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Task

User Engagement on Blog and Demo Scheduling

As a potential Dime customer, I explore industry insights and schedule a product demo, so that I can understand the benefits of Dime's solutions and evaluate how they can address my business needs.

Success definition: Given I am a visitor on the Dime website When I navigate to the blog section and read an article about data operations in asset-intensive industries, then click on the Book a demo link Then I should see the demo scheduling options presented, allowing me to book a demonstration of Dime's capabilities.

Trajectory

Step 1:

Url (before/after):

https://www.getdime.io/

https://www.getdime.io/blog

Content (before/after):

RootWebArea DIME | Manufacturing Analytics Platform, focused, url='https://www.getdime.io/'
    banner
        [37] link home, center=(320,56), url='https://www.getdime.io/'
            image
        navigation
Show more
            [43] link Blog New, center=(1310,56), inner_text=Blog
New, url='https://www.getdime.io/blog'
            [48] link Book a demo, center=(1469,56), url='https://www.getdime.io/#'
                image
            [55] link Login, center=(1619,56), url='https://app.dimemanufacturing.com/'
    main
        heading Predict Failures ‍[ Prevent Downtime]
        StaticText Dime AI predicts hardware failures before they happen
        [74] link Talk to a founder, center=(343,671), url='https://www.getdime.io/#'
            image
        image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/674deae12f789eeee70674bf_hero%20image.avif'
        StaticText [Problem]
        heading Data from industrial assets is significantly underused
        image
        image
        StaticText Features
        heading Use Cases
        image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/674e8574d02efb239daa6156_illustration-2.avif'
        image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/674e8574a0d1e88e78649c73_illustration-1.avif'
        image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/674e85746f7ad240fd664972_illustration.avif'
        StaticText 1
        image
        StaticText Comprehensive Data Search
        StaticText Dime is the single source of truth for industrial data—find what you need instantly, not in hours
        StaticText 2
        image
        StaticText Predictive Analytics
        StaticText Dime's  predictive analytics pinpoint hardware failures before they happen, keeping your machines running smoothly
        StaticText 3
        image
        StaticText Visualization
        StaticText Generate dashboards, reports and complex graphs without complex queries or data infra
        image
        heading How it Works
        image
        StaticText 01
        StaticText Dime assess your data infrastructure during a quick discovery call
        image
        StaticText 02
        StaticText Dime sets up real-time data streams and pipelines for ingestion
        image
        StaticText 03
        StaticText Get instant predictions and alerts to prevent hardware failures
        StaticText Made in Detroit
        heading From Data Overload to Operational Clarity
        link Book a demo, url='https://www.getdime.io/#'
        image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/67526aa1ab3aee556672f724_wave%20bg.avif'
    contentinfo
        link, url='https://www.getdime.io/'
            image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/671161c38a44fc343c0247de_path17.avif'
        StaticText Join our newsletter to stay up to date on features and releases.
        StaticText Follow us
        link, url='https://www.getdime.io/#'
            image
        link, url='https://www.linkedin.com/company/dime-manufacturing/'
            image
        form Email Form
            textbox Enter your email, required
            button Subscribe
        StaticText By subscribing you agree to with our
        link Privacy Policy, url='https://www.getdime.io/#'
        StaticText and provide consent to receive updates from our company.
        StaticText © 2024 Dime Procurement, Inc. All rights reserved.
        link Privacy Policy, url='https://www.getdime.io/#'
        link Terms of Service, url='https://www.getdime.io/#'
        link Cookie Settings, url='https://www.getdime.io/#'
RootWebArea Blog, focused, url='https://www.getdime.io/blog'
    banner
        [24] link home, center=(320,56), url='https://www.getdime.io/'
            image
        navigation
Show more
            [30] link Blog New, center=(1310,56), inner_text=Blog
New, url='https://www.getdime.io/blog'
            [35] link Book a demo, center=(1469,56), url='https://www.getdime.io/blog#'
                image
            [42] link Login, center=(1619,56), url='https://app.dimemanufacturing.com/'
    main
        heading The [ Journal ]
        StaticText Follow along as we share the latest in Digital Transformation, IIOT and AI in Manufacturing
        image
        list
            listitem
                [77] link an AI image about data and human, center=(472,731), url='https://www.getdime.io/blog/dime-blog/data-ops'
                    image an AI image about data and human, url='https://cdn.prod.website-files.com/673ea7367ab2e9ccc39a6a54/673f5ca3e90e42f5d3b53ccc_AdobeStock_985355495-p-500.jpg'
                StaticText Digital Transformation
                StaticText Read time:
                StaticText 5
                StaticText mintues
                StaticText The State of Data Operations in Asset-Intensive Industries
                StaticText Data utility varies widely across asset-intensive industries. The Dime team shares insights from their research on the current state of data operations and the opportunities ahead.
                link Read Now, url='https://www.getdime.io/blog/dime-blog/data-ops'
                    image
        link, url='https://www.getdime.io/'
            image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/671161c38a44fc343c0247de_path17.avif'
        StaticText Join our newsletter to stay up to date on features and releases.
        StaticText Follow us
        link, url='https://www.getdime.io/blog#'
            image
        link, url='https://www.linkedin.com/company/dime-manufacturing/'
            image
        form Email Form
            textbox Enter your email, required
            button Subscribe
        StaticText By subscribing you agree to with our
        link Privacy Policy, url='https://www.getdime.io/blog#'
        StaticText and provide consent to receive updates from our company.
        StaticText © 2024 Dime Procurement, Inc. All rights reserved.
        link Privacy Policy, url='https://www.getdime.io/blog#'
        link Terms of Service, url='https://www.getdime.io/blog#'
        link Cookie Settings, url='https://www.getdime.io/blog#'

