Revolutionizing community access to social services: IBM and Microsoft’s collaborative approach

In an era when technological advancements and economic growth are often hailed as measures of success, it is essential to pause and reflect on the underlying societal challenges that these advancements often overlook. And to consider how they can be used to genuinely improve the human condition.

IBM Consulting and Microsoft together with government leaders, are answering that call, partnering to develop a platform to bridge the division and enhance the delivery of social services support to communities in need.

Our shared purpose

Communities face a myriad of pressing societal challenges daily, from homelessness and juvenile justice to violence, mental health and food insecurity. In response, many government organizations are adopting transformative strategies with the goal of creating a society where all individuals have access to the necessary support and resources to flourish.

Take, for instance, government leaders who are adopting a “Care First” strategy. This approach is about redirecting thousands from the criminal justice system into supportive programs tailored to their “re-entry into society” needs. These programs help communities with housing, transportation, access to substance use treatment, and other essential services.

Other innovative leaders are dedicated to preventing violence, enhancing maternal health and equipping transitional age youth for success. A broader segment of leaders are embracing a whole-person care approach, focusing on the community at large rather than specific groups, thereby integrating social services across health, education and other vital sectors.

Introducing IBM Connect360

While many government organizations across the world have a wealth of different services and programs available to them. However, they are not able to bring the power of these systems to the people and communities that really need them. In many cases, the delivery models, technology (systems), and underlying data have been developed in silos and users need to work with each system and services separately.

IBM Connect360 facilitates integrated social services delivery and transforms data into actionable information and promotes cross-agency collaboration. This solution is focused on achieving five key goals:

• Enable collaboration by creating an electronic information exchange system
• Improve citizen access to services and resources through shared information
• Empower the citizen by permitting active participation in service decisions and delivery
• Strengthen decision‐making ability through data integration and business analytics
• Increase the region’s connection to community data through interoperability

IBM Connect360 is a platform that seamlessly integrates data from various siloed social services agency systems. This capability is designed to transform and align disparate data sources with the HL7 FHIR (Fast Healthcare Interoperability Resources) and HSDS (Human Services Data Specification) standards. This is so that information is standardized, protected, and easily accessible.

By adhering to the HL7 FHIR specification, IBM Connect360 also facilitates interoperability of health-related data with a wide range of healthcare systems to drive continuity and coordination of care for individuals in need.

This transformation not only makes the data readily available within IBM Connect360 but also enables seamless interoperability with other applications. As a result, service providers can exchange and update information to provide coordinated and effective assistance for those who rely on these crucial services.

IBM Connect360, hosted on Microsoft Azure, provides the level of isolation, security, performance, scale and reliability, required to support sensitive workloads across a broad spectrum of unique requirements. As we look to the future, IBM® and Microsoft’s investment in AI and their commitment to advance responsible, secured and trustworthy AI sets the baseline for future enhancements of IBM Connect360.

Transforming lives with IBM Connect360 and Microsoft Azure

Social services encompass a broad spectrum of programs from multiple departments, such as health, behavioral health, social services, housing, justice and more, all aimed at supporting individuals with complex needs.

Meeting these needs depends on interdepartmental collaboration, which is essential for improving client outcomes. Another key factor in achieving better results is the participation of Contracted Service Providers (CSPs) and Community-Based Organizations (CBOs) through the departments’ network. Beyond directly offering services, departments also have the responsibility for providing a central resource repository that their partners can use to deliver services.

The operational model that is being used is supported by IBM Connect360. In this model, the government agency provides the foundational systems and APIs, which provide access to the core systems in near real-time. This allows various business applications to interact with each other across different departments by using these APIs.

Each entity involved in this model focuses on its core competencies: The agency manages data, establishes business rules, ensures compliance and evaluates performance, while CSPs and CBOs can create service-oriented applications that are closer to the client. This model facilitates the swift introduction of new public assistance and healthcare programs by making efficient use of the existing agency resources. The ecosystem works together during the launch process to ensure that services are delivered to clients promptly, without any delays.

“At IBM, we understand the importance of effective communication and collaboration across government agencies,” said Cristina Caballé Fuguet, Vice President, Global Public Sector at IBM Consulting. “With IBM Connect360, government agencies can connect with citizens, share information, and gather feedback, all in a protected and scalable environment. We’re proud to see how IBM Connect360 with Microsoft Azure are helping governments around the world better serve their citizens and build stronger, more resilient communities.”

Case Study: How is IBM Connect 360 helping transform one citizen’s life?

Let’s consider the fictional story of Michael, a veteran who was finding the transition to civilian life challenging. Dealing with challenges including PTSD, mental health issues and substance abuse, he found himself trapped in a vicious cycle of homelessness. How did IBM Connect 360 help him?

With a care coordinator’s help, Michael set up his account on IBM Connect360. He provided information about his circumstances, IBM Connect360 assessed his needs and provided tailored recommendations. These recommendations were for services such as interim housing, substance use treatment, mental health support, transportation, skills training and ultimately helped him find a job.

With each step, Michael grew more confident and independent. He used the recommended services diligently, found solace in his supportive community of care providers, and slowly rebuilt his life, piece by piece. The technology solution was not just a guide but a constant companion in his journey to stability.

This is not just about one man’s path to stability; it shows that the right tools, combined with a supportive network, can bring about real, positive change in a person’s life. Michael’s example is a testament to the power of compassionate intervention and the potential applications of technology in social support systems. With the right tools and support, transformation is always within reach, and a brighter future is not just a dream but a possible reality. When IBM Consulting, Microsoft, Governments and Communities join forces these outcomes can happen at scale.

Experience the transformative power firsthand

IBM Connect360 along with IBM Community Health user interface and Microsoft Azure, is a powerful solution that has the potential to bring about real, positive change in people’s lives. This comprehensive and open platform is designed to support all stages of service delivery. From understanding individual needs, to locating and connecting with the service providers that can support them and effectively measure outcomes and quality of care.

