Managed Analytics – DataToBiz

MSPs for CTOs: A Faster Way to Execute Technology Roadmaps

Managed service providers are a cost-effective alternative to building a long-term internal IT team for managing the business infrastructure. Here, we’ll discuss the support MSPs for CTOs in delivering the technology roadmap without delay. A managed service provider (MSP) is a third-party company that provides remote and offshore services to manage an organisation’s IT infrastructure and end-user systems. From management to maintenance, monitoring, and upgrading, the MSP handles various responsibilities to ensure the systems are error-free and efficient. It helps reduce downtime, mitigate the risk of unexpected glitches, and upgrade the systems whenever necessary. Software, cloud, network, cybersecurity, analytics, and AI and LLM solutions are some commonly managed services by these companies. According to Fortune Business Insights, the global managed services market was $330.4 billion in 2025 and is expected to grow at a CAGR (compound annual growth rate) of 14.80% to reach $1118.2 billion by 2034. C-suites have been partnering with managed service providers in recent years. MSPs for CTOs help streamline various digital solutions, implement the data-driven model, build and maintain data pipelines, and optimize the data architecture. They take full responsibility for the services selected by enterprises and provide priority support around the clock. Technology MSP services are also the best choice for implementing the roadmap without delays. In this blog, we’ll read more about the importance of a technology roadmap and the support of MSP for CTOs in delivering the roadmap as per the long-term strategic plan. What is a Technology Roadmap and Why is it Important? A technology roadmap is a detailed strategic documentation about the various tech-based activities and adoptions planned by the enterprise for a given timeframe. It is a foundational plan of action listing how to build, deploy, and maintain the IT infrastructure, how to embrace digital transformation, how to use data analytics and advanced solutions, and how to ensure the technology used is aligned with business values and goals. Many organizations partner with data analytics companies to use their expertise in creating the technology roadmap and achieving it over the planned timeline. The C-suites actively work with outside experts in selecting the right technologies and determining when to implement them in the organization. A technology roadmap is a critical document for CTOs (Chief Technical Officers), as it also helps in driving business growth, maintaining efficiency consistently, ensuring transparency, and future-proofing the organization to make proactive decisions in competitive markets. That’s why CTOs require additional support with specialized expertise to deliver the roadmap without delays or unexpected challenges blocking progress. Why is a Technology Roadmap Important for a CTO? CTOs have the pressure to show the measurable impact of technology on business outcomes and revenue. You have to ensure alignment between business needs and the technology adopted, while considering the budget and other financial restrictions. A technology roadmap helps CTOs in the following ways: Managed services for CTOs are third-party remote solutions tailored to suit the specific requirements of the business and the executive. Certified experts offering services for data engineering, data analytics, data science, AI and ML engineering, big data, etc., work as a team to support the CTO in delivering the technology roadmap and ensuring the outcomes are measurable and deliver high ROI. Role of MSPs for CTOs in Delivering Technology Roadmaps Understanding the Business Vision and Values MSPs don’t offer readymade or one-size-fits-all solutions. Instead, they customize the strategy, services, pricing, and support based on each business’s requirements, industry, region, budget, etc. The first thing they do is to conduct an audit or gather information to understand the business vision, values, short-term goals, and long-term objectives. From consultations to meetings, an MSP for enterprise IT solutions begins with gaining an in-depth knowledge of the business. This also includes pain points, market position, growth opportunities, etc. The services provided are also aligned with industry standards and specifications to improve the organization’s position and eventually enhance visibility. Prioritizing Critical Objectives CTOs, CEOs, and CFOs know that a business has several objectives and corresponding initiatives. However, the priorities change depending on the short-term requirements, and enterprises have to adjust the budget accordingly. For example, if expansion is the immediate goal, the executives have to focus on scalability (talent-wise and technology-wise). This requires cloud adoption and migration, automation, etc. The MSPs for CTOs can provide end-to-end data engineering to build and maintain a cloud-based data architecture to support the increase in data flow and transactions. Similarly, organizations that want to enhance customer experience are likely to prioritize the optimization of CRM solutions. Creating a Tech Roadmap The technology roadmap is not just a list of tools to purchase or upgrades to make to the IT infrastructure. It is a guide for the future, to address various challenges that might affect the business today and in the future. Flexibility, scalability, sociopolitical developments, changing market trends, industry-wide patterns, etc., are common factors to consider when creating the tech roadmap. This requires external expertise and diverse perspectives from specialists in the domain, as well as the core business knowledge and insights of the C-suite. The goal is to align technology growth and adoption with the enterprise’s growth and expansion to stay one step ahead of competitors. Selecting Relevant Tools and Technologies Selecting the right tools and technologies is vital for success. MSPs for CTOs don’t just implement a document. The service provider helps executives understand which technology is beneficial for their business and which is not, even if it is being used by others or promoted as a must-have for every growing organization. For example, a mid to large enterprise would find it cost-effective to build AI data pipelines for automating data flow and analytics. This helps in generating real-time insights and sharing them with decision-makers at various levels. Eliminating the need for manual data collection and cleaning results in greater efficiency, less cost, and more accurate insights. Proactive Planning and Risk Mitigation Another critical aspect of a technology roadmap is risk management. MSPs support CTOs in identifying pain points, threats, vulnerabilities, weak areas, etc., that

