Page 13 – DataToBiz

The Role of Manufacturing Analytics Solutions in Pharma

The adoption of advanced data analytics in pharmaceutical manufacturing analytics solutions in pharma manufacturing has made it easier to analyze simplified the process of analyzing enormous datasets and produce valuable insights. As a result, the pharma companies are ahead of the game, by managing their operational efficiency and cutting cost costs related to raw material, energy, and much more. Pharmaceutical manufacturing has been impacted by global trends such as variable-cost increases, high capital expenditure requirements, increasing operational complexity, and improving savings. Also, they need to manage quality assistance, optimize their processes, and remain future-proof by minimizing their vulnerabilities. With the help of pharmaceutical manufacturing software, pharma companies can achieve these goals by continuously analyzing data and deriving meaningful outcomes. According to a report by MarketsandMarkets, the advanced analytics market will increase from USD 64.3 billion in 2023 to USD 226.2 billion by 2028, at a CAGR of 28.5%. Increasing adoption of PAT tools and other technologies, along with the urgency to address issues such as high costs, sustainability mandates, and changing demands, prompts the need for advanced manufacturing analytics solutions analytics in pharma industry. How do pharmaceutical companies use data analytics? With the help of data analytics, pharmaceutical companies analyze data from disparate sources to predict future outcomes. For example, they can estimate the possibility of drug failure during research and development, identify patient traits prone to reactions to certain medicines, and find optimal medication production timelines to prevent expiration. Discovering and developing drugs: Advanced analytics enable pharma companies and their partners to find and select effective therapeutic compounds for specific diseases. By analyzing diverse data points related to each target such as historical behavior with other proteins, past experimental outcomes, and efficacy of the previously tested drugs. Pharma Supply Chain: The pharma manufacturing companies need to ensure the timely delivery of medicines to the patients. Insights from analytics enable them to understand the fluctuations in demand concerning economic conditions or regional demographics. By leveraging these insights, drug companies can optimize resource allocation and make medicines easily accessible. Ensuring drug safety and pharmacovigilance: Drug safety and pharmacovigilance are critical for pharmaceutical companies, owing to the legal liabilities and medication recalls. Adverse drug reactions could lead to severe consequences for the patient and the pharma company. Therefore, advanced analytics serve as a valuable valuable to identifying valuable tool to identifying patient demographics prone to intolerance of specific medicines and those with high susceptibility to ADRs. Real-time PAT Tool Data Monitoring: Advanced analytics tools can process data generated from PAT instruments in real time, providing immediate insights into the manufacturing process. This allows for quick identification and response to deviations, ensuring product quality and consistency. Drug Distribution and Sales: Using manufacturing analytics solutions in pharma, the manufacturers can predict drug sales precisely. Next, they can optimize inventory management for a more streamlined distribution process, thereby lowering risks related to inadequate supply or overstocking. Comprehending historical data points such as previous sales trends in different regions and customer segments makes it easy to forecast future sales. Pharmaceutical companies can further identify and tap sales opportunities, enabling originations to assign resources strategically and improve return on investment. Marketing: Analytics enable the pharma companies to find out the patient demographics who are most likely to benefit from a specific drug throughout the drug life cycle. Customer Relationship Management makes it easy to nurture customer relations and gives a transparent view of customer interactions across different aspects of business touch points throughout sales. Also, predictive modeling enables tracking of customer experiences across channels such as online ads and email companies, allowing pharma companies to market their products effectively. Clinical Trials: Time and patient enrolment expenses are big hurdles during clinical trials. Pharma companies use data analytics to identify patients with specific traits for particular clinical trials. This approach streamlines patient selection, ensuring engagement till the trial ends. Further, the predictive models optimize research outcomes by minimizing the need for excessive test subjects, and resources, and speeding up the drug development process. What are the benefits of implementing manufacturing analytics solutions in pharma plants? By adopting manufacturing analytics solutions in pharma, pharma plants can reap the following benefits: Predictive maintenance: With the help of predictive maintenance technology, it is easy to detect glitches that signal budding issues and allow engineers to resolve them before they aggravate. Further, the plant managers can optimize maintenance scheduling, and plan downtime strategically to lower disruption. Risk mitigation: Pharma plants are risky environments. Advanced analytics tools enhance safety levels within the plant and surrounding area by ensuring smooth operations and early detection of issues to prevent health hazards. Quality control: The pharma industry needs impeccable quality control with strict vigilance. Any compromise in the quality standards poses huge risks to the patients, along with severe consequences for the pharma companies. Predictive monitoring analytics track the product quality throughout production and give warnings about minor quality variations that can be resolved immediately to prevent substantial product loss and maintain regulatory compliance. Optimize processes: Pharmaceutical companies analyze data from different production phases, giving a concrete understanding of how to improve resource utilization for better efficiency. The analytics give early notifications about any potential loopholes, enabling engineers to address them, without impacting the processing cost and product quality. Supply chain management: Manufacturing data analytics companies leverage analytics to enhance the supply chain and prevent supply shocks. The plant owners can proactively plan and procure the necessary resources, get visibility into the stock levels, ensure timely availability, and reduce potential disruptions. What measures do you need to take while using manufacturing analytics solutions in pharma plants? When using manufacturing analytics solutions in pharma, pay attention to the following factors: Challenges for pharma companies in the implementation of manufacturing analytics solutions Conclusion With insights from manufacturing analytics solutions in pharma, pharma manufacturing companies can improve their product quality, optimize resource allocation, and reduce health, environmental, and safety risks. Visibility into plant processes and operations makes it easy to detect bottlenecks, failures, and inefficiencies and reduce waste,