“IBM Connect360 ensures that every aspect of community service delivery is enhanced, fostering a more connected, efficient and impactful system,” said Angela Heise, Corporate Vice President, Worldwide Public Sector at Microsoft. “We are looking forward to continuing our strategic partnership with IBM Consulting and take the solution to the next level.”

A distinctive feature of this platform is its versatility in catering to a wide range of stakeholders, community members, service navigators, care coordinators, service providers and government leaders alike, will find immense value in its features.

We recommend you experience the transformative power of this solution firsthand. Reach out to your IBM Consulting and Microsoft representatives to schedule a personalized demo and witness how this solution can be tailored to meet your unique needs and requirements.

Source: ibm.com

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Building trust in the government with responsible generative AI implementation

At the end of 2023, a survey conducted by the IBM Institute for Business Value (IBV) found that respondents believe government leaders often overestimate the public’s trust in them. They also found that, while the public is still wary about new technologies like artificial intelligence (AI), most people are in favor of government adoption of generative AI.

The IBV surveyed a diverse group of more than 13,000 adults across nine countries including the US, Canada, the UK, Australia and Japan. All respondents had at least a basic understanding of AI and generative AI.

The survey was designed to gain an understanding of individual perspectives on generative AI and its use by companies and governments, along with their expectations and intent in using this technology at work and in their personal lives. Respondents answered questions about their levels of trust in governments and their views on governments adopting and leveraging generative AI to deliver government services.

These findings reveal the complex nature of public trust in institutions and provide key insights for government decision-makers as they adopt generative AI on a global scale.

An overestimation of public trust: Discrepancies in perception

Trust is one of the main pillars of public institutions. According to Cristina Caballe Fuguet, Global Government Leader at IBM Consulting, “Trust is at the core of the government’s ability to perform their duties effectively. Citizens’ trust in governments, from local representatives to the highest posts in the national government, depends on multiple elements, including the delivery of public services.”

Trust is essential as governments take the lead on critical issues like climate change, public health and the safe and ethical integration of emerging technologies into societies. The current digital age demands more integrity, openness, trust and security as key pillars to building trust.

According to another recent study by the IBV, the IBM Institute for the Business of Government and the National Academy of Public Administration (NAPA), most government leaders understand building trust requires focus and commitment to collaboration, transparency and competence in execution. However, the most recent IBV research indicates trust in governments among constituents is in decline.

Respondents indicate their trust in federal and central governments has declined most since the start of the pandemic, with 39% of respondents indicating that their level of trust in their country’s government organizations is very low or extremely low, compared to 29% prior to the pandemic.

This contrasts with the perceptions of surveyed government leaders in the same study, as they indicate they are confident they have established and effectively grown trust in their organizations among constituents since the COVID-19 pandemic. This discrepancy in the perception of trust indicates that government leaders must find a way to better understand their constituents and reconcile their views on how the public sector institutions are performing with how they are perceived by constituents.

The study also found that building trust in AI-powered tools and citizen services will be a challenge for governments. Nearly half of respondents indicate that they trust more traditional human-assisted services, and only about 1 in 5 indicate they trust AI-powered services more.

Open and transparent AI implementation is the key to trust

This year, more than 60 countries and the EU (representing almost half of the population of the world) will head to the polls to elect their representatives. Governments leaders face myriad challenges, including ensuring that technologies work for—and not against—democratic principles, institutions and societies. 

According to David Zaharchuck, Research Director, Thought Leadership for the IBV, “Ensuring the safe and ethical integration of AI into our societies and the global economy will be one of the greatest challenges and opportunities for governments over the next quarter century.”

Most surveyed individuals indicate they have concerns about the potential negative impacts of generative AI. This shows that most of the public is still wrapping their mind around this technology and how it can be designed and deployed by organizations in a trusted a responsible way, adhering to strict security and regulatory requirements.

The IBV study revealed that people still have a level of concern when it comes to the adoption of this emerging technology and the impact that it can have on issues like decision-making, privacy and data security or job security.

Despite their general lack of trust in the government and in emerging technologies, most surveyed individuals agree with government use of generative AI for customer service and believe the rate of adoption for generative AI by governments is appropriate. Less than 30% of those surveyed believe the pace of adoption in the public and private sectors is too fast. Most believe it is just right, and some even think it is too slow.

When it comes to specific use cases of generative AI, survey respondents have mixed views about using generative AI for various citizen services; however, a majority agree with governments using generative AI for customer service, tax and legal advisory services, and for educational purposes.

These finding show that citizens see the value in governments leveraging AI and generative AI. However, trust is an issue. If citizens don’t trust governments now, they certainly won’t if governments make mistakes as they adopt AI. Implementing generative AI in an open and transparent ways enables governments to build trust and capability at the same time.

According to Casey Wreth, Global Government Industry Leader at IBM Technology, “The future of generative AI in the public sector is promising, but the technology brings new complexities and risks that must be proactively addressed. Government leaders need to implement AI governance to manage risks, support their compliance programs and most importantly gain public trust on its wider use.”

Integrated AI governance helps ensure trustworthy AI

“As the adoption of generative AI continues to increase this year, it’s vital that citizens have access to transparent and explainable AI workflows that bring light to the black box of what’s generated using AI with tools like watsonx.governance. In this way, governments can be stewards of the responsible implementation of this groundbreaking technology,” says Wreth.

IBM watsonx™, an integrated AI, data and governance platform, embodies five fundamental pillars to help ensure trustworthy AI: fairness, privacy, explainability, transparency and robustness.

This platform offers a seamless, efficient and responsible approach to AI development across various environments. More specifically, the recent launch of IBM watsonx.governance helps public sector teams automate and address these areas, enabling them to direct, manage and monitor their organization’s AI activities.

