compounds, sequencing of RNA and DNA, enzyme studies, and other similar biological processes require the strong support of computerized tools and applications to gain pace and reduce manual errors.

Today, the world is witnessing an unprecedented health emergency in terms of the Coronavirus pandemic. Economies are collapsing, countries are under lockdown, and all hopes are pinned on the biotechnology industry to come up with a safe, effective vaccine in the shortest possible time frame. The use of Artificial Intelligence in biotechnology and related applications play a crucial role in managing biological processes, boosting medicine production, handling supply chains, and taking care of the pool of data for this industry.

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.

Figure 1Applications of Artificial Intelligence in Different Fields of Biotechnology

Applications of Artificial Intelligence in Different Fields of Biotechnology artwork

Leading biotech companies are investing in advanced AI tools to:

  • Analyze research data
  • Accelerate vaccine development
  • Classify the target market and demographic
  • Identify the right ingredient to produce the vaccine

86%of current or planned AI spending is in customer-oriented areas, with marketing and sales leading the pack

 

$1.2 TNestimated additional revenue/ shifting revenue driven by AI in three years

 

While there are still many unknowns when it comes to a successful coronavirus vaccine, this US biotech firm has applied artificial intelligence to accelerate the process of vaccine development.

The biotechnology sector will leverage artificial intelligence and its related applications with vigor in the coming years. According to an article for Medium by Melanie Matheu, Ph.D., the next generation of therapeutics entering drug pipelines will contain targets selected by AI screening, likely improving the 86% clinical trial failure rates for small molecules.

The biotechnology industry has various sub-sectors ranging from human life sciences, food industry, agricultural biotechnology, animal biotechnology, and industrial applications. These branches can all leverage the advancements seen in artificial intelligence and machine learning related applications developed in the past decade, including five key AI trends that will transform the biotechnology industry, listed below.

The Application of AI is Shifting More Towards Knowledge Workers

79%agree AI and related technologies are having a transformational impact on workflows and tools for knowledge workers

 

80% say that placing powerful AI-fueled application in the hands of knowledge workers is critical to productivity and performance

 

84% agree AI streamlines processes, freeing knowledge workers for move creative, intuitive and laterally thinking activities

 

Source: Microsoft

01Boosting Innovations: From Lab to the Market

The past decade has witnessed the need for fast-tracked innovation, production and deployment of medicines, industrial chemicals, food-grade chemicals, and other biochemistry-related raw material. AI in Biotech plays a crucial role in boosting innovation not only in the laboratories but also throughout the lifecycle of a medicine or chemical compound (right to the point where it reaches the market). Based on the target market, AI-based tools and applications help in developing the structure of molecules. Machine learning, a subset of artificial intelligence, helps in calculating permutations and combinations of various chemicals to know the right combination, without having to perform the experiments in the lab through manual processes. The use of artificial intelligence in biotechnology is bringing innovations that can help in predictive analysis to forecast the demand for a particular medicine or a chemical in the market. AI in Biotech can also help in managing the smart distribution of the raw material required by the biotechnology industry through the use of cloud computing.

Figure 2Functionalities of AI in Biotech Industry

Functionalities of AI in Biotech Industry

02Open Source AI Platforms: Faster Data Analysis

Scientists across the globe are looking at AI programs that can take over the tedious nature of data maintenance and data analysis. Tasks like gene editing, enzyme compositions, chemical studies, and such crucial informatics are analyzed systematically for faster and more accurate results. Open-source AI programs such as CRISPR libraries and H2O.ai are playing an essential role on this front by relieving lab assistants of repetitive tasks like data entries and analysis. By eliminating manual functions for healthcare providers and scientists, they can better focus their efforts on innovation-driven processes and it will be possible with the use of artificial intelligence in biotechnology.

03Pushing the Boundaries of Agricultural Biotechnology: Increasing Quality and Quantity

Biotechnology plays a crucial role in genetically modifying plants to develop more and better crops. AI-based tools become essential to this process of genetic modification to study the features of the crop, to note down and compare qualities, and to forecast plausible yield. Apart from these tools, robotics, an arm of artificial intelligence, is being used by the agricultural biotechnology industry for packaging, harvesting, and other essential tasks. AI in biotech also helps in planning the upcoming patterns in the movement of material by combining weather forecasts, data on the nature of farmlands, and the availability of seeds, manure, and pesticides.

