November 2023

Connected Worker Conference Chicago Summit

Important Take-Aways from the Connected Worker Chicago Summit

Many important topics came up at the recent Connected Worker Chicago Summit 2023, an event that explored the top digital challenges and the latest technological advancements (especially with AI and generative AI) affecting manufacturing professionals. We at Prolifics talked with a lot of attendees at our booth, in speaker sessions, and out on the floor. Here are four important issues we heard from you during our three days there: 

1) “No paper on the factory floor” 

2) Younger workers and technology  

3) “Purity” and the connected worker 

4) Using AI in business operations 

Let’s take a quick look at each and see how it could apply to your organization. 

 

1) “No paper on the factory floor” 

Knowledge sharing and workforce management came out as a huge issue for many of the manufacturing companies in attendance. As these firms update and modernize with more complex equipment, there needs to be better ways of getting complex information in front of employees. A bunch of papers stuck all around the workstations with steps on how to operate the machinery, or repair and maintenance manuals buried in a supervisor’s desk drawer somewhere, doesn’t cut it anymore. Connected worker technology, whether through tablets, virtual/mixed reality wearables or computer vision, will get the correct information in front of the worker quickly and efficiently. The use of this technology dovetails and is part of the next topic –  

 

2) Younger workers and technology 

Many manufacturers expressed dismay that they can’t find enough people to work in their factories. To engage younger people, they can’t have that above “paper on the factory floor.” Companies need more technology because that’s how their target workforce grew up – for younger workers, there was never a time without smartphones or the internet. They expect automation and technology as a matter of course. For example, a tech-savvy new worker using a wearable now has the complete knowledge base in front of them – all the information he needs, even pictures and steps to go through. It makes onboarding easier, it makes training easier, and it makes day-to-day operations easier – which not only translates into efficiency and lower costs – it also means safety, a prime concern of every manufacturer. 

The flip side of this is that older workers are leaving or retiring – and taking a lot of institutional knowledge out the door with them. One manufacturer told us, “We don’t have anything documented in terms of our processes and our procedures. I would like to take our knowledgeable workers and get them to somehow help us use Gen AI to create that documentation.” That “somehow” would be AI speech-to-text, which captures info, then generates and formats documentation the way the client wants it. 

 

3) “Purity” and the connected worker 

It may at first seem to be a niche issue, but we met with a lot of food and beverage companies that can’t use phones, tablets or wearables out on the manufacturing floor because of food purity and safety rules – when dealing with food you can’t have anything that could contaminate it. A potential solution would be sanitized, ruggedized tablets that are mounted in a way that they couldn’t contaminate anything, with employees using speech-to-text instead of touching the tablet screen. 

 

4) Using AI in business operations 

While the conference focus was on the connected worker on the manufacturing floor or out in the field, many companies took the opportunity to discuss how AI and Gen AI could help their office/business operations. These included: 

  • A company that is growing through acquisitions potentially using Gen AI to find and analyze new targets. For example, they have the historical information of how they decided to buy companies, the company profiles and the key performance indicators (KPIs) they look for. Gen AI could use all that info to generate new target recommendations. 
  • Similar to the above, an already large and growth-through-acquisition firm found that its many pieces are using different vendors to buy the same products. The firm would like to use AI to analyze its vendor spend for consolidation and price negotiation. 
  • Prolifics’ Salem Hadim, VP of Business Process Management, addressed the connected worker on the “office floor,” as opposed to the factory floor, in his conference presentation. He discussed process automation, generative AI and digital workers connecting someone sitting at their desk to the information they need to supercharge their workflows – or as we often say at Prolifics, elevate them to the complexity of their tasks.  

 

Learn more from Prolifics 

Getting The Most From Your Industrial Operators – The Connected Worker (prolifics.com) 

Panelist Q&A: The Factory Floor That Tells You More (prolifics.com) 

 

About Prolifics 

At Prolifics, the work we do with our clients matters. Whether it’s literally keeping the lights on for thousands of families, improving access to medical care, helping prevent worldwide fraud or protecting the integrity and speed of supply chains, innovation and automation are significant parts of our culture. While our competitors are throwing more bodies at a project, we are applying automation to manage costs, reduce errors and deliver your results faster. 