In essence, this tool opens the black box about where and how any AI model gets the information for its outputs, similar to the function of a nutrition label, facilitating government transparency. This tool also facilitates clear processes so organizations can proactively detect and mitigate risks while supporting their compliance programs for internal AI policies and industry standards.

As the public sector continues to embrace AI and automation to solve problems and improve efficiency, it is crucial to maintain trust and transparency in any AI solution. Governments must comprehend and manage the full AI lifecycle effectively, and leaders should be able to easily explain what data was used to train and fine-tune models, as well as how the models reached their outcomes. Proactively adopting responsible AI practices is an opportunity for all of us to improve, and it is an opportunity for governments to lead with transparency as they harness AI for good.

Source: ibm.com

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What can AI and generative AI do for governments?

Few technologies have taken the world by storm the way artificial intelligence (AI) has over the past few years. AI and its many use cases have become a topic of public discussion no longer relegated to tech experts. AI—generative AI, in particular—has tremendous potential to transform society as we know it for good, boost productivity and unlock trillions in economic value in the coming years.

AI’s value is not limited to advances in industry and consumer products alone. When implemented in a responsible way—where the technology is fully governed, privacy is protected and decision making is transparent and explainable—AI has the power to usher in a new era of government services. Such services can empower citizens and help restore trust in public entities by improving workforce efficiency and reducing operational costs in the public sector. On the backend, AI likewise has the potential to supercharge digital modernization in by, for example, automating the migration of legacy software to more flexible cloud-based applications, or accelerating mainframe application modernization.

Despite the many potential advantages, many government agencies are still grasping on how to implement AI and generative AI in particular In many cases, government agencies around the globe face a choice. They can either embrace AI and its advantages, tapping into the technology’s potential to help improve the lives of the citizens they serve. Or they can stay on the sidelines and risk missing out on AI’s ability to help agencies more effectively meet their objectives.

Government agencies early to adopt solutions leveraging AI and automation offer concrete insights into the technology’s public sector benefits—whether modernizing the US Internal Revenue Service (IRS) tax return processing or using automation to greatly improve the efficiency of the U.S. Agency for International Development’s Global Health Supply Chain Program. Other successful AI deployments reach citizens directly, including a virtual assistants like the one created by the Ukranian Embassy in the Czech Republic to provides information to Ukrainian citizens. The new wave of AI, with foundational models provided by generative AI, could represent the new major opportunity to put AI to work for governments.

Three main areas of focus 

Getting there, however, requires government agencies to focus on the main areas where AI use cases can benefit their agencies, and its customers the most. In our view, there are three main areas.

The first is workforce transformation, or digital labor. At all levels of governments, from national entities to local governments, public employees must be ready for this new AI era. While that can mean hiring new talent like data scientists and software programmers, it should also mean providing existing workers with the training they need to manage AI-related projects. With this can come improved productivity, as technologies such as natural language processing (NLP) hold the promise of relieving the need for heavy text data reading and analysis. The goal is to free up time for public employees to engage in high value meetings, creative thinking and meaningful work.  

The second major focus must be citizen support. For AI to truly benefit society, the public sector needs to prioritize use cases that directly benefit citizens. There is potential for a variety of uses in the future—whether it’s providing information in real time, personalizing services based on a citizen’s particular needs, or hastening processes that have a reputation for being slow. For example, anyone who has ever had to file paperwork, or file a claim knows the feeling all too well: Sitting in an office for hours, waiting while employees click through endless screens, hunting and pecking for information stored in different databases. What if AI’s ability to access, organize and leverage data could create new possibilities for improving government offerings, even those already available online, by unlocking data across agencies to deliver information and services more intuitively and proactively?

Third, AI is also becoming a crucial component of the public sector’s digital transformation efforts. Governments are regularly held back from true transformation by legacy systems with tightly coupled workflow rules that require substantial effort and significant cost to modernize. For example, public sector agencies can make better use of data by migrating certain technology systems to the cloud and infuse it with AI. AI-powered tools hold the potential to help with pattern detection in large stores of data, and also be able to write computer programs. This could benefit cost optimization and also strengthen cybersecurity, as it can help detect threats quickly. This way, instead of seeking hard-to-find skills, agencies can reduce their skills gap and tap into evolving talent. 

Commitment to responsible AI 

Last but not least, in IBM’s view, no discussion of responsible AI in the public sector is complete without emphasizing the importance of the ethical use of the technology throughout its lifecycle of design, development, use, and maintenance—something in which IBM has promoted in the industry for years. Along with healthcare organizations and financial services entities, government and public sector entities must strive to be seen as the most trusted institutions. That means humans should continue to be at the heart of the services delivered by government while monitoring for responsible deployment by relying on the five fundamental properties for trustworthy AI: explainability, fairness, transparency, robustness and privacy.

• Explainability: An AI system’s ability to provide a human-interpretable explanation for its predictions and insights to the public in a way that does not hide behind technical jargon.
• Fairness: An AI system’s ability to treat individuals or groups equitably, depending on the context in which the AI system is used, countering biases and addressing discrimination related to protected characteristics, such as gender, race, age, and veteran status.
• Transparency: An AI system’s ability to include and share information on how it has been designed and developed and what data from which sources have fed the system.
• Robustness: An AI system’s ability to effectively handle exceptional conditions, such as abnormalities in input to guarantee consistent outputs.
• Privacy: An AI system’s ability to prioritize and safeguard consumers’ privacy and data rights and address existing regulations in the data collection, storage and access and disclosure.

As long as AI is implemented in a way that includes all the traits mentioned above, it can help both governments and citizens alike in new ways. Perhaps the biggest benefit to AI and foundational models is its range: It can extend to even the smallest of agencies. It can be used even in state and local governmental projects, such as using models to improve how employees and citizens search databases to find out more about policies or government-issued benefits. By staying informed, responsible, and well-equipped on AI, the public sector has the ability to help shape a brighter and better future for all.  