5 Hidden Costs in Manufacturing Exposed by Managed Analytics

Manufacturing is the most challenging aspect of any business. Several factors affect manufacturing such as accuracy, focus on details, and economical use of resources. But, there is more hidden and challenging information to identify significant components. Metrics like quality, dependability, and flexibility are included in this. To find the exact metrics and make informed decisions every business requires managed analytics services. Finding this true cost of the product involves identifying hidden costs and analyzing the total cost of Ownership (TCO). TCO includes all direct and indirect expenses such as manufacturing, buying, shipping, design, inventory control, labor inefficiencies, and even refunds. However, it also provides the most exact statistics to compare different production technologies, such as 3D printing and injection molding. What is Manufacturing Analytics? Manufacturing analytics solutions are used by manufacturers to track KPIs, decrease unplanned downtime, increase customer satisfaction, and optimize production efficiency. Industry 4.0, or smart manufacturing, is the term used to describe the larger trend. To do this, data gathered from industrial machinery and traditional IT systems must be combined, and analytics software must be used to make better decisions. Additionally, by predicting bottlenecks managed analytics for the supply chain in manufacturing processes that could interfere with order fulfillment, producers can determine the underlying reasons for production mistakes. 5 Hidden Costs in Manufacturing exposed by Managed Analytics With the help of managed analytics as a service, and using managed BI for smart factories, businesses can now automate the process of converting data into insights, which will help them further accomplish objectives like successful customer retention and the ability to forecast customer behavior through predictive modeling and 360 Degree Customer View. We have covered several important subjects in our blog during the past year. This has involved deciding what has to be improved; that is, figuring out all the possible areas to enhance, picking the crucial ones, and seeing those through to the end. For your improvement activities to produce any meaningful results, this is vital. The key features that set apart businesses that truly improve are knowing what to do and having the discipline to follow through without spreading your available resources. No amount of skill, managerial ability, or procedural expertise can bring about meaningful change in the absence of these qualities. Numerous hidden expenses exist. While some are particularly detrimental in high-product-mix processes like customized fabrication, others are inherent in practically any value-producing operation. Furthermore, if these expenses are not identified and addressed, they frequently complicate other improvement initiatives. Let us now discuss the ones that are most relevant to high-product-mix operations. Information Mistakes or Errors It might be very overwhelming to have all the information you need on what to construct when to build it, what to order when to order it, dates and quantity changes, revision levels, acceptable quality, and a lot more. Many things can go wrong. The more information there is, the more varied it is, and the more likely it is that something will go wrong if it is not expressed effectively. The information problem causes numerous forms of waste. That might be a monster. The quantity and diversity of information in a high-product-mix store are unlikely to alter. You have no control over that. However, you can make improvements by converting the input data into a standard output format that is highly accurate, understandable, and actionable. The idea is to create a system that feeds accurate data to the real processing operations, particularly those that take place on the factory floor. Correctness, clarity, timeliness, understandability for all participants, and identical actionability — the ability to produce the same action independently of the person performing it — are all requirements for the information. This instruction seems quite lofty. However, upon performing a root cause analysis to determine what went wrong and what causes needless expenses, you will nearly always discover that information errors are at the top of the list. It’s also possible to overcome the majority of these problems with the help of manufacturing data warehouse services or managed analytics. Here’s a basic yet typical example: A new machine that you recently purchased can process parts 50% faster than the previous one. Isn’t it an improvement? Not if you build to the incorrect revision, overbuild, or build the incorrect thing at the incorrect moment, that is. The costs of correcting the situation will outweigh the throughput gain. And those expenses will be forgotten. These overhead costs, however, hidden, are actual, cumulative, and unavoidable if nothing is done about them. Searching Because they follow the routine as usual, search costs are hidden. We are used to watching ourselves and other people engage in the common conversation that begins with the phrase “Let’s see… where can that be?” It’s entirely avoidable, fully typical, and also quite expensive. The one benefit of search waste, which is a type of downtime and information waste, is that it is comparatively simple to improve. Eighty percent of it can be resolved with any long-term 5S/visual workplace strategy. It is one of the few enhancements that is theoretically simple to start. The execution of the sustaining plan is the sole area in which knowledge is needed. It’s difficult to discover good reasons to tolerate search waste and its associated expenses. Because search wastes time, they typically manifest as variations in efficiency and collectively cause schedule problems and delayed orders. Overexposure to Material and Labor Movement It is rather typical to move materials around in a plant. Moving people around is also common. However, moving objects and people excessively has an impact that is almost identical to searching excessively. It’s one more traditional waste that lean concepts have found. It can need changes to the structure of plants and equipment, strict adherence to quantity and timing guidelines, and an emphasis on part flow, which makes it more difficult to eliminate. However, much like search waste, it can be greatly improved. To find the best answer, experience is undoubtedly necessary. However, progress can be accomplished gradually. Two excellent examples are