Let’s accelerate your transformation journeys throughout the digital environment – Data & AI, Integration & Applications, Business Automation, DevXOps, Test Automation, and Cybersecurity. We treat our digital deliverables like a customized product – using agile practices to deliver immediate and ongoing increases in value. Visit prolifics.com. 

watson.x governance

Avoiding AI Pitfalls with AI Governance

By Gregory Hodgkinson, Prolifics CTO

“AI systems should be designed to benefit society while minimizing potential negative impacts.”

So, you’ve got your AI vision in place. As you forge your path toward differentiation and digital transformation, how do you avoid the common pitfalls along the way?

First, define your AI governance policies — your precautionary intent to prevent unintended consequences or misuse of AI. This policy framework outlines what your organization will do and not do to maintain ethical, responsible AI practices.

What should your precautionary intent for AI include?

You’d probably agree that these “should” statements make a solid foundation:

Our use of AI should:
– Promote fairness and equity
– Be accountable and auditable
– Enhance user understanding and trust
– Maintain reliability and safety standards
– Comply with all relevant laws and regulations

Stating intent is a good start — but as the saying goes, “the road to disaster is paved with good intentions.” To make policies actionable and enforceable, you need AI governance — the mechanism that ensures practice aligns with policy.

Enter IBM watsonx.governance

Watsonx.governance is a next-generation AI governance and compliance toolkit that automates and accelerates workloads across the AI lifecycle. It enhances risk management, ensures regulatory compliance, and enables transparent, auditable AI operations.

Building on IBM’s proven capabilities in AI model governance, including model inventory, workflow, evaluation, and monitoring, watsonx.governance introduces advanced features for generative AI. These features make it a unique solution for enterprises adopting large language models (LLMs) and generative AI.

Pitfall! AI Governance Edition

In a previous article introducing watsonx, I compared its components — watsonx.ai, watsonx.data, and watsonx.governance — to a band, each member playing a vital role.

For this piece, imagine a different analogy:
“Pitfall!,” the classic 1980s video game where Pitfall Harry explores a jungle, collecting treasures and avoiding traps.

Welcome to Pitfall! AI Governance Edition, where you step into the shoes of a digital policymaker navigating the complex jungle of AI governance. Every move impacts public trust, ethical integrity, and organizational reputation. With watsonx.governance as your toolkit, let’s explore how to overcome each level’s challenges — and reach the ultimate goal: trustworthy, responsible AI.

Level 1 — Responsibility Run!

Objective:
Ensure ethical AI development with transparent documentation, reliable data, and accountable workflows. These are critical for maintaining the trustworthiness of AI systems.

Pitfalls:
– Undefined use cases
– Unclear model lifecycle
– Missing model lineage

Tips:
Watsonx.governance gives you complete lifecycle visibility:

  • AI model use cases: Define each use case within a centralized inventory catalog, connecting all related assets for scalable governance.
  • Model facts: Publish detailed performance metrics, training details, and environment data alongside the model for transparency.

Bonus for Generative AI:

  • Prompt governance: Track and control generative AI prompts.
  • Risk guidance: Receive automated recommendations on potential LLM risks.
  • Cost and adoption tracking: Monitor LLM usage and associated costs across your organization.

Level 2 — Bias Bump

Objective:
Eliminate AI bias caused by skewed data or flawed algorithms to ensure fair, unbiased outcomes.

Pitfalls:
– Biased decision-making
– Lack of bias detection or analysis tools

Tips:
Watsonx.governance proactively detects and mitigates bias:

  • Bias monitor and alert: Set fairness thresholds and get notified automatically.
  • Feature selection: Monitor individual features for bias.
  • Bias analysis: Investigate bias origins and trends with detailed reporting.

Bonus for Generative AI:

  • Bias detection in outputs: Automatically monitor generated content for social bias or stigma, ensuring outputs remain ethical and inclusive.

Level 3 — Quality Quest

Objective:
Maintain AI quality assurance — ensuring models are accurate, consistent, and aligned with defined goals.