Revenue Cycle Management in Healthcare: Your 2026 Playbook

RCM is a key process in the healthcare sector and impacts revenue and patient management. Here, we’ll discuss the top practices to enhance revenue cycle management in healthcare and the role of RCM analytics in the industry. There is an increase in demand for big data analytics in the healthcare industry to handle the increasing generation of new data every day. Technology has become an integral part of the industry for effectively managing large data volumes and providing data-driven decision-making analytics. Different types of services, like patient management, revenue cycle management, financial management, data management, etc., are offered by data analytics companies to help healthcare centers streamline their internal processes. RCM analytics is similar to healthcare analytics but focuses on the financial aspect of the business. Statistics show that the global healthcare analytics market was $44.8 billion in 2024 and is projected to reach $284.5 billion by 2035 at a CAGR (compound annual growth rate) of 18.3%. RCM, aka revenue cycle management, is one of the core functions in the healthcare sector. Setting up a comprehensive RCM system can reduce the risk of errors in patient data, reduce claim denials by insurance companies, and increase patient satisfaction with the healthcare center. In this blog, we’ll explore the role of RCM analytics and the best practices to follow when adopting the process. What is Revenue Cycle Management? Revenue cycle management is managing the revenue cycle in a healthcare center. A revenue cycle can be broadly classified into three stages – patient registration, preparing to claim insurance, and collecting the payment. These are further divided into multiple steps. But what is the use of RCM in medical billing? RCM combines various tasks and departments to create a pathway for the patient’s journey with the hospital. From the time the patient arrives at the hospital and asks for an appointment to the final bill payment after the treatment ends (and any other revisits), RCM ensures the patient’s data is accurately collected, recorded, stored, and shared with relevant parties to provide medical treatment and manage insurance/ payment for the services provided. RCM analysis minimizes the risk of mismanagement of these functions and increases overall efficiency. What is an Example of RCM? Let’s say, a patient with an ear infection visits the hospital for treatment. The front office staff will gather the patient’s details and give an appointment with the specialist. The report (tests and medication) recommended by the specialist has to be updated in the patient’s file. If surgery is necessary, the patient’s insurance details are collected so that the insurance company can contact them and file a claim to reimburse the expenses. When the patient goes home, the bill is settled by tallying the claim amount with the bill amount. The patient pays the balance, if any, to end the transaction. These are a series of tasks performed by different people over a period. With revenue cycle management in medical billing, these can be streamlined and accelerated using technology. Effective RCM enhances patient satisfaction while reducing the stress on hospital staff. What are the 12 Steps of the RCM Cycle? Now that you know what the revenue cycle process is, let’s look at the various stages of revenue cycle management. 8 Top RCM Practices to Follow in 2026 To get the best of RCM analytics, the healthcare center should follow the industry-wide best practices and be open to accepting new technology and modern processes. 1. Invest in Technology In a world where technology gives a business a competitive edge, not utilizing it can lead to chaos and decline. Considering the complex stages of revenue cycle management, healthcare RCM analytics include a range of tools and technologies. For example, a data warehouse has to be set up (on-premises or cloud) to store all the data in a central database. This data warehouse is integrated with input sources to collect patient data and connected with AI tools for data analytics and data visualization dashboards. More third-party integrations can be added to send the details to insurance companies for claim submissions. Invoice generation and payment management software are also integrated with the data warehouse to create an interconnected RCM system that provides real-time information to the hospital staff. 2. Collect Patient Data Early Patients are a key part of the healthcare system. Collecting all the necessary information about the patient will create a better profile and lead to more effective treatment. Similarly, asking patients about their insurance details right during the initial registration will allow the hospital to get the required pre-authorization for claim submission. Instead of waiting until bill generation, ask for the information when they register the first time. By storing this data in the central repository, the staff can access it whenever necessary. The claims can be submitted quickly, and patients can be informed in advance about any extra payments they would have to make if the insurance payout doesn’t cover the entire bill amount. 3. Optimize Patient Registration Process Collecting patient data upfront is the first step. This information has to be verified to avoid complications later on. For example, a simple clerical mistake in adding the insurance policy number can result in claim denial and loads of paperwork. Verifying the insurance details as soon as possible will prevent such delays and decrease the claim denial rate. Similarly, RCM performance analytics can be used to optimize the registration process and simplify it for the patients. After all, people don’t want to fill out a dozen applications just to get an appointment with a doctor. Identify the bottlenecks in patient registration and eliminate unwanted steps. Keep the forms straightforward but also include enough fields to collect the required information. 4. Aggregate Patient Data (Digitally) Digitalizing the process ensures patient records are moved to the data warehouse and can be accessed by doctors and admin whenever necessary. This is also important to process insurance claims as the details should be shared with the insurer. Thankfully, today’s revenue cycle management technology is advanced and

Inhouse vs Outsourced RCM Analytics – The Ideal Choice in Healthcare?

Revenue cycle management (RCM) is managing patient data, claims, and payments from start to finish. Here, we’ll discuss the role of RCM analytics in healthcare and determine the differences between in-house and outsourced analytics services. The healthcare industry deals with many administrative and financial tasks. From patient applications to transactions with insurance companies, the processes can be complex and time-consuming. This is one of the reasons why billing takes so much time in hospitals, causing more delays and frustration for the administrators and patients. Fortunately, RCM provides an effective solution for this. To improve things, RCM analytics identifies the root cause of delays and helps streamline the entire process. But what is RCM? What does RCM stand for? RCM is Revenue Cycle Management, the process of identifying, collecting, and managing payments from patients of the healthcare center. It is necessary for patient management and financial management. The RCM market is expected to grow at a CAGR of 12.2% between 2025 and 2032 to reach $342.6 billion by 2032. Revenue cycle management (RCM) software streamlines and automates revenue cycle management. So, what is RCM software, and how does it work? RCM software is similar to medical billing software that tracks the patient’s case from initial registration to discharge. It is used to calculate the final payment, insurance payouts, etc. It also maintains a proper record of each patient with ID. However, healthcare establishments face many problems in medical billing and RCM. RCM analytics provides a reliable solution for these issues. But should a hospital opt for in-house billing or outsource the task? Let’s find answers to these questions and more! RCM Challenges in Healthcare Before we explore the differences between how in-house RCM and outsourced analytics work, let’s first understand the challenges of healthcare RCM analytics. Human Error The hospital staff is often overworked and stressed due to the extensive responsibilities they handle. By asking them to manually manage patient registrations and payments, there’s a high risk of human error or a wrong entry. Complex Process The roles and responsibilities of front-end and back-end employees are different. RCM has to effectively bridge the gap to minimize confusion, incorrect information, delays, etc. The process is just too complex and stressful without using the latest technology. Missing and Outdated Data With the administration fragmented into individual departments, there’s a risk of patient data missing from files. For example, if someone forgets to mention the information about the patient’s insurance in a report, it could lead to a series of confusion and miscommunication. RCM data management through modern data warehousing services can solve this problem. Changing Regulations The regulations in the healthcare and insurance industries can change, resulting in confusion among patients and administrative departments. It could be something as simple as a hospital not having a tie-up with a certain insurer, leading to more paperwork and exploring alternate options. Patient Volume Hospitals are among the busiest places on earth. Unfortunately, this puts excessive pressure on the staff to work around the clock. The high patient volume directly translates to tons of paperwork, reports, and bills. Using RCM software and data analytics helps handle this high volume. Fraud Detection The hospital staff also has to deal with fraudulent transactions and wrong insurance claims. Manually investigating each claim is exhausting. What if they can detect and predict such activities proactively? RCM analysis can be used for fraud detection to identify potential frauds in the early stages. In-house vs. Outsourced RCM Analytics in Healthcare: Which One to Choose RCM analytics can help healthcare businesses overcome various challenges they face in managing patient data and claims. But should they develop an in-house RCM analytics model or outsource RCM analytics to a third-party service provider? Which method is more effective? In-House RCM Let’s first check out what in-house RCM analytics in healthcare and medical billing actually are. In-house RCM is also called medical billing. The entire setup is managed by the hospital staff with little or no input from service providers. The service provider might build the RCM analytics model and hand over the responsibility to the hospital staff. This gives the business more control over the process but also increases workload. Advantages of In-house RCM Disadvantages of In-house RCM Outsourced RCM Analytics Outsourced RCM analytics are offered by third-party companies that handle all the responsibilities of setting up the analytical model, creating integrations between different systems within the establishment, and managing the central repository with patients’ details. What is outsourced RCM analysis in healthcare and medical billing? It is an interconnected approach to setting up a comprehensive and robust management system on a cloud platform to streamline and automate financial management in the healthcare center. A single interface or platform like the Power BI dashboard can be used by various departments like the front desk, billing, clinical, etc., to access patient data and update the records in real-time. It is a collaborative model aimed at boosting overall efficiency, performance, and revenue for the business. Advantages of Outsourced RCM Analytics Disadvantages of Outsourced RCM Analytics What are the 12 Steps of RCM? Data analytics companies offer nearshore and offshore RCM analytics services in the healthcare industry. They set up RCM analytics to streamline the twelve steps of revenue cycle management, manage patient data, track claims, and increase ROI. They start by identifying the KPIs to measure and improve the establishment’s financial health. What is a KPI in RCM? KPI stands for Key Performance Indicator, a metric used to measure if the RCM cycle is aligned with the hospital’s vision and objectives and is delivering the required results. The twelve steps of revenue cycle management in medical billing are as follows: Fortunately, hospitals can manage all these steps by investing in the latest revenue cycle management technology and partnering with analytics service providers to maintain the system. This reduces the pressure on hospital employees and enhances patient experience. It also maximizes efficiency and increases reimbursements by limiting denials. Conclusion Depending on the business’s mission, vision, and objectives, RCM

