We are thrilled to announce that Perficient has been recognized in Forrester’s recent report, “The Connected Product Engineering Services Landscape, Q2 2025.” Forrester defines connected product engineering services providers as:  

“Firms that conceive, design, develop, launch, and scale new connected (or embodied) products that combine a physical product with digital applications to directly deliver new revenue for their clients.” 

We believe this acknowledgment highlights our commitment to driving innovation and delivering exceptional value to our clients through connected product engineering services. 

Access The Connected Product Engineering Services Landscape, Q2 2025 to find out more. 

Driving Connected Product Innovation Across Key Industries 

Whether it’s enabling a shift to product-as-a-service models, managing the ongoing support and monetization of field-deployed connected products, or improving workforce productivity through modern workplace technologies, we believe our strategic and management consulting expertise empowers organizations to navigate complexity and deliver meaningful outcomes. Notably, we’ve achieved success for clients in the life sciences, manufacturing, and utilities industries when it comes to connected product innovation. Our clients rely on us not only for engineering and implementation, but also for the high-value strategic work that drives connected product success. 

What Are Connected Product Engineering Services? 

From Perficient’s perspective, Connected Product Engineering Services are a comprehensive suite of offerings designed to create products that blend physical components with digital applications. These services cover the entire life cycle of product development, including: 

Conception: Ideating new connected products that meet market needs and client requirements. 

Design: Crafting designs that integrate both physical and digital elements to ensure seamless functionality and user experience. 

Development: Building and programming the product, including hardware and software integration. 

Launch: Bringing the product to market, including strategies for deployment and initial user adoption. 

Scaling: Expanding the product’s reach and capabilities to grow user bases and evolving market demands. 

The goal of connected product engineering services is to deliver products that not only function effectively but also generate new revenue streams for clients by leveraging the synergy between physical and digital technologies. Perficient’s expertise in this area runs deep and provides clients with improved data strategy, monetization, and user interfaces that ultimately instill customer trust and loyalty. 

Common Disrupters and Challenges  

With the results from Perficient’s own research, we have found that as the connected product landscape evolves, so do the challenges and disruptions organizations must navigate. One disruptor we’re seeing in the marketplace is the growing customer expectation for seamless interoperability between connected products. Namely, 50% of commercial users responded that their connected products integrated only “somewhat well” with their existing systems and infrastructure. 

Buyers are increasingly making purchasing decisions based on how well new products integrate with their existing connected ecosystems. This shift is creating a strong push for increased collaboration and partnerships between OEMs to enable cross-product connectivity, such as linking garage door openers with vehicles or syncing household appliances with mobile devices. 

Another challenge is overcoming negative customer sentiment toward connected features. Some consumers view these features as unnecessary luxuries or express concerns about privacy and data security. Only 19% of consumers feel aware of data collection practices. In industrial settings like manufacturing and supply chain, connected products are sometimes perceived as intrusive or overly surveillance-focused. 

Additionally, there’s often a gap in user education. Many OEMs struggle to implement the right structures for ongoing support and training, making it difficult for customers to fully understand and leverage all available product features. Addressing these concerns through thoughtful design, transparent data practices, and strong customer enablement programs is essential for long-term success in the connected product space. 

Perficient’s Approach to Connected Product Engineering 

At Perficient, we take a comprehensive, end-to-end approach to connected product delivery, combining strategy, engineering, prototyping, and testing to bring innovative ideas to life. Especially when it comes to connected products, we understand that it starts with a strong data foundation. That’s why we prioritize helping clients define a robust data strategy from the start.  

When the foundation is solid, identifying how to utilize that data and create new revenue streams is the next step. Subscription models are becoming a key driver of connected product monetization, and we guide clients in building scalable ecosystems that support recurring revenue. Additionally, we recognize that customer experience is a critical differentiator, often enabled through companion apps that provide seamless access to product features and functionality. These strategic considerations—data, subscriptions, and experience—are essential components of a successful connected product strategy, and they remain central to how Perficient delivers value to our clients. 

Real and actionable insights drive our strategy. We’ve based our approach for connected product manufacturers on our own research – a study on the sentiments of consumers, commercial users, and manufacturers of connected products – which you can explore here. 

Learn more about our manufacturing industry expertise. 

Healthcare organizations (HCOs) face mounting pressure to boost operational efficiency, improve health and wellness, and enhance experiences. To drive these outcomes, leaders are aligning enterprise and business goals with digital investments that intelligently automate processes and optimize the health journey. 

Clinical intelligence plays a pivotal role in this transformation. It unlocks advanced data-driven insights that enable intelligent healthcare organizations to drive health innovation and elevate impactful health experiences. This approach aligns with the healthcare industry’s quintuple aim to enhance health outcomes, reduce costs, improve patient/member experiences, advance health equity, and improve the work life of healthcare teams. 

Intelligent Healthcare Organizations: Driven By Clinical Intelligence  

Our industry experts were recently interviewed by Forrester for their April 2025 report, Clinical Intelligence Will Power The Intelligent Healthcare Organization, which explores ways healthcare and business leaders can transform workflows to propel the enterprise toward next-gen operations and experiences. 

We believe the fact that we were interviewed for this report highlights our commitment to optimize technology, interoperability, and digital experiences in ways that build consumer trust, drive innovation, and support more-personalized care.  

We combine strategy, industry best practices, and technology expertise to deliver award-winning results for leading health plans and providers: 

• Business Transformation: Activate strategy for transformative outcomes and health experiences. 

• Modernization: Maximize technology to drive health innovation, efficiency, and interoperability. 

• Data Analytics: Power enterprise agility and accelerate healthcare insights. 

• Consumer Experience: Connect, ease, and elevate impactful health journeys. 

Understand and Deliver On Consumer Needs and Expectations 

Every individual brings with them an ever-changing set of needs, preferences, and health conditions. Now more than ever, consumers are flat out demanding a more tailored approach to their health care. This means it is imperative to know your audience. If you do not approach people as individuals with unique, personal needs, you risk losing them to another organization that does.  