04Discovery of New Drugs and Vaccines: Shrinking the Timeline

In a globalized world, newer diseases have a fast way to spread across continents. Thus, the biotechnology industry is at a race against time to develop newer drugs and vaccines to be able to contain such diseases. Artificial intelligence and machine learning are vital in speeding up the process of recognizing the right molecules, helping in synthesizing them in the labs, data analysis for efficacy, and it supplies to the market. Operations, which would usually take 5-10 years, have now been shrunk to 2-3 years with the use of artificial intelligence in biotechnology.

Figure 3Subsets of Artificial Intelligence in Biotechnology

Subsets of Artificial Intelligence in Biotechnology

05Facilitating Global Connect: Sharing Biotechnology Developments Worldwide

AI platforms are resourceful in letting scientists across the globe have access to imperial data regarding newer medicines and other industrial developments. Many machine learning tools are assisting scientists in decoding data and understanding patterns of a particular disease in a far-away country and utilizing it to build analytical models for their geography. The accuracy of scientific models has increased by several folds, after the introduction of AI in Biotech.

While these are the key trends, AI and related tools are helping in transforming the biotechnology industry in many ways. Coming times will see the use of artificial intelligence in biotechnology for the betterment of humankind by the progress it facilitates in the fields of biosciences and technologies.

The power of integration of Microsoft’s AI with Microsoft Dynamics 365 helps biotech companies get over the industry’s pressing challenges. Hindrances such as resource management, stringent regulations, quality management, etc., and establishes seamless workflow by ensuring unified data sharing, visibility, and connectivity across diverse channels and operations so that teams better communicate.

This collaboration with the use of artificial intelligence in biotechnology helps your company to

  • Achieve regulatory compliance
  • Gain visibility into your supply chain management
  • Track and control your inventory with accuracy, and
  • Integrate industry best practices for corrective and preventive action

Finally, the digital transformation achieved with the Full Microsoft Suite gives you data in real-time to make smart and actionable business decisions to spur company growth.

Key Takeaways

  • The biotechnology industry has progressed significantly with the application of AI and related computerized tools.
  • Be it medical, industrial or agricultural biotechnology, AI, machine learning, and robotics play critical roles in pushing the boundaries of possibilities in these fields.

Using our years of industry experience in the biotech, life sciences, and pharmaceutical industries, we suggest and help our customers with the best ways to reduce costs and mitigate implementation risks. We work with you throughout the implementation, so that you can quickly identify, address, and record any production, shipping or quality control risks, events, and complaints. A personalized, flexible D365 dashboard equips your teams to trigger a hold on products throughout the supply chain autonomously, launch nonconformance reports, send notifications to managers when test results hit a certain threshold or when a specific research milestone deadline is compromised.

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AI ml in chemical industry
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Transforming Business with AI and ML in the Chemical Industry
Transforming Business with AI and ML in the Chemical Industry 700 500 Xcelpros Team

At a Glance

  • Innovation is the name of the game for chemical companies to optimize operations and enhance profits. To fast-track innovations, use of AI and Machine Learning in the chemical industry is crucial.
  • Many in the chemical industry are touting benefits of leveraging AI and machine learning to analyze data, systemize processes and mitigate errors by minimizing manual interventions.
  • Human-machine combination is proving to be a transformational phenomenon that can change the way the chemical industry is functioning in the USA and all over the world.

Introduction

The world is growing and seeing changes at an unprecedented rate. The year 2020 has shown us that advancement in science, especially the field of chemicals (and related fields such as biotechnology that deal with the vast majority of chemicals), cannot come fast enough! We need faster, error-free methods to test chemical molecules, computer-generated models for process optimizations, and digitally-adept sensors for quality controls. AI and machine learning play an integral role in efficiently taking the chemical industry towards a trend of modernization and innovation.

The path to digital transformation involves infusing AI into crucial processes and milestones. The journey includes digitizing assets, automating processes based on those assets (known as digitalization), and then creating new ways of doing business.

Figure 1 AI is the greatest commercial opportunity in today’s economy

AI is the greatest commercial opportunity in todays economy

When organizations invest in AI, the goal is to create and enhance digital experiences. AI apps can employ skills to mimic human cognitive functions such as vision, speech, and natural language understanding. By including these human-like capabilities, AI can enable organizations to construct digital experiences that are smart, fast, and helpful to end-users.