Transforming Hotel Data Analytics : Resilient Data Warehouse

The travel and hospitality industry is evolving through the adoption of data analytics and BI solutions. This is done by modernizing the hotel data analytics infrastructure. Here, we’ll discuss the ways to build a secure and scalable data warehouse and the role of analytics in the industry. The hospitality industry is investing in data analytics and business intelligence to effectively manage the increasing demand from customers. Data analytics helps unlock the hidden trends and patterns in large amounts of data to understand customer behavior, preferences, likes, dislikes, etc. It enables hotels and similar service providers to streamline operations and personalize offerings based on customer requirements. The global hospitality market is valued at $3.95 million in 2024 and is expected to touch $7.239 million by 2027 at a CAGR (compound annual growth rate) of 10.62%. Hotels can adopt data-driven models to derive real-time hospitality business intelligence insights and reports to make faster and better decisions. For this, you need to invest in a reliable, secure, and scalable data warehouse. In this blog, we’ll read more about the role of data analytics in the industry and the best practices to follow when building a data warehouse for hotel data analytics. What is Hospitality Data Analysis? Hospitality data analytics is the use of analytical tools to process historical and real-time data from the hospitality industry. It is a powerful tool that can positively impact various aspects of the business, such as customer experience, marketing, pricing, food and beverage sales, occupancy rates, etc. Hotels prefer to partner with a reliable hospitality data analytics company to set up the necessary IT infrastructure for implementing data analytics and business intelligence. The service provider will build a data warehouse and integrate it with BI tools like Tableau, Power BI, etc., and create custom dashboards for employees to access the insights in real time. Best Practices for Building a Secure and Scalable Data Warehouse The global active data warehousing market touched $10.8 billion in 2023 and is expected to reach $21.5 billion by 2032 at a CAGR (compound annual growth rate) of 7.68%. The data warehouse is a central repository storing massive amounts of data collected from multiple sources. It can be integrated with numerous third-party applications to run real-time analytics and derive business intelligence reports. However, building a data warehouse requires planning and expertise. You should ensure it is secure, scalable, and built using the best tools and technologies in the market. Typically, a data warehouse contains three main components Each layer is equally important and has definite purposes. These have to be aligned with your business requirements and long-term goals. The data warehouse is not limited to the present but is a tool for the future. That’s why data warehouse developers and service providers follow the below-listed best practices to deliver the best travel analytics solutions to businesses. Choosing the Technology A data warehouse can be built using various databases like traditional relational databases, open-source solutions, cloud-based databases, columnar databases, etc. Here, you choose a type based on your business volume and future plans. Since it gets expensive to build multiple data warehouses, you need a model that can be easily scaled and expanded as your business grows. That way, you add more layers to the existing model without starting from scratch every time. Moreover, the data warehouse should continue to deliver efficient results without lags and breakdowns. Open-source and cloud-based data warehousing models are preferred in today’s world due to the flexibility and customizability they offer. Designing the Data Warehouse Model The data modeling method you select affects the analytics and insights you derive by processing the datasets in the data warehouse. Go for reliable data modeling techniques like snowflake schema or start schema as they allow optimization of data retrieval. This leads to efficient query processing without consuming too many resources. You should also consider the types of queries you will use during day-to-day work. For example, a hotel employee has to constantly track the number of guests, advance booking, available free rooms, etc. Streamlining the ETL Process ETL stands for Extract, Transform, and Load. This stage focuses on extracting data from multiple sources and transforming it into structured formats to eliminate redundancy and then loading it into the data storage systems. With the continuous generation of data in the hospitality industry, the derived hotel data analytics can be accurate when the ETL process is efficient and free of errors. Techniques like parallel processing, data validation, etc., can enhance the ETL pipeline and create seamless data flow in the establishment. Ensuring Data Integrity and Consistency Data is the core of data-driven decision-making models. Insights derived from low-quality data can be unreliable and incorrect, leading to wrong decisions. This can be very costly, especially in the hospitality industry, where customer experience is a priority. For a hotel to derive accurate and actionable insights, the input data used for hotel data analytics has to be of top quality and free of mistakes and duplication. The data warehouse should have the means to implement data checks at various stages to increase overall consistency and quality. Data profiling techniques have to be implemented to detect anomalies in data sets, tags, etc., and highlight missing or incorrect values before the data is used for business intelligence reporting. Focusing on Scalability and Performance With new data being created every minute, you should inevitably prepare to scale the data warehouse periodically. There are different ways to scale, such as horizontal scaling, vertical scaling, data compression, indexing, partitioning, etc., that allow the central database to accommodate more data for storage and analytics. At the same time, weighing down the data warehouse with massive amounts of datasets can result in lags and delays. This has to be countered to ensure the efficient performance of the data analytics tools. Hospitality data analytics company like DataToBiz helps businesses find the best solutions to ensure scalability and performance in the present and future. The Need for Data Backup and Recovery Planning Data backup is a must for every business. Data loss is one of the biggest concerns and

10 Ways Analytics Managed Services Will Change Your Business in the Next 5 Years

The increasing complexity of data management and the constant advancements in technology, managing and extracting insights from data may seem like a daunting task. However, analytics managed services can step in to meet the growing demands of data management. Regardless of your role as a CEO, IT head, or CXO, you’re keenly aware of the vital role data-driven decision-making plays in today’s business landscape. So here, we will delve into some transformative ways in which Analytics Managed Services are meant to reshape your business in the coming five years. Enhanced Data Governance Effective data governance is the foundation of successful data analytics. Analytics Managed Services provide robust data governance, ensuring that your data is secure, compliant, and readily available. This guarantees data integrity and mitigates risks, allowing you to focus on strategic objectives. Streamlined Data Architecture Data architecture can be complex and overwhelming, especially as your business grows. Managed Analytics Services offer expertise in data architecture, helping you design and maintain a robust infrastructure. This ensures that your data is organized, accessible, and scalable as your business expands. Establishment of a Data Warehouse As data volumes grow, traditional data warehousing may become inadequate. Managed Analytics Services can help you migrate to modern, cloud-based data warehousing solutions. This transition not only saves costs but also offers the flexibility needed for agility and growth. What’s a Data Lake? A Data Lake can be a treasure trove of insights when managed effectively. Managed Analytics Services help you set up and maintain a Data Lake, making it a valuable resource for your data analytics initiatives. This keyword-influenced strategy will be a game-changer in data management. Data Science Analytics Managed Services Data science is at the heart of making sense of data. Managed Analytics Services provide access to a pool of data scientists who can develop advanced machine learning models and algorithms, helping you extract valuable insights and predictions from your data. Big Data Implementation Big data is no longer a buzzword but a reality for many businesses. Managed Analytics Services assist in harnessing the power of big data by offering the expertise required to handle vast datasets and extract actionable intelligence from them. The Right Partner Choosing the right partner for Analytics Managed Services isn’t just about immediate benefits; it’s a strategic move that can take your business five years ahead of the competition. With the right consultant by your side, you’re not just keeping pace with current data trends; you’re anticipating and adapting to what’s coming shortly. By collaborating with companies that understand your long-term vision, you can leverage their expertise to unlock growth and innovation. This allows you to harness the power of data today while staying well-prepared for the data landscape of tomorrow. In essence, the right managed analytics service provider becomes your bridge to a data-driven future, ensuring that your business is not just competitive but leading the way in the next five years and beyond. The Next 5 Years… As we look ahead to the next five years, Managed Analytics Services will be one of the driving forces behind business transformation. For enterprises like yours, embracing these services will not only enhance your data management capabilities but also open up new opportunities for growth and innovation. In a world where data is king, Managed Analytics Services are your crown jewels, ensuring that your business stays at the forefront of the data-driven revolution. But what about the next 10 years? How will these services continue to evolve and change the way we do business? It’s a question worth brainstorming! The pace of technological advancement is relentless, and the data landscape is continually shifting. Will your business remain adaptive and competitive in this ever-changing environment? With Managed Analytics Services by your side, you’re equipping your business to thrive in the future. So, start exploring these services and consider how they will help your business. Originally Published on DataToBiz