How to Scale Your Startup With Managed Data Analytics?

Data analytics is the process of collecting, storing, and analyzing large datasets to derive actionable insights in real-time. Here, we’ll discuss the role of managed data analytics in scaling a startup and the benefits of adopting the data-driven model for decision-making. Startups usually begin on a small scale and expand over the years. However, scaling a startup is easier said than done. As per a study by the Kauffman Foundation, just one startup in every ten scales is successful. That’s when startups are worth $1215 billion in 2024, and the value of unicorns around the globe is estimated to be $4.3 trillion. So how do you scale your startup and ensure success in 2024 and beyond? Managed data analytics and artificial intelligence are the answers. Startups need to be proactive and take advantage of the data and technologies available in the market to establish themselves. Instead of following conventions and orthodox business models, startups should adopt data-driven models and advanced tools (cloud solutions, AI, ML, etc.) to reduce the risk of failure. Fortunately, plenty of third-party companies offer onshore, near-shore, and offshore managed analytics services tailored to suit the business requirements. In this blog, we’ll read more about how to successfully scale a startup by investing in data analytics and the benefits of using managed analytics in a new business. How do You Scale up Your Startup? Scaling a business is the process of growing or expanding the operations, products and services, market share, customer base, and returns. Startups scale to invite more customers which brings higher revenue and creates a brand image in the market. However, scalability can be limited to one or specific avenues as well. Not every startup scales all aspects together. Typically, you can scale a startup in any of the following ways: What is an example of a Scalable Startup? Is Managed Data Analytics Involved? Facebook, Twitter (now X), and Amazon are great examples of a scalable startup. These started as small companies run by the entrepreneur and a couple of friends or team members. Over the years, Amazon has become the number one international marketplace and Facebook is one of the tech giants. They heavily invested in business analytics (gradually) to make decisions backed by data and insights. This allowed them to quickly adapt to the changing market conditions and gain a competitive edge. How do Startups Use Managed Data Analytics? Startups cannot underestimate the importance of data analytics in modern times. From streamlining internal processes to increasing customer satisfaction, analytics can be helpful in several ways. It converts raw data from multiple sources into actionable insights that employees can access to complete daily tasks more effectively. Understand Target Markets Startups don’t have the luxury of taking major risks or investing all the money into a project without basic research. Nine out of ten startups fail and shut shop in less than a decade. This can be due to lack of funds, incorrect investments, wrong decisions, etc. Understanding the target market conditions can reduce the risk of losses and keep the business afloat. For this, you can rely on data analytics to process the datasets related to the market and derive meaningful insights. Third-party companies offer managed analytics solutions and embedded analytics to provide real-time insights whenever you need them. Analyze Customer Behavior Customer feedback is vital for every business, and startups need it more than ever. However, you cannot afford to spend your time and resources on manually analyzing this feedback. Data analytics simplifies the process by using powerful tools and sharing the reports through data visualization dashboards. Platforms like Power BI, Tableau, etc., are popular data analytics tools that can be integrated with various input and output systems to provide insights 24*7. Evaluate Competitors How else do startups use data analytics to grow their business? Managed data analytics is not limited to analyzing the internal aspects of a business. You can use public data to determine who your competitors are and how they are faring in the market. This helps in identifying weak areas in your startup and strengthening them to survive the competition. Similarly, you can track the performance of your competitors and identify growth patterns to plan your strategies accordingly. Improve Products and Services Startups face severe competition from existing and new businesses. This means you have to continuously tweak your products and services to increase sales and bring more customers. Data analytics helps by highlighting the purchase patterns and preferences for your offerings and in the market. It provides information about what customers like and how you can improve your products and services to generate more sales or get the desired number of subscriptions. Streamline Internal Operations As a startup, you don’t have access to unlimited funds. You need to make some strict decisions about where to invest, what to prioritize, etc. In such instances, managed data analytics can help by identifying processes or steps that consume excess resources but are not necessary for the business. You can shorten the cycles, automate recurring tasks, and trim areas without compromising quality. It also helps in negotiating better deals with suppliers, storing your inventory carefully to reduce wastage, increasing or decreasing production/ procurement to align with the market demand, etc. Increase Conversion Rate Marketing is another area where data management services and analytics can help your startup. A new business has to invest in offline and online marketing campaigns to reach the target audience. Generating leads is one aspect, and converting them into sales is another. Startups tend to have a hard time converting leads to sales. Data analytics can be used to create a marketing strategy that suits customer preferences. Identifying the right kind of audience and sending the right message to the right customer at the right time through the right channel is possible when you use data analytics. Identify More Avenues for Revenue Revenue cycle analytics gives startups in the healthcare and finance industries a clear idea to streamline their revenue generation avenues. It tracks every step

Why Managed Analytics Services Matter – Top 11 Benefits You Must Be Aware Of!