A recent study by Accenture shows some promising figures when it comes to use of artificial Intelligence in the chemical industry. According to research, companies that have implemented Industrial AI in the chemical sector are exhibiting significant benefits as follows:

72%report a minimum 2x improvement in some process KPIs

37%report a 5x improvement in KPIs

4 Ways of Applying AI and Machine Learning in the Chemical Industry

While every enterprise has its blueprint to follow when it comes to the application of tools and techniques on AI and Machine Learning, certain broader areas can be common for the chemical industry. Let us have a look at 4 such facets:

01.Data Crunching and Analysis for Molecular Activity Studies

Understanding chemical products and utilizing them for desired effects usually take years of analytical studies, laboratory experiments, clinical trials, farm trials, etc. However, these days, faster results that can mitigate manual errors and minimize efforts are required. Machine learning and AI tools are effectively used to feed and churn a humongous amount of data, and can systematically analyze the said data. This data churning and analysis will help separate chemicals that are effective yet have fewer or no side-effects from the ones that do not have desired effects or are toxic. Apart from the use of AI and machine learning in the pharmaceutical and pesticide industry, possibilities can also be explored in the manufacturing industry, which is heavily dependent on chemicals. Applying AI and machine learning in the chemical industry can also help expedite the efforts in fighting climate change by estimating the damage done by harmful pollutants. This will aid companies in making essential changes in their machinery and processes to minimize the pollutants being released into the water bodies and air.

02.Result-oriented Innovation and Boost in the Chemical Industry R&D Sector

R&D forms the backbone of any industry, and the chemical industry is no exception to this. Today, major players in this sector are looking for focused R&D and innovation that can yield faster and more accurate results following the use of artificial intelligence in the chemical industry. Machine learning tools can help in exercising this type of quick research with the help of computerized permutations and combinations. It can also help in recognizing the right molecules, generate formulas, and aid in knowing the precise quantities of different chemicals required. AI, on the other hand, can help in predicting chemical combinations that can be a breakthrough in terms of innovation. These innovations can boost the ongoing and upcoming efforts in the pharmaceutical, food, biotechnology, oil and gas, petrochemical, manufacturing, and many such industries.

03.Seamless Juxtaposition of Human and Machine Efforts

Since the introduction of computers in the workplace, humans and machines have proven to be the best combination for effective results. However, digital transformation and the introduction of layers and layers of machine-generated intelligence can make this combination even more successful than ever before. Imagine an idea that has come out of the human mind, but it can be analyzed, tested, and streamlined to mitigate risks or errors even before it has physically been put to the test? This can lead to unprecedented time and efforts being saved. Such amalgamation of human and machine efforts can influence the chemical industry to fast-paced innovations, productions, operations optimization, and other concurrent developments.

04.Preventative Measures and Predictive Forecasting

In today’s industrial world, competition is steep and it is essential for enterprises in the chemical industry to be prepared and to be proactive. AI and machine learning tools can help a great deal in this by predicting snafus or future maintenance requirements. Advanced analogs and mathematical models can also be used to estimate oil, gas, and other raw material demands so that the companies can streamline their supply chain in a manner that avoids potential delays and last-minute cost hikes.

While these applications of AI and machine learning cover the broad spectrum when it comes to the chemical industry, there is still a lot of research and development going on in this field. As the world embarks upon a new journey of Industry 4.0, it would be interesting to see more transformations brought in by the use of artificial intelligence in the chemical industry.

Where is the Challenge?

AI-enabled systems are helping companies achieve objectives, goals, and enhance user experience. However, each time a system is not maintained correctly, the process begins to decay by behaving unpredictably. Organizational leadership can thus lose confidence in AI as a process enhancement system. Moreover, organizations should have the required maturity—which encompasses strategy, culture, organizational structure, and core capabilities—to own an AI-based system responsibly. In some cases, this may mean a withdrawal or rejection of AI technologies based on unsuccessful attempts to adopt AI. Organizations or their customers may lose trust in AI as a technology, branding it as unpredictable or too hard to operate. This outcome will push real digital transformation further away and cause the organization to miss out on the powerful impact that AI can have on their business.