How Managed Analytics Services Enhance Customer Experience?

Have you ever wondered how businesses magically seem to know what you want, sometimes even before you do? Well, it’s not magic; it’s the power of data analytics. Do you want to know how Managed Analytics Services help you redefine the customer experiences? From interpreting large amounts of data to understanding customer needs, this blog focuses on how businesses seemingly anticipate your needs and deliver personalized meaningful experiences. In this blog, I’m going to take you on a journey to explore how managed analytics services can transform the way businesses serve you, and ultimately, how you experience their products or services. So, grab a coffee, get comfy, and let’s dive in! What Are Managed Analytics Services, Anyway? Let’s start with the basics. Managed analytics services are like having a team of data masters at your disposal but for businesses. They help companies collect, analyze, and make sense of the massive amounts of data they gather from various sources. Think of it as a behind-the-scenes superpower that organizations use to enhance their operations, and it indirectly affects you — the customer. The Heart of Customer-Centric Business In a customer-centric business, it’s not just about selling products or services; it’s about delivering a memorable and delightful experience that keeps customers coming back for more. Managed analytics solutions play a pivotal role in achieving this goal. Personalization Imagine strolling into your favorite online store, and boom! Right on the homepage, you’re greeted with a list of products that feel like they were handpicked just for you. This isn’t luck; it’s the result of analytics services at work. They use your past behavior, preferences, and even demographic data to create a personalized shopping experience. When you find what you want quickly, you’re a happy customer, right? Think about e-commerce giants like Amazon. They’re masters at suggesting products you’re likely to buy based on your past purchases and browsing history. But how do they do it? Managed analytics services are the engine behind these personalized recommendations. They analyze your data to understand your interests and behaviors, creating a tailor-made shopping experience just for you. This level of personalization goes beyond just e-commerce. Music services like Spotify and even news websites use similar techniques to keep you engaged. It’s like having your shopper, DJ, or news editor. Predicting Your Needs Before You Do Ever had Netflix recommend a show you end up binge-watching all weekend? Managed analytics services help businesses predict their future needs. Hear me out on this one! They analyze your past behavior to suggest products, services, or content that you’re likely to be interested in. It’s all about saving you time and effort by offering solutions before you even realize you need them. Predictive Analytics Let’s take the example of a food delivery app. It can use your previous orders, the time of day, and even the weather to predict what you might want to eat. So, when you open the app, your favorite cuisine is right there, ready to be ordered. It’s like they’ve read your mind, right? But it’s not just about food. Airlines use predictive analytics to anticipate delays and manage flights more efficiently. Banks use it to prevent fraudulent transactions. It’s everywhere, making our lives smoother and more convenient. Smooth Customer Support, Thanks to Analytics Imagine having an issue with a product or service and reaching out to customer support. With managed analytics services in play, the support team can access a wealth of information about your history with the company. They know what products you’ve bought, and issues you’ve faced before, and can provide tailored solutions. No more explaining your situation repeatedly; they already know you! Multi-channel Support Whether you contact customer support through chat, email, or a phone call, businesses aim to offer a seamless experience. With the help of analytics, they can track your interactions across different channels. If you start a conversation on chat and switch to a phone call, they pick up right where you left off. It’s like talking to a friend who remembers everything you’ve discussed. Moreover, analytics can identify trends in customer support queries. If multiple customers face the same issue, businesses can address it proactively, preventing further inconvenience. This means that issues get resolved faster, and you don’t have to deal with recurring problems. Streamlined User Experience When you visit a website or use an app, you want it to be smooth sailing, right? Managed analytics services play a crucial role in optimizing user experiences. They track how users interact with a website or app, identify pain points, and suggest improvements. The result? You enjoy a seamless, error-free experience. The User Journey Map Creating a user-friendly website or app is no longer guesswork. Managed analytics services help businesses understand the user journey. They analyze where users drop off or get stuck, and this insight guides improvements. For instance, e-commerce websites use analytics to enhance the checkout process. If they notice that customers abandon their carts at the payment stage, they can investigate why. Maybe it’s a complicated form or a lack of payment options. Analytics provides the data needed to identify these issues and make the necessary changes. But user experience doesn’t stop at websites and apps. Think about self-checkout kiosks at grocery stores or touch-screen menus at restaurants. Analytics ensures that these interfaces are user-friendly and efficient. Improved Product Development Businesses want to create products or services that you’ll love. Managed analytics services help in this process too. By analyzing customer feedback, usage patterns, and market trends, they can guide businesses in refining existing products or creating new ones. This means more of what you like and less of what you don’t. The Voice of the Customer Customer feedback is a goldmine for businesses. It tells them what’s working and what’s not. Managed analytics services can aggregate and analyze this feedback to extract valuable insights. For example, car manufacturers use customer feedback to design safer and more comfortable vehicles. Tech companies use it to refine software features. Even restaurants use it to tweak their