Becoming an intelligent healthcare organization (IHO) takes more than just a technology investment; it is a complete restructuring of the enterprise to infuse and securely utilize clinical intelligence in every area and interaction.

In its report, Forrester defines an IHO as, “A healthcare organization that perpetually captures, transforms, and delivers data at scale and creates and seamlessly disseminates clinical intelligence, maximizing clinical workflows and operations and the experience of employees and customers. IHOs operate in one connected system that empowers engagement among all stakeholders.”

Ultimately, consumers – as a patient receiving care, a member engaging in their plan’s coverage, or a caregiver supporting this process – want to make and support informed health care decisions that cost-effectively drive better health outcomes. IHOs focus on delivering high-quality, personalized insights and support to the business, care teams, and consumers when it matters most and in ways that are accessible and actionable.

Orchestrate Better Health Access 

Digital-first care stands at the forefront of transformation, providing more options than ever before as individuals search for and choose care. When digital experiences are orchestrated with consumers’ expectations and options in mind, care solutions like telehealth services, find-care experiences, and mobile health apps can help HCOs deliver the right care at the right time, through the right channel, and with guidance that eases complex decisions, supports proactive health, and activates conversions. 

The shift toward digital-first care solutions means it is even more crucial for HCOs to understand real-time consumer expectations to help shape business priorities and form empathetic, personalized experiences that build trust and loyalty. 

In its report, Forrester states, “And as consumer trust has taken a hit over the past three years, it is encouraging that 72% of healthcare business and technology professionals expect their organization to increase its investment in customer management technologies.”  

Clinical intelligence, leveraged well, can transform the ways that consumers interact and engage across the healthcare ecosystem. IHOs see clinical intelligence as a way to innovate beyond mandated goals to add business value, meet consumers’ evolving expectations, and deliver equitable care and services.  

Interoperability plays a crucial role in this process, as it enables more seamless, integrated experiences across all digital platforms and systems. This interconnectedness ensures that consumers receive consistent, coordinated care, regardless of where they are seeking treatment and are supported by informed business and clinical teams. 

Mandates such as Health Level 7 (HL7) standards, Fast Healthcare Interoperability Resources (FHIR), and Centers for Medicare & Medicaid Services (CMS) Interoperability and Patient Access Final Rule are creating a more connected and data-driven healthcare ecosystem. Additionally, CMS price transparency regulations are empowering consumers to become more informed, active, and engaged patients. Price transparency and cost estimator tools have the potential to give organizations a competitive edge and drive brand loyalty by providing a transparent, proactive, personalized, and timely experience. 

The most successful organizations will build a proper foundation that scales and supports successive mandates. Composable architecture offers a powerful, flexible approach that balances “best in breed,” fit-for-purpose solutions while bypassing unneeded, costly features or services. It’s vital to build trust in data and with consumers, paving the way for ubiquitous, fact-based decision making that supports health and enables relationships across the care continuum. 

Success in Action: Empowering Healthcare Consumers and Their Care Ecosystems With Interoperable Data

Enable Caregivers and Care Teams 

As the population ages, caregivers play an increasingly important role in the healthcare journey, and their experience is distinct. They may continually move in and out of the caregiver role. It’s essential to understand and engage these vital partners, providing them with important tools and resources to support quality care.  

Clinical intelligence can provide HCOs with advanced insights into the needs of caregivers and care teams, helping clinical, operational, IT, digital, and marketing leaders design systems that support the health and efficacy of these important care providers.  

Integrated telehealth and remote monitoring have become essential to managing chronic conditions and an aging population. Intuitive, integrated digital tools and personalized messaging can help mitigate potential health barriers by proactively addressing concerns around transportation, costs, medication adherence, appointment scheduling, and more.  

A well-planned, well-executed strategy ideally supports access to care for all, creating a healthier and more-welcoming environment for team members to build trust, elevate consumer satisfaction, and drive higher-quality care.  

Success in Action: A Digital Approach to Addressing Health Equity 

Improve Operational Efficiencies for Care Teams 

HCO leaders are investing in advanced technologies and automations to modernize operations, streamline experiences, and unlock reliable insights.  

Clinical intelligence paired with intelligent automations can accelerate patient and member care for clinical and customer care teams, helping to alleviate stress on a workforce burdened with high rates of burnout.  

In its report, Forrester shares, “In Forrester’s Priorities Survey, 2024, 65% or more of healthcare business and technology professionals said that they expect their organization to significantly increase its investments in business insights and analytics, data and information management, AI, and business automation and robotics in the next 12 months.”  

It’s clear the U.S. healthcare industry stands on the cusp of a transformative era powered by advanced analytics and holistic business transformation. AI-driven automations can reduce administrative costs, while AI-enabled treatment plans offer hyper-personalized precision medicine. As technology continues to shape healthcare experiences, Felix Bradbury, Perficient senior solutions architect, shares his thoughts on the topic: 

“Trust is crucial in healthcare. Understanding how to make AI algorithms interpretable and ensuring they can provide transparent explanations of their decisions will be key to fostering trust among clinicians and patients.” 

AI can be a powerful enabler of business priorities. To power and scale effective use cases, HCOs are investing in core building blocks: a modern and secure infrastructure, well-governed data, and team training and enablement. A well-formed strategy that aligns key business needs with people, technology, and processes can turn data into a powerful tool that accelerates operational efficiency and business success, positioning you as an intelligent healthcare organization.  

Success in Action: Engaging Diverse Audiences As They Navigate Cancer Care 

Healthcare Leaders Turn To Us

Discover why we have been trusted by the 10 largest health systems and the 10 largest health insurers in the U.S. Explore our healthcare expertise and contact us to learn more. 