Reasoning for action: I clicked on the Blog link as my first step because the user's instruction requires me to explore industry insights. By accessing the blog section, I will be able to find relevant articles that provide insights necessary for understanding Dime's solutions, eventually leading me to schedule a demo.

Action: click(43) # Click on the Blog link to explore the content.

Change Description: After clicking the Blog link, the browser navigated to the Blog page at 'https://www.getdime.io/blog', changing the title from 'DIME | Manufacturing Analytics Platform' to 'Blog' and updating the main content to display blog articles, including a new heading and static text describing the journal's purpose.

Screenshot before:Screenshot after:---

Step 2:

Url (before/after):

https://www.getdime.io/blog

https://www.getdime.io/blog/dime-blog/data-ops

Content (before/after):

RootWebArea Blog, focused, url='https://www.getdime.io/blog'
    banner
        [24] link home, center=(320,56), url='https://www.getdime.io/'
            image
        navigation
Show more
            [30] link Blog New, center=(1310,56), inner_text=Blog
New, url='https://www.getdime.io/blog'
            [35] link Book a demo, center=(1469,56), url='https://www.getdime.io/blog#'
                image
            [42] link Login, center=(1619,56), url='https://app.dimemanufacturing.com/'
    main
        heading The [ Journal ]
        StaticText Follow along as we share the latest in Digital Transformation, IIOT and AI in Manufacturing
        image
        list
            listitem
                [77] link an AI image about data and human, center=(472,731), url='https://www.getdime.io/blog/dime-blog/data-ops'
                    image an AI image about data and human, url='https://cdn.prod.website-files.com/673ea7367ab2e9ccc39a6a54/673f5ca3e90e42f5d3b53ccc_AdobeStock_985355495-p-500.jpg'
                StaticText Digital Transformation
                StaticText Read time:
                StaticText 5
                StaticText mintues
                StaticText The State of Data Operations in Asset-Intensive Industries
                StaticText Data utility varies widely across asset-intensive industries. The Dime team shares insights from their research on the current state of data operations and the opportunities ahead.
                link Read Now, url='https://www.getdime.io/blog/dime-blog/data-ops'
                    image
        link, url='https://www.getdime.io/'
            image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/671161c38a44fc343c0247de_path17.avif'
        StaticText Join our newsletter to stay up to date on features and releases.
        StaticText Follow us
        link, url='https://www.getdime.io/blog#'
            image
        link, url='https://www.linkedin.com/company/dime-manufacturing/'
            image
        form Email Form
            textbox Enter your email, required
            button Subscribe
        StaticText By subscribing you agree to with our
        link Privacy Policy, url='https://www.getdime.io/blog#'
        StaticText and provide consent to receive updates from our company.
        StaticText © 2024 Dime Procurement, Inc. All rights reserved.
        link Privacy Policy, url='https://www.getdime.io/blog#'
        link Terms of Service, url='https://www.getdime.io/blog#'
        link Cookie Settings, url='https://www.getdime.io/blog#'
RootWebArea Dime, focused, url='https://www.getdime.io/blog/dime-blog/data-ops'
    banner
        [18] link home, center=(320,56), url='https://www.getdime.io/'
            image
        navigation
Show more
            [24] link Blog New, center=(1310,56), inner_text=Blog
New, url='https://www.getdime.io/blog'
            [29] link Book a demo, center=(1469,56), url='https://www.getdime.io/blog/dime-blog/data-ops#'
                image
            [36] link Login, center=(1619,56), url='https://app.dimemanufacturing.com/'
    main
        heading The State of Data Operations in Asset-Intensive Industries
        StaticText Digital Transformation
        StaticText Read time:
        StaticText 5
        StaticText mintues
        image, url='https://cdn.prod.website-files.com/673ea7367ab2e9ccc39a6a54/673f5ca3e90e42f5d3b53ccc_AdobeStock_985355495-p-500.jpg'