5 Top Managed Analytics Companies for Manufacturing Startups in USA

The manufacturing industry doesn’t have to buckle under the pressure of increasing costs and demands. Data analytics empowers enterprises to make the right decisions. Here, we’ll discuss manufacturing analytics solutions providers for startups in the industry. With manufacturing enterprises moving from traditional production methods to smart factories and digitalization, managed analytics has gained prominence among established and new businesses. Gartner Digital Markets surveyed with over 3400 participants to arrive at some interesting insights. The survey report shows that 54% of manufacturers plan to spend 10% or more on software compared to 2023. Most responders said business intelligence and analytical solutions were a top priority. However, 47% agreed that identifying the right software is the biggest challenge as it directly impacts their ROI and success. The best way to overcome the challenge is to partner with a managed analytics service provider. Manufacturing startups need much more than access to technology to compete with global enterprises. You should also have the required skills and talent pool to effectively use the technology and align the processes with business goals. From data management to decision-making, the data-driven model is a collection of various tools, technologies, talents, and domain expertise. Here, we’ll understand how analytics are helpful and why manufacturing analytics services are a must for startups in the industry in the US and around the world. How Can Data Analytics be Used in Manufacturing? Data analytics is where large amounts of data are collected from multiple sources, cleaned, formatted, and stored in a central database to derive meaningful, accurate, and real-time insights. The insights are used by employees and top management to make important business decisions. Data analytics for manufacturing firms has gained prominence, with technology disrupting the industry. The data analytics provided from this sector are called manufacturing analytics and can be used to streamline a variety of factory, production, supply chain, logistics, marketing, and customer-related activities in the enterprise. According to the Business Research Company, the market size of manufacturing analytics has grown from $11.75 billion in 2023 to $14.26 billion in 2024 at a CAGR (compound annual growth rate) of 21.4%. It is expected to reach $32.39 billion by 2028 at a CAGR of 22.8%. Data analytics can be used in manufacturing in the following ways: Third-party consulting companies offer end-to-end manufacturing KPIs managed services to help enterprises identify, track, and assess their key performance indicators to determine if the business is going as per the plan. It helps survive market competition, increase return on investment, and generate more profits. 5 Top Managed Analytics Companies for Manufacturing Startups DataToBiz DataToBiz is among the top manufacturing data analytics companies in the US, with startups and established enterprises as clients. It empowers manufacturers to streamline their operational processes by unlocking the full potential of data and analytics. The company offers end-to-end services to derive actionable insights in real time using various tools and technologies like AI, ML, NLP, generative AI, LLMs, etc. It also provides customized manufacturing BI solutions by building dashboards for different parameters. The teams work with business intelligence tools like Power BI, Tableau, etc. DataToBiz is an award-winning company with a presence in different continents, including North America. The data governance solutions offered by digital transformation companies ensure manufacturers set up the necessary security systems to collect, manage, store, and use large amounts of data. The company is a certified partner of AWS, Microsoft, and Google and is trusted by many manufacturers. It provides assistance at every stage, from identifying KPIs and competitors to determining the best marketing strategy to promote the products. The company also helps with AI-based automation, IoT (Internet of Things) device implementation, robotics, OEE, supplier analytics, quality control, resource optimization, customer behavior analytics, and so on. Seeq Seeq is a global firm offering advanced analytics for manufacturing companies, petrochemicals, oil & gas industry, life sciences, pharma sector, etc., from different countries. With a headquarters in Seattle, empowers manufacturers to get better business outcomes by generating faster insights. The company has developed solutions like Seeq Workbench, Organizer, Data Lab, etc., to help enterprises convert raw data into actionable insights. The AI and ML platforms can be deployed quickly and customized to suit the client’s needs. Seeq focuses on maximizing production runs and helping businesses achieve their sustainability goals. The company assists manufacturers in streamlining operations to improve throughput, reduce production costs, and increase quality. It also empowers the workforce to use the analytics for day-to-day decision-making. The company has announced its partnership with Databricks to promote IT-OT convergence in enterprises. Furthermore, Seeq’s platforms can be integrated with AWS and Microsoft Azure. Cognex Cognex is a global service provider of software, sensors, vision analytics, and industrial barcode readers in the manufacturing sector. The company works with enterprises from various subsectors of the industry like automotive, semiconductors, electronics, machine building, vision-guided robotics, solar, etc. It assists clients in improving product quality by identifying and eliminating errors, reducing costs, monitoring production lines, etc. The company believes in intelligent automation for smart production. It helps enterprises build manufacturing data systems and integrate the latest technologies with their processes. Cognex offers a plethora of products, such as 3D vision systems, barcode readers, edge intelligence, OEM products, etc. It highlights the importance of artificial intelligence in promoting innovation and automation. Technologies like edge computing and deep learning help enterprises make data-driven decisions. The company also provides training through its classroom facilities in the US, Asia, and Europe. The training programs by Cognex are conducted online and offline and cover a wide range of courses (basic to advanced) for the manufacturing workforce. Tulip Tulip is an IoT (Internet of Things) software provider that helps manufacturers democratize technology to streamline business operations and overcome challenges. It transforms the production floor by setting up digital connections to create seamless workflows throughout the enterprise. The applications offered by the company are cloud-based and ready to be implemented in enterprises. Derive predictive analytics in manufacturing, build robust and customized solutions for specific concerns, and boost productivity. Tulip’s platform has generated 448% ROI, according to the Forrester Consulting Total Economic Impact™ study commissioned by the company. The