Microsoft has worked on defining an operational model that helps organizations assess their attributes that contribute to the adoption of AI technologies. A well designed AI Maturity Model assists organizations in gathering information related to the core characteristics required for teams. Forward-thinking organizations that have embraced AI are witnessing improvement in user behavior. The transformation meets all prime objectives of a Chemical company, mainly driving productivity, sales, Environment Health and Safety, appropriate management of hazardous chemicals in the warehouse.

Figure 2AI Maturity Model

AI Maturity Model

Additionally, Microsoft has compiled prescriptive guidance associated with adopting the right AI technologies for an organization’s current maturity level, while advising on how to increase maturity to embrace more advanced AI capabilities.

Key Takeaways

  • AI and machine learning in the chemical industry can be critical players in clinical trials, farm trials and overall study of chemical molecules.
  • With the cutting-edge application of AI and machine learning tools, the chemical industry can streamline its processes and supply chain for better operations and enhanced profitability.

Explore how you can transform processes, engage customers, and modernize your apps with Microsoft Business Applications.

ENTERPRISE PROCESS AUTOMATION TRENDS
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Upcoming Process Automation Trends That Will Transform Your Enterprise
Upcoming Process Automation Trends That Will Transform Your Enterprise 700 500 Xcelpros Team

Introduction

The ultimate goal of any enterprise is that of speeding up processes, reducing errors, and increasing business output for better revenue generation. With the onset of the digitization era, companies have upgraded their technological prowess to adapt to process automation. It is important to understand that in the rapidly transforming world, process automation is not just a technological ability to speed up processes but a strategic movement towards better use of software to streamline workforce, introduce better work practices and mitigate cost inflations. Since COVID-19, process automation has turned into a need of the hour to improve operations that are built with adherence to process compliance and yield better outputs with a limited workforce. This means process automation will transform enterprises at a larger scale to increase agility and reduce dependency on manual work.

Manual Vs Automation

Is your business still operating through manual handoffs, excel macros, and cumbersome reporting? As businesses are integrating automation in more rapidly in different facets right from HR to Marketing, Production, Sales, and Information Technology; there is a considerable reduction in human intervention for mundane and simpler tasks. A component of efficiency will be introduced with the implementation of Robotics and Artificial Intelligence (AI) in process automation. According to a leadership piece by Sogeti (1), enterprises will look into integrating robotics process automation (RPA) with AI to extract more business value. Read on to know why an enterprise should consider intelligent process automation for complete transformation and the latest trends that will help businesses along the path of said transformation.

Why Embracing the Latest Process Automation Trends and Techniques is a Necessity for an Enterprise?

As an enterprise, you need to ask yourself a key question: Where should the business’ attention be?

While at face-value this question may seem trivial, the entire enterprise architecture revolves around this key aspect. The more attention your skill base gives towards the latest trends like the Internet of Things (IoT), Machine Learning, Cloud, Advanced Analytics, Artificial Intelligence, and automated-integrated workflows, the better streamlined and agile your workforce would be. Hence it is highly significant for enterprises to explore deep into the latest process automation trends and make their employees acquainted with these trends for a competitive edge.

There is no doubt about the fact that legacy systems need upgrades and modernization to encompass latest trends of digitization, modern technologies and to become aligned with the fast-paced, changing business demands. Process automation plays a key role here. If not for process automation, the IT systems would face the brunt of not being able to keep up with business process improvements (carried out usually at a large-scale), leading to lesser productivity and overall loss of revenue. Automation helps you form ‘bundles’ of data and migrate them to platforms for systematic records management. Process automation can help your enterprise reduce the error rate, and increase productivity at a lower cost. But one point to remember is that the process automation described above would only make sense if your company has already transformed into a modern ERP system.

Figure 1 8 Reasons to Automate Your Business Processes

Reasons to Automate Your Business Processes

1.Handling the Unstructured Data Challenge: While data on systems has been very much taken care of by current process automation tools, enterprises and their related facets still struggle with unstructured forms of data such as hand-written notes, bills, invoices, images, etc. With the introduction of machine learning and artificial intelligence, businesses are digging up automation solutions that will not only recognize this type of data (with the help of Robotics), but also assimilate and use it in processes similar to structured data.