Pitfalls:
– No quality monitoring
– Undetected performance degradation

Tips:
Watsonx.governance helps uphold performance integrity:

  • Quality monitors: Detect and alert for quality drops in real-time.
  • Comprehensive metrics: Track accuracy, precision, recall, and AUC.
  • Threshold management: Define upper and lower limits for quality benchmarks.

Bonus for Generative AI:

  • Generative quality evaluation: Continuously assess prompt templates for summarization, classification, or content generation.
  • PII protection: Automatically monitor prompts to prevent personal data leakage — essential for compliance and privacy.

Level 4 — Drift Dilemma

Objective:
Prevent model drift — when models lose accuracy due to evolving data or environmental changes.

Pitfalls:
– Undetected model degradation
– No drift tracking or alerts

Tips:
Watsonx.governance safeguards against performance drift:

  • Drift monitors: Continuously compare model predictions against new data realities.
  • Output and feature drift detection: Identify performance or data shifts in real time to maintain accuracy.

Level 5 — The Transparency Trial

Objective:
Promote AI explainability and transparency — enabling humans to understand how AI makes decisions.

Pitfalls:
– Inability to explain AI decisions
– Lack of reasoning or decision traceability

Tips:
Watsonx.governance enhances clarity and accountability:

  • Explain transaction: View complete decision histories and rationales.
  • What-if analysis: Simulate alternate data inputs to see how decisions would change.
  • Tipping points: Identify data thresholds that influence model outcomes.

Bonus for Generative AI:

  • Attribution tracing: Trace generated content back to original input data to understand “where that came from.”

AI Pitfalls Avoided — Congratulations!

You did it — final level complete! You’ve successfully navigated every governance challenge. With a robust AI governance framework, supported by watsonx.governance, your organization can confidently pursue its AI vision while ensuring compliance, ethics, and long-term success.

About the Author

Gregory Hodgkinson is the Chief Technology Officer and Worldwide Head of Engineering at Prolifics, and an IBM Lifetime Champion. He leads innovation across practices, empowering clients with modern engineering solutions that improve software development, delivery, and enterprise transformation.

About Prolifics

At Prolifics, our work with clients drives meaningful impact — from improving healthcare access to protecting global supply chains. We combine innovation and automation to accelerate digital transformation across Data & AI, Integration & Applications, Business Automation, DevXOps, Test Automation, and Cybersecurity.

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Empowering Claims Processing with a New User Experience  

Client

Our client provides and administers healthcare benefit plans serving a diverse range of U.S. market segments.

Challenge

The client’s claims processing division manages the validation and payment of insurance claims through electronic forms known as EDI X12 transactions (such as 837, 835, and 834). Their process heavily relied on a legacy “green screen” application — a character-based, text-heavy interface requiring manual input.

For example, when a healthcare provider submitted an 837 form, an employee had to manually enter the details into the green screen system. Similarly, responses like 835 transactions from the insurer were processed manually through the same interface.

This outdated, labor-intensive process caused significant inefficiencies, increased the risk of human error, and created challenges in hiring and retaining skilled staff. Additionally, it resulted in a suboptimal client experience. The organization wanted to accelerate claims processing to secure more profitable yet complex contracts, but the existing system’s limited scalability made this difficult.

Specific challenges included:

  • Difficulty recruiting and retaining claims examiners.
  • Lack of familiarity among new hires with the outdated adjudication tools.
  • Extensive onboarding and training time—up to nine months for new examiners.
  • Daily frustrations with the green screen application leading to high turnover.
  • Inability to respond promptly to client needs due to manual inefficiencies.

The client required a modern, user-friendly interface to enhance the speed, accuracy, and efficiency of their claims processing operations.

Action

While most EDI X12 transactions (834, 837, 835, etc.) are processed automatically, rejected claims still require manual intervention and troubleshooting. Because EDI formats are not user-friendly, end-users needed an intuitive interface to understand and resolve these issues efficiently.

Prolifics addressed this challenge by leveraging Rocket Software to develop a modern web-based UI layered on top of the existing green screen system. This solution consolidated key information into a single-pane view, allowing users to quickly assess claims and take action. It also combined alerts, comments, and error messages; improved navigation flexibility; and introduced a manager dashboard to allocate work based on availability, skill level, confidentiality, and SLA priorities.