As technology continues to advance, patients and care teams expect to seamlessly engage with tools that support better health and accelerate progress. These developments demand the rapid, secure, scalable, and compliant sharing of data. 

By aligning enterprise and business goals with digital technology, healthcare organizations (HCOs) can activate strategies for transformative outcomes and improve experiences and efficiencies across the health journey. 

IDC Market Glance: Healthcare Provider Operational IT Solutions, 1Q25 

Perficient is proud to be included in the categories of IT Services and SI services in the IDC Market Glance: Healthcare Provider Operational IT Solutions, 1Q25 report (doc #US52221325, March 2025). We believe our inclusion in this report’s newly introduced “Services” segmentation underscores our expertise to leverage AI-driven automation and advanced analytics, optimize technology investments, and navigate evolving industry challenges. 

IDC states, “This expansion reflects the industry’s shift toward outsourced expertise, scalable service models, and strategic partnerships to manage complex operational IT and infrastructure efficiently.” 

IDC defines IT Services as, “managed IT services, ensuring system reliability, cybersecurity, and infrastructure optimization. These solutions support healthcare provider transformation initiatives, helpdesk management, network monitoring, and compliance with healthcare IT regulations.” The SI Services category is defined by IDC as, “system integration services that help deploy technologies and connect disparate systems, including EHRs, RCM platforms, ERP solutions, and third-party applications to enhance interoperability, efficiency, automation, and compliance with industry standards.”  

Advanced Solutions for Data-Driven Success 

We imagine, engineer, and optimize scalable, reliable technologies and data, partnering with healthcare leaders to better understand consumer expectations and strategically align digital investments with business priorities.  

Our end-to-end professional services include: 

• Digital transformation strategy:  The healthcare industry’s rapid evolution requires attention in several areas – adopting new care models, capitalizing on disruptive technologies, and affecting regulatory, operational, financial, and organizational change. We equip HCOs to recognize and speed past potential hurdles in order to maximize ROI by making the most of technology, operational, and financial resources. 

• Cloud-native environments: Cloud technology is the primary enabler of business transformation and outcomes-focused value. Investing in cloud allows HCOs to overcome limitations of legacy systems, improve stability, and reduce costs. It also leads to better solution quality, faster feature delivery, and encourages a culture of innovation. Our expert consultants tailor cloud solutions to unique business needs, empowering teams and fueling growth, intelligence, and long-term profitability. 

• Hyper-scalable data infrastructures: We equip HCOs to maximize the value of information across the care ecosystem by uncovering the most meaningful, trustworthy data and enriching it with critical context so you can use it to answer difficult questions, power meaningful experiences, and automate smart decisions. Trusting data begins with having trust in the people, processes, and systems that source, move, transform, and manage that data. We partner to build data into a powerful, differentiating asset that can accelerate clinical, marketing, and operational excellence as information is exchanged across organizations, systems, devices, and applications. 

• AI ecosystems: HCO’s face mounting competition, financial pressures, and macro uncertainties. Enhance operations with innovative and intelligent AI and automation solutions that help you overcome complex challenges, streamline processes, and unlock new levels of productivity. Holistic business transformation and advanced analytics are front and center in this industry evolution, and generative AI (GenAI) and agentic AI have fundamentally shifted how organizations approach intelligence within digital systems. According to IDC, “GenAI will continue to redefine workflows, while agentic AI shows promise to drive real-time, responsive, and interpretive orchestration across operations.” Position yourself for success now and in the future with enhanced customer interactions, reduced operational costs, and data-driven decision-making powered by our AI expertise. 

• Digital experiences: Digital-first care options are changing the face of healthcare experiences, bringing commerce-like solutions to consumers who search for and choose care that best fits their personal priorities and needs. We build high-impact experience strategies and put them in motion, so your marketing investments drive results that grow lasting relationships and support healthy communities. As the healthcare landscape continues to evolve – with organizational consolidations and new disruptors reshaping the marketplace – we help you proactively and efficiently attract and nurture prospective patients and caregivers as they make health decisions. 

We don’t just implement solutions; we create intelligent strategies that align technology with your key business priorities and organizational capabilities. Our approach goes beyond traditional data services. We create AI-ready intelligent ecosystems that breathe life into your data strategy and accelerate transformation. By combining technical excellence, global reach, and a client-centric approach, we’re able to drive business transformation, boost operational resilience, and enhance health outcomes. 

Success in Action: Illuminating a Clear Path to Care With AI-Enabled Search 

Empower Healthcare Experiences Through Innovative Technology 

Whether you want to redefine workflows, personalize care pathways, or revolutionize proactive health management, Perficient can help you boost efficiencies and a competitive edge.  

We combine strategy, industry best practices, and technology expertise to deliver award-winning results for leading health systems: 

• Business Transformation: Transform strategy into action: improve operations, lower costs, build operational resilience, and optimize care. 

• Modernization: Provide quality, cost-effective tools and platforms that enable exceptional care. 

• Data Analytics: Enable trusted data access and insight to clinical, operational, and financial teams across the healthcare ecosystem. 

• Consumer Experience: Harness data and technology to drive optimal healthcare outcomes and experiences. 

Discover why we have been trusted by the 10 largest health systems and the 10 largest health insurers in the U.S. Explore our healthcare expertise and contact us to learn more.

From Exploration to Integration

When the co-founder and “Senior Maverick” at Wired magazine, Kevin Kelly, speaks, you listen.

In our latest episode of What If? So What? Jim Hertzfeld sits down with Kevin Kelly, the Co-Founder of Wired magazine and one of the most respected observers of the digital age. Their conversation spans AI, organizational change, emotional technology, and the importance of staying endlessly curious.

It’s not about where the frontier is—it’s about how we navigate toward it.

“We discover things by using them.”

Kelly is quick to push back against the idea that insight can come from speculation alone.

“I think there’s a lot of Thinkism… the fallacy that you can figure things out by thinking about them,” he explains. “I think we discover things by using them.”