Managed analytics services enhance customer insights and provide real-time data-driven insights. Businesses with strong analytics capabilities see 2x higher performance and 30% annual growth. Leveraging these services, companies can optimize operations, and gain a competitive edge through specialized expertise. Digital transformation is advancing and this goes hand in hand with the need to engage data in decision-making processes. Additionally, the complexity of the technology landscape is also growing significantly with the advent of Industrial Revolution 4.0. So, to ensure businesses have 24×7 access to analytical data, businesses are looking forward to Managed Analytics Services, for seamless operations. However, from a business perspective, managed analytics services come with a cost along with your internal team. Does the cost justify the benefits? Do managed analytics services actually add value to the business? Let’s find out! In this blog, we’ll focus on Managed Analytics Services and the benefits they reap for the organization. But before, we need to understand, what exactly is managed analytics services. What Are Managed Analytics Services? Managed analytics services provide an end-to-end data analysis and intelligence service that makes data useful for business decisions. This is far better than following the limitations of hiring data science experts and dealing with technical issues. This approach features an already validated and readily available data architecture and automation to add to ongoing training and tutorials from data professionals. As the name suggests, it is self-service oriented in terms of a business and its stakeholders, resulting in a lower TCO (Total cost of ownership). Unlike the common approach of assembling internal data teams and then starting rigid implementations, managed analytics services are the end-to-end solutions. These services offer capabilities ranging from data aggregation, process integration, and cloud data storage as well as processing up to sophisticated analytical work as well as data visualization and reporting in an interface-based format. Features of Managed Analytics Services It is critical to note that nearly 85% of data analytics projects do not succeed. One of the primary reasons is that the organization does not have a clear data strategy in place. The continued partnership with managed analytics services providers guarantees that all data assets are useful and Davis’ strategy is optimal. Benefits of Leveraging Managed Analytics Services Before investing in managed data analytics, it’s essential to evaluate if data analytics is suitable for your company. For many organizations, properly implemented management data analytics yields a significant return on investment. According to Forrester, companies that invest in data analytics experience an annual growth rate of 30%, compared to an average of 3% for other organizations. Transforming into an insights-driven business offers numerous clear and measurable advantages. 1. Enhancing Customer Insights Managed Analytics Services helps in tracking customer interactions and provides a comprehensive view of who they are and how well their needs are met. Product managers use data analytics in several ways: Bain & Company’s research shows that companies with superior analytical capabilities are 2x as likely to be top financial performers. This approach ensures better business decisions and outcomes. 2. Easy to Scale at Large Few businesses can justify the significant expense of building their own data teams from scratch, which averages around $520,000 annually. Moreover, smaller enterprises, including startups and scaleups, often don’t require a full team of full-time data engineers, analysts, and report developers. Nevertheless, these businesses still need to scale and adapt to dynamic market conditions and evolving needs. Thankfully, the on-demand nature of today’s service economy makes managed analytics services an ideal solution to overcome the challenges (and risks) associated with scaling – without excessive costs. By accessing expertise and resources on demand, businesses can enhance their agility in developing data capabilities. 3. Stay Ahead of the Curve Bring some realization to today’s fast-paced business environment the opportunities that a firm has must be grabbed to remain a force to reckon with. However, decisions where time is important like the following; Price discounts, and new product releases among others are quite risky. Decisions made have to be accurate and as well made in good time. Through outsourcing and applying a managed services team to the process of data analytics, businesses can obtain almost real-time results. More frequently, it is the speed to insight that matters. The dawn of an empowered marketing team is hampered by no time for manual spreadsheet analysis, report compilation, and meetings to debate over metric definitions. Fortunately, a modern business analytics solution will be able to avoid such bottlenecks. 4. Cost Reduction and Efficiency Enhancement The most important current objective of managed services from a finance perspective is cost control, but data analytics help to find more resources that can be cut down than might have been detected through other means. So, by using big data reflecting the pricing strategies of suppliers’ historical negotiation results or the current market situation of the commodity, many organizations across the globe can obtain more beneficial purchasing agreements, look for cheaper substitutes, and use their available resources effectively. 5. Enhances the Core Competencies Every company today relies on technology, but this shouldn’t detract from focusing on core strengths. Businesses must ensure technology serves their goals without overwhelming their teams. Managed analytics services are designed to alleviate the burden on in-house IT teams, cutting costs and reducing dependency. Specifically, managed data services handle the complexities of setting up data analytics systems tailored to your needs. This includes deploying cloud warehousing infrastructure and creating secure, interactive dashboards that provide essential insights. This approach eliminates the need for hiring expensive, niche skill sets, allowing businesses to concentrate on their primary competencies. 6. Informed Decision Making Every day you and your team make a myriad of decisions; from how to respond to an email to a major strategic choice. These decisions may be small, some may be major. There are primary and secondary approaches that are conventional and some of them are tactical and innovative. Frequently, information that could promote effective results is stored in the diverse databases of the business applications your organization employs. Bain