This approach enabled the client to preserve their existing green screen infrastructure while benefiting from a modern web interface. Prolifics supported both the implementation and ongoing management of the solution, including maintenance, support, and security, ensuring continuous operational excellence.

The project was executed in three iterations, with QA and user acceptance testing (UAT) integrated early in each phase. This agile approach allowed rapid feedback loops and progressive improvement. As a result, the solution was delivered on time and under budget.

Results

The new solution revolutionized the client’s claims processing operations by introducing a modern web interface that simplified workflows, enhanced usability, and automated key processes.

Key outcomes:

  • 25% increase in employee efficiency, improving overall claims throughput.
  • Training time for new examiners reduced from nine months to just three.
  • Projected savings of over $2 million in business and IT efficiencies over 3.5 years.

The modernization also introduced several new capabilities previously impossible within the green screen environment:

  • Claims Assignment: A new dashboard enables managers to prioritize contracts and assign claims effortlessly. Tasks once managed through manual emails and spreadsheets are now automated, with built-in internal messaging for collaboration.
  • Screen Aggregation: Multiple green screens are consolidated into a single interface, allowing examiners to view and act on multiple data points simultaneously—skipping irrelevant steps when appropriate.
  • Web-Enabled Functionality: Integrated help features, command explanations, and user guidance improve system usability and reduce dependency on specialized training.
  • Reference Data Integration: Key data sources are now presented side-by-side with claims screens, streamlining access to relevant information.
  • Advanced Search Capabilities: Users can instantly locate claims, diagnosis codes, examiners, and reference data without manual spreadsheet lookups.
  • Comprehensive Audit History: The system now logs a complete audit trail of claims activities, improving transparency and compliance.
  • Future Scalability: Built-in frameworks allow for easy extension and addition of new commands and features as business needs evolve.

Technology

Rocket Modern Experience is a robust mainframe modernization platform that transforms legacy green screen applications into intuitive web, mobile, or cloud experiences. By leveraging this technology, Prolifics enabled the client to retain existing mainframe investments while introducing a seamless, user-centric web layer that enhances efficiency and agility.

About Prolifics

At Prolifics, the work we do with our clients truly matters. Whether it’s keeping the lights on for thousands of families, improving access to healthcare, preventing global fraud, or safeguarding supply chains, innovation and automation are at the heart of everything we do.

Unlike competitors who scale projects with additional manpower, Prolifics leverages automation to manage costs, minimize errors, and deliver faster results. Our agile, product-driven approach ensures ongoing value across every stage of your digital transformation—spanning Data & AI, Integration & Applications, Business Automation, DevXOps, Test Automation, and Cybersecurity.

Technology, holding hands with environmental Icons via Network connection on green background

Data-Driven Insights for a Sustainable Future

Some people care about being green, and some people don’t. But for companies, it’s a big deal. It can affect their reputation, consumer base, and ROI. One way to be green is to focus efforts on lowering carbon emissions and adhering to environmental, social, governance (ESG) principles. This helps companies comply with regulations, meet consumer demand, stay competitive, reduce risks, save costs, and build trust with stakeholders. 

At issue – data that doesn’t actually help you  

It’s one thing to say you’re a company that promotes sustainability, but you need solid data to prove it. 

Your company may have plenty of data, but it could be scattered across various sources, involve manual data entry, and lack real-time reporting capabilities. This hinders your ability to effectively manage, interpret, and report this data, slowing down decision-making for sustainability goals.  

The goal would be to adopt a more modern data approach by creating one centralized dashboard, providing visibility and actionable insights. This empowers informed decision-making for ESG initiatives. The difference between regular data methods and modernized data methods lies in the approach and tools used for collecting, managing, and interpreting data. Here are some features of these modernized approaches: 

  • Automation of data collection processes for efficiency. 
  • Integrated platforms and centralized databases for comprehensive data storage. 
  • Reduced errors with automated data handling. 
  • Cloud-based accessibility, enabling remote collaboration. 
  • Dynamic reporting and visualization tools for real-time insights. 
  • Integration of advanced analytics and AI for predictive and sophisticated data interpretation. 
  • Scalable solutions capable of handling evolving data needs. 
  • Enhanced security measures to ensure data integrity and confidentiality. 