That simple shift—from theorizing to experimenting—is at the heart of innovation. He encourages direct interaction with new tools as the only real way to grasp their potential. “If I can’t use it, I want to talk to someone else who’s actually using them in some way. Because that’s where we’re going to learn.”

Innovation moves fast. Adoption moves differently.

While headlines often suggest exponential speed, Kelly brings the conversation back to reality.

“The frontier is moving very, very, very fast,” he says. “But the adoption is just going to take a long time… You can’t just introduce this technology nakedly. You have to adjust workflow, organizational shape… you have to adjust the infrastructure to maximize it.”

It’s not resistance. It’s pacing. And it’s a pattern we’ve seen before—he compares it to the slow but transformational adoption of electricity, which reshaped industries not just functionally but structurally. That same shift is playing out now with AI.

From digital to cloud to AI

Kelly observes that many companies aiming to embrace AI first seek to digitize, but that step alone may not be enough.

“There’s a step after digitization… which is they have to become a cloud company,” he says. “That’s really the only way that the AI is going to work at a large scale in a company like that.”

It’s not a warning. It’s a reflection—on what’s required to unlock the full potential of these tools.

When AI becomes emotional

There’s one dimension of AI that Kelly believes most people haven’t fully anticipated: the emotional bond.

“People will work with [AI] every day and become very close to them in an emotional way that we are not prepared for,” he explains. “It’s like… those who don’t have their glasses, and they need them to function. So, it’s not like falling in love with their glasses—it’s like, no, you are at your best with this thing.”

In that sense, AI won’t just reshape productivity. It may reshape the way we relate to technology altogether.

What does “digital” even mean anymore?

When asked to define “digital,” Kelly pauses. “At least in my circle, I don’t hear that term being used very much more,” he says.

But if pressed? He points to pace as the key distinction: not just whether something is digital or analog, but how fast it’s moving, how quickly it evolves.

That framing helps explain why some technologies feel modern and others feel legacy—it’s not just the format. It’s the momentum.

“You’re going to be a newbie for the rest of your life.”

Kelly closes the conversation with one piece of advice that applies to everyone, at every stage:

“No matter what age you are, you’re gonna spend the rest of your life learning new things,” he says. “So, what you want to do is get really good at learning… because you’re gonna be a newbie for the rest of your life.”

It reminds us that in a world of constant transformation, our greatest advantage isn’t what we know—it’s how we grow.

Listen to the full conversation

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Meet our Guest – Kevin Kelly

Kevin Kelly is Senior Maverick at Wired magazine. He co-founded Wired in 1993, and served as its Executive Editor for its first seven years. His newest book is Excellent Advice for Living, a book of 450 modern proverbs for good living. He is co-chair of The Long Now Foundation, a membership organization that champions long-term thinking and acting as a good ancestor to future generations. And he is founder of the popular Cool Tools website, which has been reviewing tools daily for 20 years. From 1984-1990 Kelly was publisher and editor of the Whole Earth Review, a subscriber-supported journal of unorthodox conceptual news. He co-founded the ongoing Hackers’ Conference, and was involved with the launch of the WELL, a pioneering online service started in 1985. Other books by Kelly include 1) The Inevitable, a New York Times and Wall Street Journal bestseller, 2) Out of Control, his 1994 classic book on decentralized emergent systems, 3) The Silver Cord, a graphic novel about robots and angels, 4) What Technology Wants, a robust theory of technology, and 5) Vanishing Asia, his 50-year project to photograph the disappearing cultures of Asia.  He is best known for his radical optimism about the future.

Learn More about Kevin Kelly

Meet our Host

Jim Hertzfeld is Area Vice President, Strategy for Perficient.

For over two decades, he has worked with clients to convert market insights into real-world digital products and customer experiences that actually grow their business. More than just a strategist, Jim is a pragmatic rebel known for challenging the conventional and turning grand visions into actionable steps. His candid demeanor, sprinkled with a dose of cynical optimism, shapes a narrative that challenges and inspires listeners.

Connect with Jim:

LinkedIn | Perficient

Data Summit 2025 is just around the corner, and we’re excited to connect, learn, and share ideas with fellow leaders in the data and AI space. As the pace of innovation accelerates, events like this offer a unique opportunity to engage with peers, discover groundbreaking solutions, and discuss the future of data-driven transformation. 

We caught up with Jerry Locke, a data solutions expert at Perficient, who’s not only attending the event but also taking the stage as a speaker. Here’s what he had to say about this year’s conference and why it matters: 

Why is this event important for the data industry? 

“Anytime you can meet outside of the screen is always a good thing. For me, it’s all about learning, networking, and inspiration. The world of data is expanding at an unprecedented pace. Global data volume is projected to reach over 180 zettabytes (or 180 trillion gigabytes) by 2025—tripling from just 64 zettabytes in 2020. That’s a massive jump. The question we need to ask is: What are modern organizations doing to not only secure all this data but also use it to unlock new business opportunities? That’s what I’m looking to explore at this summit.” 

What topics do you think will be top-of-mind for attendees this year? 

“I’m especially interested in the intersection of data engineering and AI. I’ve been lucky to work on modern data teams where we’ve adopted CI/CD pipelines and scalable architectures. AI has completely transformed how we manage data pipelines—mostly for the better. The conversation this year will likely revolve around how to continue that momentum while solving real-world challenges.” 

Are there any sessions you’re particularly excited to attend? 

“My plan is to soak in as many sessions on data and AI as possible. I’m especially curious about the use cases being shared, how organizations are applying these technologies today, and more importantly, how they plan to evolve them over the next few years.” 

What makes this event special for you, personally? 

“I’ve never been to this event before, but several of my peers have, and they spoke highly of the experience. Beyond the networking, I’m really looking forward to being inspired by the incredible work others are doing. As a speaker, I’m honored to be presenting on serverless engineering in today’s cloud-first world. I’m hoping to not only share insights but also get thoughtful feedback from the audience and my peers. Ultimately, I want to learn just as much from the people in the room as they might learn from me.” 