Business Analytics Consulting- Emerging Startups in 2025

Emerging business analytics consulting startups like DataToBiz, Edvantis, Mitrix Technology, and others leverage advanced analytics and AI technologies to drive business growth and efficiency. These firms offer tailored solutions across diverse industries, with a global market forecast to surpass $303.4 billion by 2030. Globally, did you know that approximately 1.145 trillion megabytes of data are created daily? Thankfully, this is starting to happen because new analytics technologies make it possible to tap into virtually unlimited opportunities in these vast data stores. A necessary step to making more informed decisions and reacting to trends is analyzing data from available digital systems. Big data and data science are playing a major role in improving performance and expanding market incorporation, sales, and new processes as well as in solutions development for businesses. Market Research Future forecasts the global analytics market to exceed $303.4 billion by 2030, with a CAGR of 27.6%. This has boosted an industry in which business analytics consulting companies have been providing various types of Analytics and Business Intelligence (BI) solutions, and businesses are searching for professionals in the domain. In this blog, we will discuss the top 11 business analytics consulting startups in 2025 that will change the future. Top Business Analytics Consulting Startup Companies to Watch in 2025 Here’s the list of the top 11 business analytics consulting startups to look out for in 2025. DataToBiz DataToBiz, established in 2018, offers a comprehensive suite of services including AI/ML, digital transformation, business intelligence, and business analysis consulting. With a focus on managed analytics services and AI product development, we deliver intelligent solutions that facilitate rapid decision-making and ensure alignment with your unique business goals and product visions. Key Features of DataToBiz: Average Rating: 4.8 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Edvantis Edvantis is a leading business analytics consulting firm, boasting a team of over 400 skilled professionals based in Central & Eastern Europe and the USA. The company has garnered the trust of prominent companies like Indeed, BigCommerce, Kardex Remstar, Unicepta, TrustRadius, Modulsystem, and SAP Labs (a SAP subsidiary), thanks to its reliable service and outstanding product delivery. Key Features of Edvantis: Average Rating: 4.7 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Mitrix Technology Mitrix Technology is an established business analytics firm that has been collaborating with technology leaders for nearly a decade to help them rapidly scale their teams and address complex business challenges through expert consultations and efficient development practices. Key Features of Mitrix Technology: Average Rating: 5.0 Note: As researched and curated on rating platforms such as Clutch, Glassdoor InData Labs Established in 2014, InData Labs is a notable business analytics consulting company and provider of AI solutions focused on driving business growth through artificial intelligence. The company assists organizations of varying sizes in creating intelligent products, services, and operational workflows. Clients range from emerging startups to established enterprises, and they depend on InData Labs to tackle their intricate data-related issues. Key Features of InData Labs: Average Rating: 4.9 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Cymetrix Software Cymetrix Software is a forward-thinking IT solutions provider established in 2016. Its vision is to streamline business operations through cutting-edge technology. As an accredited Salesforce consulting partner and a prominent business analytics consultant, Cymetrix excels in crafting custom solutions to enhance business efficiency during growth phases. Key Features of Cymetrix Software: Average Rating: 4.9 Note: As researched and curated on rating platforms such as Clutch, Glassdoor PixelPlex PixelPlex is a reputable technology partner with more than 15 years of experience in custom software development. They are experts in ground-breaking digital solutions and architectures, with a special interest in blockchain technologies and business analytics consulting. With more than 100 professional creative cloud minds, the PixelPlex team can smoothly handle huge projects and bumpy challenges of any sort and size. Key Features of PixelPlex: Average Rating: 4.9 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Kellton Kellton is a global technology company and can provide cutting-edge technology solutions to clients. Kellton specializes in helping businesses achieve their full potential and succeed at any level by leveraging the power of new digital technologies in the face of new technologies. Key Features of Kellton: Average Rating: 4.7 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Vox Code Founded in 2015 in Belgrade, Serbia, Vox Code is a top IT services provider The firm provides topnotch yet affordable database programming, software development, business analytics consulting and various Salesforce services to clients worldwide. Using tailor-made business analytics software solutions Vox Code has taken business operations both in terms of profitability and efficiency to the next level for various industries and institutions. Key Features of Vox Code: Average Rating: 5.0 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Sedin Technologies Sedin Technologies is an established software development and consulting company delivering services to create custom business solutions of different complexity level for small and medium businesses. Based on a reputation for cutting-edge technologies and practices for Agile development, the company has grown to one of the best technology consulting firms on the globe. Key Features: Average Rating: 4.6 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Denologix Inc. Denologix specializes in Systems Integration and Visualization, offering robust IT Professional Services and Solutions that enable companies to make informed decisions. They assist customers in understanding their market, competitors, risks, operations, and customers through data analytics managed services, data integration, and data quality. Key Features of Denologix Inc.: Average Rating: 4.7 Note: As researched and curated on rating platforms such as Clutch, Glassdoor Sparkfish Sparkfish is a distinguished software development company based in the United States, known for its dedication and skilled team of professionals. Since its inception, DeSparkfish has specialized in crafting exceptional solutions tailored to meet clients’ diverse needs across multiple industries. Key Features of Sparkfish: Average Rating: 5.0 Note: As researched