This type of approach would enhance sustainability efforts, enabling businesses to make informed decisions for measurable ESG impact.  

Let’s apply this to a real scenario  

A prominent automobile manufacturer needed a clear way to accurately measure and reduce carbon emissions. This would enable informed decision-making and accurate reporting to stakeholders. The goal is to demonstrate their commitment to ESG and sustainability and achieve carbon neutrality by 2050. 

They had accumulated extensive data related to carbon emissions from various sources like cars, manufacturing plants, and more. However, the collection and reporting process of this data was entirely manual, which limited their visibility to pinpoint where the issues are coming from. This hindered their transparency and efficiency especially in communicating sustainability efforts. They need a centralized location to visualize their data. 

Prolifics can employ sustainability management software to answer the challenge. It would provide a centralized, automated, and analytics-driven solution that empowers the automobile manufacturer to effectively manage, interpret, and report ESG data.  

We would also look at the big picture to determine how to make this solution even better, such as integration with other tools like IoT (Internet of Things) and enterprise asset management (EAM) software. This would help the client manage their assets (EAM), while another system (sustainability software) keeps an eye on the environment and sustainability goals, with the help of real-time data from all their equipment (thanks to IoT). 

The Benefits 

The client can now address and monitor carbon emissions effectively. They have data in one spot that they can trust and make informed decisions on. They can accurately report to stakeholders, increasing their reputation and commitment to a sustainable future. Other benefits include: 

  • Improved data accuracy and reporting. 
  • Reduced energy consumption across facilities.  
  • Improved investor perception and feedback.  
  • Improved brand image and customer loyalty. 

For this client, they don’t just have data; they use the data to make better decisions for a sustainable future.  

Why Prolifics for your data solutions? 

With Prolifics as your data and analytics partner, you’ll achieve digital disruption by the way you analyze, govern and manage your data. This goes beyond business intelligence. We look at your business holistically and objectively – we begin by talking about your issues, not only the technology.  

We focus on business value, data-driven decision-making, collaboration, continuous improvement, and ethical considerations. We provide you with deeper insights that drive innovation and better business outcomes – all designed to keep you ahead of your competition. 

Learn more about Data at Prolifics.  

3d rendering of an abstract model of a boat in the form of a globe, Generative AI illustrations.

CIO & Leader Blog – Generative AI and Semantic Models

Digital Transformation With Generative AI And Semantic Models

LLMs have catapulted language understanding by overcoming the limitations of NLP/ NLU techniques using pre-trained models. 

This article was written by Prolifics Offshore Head of Engineering, Ajay Malgaonkar, and first published in CIO and Leader.

READ NOW

10 min. read

This blog explores the potential of generative AI, focusing on the Retrieval-Augmented Generation (RAG) technique for tasks like question-answering and summarization. A practical scenario illustrates how generative AI aids troubleshooting in industries, streamlining issue resolution. This blog advises enterprises on building Gen AI platforms to overcome adoption challenges, emphasizing the importance of semantic models for a unified analytics platform. 

Learn more about Prolifics Generative AI.  

Future Proofing with Gen AI

Harnessing Gen AI – A Five-Step Blueprint for Business Leaders

“Building an AI strategy inclusive of GenAI requires a rigorous approach — from developing a business-driven vision to planning which initiatives and technologies to adopt and why.” – Gartner 

Getting started with Generative AI for your business may seem overwhelming, but it doesn’t have to be. In fact, with the right approach it can be a game-changer for your organization.  

This eBook offers a well-defined path for business leaders to implement tailored generative AI solutions effectively, from developing a business-driven vision to planning which initiatives and technologies to adopt and why. Addressing these considerations empowers your organization to make informed decisions, ensuring that Generative AI solutions.

AI Strategy Roadmap

5 Steps for Gen AI Success

Step into the spotlight with Generative AI and Prolifics as your guide. Discover the five key steps for Gen AI success, from vision to grand premiere. Lights, Camera, Gen AI: Let’s roll!

 

Connect with a Prolifics Gen AI Expert to start your journey, and check out our Generative AI resources to learn more!

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