        paragraph
            StaticText Thirteen years ago, at a fair in Hanover, Germany, the term “Industry 4.0” entered the industrial lexicon. The timing was fitting. The HTC Evo had just launched as the first 4G phone and 30% of Americans had adopted smartphones. Digital transformation was the buzzword of the day and the vision of smart factories with autonomous, data-driven machines seemed to be only years away.
        paragraph
            StaticText Fast forward to today, and that vision is slowly becoming reality. Across the industry, companies are taking steps to digitize operations and unlock the potential of their data. But the path to Industry 4.0 is a spectrum - some factories deploy cutting-edge ML and others still rely on clipboards to track production.
        paragraph
            StaticText Over the past few months, the Dime team has spoken to dozens of manufacturing and data engineers, and here’s what we’ve learned about where the industry stands today.
        heading The Current Landscape of Data Operations
            strong
        paragraph
            StaticText The reality for many manufacturers is shaped by legacy equipment. Machines purchased decades ago often lack the sensors or connectivity to generate meaningful data, let alone feed it into modern systems. American manufacturing’s slowdown since the 1970s left many plants with infrastructure built for a different era. Yet, despite these challenges, some industries—particularly those with continuous operations like oil & gas, chemicals, and food & beverage—are much further along in their digital journeys. These companies have the most to gain from incremental improvements, where even a 1% increase in efficiency can mean millions in savings.
        paragraph
            StaticText In contrast, discrete manufacturers, like medical device companies with human-driven assembly stations, are often able to spot issues through observation and experience. For them, the urgency to invest in data operations isn’t as strong. As a result, the maturity of data operations varies widely across industries and even within companies.
        heading Stages of Digital Transformation
            strong
        paragraph
            StaticText Manufacturers tend to fall into one of four stages on their data operations journey:
        list
            listitem
                ListMarker 0.
                strong
                    StaticText Production Tracking with Basic Data Extraction
                StaticText For most manufacturers, the first step is understanding what’s happening on the factory floor. In the past, whiteboards and clipboards were the go-to tools, but they’re impractical for real-time insights in a 100K+ square foot facility. Modern machine monitoring tools now fill this gap, enabling plant managers to track production remotely. Even older machines can be retrofitted with voltage sensors to estimate cycle counts. It’s not perfect, but it’s a start.
            listitem
                ListMarker 0.
                strong
                    StaticText Flexible Visualizations
                StaticText Companies with connected assets are finding new ways to visualize their operations. Tools like PowerBI have become invaluable, allowing manufacturing teams to create dashboards that transform raw data into actionable insights. By leveraging historians, manufacturers can track performance and identify bottlenecks. However, these tools often require the expertise of BI analysts to unlock their full potential.
            listitem
                ListMarker 0.
                strong
                    StaticText Retroactive Analysis with Data Engineers
                StaticText The most advanced manufacturers take things further, employing teams of data engineers to analyze historical data and identify opportunities for improvement. Moving data from on-prem historians to the cloud opens up new possibilities for analysis and optimization. For companies running 24/7 operations, even small improvements in yield or uptime can have a massive impact on the bottom line.
            listitem
                ListMarker 0.
                strong
                    StaticText Automated Real-Time Optimization