What’s one thing you hope listeners take away from your presentation? 

“My main takeaway is simple: start. If your data isn’t on the cloud yet, start that journey. If your engineering isn’t modernized, begin that process. Serverless is a key part of modern data engineering, but the real goal is enabling fast, informed decision-making through your data. It won’t always be easy—but it will be worth it.

I also hope that listeners understand the importance of composable data systems. If you’re building or working with data systems, composability gives you agility, scalability, and future-proofing. So instead of a big, all-in-one data platform (monolith), you get a flexible architecture where you can plug in best-in-class tools for each part of your data stack. Composable data systems let you choose the best tool for each job, swap out or upgrade parts without rewriting everything, and scale or customize workflows as your needs evolve.” 

Don’t miss Perficient at Data Summit 2025. A global digital consultancy, Perficient is committed to partnering with clients to tackle complex business challenges and accelerate transformative growth. 

Isn’t SFO an airport?  The airport one would travel if the destination is Oracle’s Redwood Shores campus.  Widely known as the initialism for the San Francisco International Airport, the answer would be correct if this question were posed in that context.  However, in Oracle Fusion, SFO stands for the Supply Chain Financial Orchestration. Based on what it does, we cannot call it an airport, but it sure is a control tower for financial transactions.

As companies are expanding their presence across countries and continents through mergers and acquisitions or natural growth, it becomes inevitable for the companies to transact across the borders and produce intercompany financial transactions.

Supply Chain Financial Orchestration (SFO), is the place where Oracle Fusion handles those transactions. The material may move one way, but for legal or financial reasons the financial flow could be following a different path.

A Typical Scenario

A Germany-based company sells to its EU customers from its Berlin office, but ships from its warehouses in New Delhi and Beijing.

Oracle Fusion SFO takes care of all those transactions and as transactions are processed in Cost Management, financial trade transactions are created, and corporations can see their internal margins, intercompany accounting, and intercompany invoices.

Oh wait, the financial orchestration doesn’t have to be across countries only.  What if a corporation wants to measure its manufacturing and sales operations profitability?  Supply Chain Financial Orchestration is there for you.

In short, SFO is a tool that is part of the Supply Chain management offering that helps create intercompany trade transactions for various business cases.

Contact Mehmet Erisen at Perficient for more introspection of this functionality, and how Perficient and Oracle Fusion Cloud can digitalize and modernize your ERP platform.

www.oracle.com

www.perficient.com

Keeping up with today’s fast-paced technological environment, with businesses undergoing a significant transformation in operations, customer interactions, and innovation, can be challenging. Partnering with the right digital transformation service provider is essential for success. A proven track record in guiding businesses through digital complexities is crucial for unlocking their full potential, driving efficiency, and ensuring exceptional customer experiences, leading to long-term success.

The Digital Transformation Services Landscape, Q2 2025 Report

The recent Forrester report defines digital transformation services as – “Service providers that offer multidisciplinary capabilities to support enterprises in articulating, orchestrating, and governing strategy-aligned business transformation journeys, driving change across technology, ways of working, operating models, data, and corporate culture to continuously improve business outcomes.” This report provides an in-depth overview of 35 digital transformation service providers, offering valuable insights into the current market landscape.

Understanding the Providers

Forrester meticulously researched each service provider through a comprehensive set of questions. According to Forrester, “organizations leverage digital transformation services to:

• Articulate and orchestrate strategy-aligned transformation journeys.
• Align tech modernization with people, organization, and culture changes.
• Navigate transformation risks.”

Leaders can compare digital transformation service providers listed in the report based on size, offerings, geography, and business scenario differentiation to make informed decisions.

Core Business Scenarios

The report identifies the core business scenarios that are “most frequently sought after by buyers and addressed by digital transformation services solutions.” These scenarios include enterprise transformation, customer experience (CX) transformation, data and analytics transformation, and infrastructure and operational transformation.

Our Inclusion

We are proud to be listed in the Forrester Digital Transformation Services Landscape report as a digital transformation consultancy with an industry focus in the sectors of financial services, healthcare, and industrial products, and a geographic focus in four regions: North America (NA), Asia Pacific (APAC), and Latin America (LATAM).

As a dynamic global organization, we believe that with our cohesive, integrated strategy, we can deliver from any of our geographic locations and bring together the best team and the best value for the customer.

Access the Forrester report, The Digital Transformation Services Landscape, Q2 2025 to find out more.

Your Digital Transformation Journey

Seeing the world through your customers’ eyes is the best way to meet their needs. Our Digital Business Transformation practice enables leaders to meet the demands of today’s fast-changing, customer-centric world. We help you articulate a vision, formulate strategy, and align your team around the capabilities you need to stay ahead of disruption. Together, we resolve uncertainty, embrace change, and establish a North Star to guide your transformation journeys.

We implement the Envision Strategy Framework, a continuous and adaptive process that feeds real-world insights back into strategic decisions. This framework is informed by customer empathy and grounded in executional know-how. We put customers at the center of our digital strategy formulation process.

Supporting this is Envision Online, a comprehensive digital transformation platform that amplifies strategic decision-making based on the Envision Framework. With proprietary tools and a wealth of industry data, we deliver swift, actionable insights to help understand your organization’s competitive positioning.

Learn more about the report.

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. For more information, read about Forrester’s objectivity here .

Generative AI (Gen AI) transforms how organizations interact with data and develop high-quality software. GenAI is a game changer in multiple industries, automating processes, increasing accuracy, and providing predictive insights. Here, we concentrate on its uses in data management, effects on efficiency, innovation, and cost savings.