7 Analytics as a Service Firms To Watch Out For In 2025

Data and analytics as a service play a vital role in today’s world. Businesses require managed analytics services to achieve their goals efficiently. Here, we will discuss the role of data analytics in a business and the top analytics as a service (AaaS) firms to partner with in 2025. Businesses in today’s world need to utilize their data to derive insights and make efficient decisions. Small, medium, and large businesses from different industries can benefit from investing in managed data analytics. However, not all of them want to build the analytical models from scratch or make major changes to the systems on the premises. Analytics as a Service(AaaS) or managed data analytics is the best solution for such organizations. They can quickly access the analytical tools and reports through cloud platforms and derive real-time insights. According to Statista, the analytics as a service (AaaS) market is estimated to be $69 billion by 2028. Another report says that the increasing adoption of AaaS solutions will take the market share to $85.1 billion by 2032 and cross $110 billion by 2034. AaaS is a kind of managed analytics service offered by third-party service providers. In this blog, we’ll read more about data analytics as a service and which firms offer these services to businesses from around the globe. What is Analytics as a Service? Analytics as a Service or managed analytics is a cloud solution where third-party providers offer data analytics services through cloud platforms. For example, suppose you want to analyze your business data. In that case, you can partner with an AaaS provider who will take care of the entire process from end to end and share the final reports (data visualizations) with your employees. This is done by personalizing the dashboards and connecting them to cloud analytics tools through various ready-made solutions like Power BI data connectors. Here, you pay only for the resources you consume for your business. There is no need to make heavy investments to buy the software or develop new processes in your enterprise. Data analytics managed services can be quickly set up by the service providers based on your requirements. What is Analytics in SaaS? Software as a Service (SaaS) has been helping many business enterprises unlock the full potential of their data to derive meaningful insights. Analytics in SaaS refers to analytics as a service. It includes several processes like data collection, data storage, data cleaning, data analytics, and data visualization. You can track various KPIs like inventory, production, customer behavior, sales, accounts, conversion rate, customer LTV (lifetime value), churn rate, etc. Analytics in SaaS can also be termed managed analytics. Simply put, you rely on a third party to provide the necessary insights and pay accordingly. 7 Top Analytics as a Service Firms To Partner with in 2025 1. DataToBiz DataToBiz is an end-to-end digital transformation and AI company offering tailored data & analytics managed services to SMBs, MSMEs, and large enterprises from various industries. The company provides analytics as a service through a tried and tested customer-centric approach. It helps businesses understand the gaps in their processes and find robust methods to strengthen the weak areas. Businesses could enhance customer satisfaction by 99% and make 3x timely decisions by partnering with DataToBiz to streamline their data and analytical models. The award-winning company offers a range of solutions like big data, data warehousing, data lake, data architecture, data engineering, data governance, AI and ML adoption, cloud computing, and long-term maintenance. The company is a certified partner of Microsoft Azure, Google Cloud, and AWS. 2. Infosys Infosys is a leading consulting company offering analytics managed services to various clients from around the world. It is a digital transformation service provider that helps businesses accelerate growth, build a connected ecosystem, and become efficient. The company brings flexibility and scalability to the organization by delivering data and insights in real time. It also offers self-servicing solutions and advanced analytics in industries like manufacturing, IT, healthcare, oil & gas, agriculture, retail, travel, and many more. Infosys customizes the solutions to suit the client’s requirements. It is an effective analytics as a service provider for large establishments. 3. Accenture Accenture is a global consulting company with numerous clients from the Fortune 500 list. It offers customized managed analytics services to help businesses revamp their outdated systems and benefit from data-driven models. The company promotes the adoption of artificial intelligence to give enterprises an edge over competitors. It offers varied data services to enhance speed, scale, and innovation. Accenture provides 360-degree value to businesses by helping them embrace change to adopt the latest technological solutions. The company’s data analytics services and cloud-based analytics as a service solutions are designed to support enterprises unlock the full data potential and make decisions using real-time insights. 4. Deloitte Deloitte is a group of firms offering varied services to business organizations from around the globe. It specializes in tax consulting, IT services, and analytical solutions. The company’s strategy and analytics services are aimed at helping businesses leverage proprietary solutions for greater agility. It combines the power of AI and managed analytics to provide automated insights through customized dashboards. Deloitte also offers DataOps services to facilitate seamless digital transformation. The company works towards making businesses sustainable by creating a long-term strategy and providing continuous support to implement it. The company has many clients from the Fortune 500 list and works with the world’s leading brands from various industries. Its analytics as a service model helps many businesses from different industries to unlock the potential of their data. 5. TCS Tata Consultancy Services is a global business process transformation company offering diverse services to small, medium, and large enterprises. The company boosts business performance with accelerated analytics managed services. It helps clients use analytical insights for product development, enhancing customer satisfaction, and achieving business goals. TCS follows a four-fold approach for data management, automation, scalability, and cloud management. It creates a robust data ecosystem for businesses to tap into the unexplored potential and gain

Why Should You Invest in Managed Data Analytics in 2024?

Data analytics managed services streamline and simplify business processes and help solve complex data challenges. We’ll discuss the importance of managed data analytics and reasons to invest in the data-driven decision-making model. We live in a complex world where businesses have to adapt to the changing conditions constantly. In such instances, you cannot afford to ignore the importance of data and business analytics. When huge amounts of data are generated daily, your business can benefit from the hidden patterns, trends, and insights it offers. This is done by investing in data analytics solutions. You can make proactive business decisions and stay ahead of your competitors by implementing the data-driven model. As per a report by Fortune Business Insights, the global big data analytics market is likely to touch $348.21 billion in 2024 and reach $924.39 billion by 2032 at a CAGR (compound annual growth rate) of 13%. This indicates the growing demand for managed data analytics services. Whether you own a small, medium-sized, or large enterprise, data analytics is a worthy investment choice to expand your establishment and become successful. In this blog, let’s find out more about the importance of managed analytics in 2024. What is a Managed Data Analytics Service? Managed analytics services are end-to-end data analytics solutions, starting from strategy formation to deployment, transformation of data to insights, and reporting through data visualizations. Without building an in-house team, you can rely on a third-party provider to handle the necessary aspects. This is different from the traditional approach, where your employees take care of everything. Instead of hiring more employees or sharing your internal resources, you hire a service provider to work on the project and share the reports with you in real-time. Managed analytical models are hosted on the cloud platforms. The dashboards are integrated with your systems so that your employees can access the insights and reports whenever necessary. It is a cost-effective and efficient way to adopt the data-driven model for decision-making. Reasons to Invest in Managed Data Analytics in 2024 Managed analytics services accelerate the adoption of data-driven models and allow businesses to use intelligence reports for daily decision-making. Service providers offer the necessary expertise, technology, tools, support, training, guidance, and documentation to ensure you can reduce costs while increasing overall business productivity and performance. Here are a few important reasons to opt for managed analytics in 2024: Access to Expertise The biggest reason to opt for managed data analytics is to gain direct access to industry expertise. Instead of spending your resources on recruiting a team of professionals, you can work with experts from outside to get the same or better results. Additionally, service providers have diverse teams with data analysts, data engineers, AI and ML engineers, data scientists, etc. This can vastly benefit your business. Efficient Data Management Managing internal and external data can be a challenge for many businesses. However, when you partner with managed service providers, you can easily overcome the problem. The company will streamline your data sources, set up the necessary connections, and build a central data repository on-premises or on the cloud. The managed service provider will directly deliver the insights to your dashboards. You don’t need to hire another partner for data management. Greater Data Security and Governance No business can ignore data security and governance in today’s world. The last thing you want is to end up with a lawsuit for breaching data protection laws. With analytics managed services, you can ensure that the service provider will help you comply with the relevant laws and regulations in your region. They also implement multiple security measures to keep your data safe and minimize the risk of cyberattacks. Make Informed Decisions Business decisions backed by data and analytical insights are much more likely to give the desired results than relying on guesswork. While your employees’ experience is valuable, relevant analytical reports can support and support it to make important decisions. Additionally, managed analytics are delivered to customized dashboards and are easily accessible by employees from different departments. This simplifies the process and results in quality decision-making. Optimize Resource Allocation Another advantage of partnering with a managed analytics provider is the chance to optimize the use of your business resources. When you have an in-house team, you should distribute your resources among all departments. This can increase the overheads and lead to budget constraints. However, with a managed service provider, you don’t have to dilute your resources. The third-party company will use its resources for the project. Greater Focus on Core Business When you outsource additional tasks to experts, your in-house teams can continue to focus on their jobs without distractions or excess workload. Your middle-level teams and C-level executives can work on the core business activities like strengthening the brand position and increasing revenue, while the service provider supplies the necessary and reliable insights for analysis and decision-making. Faster Time-to-Market We live in fast-paced worlds where the early bird gets the worm. Businesses cannot spend too much time completing the production cycle. However, you cannot compromise quality. So, the best way to achieve your goals is to hire a managed analytics partner to deliver the insights that can be directly implemented in the business to streamline and automate workflows. Reduce Risks With data analytics managed services, you can mitigate risks at various levels and strengthen your business processes. The external experts will assist your employees in correctly implementing the models and effectively using the data visualization dashboards for day-to-day work. You can take advantage of the latest technologies and tools without making major investments or worrying about ROI. Additionally, businesses can scale the systems without building everything from scratch. Enhanced Customer Experience Businesses need to keep their end goal in sight at all times. Managed analytics supports R&D, production, marketing, and customer service teams to work together and enrich customer experience with the enterprise. This will increase your brand image, generate greater revenue, and allow your business to expand into newer markets with ease. You can build a loyal customer base and continue to stay one step ahead of your competitors. What are the 4 Types of Analytics? Data and managed analytics are divided into four major types based on why and when it is used in businesses. Descriptive Analytics