                    StaticText ‍
                StaticText At the top of the pyramid are companies that have mastered their infrastructure and are deploying machine learning models in real time either natively in their control systems or utilizing technology like OPC UA. These teams can extract actionable insights in real-time, enabling immediate adjustments through closed feedback loops integrated directly into control systems. While this level of sophistication remains rare, it sets the standard for what’s possible and offer a glimpse into the future for manufacturers with the resources to invest.
        heading The Problem with the Status Quo
            strong
        paragraph
            StaticText Despite the progress, most manufacturers are locked out of advanced data operations. The cost of integration for top-end platforms can run into the millions, and hiring the specialized talent to make sense of the data adds an ongoing operating expense. This creates a gulf between the largest players, who have the resources to innovate, and everyone else, who are left behind.
        heading Can GenAI Actually Help?
            strong
        paragraph
            StaticText This is where GenAI has the potential to change everything. By automating complex data transformations, it can drastically reduce the time and cost of integrating advanced tools. More importantly, it can democratize access to insights. With innovations like text-to-SQL and context-based query generation, manufacturing and process engineers can interact with their data directly—no data science team required.
        paragraph
            StaticText At Dime, we’re building tools to make this vision a reality. Our platform bridges the gap, enabling manufacturers of all sizes to extract value from their data without breaking the bank.
        paragraph
            StaticText The dream of Industry 4.0 was never just about technology. It’s about creating a future where every manufacturer—big or small—can run smarter, leaner, and more connected operations.
        paragraph
            StaticText Ready to unlock the potential of your data?
            link Schedule a demo, url='https://calendly.com/ashish-dime/30min'
            StaticText and let’s explore how Dime can empower your operations.
        StaticText Share to
        [95] link, center=(1378,247), url='https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fwww.getdime.io%2Fblog%2Fdime-blog%2Fdata-ops'
            image
        [98] link, center=(1438,247), url='https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.getdime.io%2Fblog%2Fdime-blog%2Fdata-ops'
            image
        [101] link, center=(1498,247), url='https://twitter.com/intent/post/?url=https%3A%2F%2Fwww.getdime.io%2Fblog%2Fdime-blog%2Fdata-ops&text=Dime'
            image
        [104] link, center=(1558,247), url='https://www.getdime.io/blog/dime-blog/data-ops#'
            image
        image, url='https://cdn.prod.website-files.com/673ea7367ab2e9ccc39a6a54/673f57a50bb3d327ae379ffd_Bajaj_Ashish_161-Pilot-0237-2658-Edit_Bookface-p-500.jpg'
        StaticText Ashish Bajaj
        StaticText November 25, 2024
    contentinfo
        link, url='https://www.getdime.io/'
            image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/671161c38a44fc343c0247de_path17.avif'
        StaticText Join our newsletter to stay up to date on features and releases.
        StaticText Follow us
        link, url='https://www.getdime.io/blog/dime-blog/data-ops#'
            image
        link, url='https://www.linkedin.com/company/dime-manufacturing/'
            image
        form Email Form
            textbox Enter your email, required
            button Subscribe
        StaticText By subscribing you agree to with our
        link Privacy Policy, url='https://www.getdime.io/blog/dime-blog/data-ops#'
        StaticText and provide consent to receive updates from our company.
        StaticText © 2024 Dime Procurement, Inc. All rights reserved.
        link Privacy Policy, url='https://www.getdime.io/blog/dime-blog/data-ops#'
        link Terms of Service, url='https://www.getdime.io/blog/dime-blog/data-ops#'
        link Cookie Settings, url='https://www.getdime.io/blog/dime-blog/data-ops#'