GenAI in Data Management

Gen AI revolutionizes the data lifecycle by improving data quality, automating processes, and thus accelerating and improving decision-making. Key applications include:

• Data Augmentation: Gen AI generates synthetic data to augment existing datasets. This is more advantageous when training machine learning models that require diverse and large-scale data inputs.
• Data Cleansing finds and corrects duplicates, errors, missing values, and inconsistent formats, providing high-quality datasets ready for analysis.
• Data Enrichment: Gen AI generates fresh features for existing data (e.g., generating customer demographics based on purchase history or activity logs).
• Real-time Data Processing: Gen AI uses complex algorithms for real-time ingestion, cleansing, and transformations, guaranteeing seamless integration across systems.
• Predictive Analytics observes patterns and anomalies in data to forecast trends or spot a critical problem before it escalates.

Benefits of Data Management

• Accuracy and consistency of datasets are improved
• Operational costs and manual intervention are reduced.
• Improved innovation with high-quality data for better product development.

GenAI in Quality Assurance (QA)

GenAI is also transforming QA processes by automating test cases, generating test data, detecting bugs at an early stage, and performing predictive analysis. Its dynamic capabilities enhance the efficiency of software testing and reduce costs.

Applications in QA

Synthetic Test Data Generation: GenAI synthesizes realistic datasets critical for unbiased testing, assisting organizations with the ethical concerns of real-world data. It is especially relevant for healthcare.

Automated Test Case Generation: GenAI examines user stories and requirements using retrieval-augmented generation (RAG) and advanced algorithms to automatically create comprehensive test cases.

Exploration of Scenarios: QA teams can validate rare case scenarios that are difficult to find manually. GenAI is generating complexities that truly reflect realistic usages.

Continuous Monitoring: Unlike traditional AI approaches, GenAI monitors software performance in real-time even as development cycles run.

Test Automation: Generative AI enables tools like GitHub Copilot and AWS Code Whisperer to generate reusable code snippets to deploy automated tests, reducing manual work.

Benefits in QA

• Better, wider coverage of the test scenario and device.
• Predictive insights to identify defects faster.
• Saves Cost due to reduction of manual testing efforts.

Generative AI implementation challenges

As the advantages are considerable, there are some challenges to Gen AI implementation:

Integration Challenges: It may be challenging to ensure Compatibility with existing systems.

Data Sovereignty: Following regulations on how to handle sensitive or synthetic data e.g. GDPR compliance.

Resistant to Change: Individual teams might be unwilling to adjust to new tools because they either lack knowledge of how to utilize them or fear being displaced, not just by the tools themselves but also, in a wider sense, by automation.

Firm plans, stakeholder engagement, and clear guidance on AI tool use will help to ameliorate these challenges.

Conclusion

Generative AI is used to revolutionize data management and QA processes. Automating tasks to improve performance and accuracy for reducing errors and predictive analytics via synthetic data creation is a way to distinguish oneself as the foundation of certain emerging digital transformation strategies today. The more businesses collaborate with GenAI throughout their workflows, the more its capabilities will reveal efficiency and innovation, at blazing speed.

AI is revolutionizing our daily lives, reshaping how we work, communicate, and make decisions. From diagnostic tools in healthcare to algorithmic decision-making in finance and law enforcement, AI’s potential is undeniable. Yet, the speed of adoption often outpaces ethical foresight. Unchecked, these systems can reinforce inequality, propagate surveillance, and erode trust. Building ethical AI isn’t just a philosophical debate, it’s an engineering and governance imperative.

Imagine an AI system denying a qualified candidate a job interview because of hidden biases in its training data. As AI becomes integral to decision-making processes, ensuring ethical implementation is no longer optional, it’s imperative.

What is AI Ethics?

AI ethics refers to a multidisciplinary framework of principles, models, and protocols aimed at minimizing harm and ensuring human-centric outcomes across the AI lifecycle: data sourcing, model training, deployment, and monitoring.

Core ethical pillars include:

Fairness: AI should not reinforce social biases. This means actively reviewing data for gender, racial, or socioeconomic patterns before it’s used in training, and making adjustments where needed to ensure fair outcomes across all groups.

Transparency: Ensuring AI decision-making processes are understandable. Using interpretable ML tools like SHAP, LIME, or counterfactual explanations can illuminate how models arrive at conclusions.

Accountability: Implementing traceability in model pipelines (using tools like MLflow or Model Cards) and establishing responsible ownership structures.

Privacy: Protecting user privacy by implementing techniques like differential privacy, federated learning, and homomorphic encryption.

Sustainability: Reducing AI’s carbon footprint through greener technologies. Optimizing model architectures for energy efficiency (e.g., distillation, pruning, and low-rank approximations) and utilizing green datacenter solutions. The role of Green AI is growing, as organizations explore energy-efficient algorithms, low-power models for edge computing, and the potential for quantum computing to provide sustainable solutions without compromising model performance.

Fairness: Understanding the Nuances

Fairness in AI is not as straightforward as it may initially appear. It involves navigating complex trade-offs between different fairness metrics, which can sometimes cause conflict. For example, one metric might focus on achieving equal outcomes across different demographic groups, while another might prioritize minimizing the gap between groups’ chances of success. These differing goals can lead to tensions, and deciding which metric to prioritize often depends on the context and values of the organization.

In some cases, achieving fairness in one area may inadvertently reduce fairness in another. For instance, optimizing for equalized odds (ensuring the same true positive and false positive rates across groups) might be at odds with predictive parity (ensuring similar predictive accuracy for each group). Understanding these trade-offs is essential for decision-makers who must align their AI systems with ethical standards while also achieving the desired outcomes.

It’s crucial for AI developers to evaluate the fairness metrics that best match their use case, and regularly revisit these decisions as data evolves. Balancing fairness with other objectives, such as model accuracy, cost efficiency, or speed, requires careful consideration and transparent decision-making.

Why Ethics in AI Matter

AI is being integrated into high-stakes areas like healthcare, finance, law enforcement, and hiring. If ethics are left out of the equation, these systems can quietly reinforce real-world inequalities, without anyone noticing until it’s too late. 