Managed Data Analytics In USA- Top 10 Players In The Game

Managed data analytics involves analyzing large data sets to identify trends and get actionable insights. Finding the right managed data analytics company is a cumbersome process. Here’s help. We have shortlisted the best companies that offer good data analytics managed services to help you with your data processing and analyzing tasks. “Data analytics is the future, and the future is NOW!” Every mouse click, keyboard button press, swipe, or tap is used to shape business decisions. Everything is about data these days. Data is information, and information is power.” ~ Radi, data analyst at CENTOGENE As this quote aptly demonstrates, data is present everywhere. Organizations that know how to use it are riding the tide. Fortune Business Insights has revealed that the global data analytics managed services market reached a valuation of $51.55 billion in 2022 and will reach $279.31 billion in 2030. What is Managed Data Analytics? Managed analytics includes outsourcing data processing and analyzing tasks to a third-party service provider. These business analytics companies handle all aspects of data management – integration, automation, warehousing, advanced analytics, and interactive reporting. Here are a few benefits of managed analytics services: 10 Top Managed Analytics Companies in The Game Now here is a list of the best managed data analytics companies in the USA that can help you with data analytics services: DataToBiz DataToBiz is a leading company that offers reliable data analytics managed services. Partnering with DataToBiz gives you access to analytics experts who analyze your business data and offer insights to make informed decisions. The company offers real-time insights through advanced managed data analytics companies or integrates them into your on-premises operational systems. Along with this, you can get to continuous monitoring and quick issue resolution to ensure business continuity. Average Rating Review: 4.8 Guavus Guavus is a managed analytics company that uses AI and machine learning to assist telecommunication businesses in increasing their operating efficiency. It offers an analytics solution named Guavus-IQ that enables telecom operators to identify usage patterns and enhance network operations. With more than 15 years in the industry, the company has a team of telecom experts with experience in software engineering and data science. It mainly uses big data to streamline analytics by analyzing large amounts of data, minimizing costs, improving quality and customer experience. Average Rating Review: 3.2 Blackburn Labs Blackburn Labs is a renowned managed data analytics and business intelligence company that helps you convert your raw data into powerful assets. It has a team of managed analytics experts who create ETL processes and custom APIs to ensure smooth data flow. They use Supermetrics to connect data from multiple sources, follow HIPPA and GDPR, and implement Homomorphic Encrypted Data to ensure the privacy and security of customer data. Its technology stack includes Power BI, Amazon QuickSight, Tableau, Google Looker Studio, Python, R, AI and ML. Average Rating Review: 5.0 Sigma Data Systems A popular provider of data analytics managed services, Sigma Data Systems offers analytics services for businesses of all sizes. It uses predictive analytics and data visualization to process and analyze raw data to facilitate data-backed insights. Some of the main tools and technologies include: Average Rating Review: 4.8 Virtusa Virtusa offers consulting services for analytics related to managed services. It has a team of 100+ Hadoop consultants, data mining and predictive analytics experts. The services include: The technology stack includes: Apache Hadoop ecosystem, IBM Big Insights, Talend Big Data Platform, Cloudera, Cassandra, NoSQL Platform-Apache HBase, Mongo DB, neo4j, Tableau, Qlik, Spotfire, R, Python Splunk, H2O, IBM Watson. Average Rating Review: 3.7 Affirma Affirma is a managed data analytics consultancy that helps businesses with strategic analytics techniques and data visualization. The company offers analytics services to overcome the problems such as data siloes and manual reporting analytics, ensuring data integrity. Affirma’s data engineering team collects and consolidates data from sources such as ERPs and CRMs. AWS, Google Cloud Platform, Azure, and Snowflake are deployed for data warehousing needs. Average Rating Review: 4.7 Oxagile Oxagile helps you with all kinds of big data development services to move your data to the cloud and build scalable ETL/ELT data pipelines. The company provides data analysis and visualization services through custom reporting dashboards, advanced ML analytics, BI tools and systems. Oxagile’s team of experts implements different types of data management techniques to retrieve and store data. They implement a set of standards to configure data pipeline monitoring and use data lineage to predict data flow across different systems. Average Rating Review: 4.4 Addepto Addepto uses modern tools and technologies to deliver reliable data analytics managed services. The experts build statistical models with the help of data to validate and quantify specific business problems. Further, they create custom reports to create relevant and useful information. Here’s an overview of the technology stack: TensorFlow: Helps to build and train machine learning models. PyTorch: Used to prototype and deploy machine learning models using Python. R: Includes data visualization tools to create charts, graphs, and custom reports. Average Rating Review: 4.7 Sparkfish Sparkfish is a managed data analytics company that helps you with a consolidated view of your organization’s data from different sources. The experts gather data from disparate sources such as CRMs, ERPs, advertising platforms, third-party sales data, and websites. They use comprehensive data management strategies to ensure accuracy and integrity of data making a single source of truth across the organization. Some of the top services include breaking down data siloes, accessing and analyzing data in real-time, and reporting. Average Rating Review: 5.0 Teradata Teradata is a managed data analytics company that helps businesses become data-driven. The company has a flagship product ‘Teradata Database’ which is a scalable database to manage in-house data analytics, queries, and analytics workloads. Teradata serves customers across different industries including retail, finance, healthcare, and manufacturing. Its team of trained professionals helps you throughout the data analytics operations with advanced analytics solutions to convert data into meaningful information that can be put to use. Average Rating Review: 3.8 Empeek Empeek is a healthcare managed