Reasoning for action: I clicked on the 'Read Now' link (77) because doing so allows me to access the specific article about data operations in asset-intensive industries. Reading this article is critical for understanding the insights provided by Dime which will help evaluate how Dime's solutions can address the user's business needs. This step directly supports the user story by ensuring I gather relevant information before attempting to book a demo.

Action: click(77) # Click on the 'Read Now' link for the featured article to explore its content.

Change Description: After clicking the 'Read Now' link, the browser state changed to display the full content of the article titled 'The State of Data Operations in Asset-Intensive Industries,' with an updated URL reflecting the specific page for this article, and alterations to the main content area to include several paragraphs discussing digital transformation in manufacturing, along with relevant headings and images.

Screenshot before:Screenshot after:---

Step 3:

Url (before/after):

https://www.getdime.io/blog/dime-blog/data-ops

https://www.getdime.io/blog/dime-blog/data-ops

Content (before/after):

RootWebArea Dime, focused, url='https://www.getdime.io/blog/dime-blog/data-ops'
    banner
        [18] link home, center=(320,56), url='https://www.getdime.io/'
            image
        navigation
Show more
            [24] link Blog New, center=(1310,56), inner_text=Blog
New, url='https://www.getdime.io/blog'
            [29] link Book a demo, center=(1469,56), url='https://www.getdime.io/blog/dime-blog/data-ops#'
                image
            [36] link Login, center=(1619,56), url='https://app.dimemanufacturing.com/'
    main
        heading The State of Data Operations in Asset-Intensive Industries
        StaticText Digital Transformation
        StaticText Read time:
        StaticText 5
        StaticText mintues
        image, url='https://cdn.prod.website-files.com/673ea7367ab2e9ccc39a6a54/673f5ca3e90e42f5d3b53ccc_AdobeStock_985355495-p-500.jpg'
        paragraph
            StaticText Thirteen years ago, at a fair in Hanover, Germany, the term “Industry 4.0” entered the industrial lexicon. The timing was fitting. The HTC Evo had just launched as the first 4G phone and 30% of Americans had adopted smartphones. Digital transformation was the buzzword of the day and the vision of smart factories with autonomous, data-driven machines seemed to be only years away.
        paragraph
            StaticText Fast forward to today, and that vision is slowly becoming reality. Across the industry, companies are taking steps to digitize operations and unlock the potential of their data. But the path to Industry 4.0 is a spectrum - some factories deploy cutting-edge ML and others still rely on clipboards to track production.
        paragraph
            StaticText Over the past few months, the Dime team has spoken to dozens of manufacturing and data engineers, and here’s what we’ve learned about where the industry stands today.
        heading The Current Landscape of Data Operations
            strong
        paragraph
            StaticText The reality for many manufacturers is shaped by legacy equipment. Machines purchased decades ago often lack the sensors or connectivity to generate meaningful data, let alone feed it into modern systems. American manufacturing’s slowdown since the 1970s left many plants with infrastructure built for a different era. Yet, despite these challenges, some industries—particularly those with continuous operations like oil & gas, chemicals, and food & beverage—are much further along in their digital journeys. These companies have the most to gain from incremental improvements, where even a 1% increase in efficiency can mean millions in savings.
        paragraph
            StaticText In contrast, discrete manufacturers, like medical device companies with human-driven assembly stations, are often able to spot issues through observation and experience. For them, the urgency to invest in data operations isn’t as strong. As a result, the maturity of data operations varies widely across industries and even within companies.
        heading Stages of Digital Transformation
            strong
        paragraph
            StaticText Manufacturers tend to fall into one of four stages on their data operations journey:
        list
            listitem
                ListMarker 0.
                strong
                    StaticText Production Tracking with Basic Data Extraction
                StaticText For most manufacturers, the first step is understanding what’s happening on the factory floor. In the past, whiteboards and clipboards were the go-to tools, but they’re impractical for real-time insights in a 100K+ square foot facility. Modern machine monitoring tools now fill this gap, enabling plant managers to track production remotely. Even older machines can be retrofitted with voltage sensors to estimate cycle counts. It’s not perfect, but it’s a start.
            listitem
                ListMarker 0.
                strong
                    StaticText Flexible Visualizations
                StaticText Companies with connected assets are finding new ways to visualize their operations. Tools like PowerBI have become invaluable, allowing manufacturing teams to create dashboards that transform raw data into actionable insights. By leveraging historians, manufacturers can track performance and identify bottlenecks. However, these tools often require the expertise of BI analysts to unlock their full potential.
            listitem
                ListMarker 0.
                strong
                    StaticText Retroactive Analysis with Data Engineers
                StaticText The most advanced manufacturers take things further, employing teams of data engineers to analyze historical data and identify opportunities for improvement. Moving data from on-prem historians to the cloud opens up new possibilities for analysis and optimization. For companies running 24/7 operations, even small improvements in yield or uptime can have a massive impact on the bottom line.