Some real-world examples:

• Amazon eliminated an internal recruiting AI when it was found to favor male candidates over female ones.
• The Netherlands’ childcare benefits scandal exposed how algorithmic bias led to thousands of wrongful fraud accusations.
• In 2024, a major financial institution came under fire after its AI loan approval system disproportionately rejected applicants from minority communities.

These examples illustrate the potential for harm when ethical frameworks are neglected.

Key Ethical Challenges in AI

Bias: When Machines Reflect Our Flaws

Algorithms reflect the data they’re trained on, flaws included. If not carefully reviewed, they can amplify harmful stereotypes or exclude entire groups.

Why Transparency Isn’t Optional Anymore

Many AI models are “black boxes,” and it’s hard to tell how or why they make a decision. Lack of transparency undermines trust, especially when decisions are based on unclear or unreliable data.

Accountability Gaps

Determining responsibility for an AI system’s actions, especially in high-stakes scenarios like healthcare or criminal justice, remains a complex issue. Tools and frameworks that track model decisions, such as audit trails, data versioning, and model cards, can provide critical insights and foster accountability.

Privacy Concerns

AI systems are collecting and using personal data very quickly and on a large scale, that raises serious privacy concerns. Especially given that there is limited accountability and transparency around data usage. Users have little to no understanding of how their data is being handled.

Environmental Impact

Training large-scale machine learning models has an energy cost that is substantially high and degrades the environment. Sustainable practices and greener tech are needed.

Strategies for Implementing Ethical and Efficient AI

Organizations should proactively implement ethical practices at all levels of their AI framework:

1. Create Ethical Guidelines for Internal Use

• Develop a comprehensive ethics policy that outlines acceptable AI use cases, decision-making protocols, and review processes.
• Create an AI Ethics Committee to monitor compliance with these guidelines.

2. Diversity in Data and Teams

• Ensure datasets are representative and inclusive.
• Assemble diverse teams to bring varied perspectives to AI development. Having teams that are diverse in background will help to see ethical blind spots.

3. Embed Ethics into Development

• Considering ethical implications at each stage of AI development.
• Use tools like IBM’s AI Fairness 360 or Google’s What-If Tool to regularly test for bias in models.

4. Lifecycle Governance Models

• Using ModelOps and continuous integration pipelines that support versioning, rollback, and ethical red teaming. Ethics isn’t static, it evolves as data and models do.

5. Stakeholder Education and Engagement

• Build cross-functional literacy about how models impact stakeholders, both inside and outside the organization. Embed these insights into model documentation and UX. Engaging stakeholders in an open-source ethical AI model for feedback can create a more inclusive development process.

6. Engage in Standards and Compliance Frameworks

• Align with IEEE’s Ethically Aligned Design, the OECD AI Principles, and regulatory bodies like NIST and the EU AI Act. Ethics must be interoperable and audit ready.

Forging the Future

Indeed, an ethically responsible approach to AI is both a technical challenge and a societal imperative. By emphasizing fairness, transparency, accountability, and privacy protection, organizations can develop systems that are both trustworthy and aligned with human values. As the forces shaping the future continue to evolve, our responsibility to ensure inclusive and ethical innovation must grow alongside them.

By taking deliberate steps toward responsible implementation today, we can shape a future where AI enhances lives without compromising fundamental rights or values. As AI continues to evolve, it’s our collective responsibility to steer its development ethically.

Ethical AI is a shared responsibility. Developers, businesses, policymakers, and society all play a part. Let’s build AI that prioritizes human values over mere efficiency, ensuring it uplifts and empowers everyone it touches.

A ticketing system, such as a Dynamic Tracking Tool, can be a powerful tool for MSO support teams, providing a centralized and efficient way to manage incidents and service requests. Here are some more details on the benefits.

1. Organize and triage cases: With a ticketing system, MSO support teams can easily prioritize cases based on their priority, status, and other relevant information. This allows them to quickly identify and resolve critical issues before they become major problems.
2. Automate distribution and assignment: A ticketing system can automate the distribution and assignment of incidents to the right department staff member. This ensures that incidents are quickly and efficiently handled by the most qualified support team members.
3. Increase collaboration: A ticketing system can increase collaboration between customer service teams and other stakeholders. It allows for easy and quick ticket assignment, collaboration in resolving issues, and real-time changes.
4. Consolidate support needs: Using a ticketing system consolidates all support needs in one place, providing a record of customer interactions stored in the system. This allows support teams to quickly and easily access customer history, track communication, and resolve issues more effectively.
5. Dynamics Tracking Tool: This shows various reports, such as the Real-Time Tracking Report and Historical Data Report, which are provided to monitor and analyze tracking data efficiently.

Overall, a ticketing system can help MSO support teams to be more organized, efficient, and effective in managing incidents and service requests.

Benefits of a Dynamic Ticketing Management System

1. Prioritization: A ticketing system efficiently prioritizes incidents based on their impact on the business and their urgency. This ensures critical issues are resolved quickly, minimizing downtime and maximizing productivity.
2. Efficiency: A ticketing system streamlines the incident management process, reducing the time and effort required to handle incidents. It allows support teams to focus on resolving issues rather than spending time on administrative tasks such as logging incidents and updating users.
3. Collaboration: A ticketing system enables collaboration between support teams, allowing them to share information and expertise to resolve incidents more efficiently. It also enables users to collaborate with support teams, providing real-time updates and feedback on the status of their incidents.
4. Tracking & Reporting: A ticketing system provides detailed monitoring and reporting capabilities, allowing businesses to analyze incident data and identify trends and patterns. This information can be used to identify recurring issues, develop strategies to prevent incidents from occurring, and improve the overall quality of support services.
5. Professionalism: A ticketing system provides a professional and consistent approach to incident management, ensuring that all incidents are handled promptly and efficiently. This helps to enhance the reputation of the support team and the business as a whole.
6. Transparency: A ticketing system provides transparency in the incident management process, allowing users to track the status of their incidents in real time. It also provides visibility into the actions taken by support teams, enabling users to understand how incidents are being resolved.
7. Continuity: A ticketing system provides continuity in the incident management process, ensuring that incidents are handled consistently and effectively across the organization. It also ensures that incident data is captured and stored in a centralized location, providing a comprehensive view of the incident management process.