IBM is committed to unleashing the transformative potential of foundation models and generative AI to help address high-stakes challenges. We provide open and targeted value creating AI solutions for businesses and public sector institutions. IBM watsonx, our integrated AI and data platform, embodies these principles, offering a seamless, efficient, and responsible approach to AI deployment across a variety of environments. IBM stands ready to empower governmental organizations in the age of AI. Let’s embrace the age of AI value creation together.

Source: ibm.com

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Human-centered design and data-driven insights elevate precision in government IT modernization

Government agencies are under pressure to close the gap between the needs and expectations of their residents and the level of services that government IT systems can realistically support. When substantial investments of taxpayers’ money are allocated toward IT modernization, agencies are mandated by local legislature and judiciary to deliver meaningful improvements. Government executives face several uncertainties as they embark on their journeys of modernization. The bulk of these uncertainties do not revolve around what software package to pick or whether to migrate to the cloud; they revolve around how exactly to apply these powerful technologies and data with precision and control to achieve meaningful improvements in the shortest time possible. Residents judge the success of modernization by how much easier it becomes to transact with the government on digital devices and how much faster the government can respond to their needs. And government employees can appreciate the effort of IT transformations that make it easier and faster to do their jobs servicing the residents.

The challenge is that the IT systems that power core business functions for even a single agency are complex, supporting thousands of employee workflows and resident touchpoints. While the underlying business framework for an agency may be well established and similar across different states, the human workflows are unique to the given agency or state. Because of that, even a robust software package could not effectively meet the needs of human users right out of the box. What makes or breaks the success of a modernization is our willingness to develop a detailed, data-driven understanding of the unique needs of those that we aim to benefit. We must allow this understanding to lead the process of configuring the technology, so it meets both human and business needs with precision and control. That is exactly what most successful players in the commercial space (such as Apple) have been doing for decades—letting human-centered design determine how technology is configured (not the other way around). Often, the reason digital government experiences lag behind commercial enterprises is not a lack of funding, but a lack of human-centered design.

To reduce the risk of shortcomings and ensure that transformations are on track to meet resident, employee and business needs, those in charge of government IT transformations need to consider the following four areas, prior to technical implementation:

◉ What to improve: Understand exactly what’s “broken” and what enhancements and new capabilities are needed to fix it.

◉ How to prioritize: Use data to understand what enhancements and capabilities would bring the greatest benefit.

◉ What good experience looks like: Validate that the experience you propose is right and will be adopted by the users, before implementing it.

◉ How to quantify the impact: Quantify, articulate and measure the expected long-term benefit of a capability to justify the investment.

Using data, user research and human-centered design to effectively address these considerations can help you develop a clear modernization strategy that objectively drives your priorities, backlogs and roadmaps. This strategy is not based on a “gut feel” or anecdotal knowledge of a few individuals, but on a well-documented, expansive set of findings, business analysis and calculated projections. This approach also provides a framework that is fully transparent and traceable to the source of every finding and decision. It builds confidence that you are on the right track and enables you to articulate benefit to your stakeholders and the community in detailed and quantifiable terms.

Case study: state of Arizona

The Arizona Department of Child Safety (AZDCS) requested help from IBM to build human-centricity into a major IT transformation to advance the way their child welfare workforce and their service provider community provide services to children and their families. The motivation behind this request was the agency’s experience with an out-of-the-box platform that struggled to get traction and adoption due to its “technology-first” approach. The community of workers and providers often avoided using it because it was not designed with human users’ needs and priorities in mind. This severely reduced the business benefit expected from the platform and perpetuated negative sentiment around the digital experience provided by the agency.

As AZDCS embarked on a 3-year transformation, Steven Hintze (AZDCS Chief Data and Product Officer) prioritized a human-centric design approach to elevate the usefulness and efficiency of their Comprehensive Child Welfare Information System (CCWIS) technology platform.  They focused on a clear data-supported blueprint to achieve high marks with the platform’s human users, leading to widespread adoption, positive sentiment and measurable advancements in how well the platform supports their child welfare workforce and their service providers’ critical work functions.

To help AZDCS, IBM leveraged our Service Design for Governments methodology that was developed to solve these exact types of challenges. Focused on business and human outcomes first to inform technology decisions, the IBM team of UX designers and child welfare subject matter experts conducted user research by engaging a diverse group of stakeholders and end users of the platform. The team implemented a phased approach to the human-centered design assessment, which led to a data-driven roadmap of recommended technological enhancements. Each recommendation was grounded in the user research conducted and validated to render significant return on investment (ROI) to the business mission of AZDCS. This meant that each enhancement recommendation was not only infused with the voice of the stakeholders and end users, but also included strategic business case developments in which AZDCS was able to measure and report upon the impacts to their business.

The IBM Service Design for Government methodology follows a phased approach that focuses on improving the end user experience with data-driven prioritization with the downstream effect of increasing user adoption, leading to substantially improved business and resident outcomes.

Phase 1: Understand needs

Acknowledging that we ourselves are not the users of the agency platform is one of the most often overlooked realities in implementing technology into the health and human services’ space. This acknowledgement is critical to designing and implementing technology that meets the needs of the intended end users. For AZDCS, end user groups included internal workforce roles, contracted community service providers, foster caregivers, kinship caregivers and adoptive parents. Creating assumptions around what we believe we know about these users is not enough; we must do our due diligence and conduct research. In a Service Design engagement, user research is a collaborative and robust process that focuses on understanding user challenges and pain points, as well as gathering the data needed to measure the negative value of these challenges, so the agency can address problem areas and prioritize the roadmap. Through the analysis of collected data, potential opportunities for improvement are uncovered.