Importance of Manufacturing Analytics in Industry 4.0

Data analytics in manufacturing, called manufacturing analytics, is highly useful for enterprises to use their data in making proactive decisions, eliminating unwanted processes, identifying bottlenecks and overcoming them, increasing production quality, improving employee performance, and amplifying revenue. According to the Business Research Company, the global manufacturing analytics market is likely to be $14.26 billion in 2024 and is expected to reach $32.39 billion by 2028 at a CAGR (compound annual growth rate) of 22.8%. Additionally, Emergen Research shows that the global Industry 4.0 market value will touch $279.75 billion by 2028 with a CAGR of 16.3%. It’s clear that manufacturing analytics is a huge part of Industry 4.0 and will continue to play a vital role in helping enterprises adopt the data-driven model to make faster, better, and more effective decisions in real time. Let’s find out how manufacturing analytics solutions can help an enterprise achieve its objectives by streamlining various aspects of the business. What is Manufacturing Analytics? Manufacturing analytics is the use of data analytical and business intelligence tools to collect, store, clean, process, and analyze large amounts of data to derive actionable insights and share data visualization reports throughout the enterprise. Manufacturing analytics solutions can help implement smart manufacturing methodologies through the adoption of digital tools and technologies. Data is collected from internal and external sources and stored in a central repository like a data warehouse or a data lake. This data can be accessed by employees from different departments to make timely decisions. Data is also collected from factories and machinery using IoT (Internet of Things) devices. The insights provided by manufacturing analytics are useful for improving operational efficiency, preventing machine breakdowns, making the factory safer for workers, automating production, and making the business model more agile and customer-centric. Manufacturing analytics companies offer end-to-end services to assist enterprises in strategizing, building, implementing, customizing, and maintaining digital data-driven models and technologies. Why is Industry 4.0 Important in Manufacturing? Industry 4.0 aka, the Fourth Industrial Revolution, deals with the digital transformation of the manufacturing industry and the adoption of advanced technologies like AI, ML, big data, etc., in MSMEs and large enterprises around the world. It aims to make manufacturing units agile, flexible, and scalable to handle the changing customer demands without increasing expenses. It is a continuous and long-term process where the entire business infrastructure, procedures, systems, tools, etc., are digitalized to create seamless connectivity across the enterprise. Data Democratization The manufacturing industry was no different from other sectors and followed the same traditional methods of storing data in individual silos in various departments and levels. This leads to data duplication and prevents the enterprise from fully utilizing the potential of its datasets. Industry 4.0 provides a comprehensive solution for data democratization by collecting it from different silos and building a central repository that can be accessed by anyone in the enterprise. It also allows decision-makers to take advantage of advanced manufacturing analytics and derive real-time insights. Reduce Cost Increasing expenditure is always a concern in the manufacturing sector, no matter what products they produce. Industry 4.0 promotes greater transparency across the supply chain to help manufacturers decrease downtime, increase throughput, improve the OEE score, and find suppliers who offer quality products at cost-effective prices. Optimize Resources Wouldn’t it be helpful when an enterprise can save its resources without compromising quality or productivity? Industry 4.0 helps to achieve this by highlighting areas with excess or unwanted resource consumption. Manufacturing analytics provides detailed reports and offers effective solutions to overcome the challenges. When a manufacturing unit can reduce resource consumption and improve overall performance, it can become sustainable in the long run. Better Customer Experience Customers are the key to any business. Manufacturers need to consider customer requirements at every stage, be it procurement, production, or logistics. Providing a better experience to customers will increase retention and acquisition rates. The enterprise can use Industry 4.0 practices to understand what the target audience wants and adjust their processes and products accordingly. What are the Industry 4.0 Manufacturing Processes? Several technologies are a part of the fourth industrial revolution apart from data analytics in the manufacturing industry. Artificial Intelligence AI has a diverse role in manufacturing. It facilitates automation, analytics, decision-making, transparency, and resilience for a sustainable future. AI and ML models are used to streamline production, supply chain, marketing, transportation, equipment maintenance, customer experience, and much more. Industrial Internet of Things (IIoT) IoT devices are connected to the factory equipment or provided to workers as wearables to collect data in real time and share it with other applications in the network. IIoT devices are attached to robots, machinery, products, vehicles, etc., to help managers stay on track at all times by anticipating and avoiding delays. Cloud Computing Analytics in manufacturing or any other Industry 4.0 process is effective when it is used on the cloud platform. Enterprises digitally transform their systems to move the IT infrastructure to the cloud (private, public, or hybrid) so that decision-makers can access the data and insights at any time and from any location. It is the first step to adopting Industry 4.0 technologies in an enterprise. Big Data Analytics Big data analytics uses data from multiple sources to discover hidden patterns, trends, and correlations. It provides measurable and actionable insights in real-time for manufacturers to stay one step ahead of competitors and make proactive decisions to grab market opportunities. AI and ML tools are used for advanced analytics such as predictive analytics, production analytics, sales analytics, etc. Autonomous Robots Autonomous robots are AI-based devices that can perform a set of tasks repeatedly with minimal human intervention. This frees up time and resources for employees to focus on the core aspects of the job. It also increases workplace safety as robots can be used to complete risky jobs on the factory floor. Additive Manufacturing Though addictive manufacturing started as a prototyping tool, it can now be used for mass customization, distributed manufacturing, 3D printing, etc., to reduce production costs, save time, and offer a wider range of products to customers. Horizontal and Vertical Integration While horizontal integration refers to the connections between different processes at the field level, vertical integration deals with bringing together the various layers of the enterprise. This allows the manufacturer to consider the establishment, as a single unit with interconnected processes. It also allows employees to easily access data from other departments to