            listitem
                ListMarker 0.
                strong
                    StaticText Automated Real-Time Optimization
                    StaticText ‍
                StaticText At the top of the pyramid are companies that have mastered their infrastructure and are deploying machine learning models in real time either natively in their control systems or utilizing technology like OPC UA. These teams can extract actionable insights in real-time, enabling immediate adjustments through closed feedback loops integrated directly into control systems. While this level of sophistication remains rare, it sets the standard for what’s possible and offer a glimpse into the future for manufacturers with the resources to invest.
        heading The Problem with the Status Quo
            strong
        paragraph
            StaticText Despite the progress, most manufacturers are locked out of advanced data operations. The cost of integration for top-end platforms can run into the millions, and hiring the specialized talent to make sense of the data adds an ongoing operating expense. This creates a gulf between the largest players, who have the resources to innovate, and everyone else, who are left behind.
        heading Can GenAI Actually Help?
            strong
        paragraph
            StaticText This is where GenAI has the potential to change everything. By automating complex data transformations, it can drastically reduce the time and cost of integrating advanced tools. More importantly, it can democratize access to insights. With innovations like text-to-SQL and context-based query generation, manufacturing and process engineers can interact with their data directly—no data science team required.
        paragraph
            StaticText At Dime, we’re building tools to make this vision a reality. Our platform bridges the gap, enabling manufacturers of all sizes to extract value from their data without breaking the bank.
        paragraph
            StaticText The dream of Industry 4.0 was never just about technology. It’s about creating a future where every manufacturer—big or small—can run smarter, leaner, and more connected operations.
        paragraph
            StaticText Ready to unlock the potential of your data?
            link Schedule a demo, url='https://calendly.com/ashish-dime/30min'
            StaticText and let’s explore how Dime can empower your operations.
        StaticText Share to
        [95] link, center=(1378,247), url='https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fwww.getdime.io%2Fblog%2Fdime-blog%2Fdata-ops'
            image
        [98] link, center=(1438,247), url='https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.getdime.io%2Fblog%2Fdime-blog%2Fdata-ops'
            image
        [101] link, center=(1498,247), url='https://twitter.com/intent/post/?url=https%3A%2F%2Fwww.getdime.io%2Fblog%2Fdime-blog%2Fdata-ops&text=Dime'
            image
        [104] link, center=(1558,247), url='https://www.getdime.io/blog/dime-blog/data-ops#'
            image
        image, url='https://cdn.prod.website-files.com/673ea7367ab2e9ccc39a6a54/673f57a50bb3d327ae379ffd_Bajaj_Ashish_161-Pilot-0237-2658-Edit_Bookface-p-500.jpg'
        StaticText Ashish Bajaj
        StaticText November 25, 2024
    contentinfo
        link, url='https://www.getdime.io/'
            image, url='https://cdn.prod.website-files.com/671158186360e33acd80ae09/671161c38a44fc343c0247de_path17.avif'
        StaticText Join our newsletter to stay up to date on features and releases.
        StaticText Follow us
        link, url='https://www.getdime.io/blog/dime-blog/data-ops#'
            image
        link, url='https://www.linkedin.com/company/dime-manufacturing/'
            image
        form Email Form
            textbox Enter your email, required
            button Subscribe
        StaticText By subscribing you agree to with our
        link Privacy Policy, url='https://www.getdime.io/blog/dime-blog/data-ops#'
        StaticText and provide consent to receive updates from our company.
        StaticText © 2024 Dime Procurement, Inc. All rights reserved.
        link Privacy Policy, url='https://www.getdime.io/blog/dime-blog/data-ops#'
        link Terms of Service, url='https://www.getdime.io/blog/dime-blog/data-ops#'
        link Cookie Settings, url='https://www.getdime.io/blog/dime-blog/data-ops#'
RootWebArea Dime, focused, url='https://www.getdime.io/blog/dime-blog/data-ops'
    banner
        [18] link home, center=(320,56), url='https://www.getdime.io/'
            image
        navigation
Show more
            [24] link Blog New, center=(1310,56), inner_text=Blog
New, url='https://www.getdime.io/blog'
            [29] link Book a demo, center=(1469,56), focused, url='https://www.getdime.io/blog/dime-blog/data-ops#'
                image
            [36] link Login, center=(1619,56), url='https://app.dimemanufacturing.com/'
    main
        heading The State of Data Operations in Asset-Intensive Industries
        StaticText Digital Transformation
        StaticText Read time:
        StaticText 5
        StaticText mintues
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        paragraph
            StaticText Thirteen years ago, at a fair in Hanover, Germany, the term “Industry 4.0” entered the industrial lexicon. The timing was fitting. The HTC Evo had just launched as the first 4G phone and 30% of Americans had adopted smartphones. Digital transformation was the buzzword of the day and the vision of smart factories with autonomous, data-driven machines seemed to be only years away.
        paragraph
            StaticText Fast forward to today, and that vision is slowly becoming reality. Across the industry, companies are taking steps to digitize operations and unlock the potential of their data. But the path to Industry 4.0 is a spectrum - some factories deploy cutting-edge ML and others still rely on clipboards to track production.