A Support System Orbits Around 3-Tiered Support

Tier 1

Tier 1 tech support is typically the first level of technical support in a multi-tiered technical support model. It is responsible for handling basic customer issues and providing initial diagnosis and resolution of technical problems.

A Tier 1 specialist’s primary responsibility is to gather customer information and analyze the symptoms to determine the underlying problem. They may use pre-determined scripts or workflows to troubleshoot common technical issues and provide basic solutions.

If the issue is beyond their expertise, they may escalate it to the appropriate Tier 2 or Tier 3 support team for further investigation and resolution.

Overall, Tier 1 tech support is critical for providing initial assistance to customers and ensuring that technical issues are addressed promptly and efficiently.

Tier 2

Tier 2 support is the second level of technical support in a multi-tiered technical support model, and it typically involves more specialized technical knowledge and skills than Tier 2 support.

Tier 2 support is staffed by technicians with in-depth technical knowledge and experience troubleshooting complex technical issues. These technicians are responsible for providing more advanced technical assistance to customers, and they may use more specialized tools or equipment to diagnose and resolve technical problems.

Tier 2 support is critical for resolving complex technical issues and ensuring that customers receive high-quality technical assistance.

Tier 3

Support typically involves highly specialized technical knowledge and skills, and technicians at this level are often subject matter experts in their respective areas. They may be responsible for developing new solutions or workarounds for complex technical issues and providing training and guidance to Tier 1 and Tier 2 support teams.

In some cases, Tier 3 support may be provided by the product or service vendor, while in other cases, it may be provided by a third-party provider. The goal of Tier 3 support is to ensure that the most complex technical issues are resolved as quickly and efficiently as possible, minimizing downtime and ensuring customer satisfaction.

Overall, Tier 3 support is critical in providing advanced technical assistance and ensuring that the most complex technical problems are resolved effectively.

Determine The Importance of Tickets/Incidents/Issues/Cases

The first step in a support ticketing system is to determine the incident’s importance. This involves assessing the incident’s impact on the user and the business and assigning a priority level based on the severity of the issue.

1. Receiving: The step is to receive the incident report from the user. This can be done through various channels, such as email, phone, or a web-based form.
2. Validating: This step involves validating the incident and verifying that it is a valid issue that needs to be addressed by the Support team.
3. Logging: Once the incident has been validated, it is logged into an incident application, which is used to track and manage it throughout the process.
4. Screening: The next step is to screen the incident and determine the user’s symptoms. This involves asking questions to gather more information about the issue and to identify any patterns or trends that may help resolve the incident.
5. Prioritizing: Once the symptoms have been identified, the next step is to prioritize the incident based on its impact on the user and the business.
6. Assigning: After the incident has been prioritized, it is assigned to a support team that will handle it. If the support team cannot handle the incident, it is escalated to a higher-level tier.
7. Escalating: If the incident requires more advanced expertise or resources, it is escalated to a higher-level tier where it can be resolved more effectively.
8. Resolving: The support team or higher-level tier works on resolving the incident and provides updates to the user until the issue is resolved.
9. Closing: Once the incident has been resolved, the ticket is closed by logging the resolution and changing the ticket status to indicate that the incident has been successfully resolved.

Summary

Ticketing systems are essential for businesses that want to manage customer service requests efficiently. These systems allow customers to submit service requests, track the progress of their requests, and receive updates when their requests are resolved. The ticketing system also enables businesses to assign service requests to the appropriate employees or teams and prioritize them based on urgency or severity. This helps streamline workflow and ensure service requests are addressed promptly and efficiently. Additionally, ticketing systems can provide valuable insights into customer behavior, allowing businesses to identify areas where they can improve their products or services.

Health insurers today are navigating intense technological and regulatory requirements, along with rising consumer demand for seamless digital experiences. Leading organizations are investing in advanced technologies and automations to modernize operations, streamline experiences, and unlock reliable insights. By leveraging scalable infrastructures, you can turn data into a powerful tool that accelerates business success.

IDC Market Glance: Payer, 1Q25

Perficient is proud to be included in the IDC Market Glance: Payer, 1Q25 (doc#US53200825, March 2025) report for the second year in a row. According to IDC, this report “provides a glance at the current makeup of the payer IT landscape, illustrates who some of the major players are, and depicts the segments and structure of the market.”

Perficient is included in the categories of IT Services and Data Platforms/Interoperability. IDC defines the IT Services segment as, “Systems integration organizations providing advisory, consulting, development, and implementation services. Some IT Services firms also have products/solutions.” The Data Platforms/Interoperability segment is defined by IDC as, “Firms that provide data, data aggregation, data translation, data as a service and/or analytics solutions; either as off-premise, cloud, or tools on premise used for every aspect of operations.”

Discover Strategic Investments for Innovation and Success

Our strategists are committed to driving innovative solutions and guiding insurers on their digital transformation journey. We feel that our inclusion in this report reinforces our expertise in leveraging digital capabilities to unlock personalized experiences and drive greater operational efficiencies with our clients’ highly regulated, complex healthcare data.

The ten largest health insurers in the United States have counted on us to help drive the outcomes that matter most to businesses and consumers. Our experts can help you pragmatically and confidently navigate the intense regulatory requirements and consumer trends influencing digital investments. Learn more and contact us to discover how we partner to boost efficiencies, elevate health outcomes, and create differentiated experiences that enhance consumer trust.