A pain point tracker (a repository of business, human-centered design and technology issues that inhibit users’ ability to execute critical tasks) captures themes that arise during the data collection process. The pain point tracker clusters the foundational data in which value metrics are then applied. For an agency with a child welfare mission like AZDCS, value metrics include multiple dimensions such as volume (what roles are impacted and how many people?), frequency (how many occurrences?), time (how much time is lost?) and quality (how does this impact service delivery, business process and data quality?). The positive value of an enhancement can be measured by how quickly a worker can navigate to data needed for timely and critical decision making; or how easily and rapidly workers can enter required data into the system, freeing up more time to engage in higher value tasks such as face-to-face time with the children and families on their caseload; or decreasing the amount of time it takes for a family to be connected with the right services that will enable them to stabilize sooner (and with better, longer-term outcomes).

Phase 2: Map current state

From the data collected in Phase 1, current state user journey maps are synthesized into golden threads—critical interconnected workflows for the top user segments.

For an agency like AZDCS, an example of a golden thread might be the journey of an ongoing case specialist, a referral specialist and a payment specialist, as each contribute within the workflow to request an out-of-home placement for a child. Throughout the visual representation of the journey, pain points are plotted accordingly. Each pain point is referenced back to the pain point tracker for full traceability of how it was uncovered and how the value was calculated, providing the basis for the ROI if the pain point is resolved.

Phase 3: Envision the future

Phase 3 shifts focus to guided co-creation with key stakeholders, sponsor users, and business and technical subject matter experts. Engaging in a set of design thinking sessions, this group converges on a future state system of experiences. This part of the process effectively turns the existing pain points and challenges into opportunities to innovate efficient and intelligent ways to conduct key business and user functions that leverage the full potential of the supporting technology. This cross-disciplinary, real-time collaboration enables rapid decision making that considers human needs, business priorities and technological realities. This shapes a path forward that delivers the maximum benefit to residents in the shortest time, with a focused investment of resources.

As stated earlier, for AZDCS the goal was a platform design that leads to high user adoption, positive sentiment and measurable advancements in how well the platform supports their child welfare workforce and their service providers’ critical work functions. Key opportunities revealed during pain point analyses (along with the measurable impacts and current state mappings) serve as the basis for the design phase of the project. They also leverage ideas from design thinking workshops where platform users and stakeholders are encouraged to think big. Subsequent activities break each big idea into smaller, more manageable technical enablers that the group can prioritize based on measurable impacts to the user and to the business.

Phase 4: Prototype & validate

In this phase of the methodology, the group builds prototypes of key user journeys using the prioritized future state ideas generated by stakeholders and end users in Phase 3. This provides an opportunity to review proposed experiences and obtain essential feedback from end users. These reviews can be factored in before enhancements make their way into production. Ideas are also vetted against available technology, as well as the agency’s platform architecture and prior investments, to further determine the value of each proposed enhancement. In this process, AZDCS and the IBM methodology work together to apply greater value metrics to determine where standard configuration of the platform/product can be achieved and where customization may be necessary. The prototype building process prioritizes the ideas that receive the highest marks for business value that are also the most feasible to implement.  As prototypes are finalized, key stakeholders and end users are brought in again to validate and refine the designs. The output in Phase 4 is an experience blueprint and product roadmap that represents the best of collaboration between IT, design and front office business. It also ensures that the agency’s platform/product roadmap infuses the voices of the end users and also represents enhancements that will deliver the greatest value to the business if implemented in upcoming builds.

Realized impact

In the absence of a human-centered, data-driven project, many agencies find themselves modernizing with a technology platform that fails to meet the needs of their workforce and stakeholders. It often requires costly iterations of customizations that still do not produce the intended value. AZDCS’ strong leadership, vision and prioritization of creating a human-centered, value-based and modernized child welfare technology platform/product is producing favorable outcomes. Rather than modernizing their system for the sole purpose of being federally compliant, AZDCS’ Chief Data and Product Officer Steven Hintze is infusing the department’s workforce with optimism, excitement and a sense of value in participating in the design of the platform.

“With a large enterprise system change like this, it’s important to engage all customers and stakeholders. When those stakeholders speak up, listen to them, and do something with their information. That doesn’t mean saying yes to everything, but it does mean making information accessible to them, being transparent with problems, teaming with them on key decisions, and trusting them as much as you expect them to trust the implementation team.”

Steven continues to lead the future of their CCWIS by co-creating with stakeholders in building an internal culture that feels supported by the modernized technology. He is dedicated to a product roadmap based on value to the workforce, value to the business and, ultimately, value to those who interact with the agency. Through a human-centered service design engagement, AZDCS is now equipped with a data-driven, value-metric orchestrated road map that guides their technology enhancement decisions.

Guided by an attitude of trust and transparency, AZDCS continues to put voices of the end users at the forefront. With an open-door invitation, the agency continues to listen to feedback and maintains consistent communication with the department’s workforce and provider community. Rather than waiting two years to fully design something new (a pain point experienced often in the design, development and implementation life cycle common to some technology projects), department leadership places high value on the service design outputs and is purposeful about adding new, human-centered design enhancements into their maintenance and operation quarterly builds.

Source: ibm.com

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Data is key to intelligent asset management

Planning for business disruptions is the new business as usual. To get ahead in a rapidly shifting environment, industrial businesses are leaning more on integrating operational technology (OT) with IT data, which allows them to move from time-based to predictive maintenance, monitoring and management. But collecting and deriving insights from data that resides across disparate applications, legacy databases, machines, sensors and other sources is a complex affair. In fact, two-thirds of business data remains unleveraged. If companies can’t turn their data into value, it’s useless.

Read More: C1000-059: IBM AI Enterprise Workflow V1 Data Science Specialist

This is where intelligent asset management (IAM) comes in.