        paragraph
            StaticText Over the past few months, the Dime team has spoken to dozens of manufacturing and data engineers, and here’s what we’ve learned about where the industry stands today.
        heading The Current Landscape of Data Operations
            strong
        paragraph
            StaticText The reality for many manufacturers is shaped by legacy equipment. Machines purchased decades ago often lack the sensors or connectivity to generate meaningful data, let alone feed it into modern systems. American manufacturing’s slowdown since the 1970s left many plants with infrastructure built for a different era. Yet, despite these challenges, some industries—particularly those with continuous operations like oil & gas, chemicals, and food & beverage—are much further along in their digital journeys. These companies have the most to gain from incremental improvements, where even a 1% increase in efficiency can mean millions in savings.
        paragraph
            StaticText In contrast, discrete manufacturers, like medical device companies with human-driven assembly stations, are often able to spot issues through observation and experience. For them, the urgency to invest in data operations isn’t as strong. As a result, the maturity of data operations varies widely across industries and even within companies.
        heading Stages of Digital Transformation
            strong
        paragraph
            StaticText Manufacturers tend to fall into one of four stages on their data operations journey:
        list
            listitem
                ListMarker 0.
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                    StaticText Production Tracking with Basic Data Extraction
                StaticText For most manufacturers, the first step is understanding what’s happening on the factory floor. In the past, whiteboards and clipboards were the go-to tools, but they’re impractical for real-time insights in a 100K+ square foot facility. Modern machine monitoring tools now fill this gap, enabling plant managers to track production remotely. Even older machines can be retrofitted with voltage sensors to estimate cycle counts. It’s not perfect, but it’s a start.
            listitem
                ListMarker 0.
                strong
                    StaticText Flexible Visualizations
                StaticText Companies with connected assets are finding new ways to visualize their operations. Tools like PowerBI have become invaluable, allowing manufacturing teams to create dashboards that transform raw data into actionable insights. By leveraging historians, manufacturers can track performance and identify bottlenecks. However, these tools often require the expertise of BI analysts to unlock their full potential.
            listitem
                ListMarker 0.
                strong
                    StaticText Retroactive Analysis with Data Engineers
                StaticText The most advanced manufacturers take things further, employing teams of data engineers to analyze historical data and identify opportunities for improvement. Moving data from on-prem historians to the cloud opens up new possibilities for analysis and optimization. For companies running 24/7 operations, even small improvements in yield or uptime can have a massive impact on the bottom line.
            listitem
                ListMarker 0.
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                    StaticText Automated Real-Time Optimization
                    StaticText ‍
                StaticText At the top of the pyramid are companies that have mastered their infrastructure and are deploying machine learning models in real time either natively in their control systems or utilizing technology like OPC UA. These teams can extract actionable insights in real-time, enabling immediate adjustments through closed feedback loops integrated directly into control systems. While this level of sophistication remains rare, it sets the standard for what’s possible and offer a glimpse into the future for manufacturers with the resources to invest.
        heading The Problem with the Status Quo
            strong
        paragraph
            StaticText Despite the progress, most manufacturers are locked out of advanced data operations. The cost of integration for top-end platforms can run into the millions, and hiring the specialized talent to make sense of the data adds an ongoing operating expense. This creates a gulf between the largest players, who have the resources to innovate, and everyone else, who are left behind.
        heading Can GenAI Actually Help?
            strong
        paragraph
            StaticText This is where GenAI has the potential to change everything. By automating complex data transformations, it can drastically reduce the time and cost of integrating advanced tools. More importantly, it can democratize access to insights. With innovations like text-to-SQL and context-based query generation, manufacturing and process engineers can interact with their data directly—no data science team required.
        paragraph
            StaticText At Dime, we’re building tools to make this vision a reality. Our platform bridges the gap, enabling manufacturers of all sizes to extract value from their data without breaking the bank.
        paragraph
            StaticText The dream of Industry 4.0 was never just about technology. It’s about creating a future where every manufacturer—big or small—can run smarter, leaner, and more connected operations.
        paragraph
            StaticText Ready to unlock the potential of your data?
            link Schedule a demo, url='https://calendly.com/ashish-dime/30min'
            StaticText and let’s explore how Dime can empower your operations.
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        StaticText Ashish Bajaj
        StaticText November 25, 2024
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