Why Leading US Tourism Brands Are Investing in Data Warehousing (And You Should Too)

Data warehouses store large amounts of structured and unstructured data from different sources such as travel agencies, customers, and vendors. Let’s explore how travel analytics services help to deliver optimal customer experience, enhance operational efficiency, and grow the travel business. Data analytics enable travel businesses to explore huge datasets spanning customer preferences, feedback, and bookings to optimize their operations and services. Data warehouses play an important role in supporting data analytics by giving a unified view of data facilitating easy and reliable analysis. According to GlobeNewswire, the DWaaS (Data Warehouse as a Service) market is projected to reach USD 7.69 billion, at a compound annual growth rate of 24.5% by the year 2028. In this blog, we will find out why investing in data warehousing is important for tourism brands to stay ahead in the game. Types of Data in the Tourism Industry Benefits of Managed Analytics for the Travel Industry Now let’s discuss the benefits of managed analytics in the travel and tourism industry: Better Customer Experience: With advanced data analytics, travel companies get relevant information about customers regarding their preferences, buying patterns, and behaviors. The companies analyze this information to predict insights and personalize their service offerings to deliver exceptional experiences. Enhances Operational Efficiency: Using data analytics, travel companies run smoothly by recognizing patterns and ways to improve them. For example, airline operations analytics enable airlines to pick the best routes to save fuel. Competitive Pricing: The pricing in the tourism industry often fluctuates depending on peak and off-peak seasons, demand, special events, and competitor pricing. Travel companies can analyze these factors to optimize their prices and remain profitable at the same time. High ROI: Analysts use data analytics (obtained by tracking metrics such as conversion rates, and click-through rates) to assess how well the marketing campaigns are performing, comprehending which channels and strategies yield the highest value. Data-related Challenges in the Tourism Industry Some of the common challenges faced by travel agencies are: Privacy and Security: The tourism regulatory frameworks in the US such as the US Travel and Tourism Advisory Board (TTAB) enforce that all travel companies must comply with the standards of collection, storage, and usage of customer data. Any breaches or infringements are liable to penalties. Processing and Interpretation in Real-time: Elements such as cost, customer preferences, and availability keep changing frequently. Gathering and processing this data becomes difficult. Even if travel companies manage to collect and analyze data, interpreting it to obtain meaningful results needs the expertise of analysts and data scientists, resulting in a skill gap. Data Quality: There are possibilities of duplication and errors in the recorded data which may lead to wrong insights and decision-making. Since travel analytics solutions get data inputs from disparate sources (CRMs, booking platforms, and social media channels), integrating these huge data sets is a tough task. Ethical Handling of Data: Apart from abiding by regulatory compliance, travel analytics solutions must implement ethical considerations to handle data by preserving customer privacy. How can Data Warehouses help overcome the above Challenges? Data warehouses play an important role in overcoming the challenges by offering a centralized and organized repository to store, arrange, and analyze huge data volumes. Since travel companies collect data from diverse sources, data warehouses make it easy to consolidate information. It allows users to access data stored in a single repository from anywhere, saving time and facilitating quick decision-making for predictions. Data warehouses ensure uniformity and reliability of information across all levels, allowing seamless processing. They aid in integrating data from multiple sources, hence minimizing the time needed for comprehensive reporting and analysis. Important Factors to Consider when Choosing a Data Warehouse for your Travel Business Choosing the data warehouse for your business requires these considerations beforehand: Data types: Determine the kind of data that you want to store in your data warehouse. Performance: Find out the query processing speed for easy data retrieval. Size: Asses the size of the datasets you need to store in the data warehouse. Maintenance: Evaluate the efforts to oversee and control data warehousing processes. Cost: Estimate the budget that you can spend on data warehouse deployment. Community: Find out which tools and resources are required for integration after the data warehouse has been deployed. How Does the Travel Industry Use Data Analytics? Data analytics allows travel businesses to conclude meaningful insights and make concrete decisions by assessing market trends, customer feedback, and real-time data. Let’s explore how: Forecasting Travel Demand: Travel companies can predict the demand for travel services by analyzing existing trends and analyzing historical data. For example, an increase in flight reservations indicates growing interest, allowing the companies to advertise related services and launch targeted marketing campaigns. Customizing Customer Experiences: In response to the ever-evolving customer needs, the travel industry is moving towards delivering personalized experiences, supported by data analytics. By analyzing customer data, companies can cater to individual preferences. Also, businesses assess customer feedback and complaints to find out well-performing areas and areas that need improvement. Sentiment analysis classifies emotions as positive, negative, or neutral. The travel companies review their services accordingly, enhancing customer loyalty and satisfaction. Strategic Planning: It becomes easy for travel companies to identify evolving trends such as increasing preference for eco-tourism. These insights allow the marketing teams to plan strategically, launch marketing campaigns, and tap new opportunities. Managing Risks: Unforeseeable situations such as adverse weather conditions or epidemics may bring paramount havoc to the travel industry. With the help of real-time data analytics, travel companies can handle associated risks and send alerts for disruptions. This enables them to make arrangements to reduce adverse effects on the travel plans of customers. Conclusion: Travel and tourism companies can grow by leaps and bounds by implementing data warehouses. The travel analytics solutions provide meaningful insights to enhance operational efficiency, lower risks, assess marketing campaigns, forecast trends, and deliver incredible customer experiences. These platforms also aid in overcoming the challenges that pop up when dealing with large volumes of data with the help of reliable data governance practices. Data is an integral force and