Announced today at MaximoWorld, IBM’s intelligent asset management brings together powerful solution suites for asset management, facilities management and environmental intelligence in one integrated place. It empowers the entire organization, from the C-suite to the frontline and all along the supply chain, to make more informed, predictive decisions across key operational and functional arenas. With IAM, all players can:

◉ Monitor and measure operations for a 360-degree view of internal and external data, using asset and sustainability performance management capabilities to help balance net income with net-zero objectives.

◉ Manage assets, infrastructure and resources to optimize and prioritize activities that improve the bottom line, including new integrations between Maximo and TRIRIGA to merge best practices across property, plant and equipment.

◉ Improve product and service quality with AI and next-gen technologies that increase customer satisfaction and cost control with intuitive visual inspection and occupancy experience solutions.

IAM breaks down the walls between these traditionally siloed data sets through a holistic approach to asset management, allowing organizations to untangle their data and bring sustainability and resiliency into their business. Here are just a few examples of how clients are utilizing IAM today.

Creating an end-to-end digital utility

One example is the New York Power Authority (NYPA). The NYPA, already the largest state public power organization in the U.S., seeks to become the nation’s first fully digital public power utility. This ambitious goal is part of the organization’s VISION2030 strategic plan, which provides a roadmap for transforming the state’s energy infrastructure to a clean, reliable, resilient and affordable system over the next decade.

To help unify its asset management system and integrate its Fleet Department, the NYPA turned to IBM Maximo®. The NYPA already uses several Maximo solutions — including the Assets, Inventory, Planning, Preventive Maintenance and Work Order modules — to help manage its generation and transmission operations. But its Fleet Department still relied on separate, standalone software for fleet management, preventing cross-organizational visibility into vehicle information. With the Maximo for Transportation solution, the Fleet Department is helping to ensure optimal management of approximately 1,600 NYPA vehicles. Using this central source reduces operational downtime and cuts costs while boosting worker productivity. It also supports the NYPA’s clean energy goals to decarbonize New York State.

Harnessing weather predictions to deliver power across India

Leading companies are also turning to IAM solutions to become more responsive to changes and to ensure business continuity. They are leveraging tools like the IBM Environmental Intelligence Suite, which provides advanced analytics to plan for and respond to disruptive weather events and avoid outages.

In recent years, India has made massive strides in ensuring that every electricity-consuming entity has access to the power they need. But the country struggled when it came to the reliability and efficiency of these services. Government officials had to calculate energy predictions manually using spreadsheets that could only consider historical energy usage. This process left much room for inefficiencies, waste, and financial loss. Officials needed a new way to understand all the factors that impact demand.

Delhi-based Mercados EMI, a leading consultancy firm that specializes in solving energy sector challenges, worked with IBM to create an AI-based demand forecasting solution to help address this problem. The model combined historical demand data with weather pattern information from The Weather Company’s History on Demand data package, which enabled officials to accurately predict when and where energy would be consumed based on environmental conditions. With this data, Mercados could provide utilities with demand forecasts with up to 98.2% accuracy rate to reduce the chances of outage and optimize their costs when it came to buying capacity. This allowed officials to make better overall decisions to balance supply, demand and costs to the consumers.

Keeping cities safe and sustainable with AI and IoT

As the economics of leveraging AI and monitoring assets remotely become more favorable than large supervisory systems, ensuring this lightweight infrastructure can also provide rapid insights from real-time situation data becomes critical. This challenge is particularly pronounced when it comes to environmental issues, where connecting city systems and infrastructure resources with real-time awareness can make all the difference.

Take Melbourne, Australia as an example. Due to climate change, Melbourne is experiencing more extreme weather such as severe rainfall events. In 2018, over 50 mm (2 in.) of rain fell in 15 minutes, resulting in flash floods and widespread power outages.

To help provide protection against flooding, the city’s water management utility, Melbourne Water, operates a vast drainage network that includes approximately 4,000 pits and grates. To function properly, the stormwater drainage system requires regular inspection and maintenance, which in turn requires thousands of hours of manpower every year, often executed during the most dangerous conditions.

That is why Melbourne water turned to AI-powered visual inspection technology in the IBM Maximo Application Suite. This allowed them to use cameras to capture real-time information about their stormwater system, then leverage AI to analyze the situation and detect blockages. And because Maximo allows easy integration between management, monitoring and maintenance data and applications, crews can focus on the areas that pose the most risk to Melbourne and its citizens.

Source: ibm.com

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How AI and automation are helping America’s Internal Revenue Service better serve we the people

The delivery of public services by the government continues to evolve as citizens increasingly look for more personalized and seamless experiences. The last three years have acted as a tailwind, further pushing the demand and forcing government to rethink their service delivery models. The Internal Revenue Service’s (IRS) tax return processing function, the quintessential citizen service that touches every American household, is a powerful example of the innovation that can come from viewing public services through the lens of citizens.

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In 2020 the IRS faced significant paper tax return processing backlogs. Tractor trailers full of paper were sitting at processing centers to be opened, scanned, sorted, properly inventoried and manually processed onsite. Tax return processing delays can impact the timing of refunds for taxpayers by as much as six months or longer. And although the increase in electronic filing of tax returns has greatly reduced the number of paper returns the IRS receives in an ordinary filing season, paper tax return volume is still significant. In alignment with the agency’s strategic goals to make the IRS more accessible, efficient and effective by continually innovating operations, adopting industry leading technology and increasing the efficiency and currency of technology investments, the IRS engaged IBM to digitize its tax year 2020 and 2021 paper tax return intake process to enable remote scanning, validation and processing.

The project went well beyond paper scanning and the automated extraction of data from paper tax returns. Enabled by artificial intelligence and a digital extraction tool, with IBM’s automated data validation process, the IRS’s Modernized e-File (MeF) system ultimately accepted 76% of paper tax returns processed without human intervention. In the end, working with the IRS, the team processed nearly 140,000 paper tax returns at a significantly higher rate of quality relative to human transcription — providing the IRS with the simplicity and efficiency needed to tackle its backlog challenge. Technologies used for the project also laid the foundation for the possibility of future anomaly and fraud detection during the tax return intake process — even for paper tax returns.