2.Low-Code Solutions for Faster Results: Robotic process automation when integrated with low code solutions forms a golden bridge of zero human intervention and faster application development. These low code solutions enhance efficiency as well as help in transforming core processes like Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP).

3.Integration of Robotic Process Automation (RPA) with Business Process Automation (BPA): Interdependent workflows have always been a part of large enterprises and the IT skill set in an organization has mostly been at the helm of managing these interconnecting processes in a complex workflow system. The latest automation tools will help in integrating RPA with BPA resulting in the formation of intricate workflows and implementation of all the related processes.

4.Real-Time Automated Decision Making: Enterprises will see more and more management of big data with the help of artificial intelligence and this will facilitate the way for flexible tools for IT operations that will preempt glitches and provide real-time solutions. This will help in better resource-allocation, lesser communication gaps, and fewer outages.

5.A Chance Towards Skill Set Upgrade: When computers were introduced as a tool to reduce human effort, they were met with a lot of apprehensions. In fact, many considered them as machines that would make a human contribution to technology obsolete. Similar apprehension and even cynicism can be seen in the case of process automation tools and software. After all, process automation eliminates the need for human intervention, making many technical jobs outworn.

However, enterprises are now looking up to this advancement in process automation as a chance to upgrade the skill set of their current employee base and make them adept in the latest technologies and tools. This will not only help the IT personnel move from labor-intensive, monotonous jobs to skill-based, dynamic ones, but it will also create a learning curve in the industry resulting in more innovations. When put in perspective, automation is not the cause for losing jobs, it is instead an opportunity for companies to fill the skill set gap and enhance the expertise of their IT personnel for innovation and better strategic output.

By 2023, AI-enabled automation in data management will reduce the need for IT specialists by 20%Source: Gartner report

The Changing Landscape

An enterprise cannot deny the fact that adapting to the need of the hour with the latest process automation trends is going to work in favor of its core business value. Numerous users across organizations will gain access to data, automated workflows that will be systematically prepared, and actionable insight that will aid towards building an agile enterprise. In the current market being agile as a company will be your strong suit. As they say, the cards are laid on the table; it is up to the businesses now to play their hand wisely!

Remote work is becoming more prevalent post-COVID-19. Companies are looking for more ways to streamline operations, engage the workforce, and yet meet the needs of customers. Process automation plays a major role in volatile market conditions during COVID-19. A combination of Microsoft’s Power Platform, AI – ML, Dynamics 365 for Sales and Dynamics 365 ERP, integrated with Teams allows users to streamline their processes and build needed visibility for management to effectively view the progress of operations remotely.

In fact, a successful use case off-late within various companies is to integrate Dynamics 365 with flow, teams, planner, and SharePoint to enhance compliance of process, coordination with team members remotely, track processes that are running in each department and provide task execution clarity for each employee within a department. More companies are adopting this suite of tools to improve productivity and simplify workforce engagement. All major functions of a company – be it Procurement, Sales, Manufacturing, Quality, Finance or HR, when unified together help a business stay afloat during challenging market conditions and support the over well-being of a business.

Key Takeaways

  • Introduction of Automated workflows, Artificial Intelligence, Cloud, Big Data, Machine Learning, and Advanced Electronics has changed the face of process automation for better and faster results.
  • Enterprises will need to invest more in advanced process automation tools to stay ahead in the competition and to gain critical business value.
  • Evaluate low-cost solutions for process automation that is easily customizable for your business and build enhanced visibility of how your company is performing in a challenging market.

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artificial intelligence in insurtech reshaping the insurance industry
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Artificial Intelligence in Insurtech: Reshaping the Insurance Industry
Artificial Intelligence in Insurtech: Reshaping the Insurance Industry 700 500 Xcelpros Team

An insurance firm recently released a claim within seconds using its bots. Sounds hard to believe! The new wave of Artificial Intelligence in the insurance industry is going to bring this paradigm shift where adopting advanced, seamless digital solutions will process the claims rapidly. The technology will not only improve the customer experience but also aid insurance companies in better risk assessment and real-time damage prevention. This infographic gives you a detailed overview on how artificial intelligence is disrupting every area of the insurance value chain. Check the picture below on how AI is helping to improve operations.

Artificial Intelligence in Insurtech

AI for Insurance is helping companies streamline business functions and improve the overall user engagement Contact us for a trial.

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