5 Top Manufacturing Analytics Solutions Provider for 2024

Investing in manufacturing analytics solutions is the stepping stone to revolutionizing the enterprise with advanced technologies. Here, we’ll discuss the importance of managed analytics and the top solution providers offering manufacturing analytics in the USA. Industry 4.0 has revolutionized the manufacturing industry by bringing advanced technologies like artificial intelligence, big data analytics, machine learning, generative AI, etc., to unlock the power of manufacturing data and use it to make faster and better decisions. Manufacturing enterprises are adopting the technologies to reduce the risk of uncertainties and minimize disruptions to production, supply chain, and logistics. The ReportLinker said that the manufacturing analytics market is likely to reach $22.7 billion by 2027 at a CAGR (compound annual growth rate) of 22.8%. According to a report by Imarc Group, the global manufacturing analytics market size was estimated at $12.8 billion in 2023 and is predicted to reach $60.5 billion by 2032 at a CAGR of 18.2%. While North America is the largest region, Asia-Pacific is the fastest-growing region adopting manufacturing analytics. Software and service are the two main components of manufacturing analytics. Software refers to business intelligence and data analytical tools, whereas service implies the role of third-party analytical solution providers. They offer end-to-end manufacturing analytics services to help manufacturers adopt data-driven models in the enterprise and use business data to derive real-time insights for effective decision-making. Let’s read more about manufacturing analytics and the top service providers in the US. What is Analytical Manufacturing? The use of data analytical tools to collect, store, clean, process, and analyze manufacturing data is known as manufacturing analytics. It helps reduce downtime, improve production and performance, enhance customer experience, make proactive decisions, understand market conditions, and increase ROI. From eliminating bottlenecks during production to streamlining the supply chain and transportation, it can help an enterprise gain complete control over its processes. Cloud-based analytics for the manufacturing industry are used to monitor KPIs (key performance indicators), identify revenue streams, eliminate errors, and handle risk effectively. In short, manufacturing analytics have a versatile and diverse role in the sector. So, what insights can you provide with analytics to the manufacturing industry? A few examples are as follows: Many consulting firms offer services to implement and customize BI for manufacturing analytics and insights. We’ll look at the top service providers in the next section. Top Manufacturing Analytics Solutions Providers for 2024 DataToBiz DataToBiz offers comprehensive managed manufacturing analytics solutions for MSMEs and large enterprises in the industry. It has clients from various continents like North and South Americas, Asia, Australia, Africa, and the Middle East regions. The award-winning company empowers enterprises by sharing actionable insights about manufacturing operations, logistics, resources, machinery, assets, etc. From identifying KPIs to tracking them through customized dashboards, the team follows a systematic approach to streamline the process and share real-time insights. DataToBiz also provides manufacturing data governance services to collect, store, clean, and update enterprise data as per the data security and data privacy regulations. Identify gaps in the supply chain, increase OEE (overall equipment effectiveness) score, control overhead costs, and improve production efficiency. It also uses generative AI and LLMs (large language models) to enhance manufacturing processes. The company is a certified partner of Google, AWS, and Microsoft. It helps manufacturers gain greater transparency and become sustainable in the long term. It also provides automation and IoT-enabled (Internet of Things) analytics to promote greater flexibility, scalability, and agility in the enterprise. DataToBiz offers end-to-end integration services with Industry 4.0 technologies to help manufacturers increase ROI and revenue. DiLytics DiLytics is a pure-play analytics company with expertise in offering cloud and on-premises data analytics services to businesses from different industries. It provides end-to-end spectrum services, ranging from strategic consultation to implementation and managed solutions for manufacturers with diverse requirements. The company has a plethora of plug-and-play tools to offer managed analytics for supply chains in manufacturing and other department-based requirements. Moreover, it works with private and public sector enterprises. DiLytics categorizes its services into three aspects – think, build, and run. While strategy, roadmap, audit, and technology evaluation belong to the ‘think’ category, self-servicing analytics, predictive analytics, system migration and upgrades, etc., fall into the ‘build’ category. Testing and long-term maintenance support are a part of the ‘run’ solutions. The cross-functional analytics offered by the company help eliminate bottlenecks, improve inventory management, and get better control over the finances and resources. DiLytics also implements custom warehouse solutions for large-scale manufacturers. ThirdEye Data ThirdEye Data is a data analytics and AI company that enables enterprises to increase production accuracy and gain operational efficiency by leveraging advanced technologies. The company offers customized BI for manufacturing processes, along with ChatGPT-based insights and AI/ ML automation to empower businesses. It helps clients make informed decisions with effective data engineering services. The company specializes in building bespoke smart factories with AI technologies to empower enterprises to tackle real-world problems using data-driven solutions. ThirdEye Data follows a step-by-step process to build AI applications and integrate them with enterprise systems. Aspects like data security and compliance are given importance. The company also provides scaling, monitoring, and maintenance services for clients. Predictive analytics, supply chain management, and quality control are some manufacturing services offered by ThirdEye Data. The company has ISO 27001:2013 and SOC 2 Type 1 certifications. It is a Microsoft Silver Partner and has the necessary experience to help enterprises achieve digital transformation on any scale. Indium Software Indium is a fast-growing digital engineering company that builds next-gen cutting-edge technologies to help businesses achieve their goals. It works with Fortune 500 and Global 2000 companies in various industries. It has also partnered with industry leaders like AWS, Databricks, etc., to help enterprises use the latest tools and technology for digitalization. The company offers customized managed BI solutions for smart factories without disrupting the existing workflow in the enterprise. It helps manufacturers understand the challenges of finding effective long-term solutions. Indium provides digital manufacturing and operational solutions such as IT/ OT convergence, data insights, twin-centric architecture, industrial IoT sensor installation and connectivity, predictive analytics, intelligent asset management, Industry 4.0 adoption, inventory management, transportation management, etc. The company provides continuous