The IRS is at a self-defined inflection point. IBM’s IT modernization work with the IRS is a demonstration of the agency’s commitment to the delivery of more seamless citizen services. However, as with all digital transformations, there’s still work to be done. Backlogs of tax returns may unfortunately continue into the 2023 filing season, and IBM is prepared to continue assisting the IRS in this critical work for the American people.

In today’s rapidly changing, technology enabled world where citizens have become used to services only a click away, government agencies are under increasing pressure to keep pace. As we learned during this work with the IRS, digital transformation is a marathon, not a sprint. It’s steered by continuous technology innovation that presents new, more effective ways to conduct business and deliver services. Complex challenges and growing citizen expectations make it imperative that agencies maintain the accelerated pace of digital innovation to deliver value today and tomorrow.

Source: ibm.com

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To comply with GASB 87, government organizations need a better lease management solution

Over the past few years, the corporate world has worked through achieving compliance with lease accounting standards for real estate and assets. Adherence to ASC 842 and internationally, with IFRS 16, has been a challenging journey for many. Now it’s state and local governments’ turn to shine new light on their lease obligations.

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Asset leasing is just as widespread across state and local governments as it is with private sector enterprises. While lease accounting requirements are usually applied to real estate and facilities assets, many other asset classes are commonly leased, such as IT equipment, warehouse space, warehouse equipment, water towers, vehicle fleets, cell towers and office equipment.

In the U.S., all leases associated with these asset classes must comply with regulations from the Governmental Accounting Standards Board (GASB). GASB 87, which took effect in 2021, is the new lease accounting standard issued by GASB to more accurately portray lease obligations and improve governmental financial statements.

Successfully navigating the complexities of GASB 87 compliance requires a cross-functional effort from stakeholders across the organization. Financial and accounting executives need to stay informed about the new accounting rules and the increased complexity associated with financial forecasting in the context of lease management and accounting. Real estate directors can increase efficiencies to reduce balance sheet impacts as they oversee facilities portfolios. And IT executives need to upgrade IT systems to manage finance, real estate and other core asset optimization functions.

What’s changed with the new GASB 87?

For all public sector entities, lease accounting and reporting are being wholly redefined. Under the old GASB 13 and GASB 62 standards, there was a determination about which leases had to appear on balance sheets. That’s no longer the case. Now, with minor exceptions, all leases are considered finance leases and are required to appear on balance sheets.

Further difficulty may arise when leases are scattered across departments throughout the organization. Facility leases may be part of core infrastructure groups, while transportation departments may hold vehicle or truck leases and IT may be leasing laptops, devices or datacenter equipment. There may be other unidentified specialty leases. Finally, there may be leases embedded in service agreements, which need to be identified and accounted for.

All of these leases must comply with GASB 87 standards.

Governments need a more sophisticated lease management solution

Government organizations ultimately obtain funding from legislatures and the implied consent of citizens. The ability to accurately project near-term needs and longer-term obligations through demonstrated financial control is imperative to establishing confidence to obtain future funding. GASB 87 provides an opportunity for improved financial transparency and a better understanding of asset portfolios.

Most government entities will have more than 200 leases, large ones will have far more. It won’t be possible to comply through manual efforts or spreadsheet tracking of leases. Accounting and finance leaders will have to invest in a lease management solution to help. It is not uncommon for an organization to keep documents in file cabinets, transactions in ERP systems, critical dates and options managed in spreadsheets, and workflow managed through e-mail.

Local and state government entities can focus first on integrating all leases and contracts into a digital repository to assess the portfolio. They must identify which contracts contain a lease and which are subject to GASB 87 compliance. There can also be embedded leases in some service agreements. The complexities of these contracts and leases can only be managed effectively with the right technology.

To manage real estate and asset lease contracts, organizations need a consolidated document repository and system of record. A 360-degree view containing lease history, metadata and documents with workflow is vital for contract management and regulatory compliance.

A good lease management solution does the following:

◉ Provides pre-built data structures and processes for all lease types

◉ Integrates with financial and other critical business systems

◉ Identifies underperforming and underused facilities

◉ Models alternative planning scenarios

◉ Compares financial and non-financial returns

◉ Alerts organizations to required lease accounting reviews

◉ Automates lease accounting controls

◉ Supports audits approvals and processes

Manage lease contracts with IBM TRIRIGA

IBM TRIRIGA® provides a comprehensive system of record repository to better manage real estate and asset lease contracts. It has long been among the leading integrated workplace management (IWM) solutions helping clients with real estate and lease management, space optimization, capital projects, sustainability and maintenance needs.

TRIRIGA has helped organizations manage changes in lease accounting standards and portfolio management for over 10 years, helping clients achieve ASC and IFRS compliance since those mandates went into effect.

Beyond delivering a complete solution for GASB 87 compliance, IBM TRIRIGA enables a greater sense of overall confidence in managing asset portfolios. Lease management executives can use TRIRIGA to create a repository and achieve compliance through every step of contract management, lease accounting, and lease administration.

Managing lease contracts is a complex process involving multi-step workflows that require an intelligent set of approvals and routings to provide the necessary controls over each action in the process. Once leases are executed, the monthly payment processing, OPEX management and payment adjustments can be administered. IBM TRIRIGA helps automate the entire process and reduce manual actions by enabling alerts on contracts that may trigger reviews or re-assessment. Users can replace spreadsheets with a digitized document repository and system functionality that helps to accurately determine the carrying value of lease liabilities and right-of-use assets.

TRIRIGA handles the full scope of accounting treatments to support GASB 87 compliance, from standard adoption and activation of leases to modification, reassessment and ultimately expiration or termination.