5 Top Consulting Firms for AI Adoption in the US Tech Startups

AI adoption is fast becoming compulsory to survive the changing market conditions. It helps gain a competitive edge and boosts revenue. Here, we’ll discover the top consulting firms for AI adoption in the US that work with tech startups and its role in boosting revenue.. Artificial intelligence adoption has picked up pace in the global market. Generative AI has further boosted the demand for AI tools across various industries. AI is no longer limited to large brands but is just as accessible to startups and small businesses. According to statistics, the world spent $154 billion on AI solutions in 2023. The global AI market was valued at $207.9 billion, a 50% increase from 2022. This amount is expected to touch $1.35 trillion by 2030, with artificial intelligence contributing $15.7 trillion to the global economy. The global AI adoption rate was 35% a couple of years ago. This is expected to increase as more businesses invest in new technology. Another report shows that over 25% of the startup funding in the US went to AI startups in 2023. Around 78% of executives say that they believe generative AI offers more benefits than risks. However, to minimize the risk and maximize profits, the startup should have the necessary expertise and guidance to adopt AI successfully. This can be achieved by partnering with consulting firms offering AI solutions for tech startups in the US and around the globe. Let’s look at the top service providers in this blog. What is an AI Consulting Firm? One of the main barriers to AI adoption is the lack of expertise. Technical know-how, experience, strategy formation, etc., are some concerns that make businesses wary of investing in something they don’t know. That’s where consulting firms provide support and assistance. An AI consulting firm is a third-party (onshore and offshore) service provider that helps an organization plan, build, deploy, customize, upgrade, and maintain artificial intelligence-based tools to streamline business processes and gain a competitive edge. An AI consulting company has a diverse role and offers the following services: However, not all AI consulting firms offer every service listed above. Only some firms, like DataToBiz, provide complete end-to-end solutions for tech startups. Some may offer only strategic consultation, executive consulting, or cloud services. The big four companies, like Deloitte, PwC, EY, and KPMG, cater to established large brands, making them too expensive for startups and SMBs. 5 Top Consulting Firms for AI Adoption in the US DataToBiz DataToBiz is among the leading AI product development companies in the USA, with clients from varied industries. It works with startups, SMBs, MSMEs, and large enterprises in America and other countries around the world. The award-winning company offers comprehensive solutions to tech startups and guides them through every stage, from planning to implementation. It is a certified partner of Google, AWS, and Microsoft. The company’s clients prefer long-term partnerships to benefit from the team’s expertise and make the most of its maintenance services. DataToBiz builds AI/ ML models and NLP (natural language processing) and deep learning algorithms. It offers vision analytics and develops LLMs (large language models) for startups to establish a robust IT infrastructure from the initial days. The company also takes care of automation and product development. It can create custom apps or personalize existing tools to suit the startup’s requirements. Data harmonization, big data management, installing IoT (Internet of Things) devices, etc., are also a part of the company’s offerings. DataToBiz is a one-stop destination for tech startups to achieve their goals and increase ROI. HensonGroup HensonGroup is a US-based global Azure managed service provider. It provides digital transformation services to businesses from industries like manufacturing, retail, education, healthcare, nonprofits, etc. The company specializes in intelligent managed services to offer the best support for businesses to make data-driven decisions. From Microsoft Azure migrations to management, it takes care of everything to increase the cost-efficiency of the business through cloud computing solutions. HensonGroup offers a range of services, though predominantly focused on Azure cloud computing and Microsoft solutions. It also has OpenAI expertise and helps businesses choose the best cutting-edge technologies to revamp their business. The company has an OpenAI Accelerator Program for startups and established businesses to effectively adopt generative AI and integrate it seamlessly with their existing processes. It also has ISO certifications – 27001:2013, 9001:2015, and 20000-1:2018. Juniper Networks Juniper Networks is an AI service provider offering a plethora of solutions to manage the IT infrastructure, networks, and other technologies in the business. It offers startup AI strategy and consulting services through innovation, automation, and cloud operations. The company works with businesses from many industries, ranging from banking to healthcare and more. It believes in simplicity while embracing diverse ideas to promote the adoption of advanced technology. It also takes social responsibility seriously and has an integrity-driven supply chain. Juniper Networks is a dependable service provider and helps clients achieve sustainable growth. For example, Juniper Apstra is a networking software that automates and validates the design, deployment, and operation of data center networks. The company combines multi-cloud computing and 5G technologies to ensure reliable, fast, agile, and scalable solutions for startups and other popular businesses. The company also handles security solutions to increase system security for devices, apps, IT infrastructure, and users (employees, stakeholders, and customers). LeewayHertz LeewayHertz is an AI development company offering cutting-edge software for startups and enterprises. The company builds innovative and creative tools to help businesses keep up in this fast-paced world. It provides end-to-end AI services and integrates apps with business systems to accelerate digital transformation. The company has expert teams to fine-tune foundation LLMs like GPT and LLaMA. It also creates customized domain-specific models to suit client’s requirements. LeewayHertz has successfully built over 50+ AI solutions to help businesses make data-driven decisions. Experienced software developers and AI engineers work closely to handle everything from conceptualization to implementation. The process is tailored to align with each business’s needs so that the establishment can harness the full potential of data and artificial intelligence. The company builds web and mobile apps, enterprise-grade tools, and generative AI models for