Once contracts and leases are in order, finance directors and real estate executives can also take a fresh look at portfolio planning and transaction management. TRIRIGA also supports improved sustainability and environmental management, facilities maintenance, capital projects and facilities optimization. Executives can transform the future course of their institutions with the confidence of their stakeholders.

IBM is a leader in the industry with years of experience helping worldwide clients with lease accounting compliance and portfolio management. We are now making this experience and expertise available to state and local government clients. It’s easy to grow with TRIRIGA, using our solution beyond GASB 87 compliance to create an ideal, comprehensive solution for you.

Source: ibm.com

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Commercial autonomous drone advancement

Since Amazon announced the testing of drone deliveries nearly a decade ago, commercial drones have continued their flight across a variety of industries. Organizations around the world deploy commercial drones for deliveries or to gather video or images with an onboard camera. Drone inspections are already popular in several industries, but commercial drone usage received a boost with the recent announcement that the UK is set to become the world’s largest automated drone superhighway in two years.

What are autonomous drones?

The European Union Aviation Safety Agency defines an autonomous drone as “able to conduct a safe flight without the intervention of a pilot […] with the help of artificial intelligence, enabling it to cope with all kinds of unforeseen and unpredictable emergency situations.”

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If drones can use artificial intelligence (AI) to determine when to take off, which direction to fly, how to deal with external factors and how to return once the mission is over, there will be less need for pilots or drone operators.

Why are unmanned air system traffic management and “beyond visual line of sight” critical to the future of commercial drones?

Many countries are drawing up regulatory frameworks for low-altitude traffic management to accommodate the future of drones. This framework will cover roles, responsibilities and protocols to share data as part of drone operations. In the U.S., federal agencies are creating Unmanned Aircraft System Traffic Management (UTM). In the UK, the Civil Aviation Authority (CAA) is working toward something similar.

Just like road vehicles, identification of a drone is one part of the requirement for UTM, and the FAA in the US already requires all drones to be identified. There are also plans to include Remote ID for drones that will provide identification and location information that others can obtain.

In the U.S., a drone operator is legally required to have visual line of sight (LOS) to the drone. To enable large-scale commercial drone usage like the UK’s superhighway, the regulatory framework needs to allow for “beyond visual line of sight” (BVLOS) piloting.  Some countries with large amounts of remote locations, such as Iceland, Norway and Sweden, have already enabled BVLOS as means of supporting isolated communities.

How can drone-in-a-box help?

Frost & Sullivan defined drone-in-a-box in a 2018 report on drone delivery: “Sensor, communications, hardware and software technologies have advanced to the point that innovative companies can offer semi- or fully autonomous vehicles that can be automatically launched and recovered to base stations or enclosures. These solutions are often referred to as ‘drone-in-a-box’ because structures are required to recharge, protect, or recharge and protect drones between mission legs or between different missions.”

Today many companies invest in drone-in-a-box as a mainstream component of future industrial drone operations. At least two other features will become part of this component as 5G becomes the connectivity infrastructure:

1. Transfer of the drone imagery from the base station to the processing organization to enable near real-time decision making.

2. Support for edge computing, so the drone can be directed based on what it sees during an inspection.

What supports will maximize benefits from commercial drone inspections?

When adopting drone monitoring technology into an enterprise, it is vital to create a plan that maximizes efficiency. By combining drone-captured images and videos with these seven technologies, enterprises can automate workflows and improve the productivity of their business operations.

1. Storage for imagery

Drones capture high-resolution videos of the infrastructure or asset that needs to be monitored during a drone inspection. In general, a 4K-resolution video taken at 30 frames per second needs about 760 MB of storage for every minute recorded. Recording drone footage for even just a few days can add up to terabytes of storage. Therefore, enterprises have realized cloud storage is a cost-effective way to store and back up footage for later analysis.

2. Image stitching

Stitching videos or images together allows companies to see the full structure of an asset rather than spending time and money to monitor footage for changes. This is particularly useful in large structures like bridges or construction sites. This efficient tool helps managers identify issues and observe the pace and progress of solutions.

3. Other relevant datasets to support analytics

Initially, analytics may simply compare the change in the asset over time. When additional aspects of data are included, planners can achieve richer interpretation, analysis and pattern discovery. For instance, when data on the rate of rusting, types of rust, types of structural damage from rust and types of weather patterns are used with drone images of a bridge, it assists in predicting areas of potential structural damage versus superficial changes.

Urban planners can quickly complete planning activities when existing data of nearby topography, buildings, roads and infrastructure are used along with drone images of a particular area. Similarly, the use of weather data such as temperature, wind direction, potential for rain and past data of wildfires may help experts monitor and identify a change more quickly than with just the drone images.

4. Finding patterns with people

A bridge inspector who has spent 20 years on the job is able to look at a particular crack or concrete spalling and immediately tell if it is a cause of concern or not. The expert inspector considers depth, color, location and other factors to make this assessment. Human expertise and knowledge help identify patterns to create relevant datasets that can train computers.

5. Computer vision

Computer vision trains AI to identify the same patterns an expert inspector would see. For example, by training computers to identify imagery of a variety of concrete spalling, AI can automatically monitor images of the bridge to locate defects. This complementary drone solution eliminates the need for people to go through hundreds of hours of drone footage.

6. Rules and decision making

Once people identify a set of patterns in the imagery and teach AI to do the same, organizations can set up business rules. For example, if a particular type of structural defect is found on the roof of a house, run the drone inspection again in x months to see if there is a change. In a more critical scenario, such as if the construction blueprint and actuals are out of sync, a variety of departments will be prompted to act immediately.

7. Digital twins

Drone mapping of a building or set of structures, such as a telecommunication tower, can help create a digital twin. This digital twin can then help companies understand how the physical asset is functioning based on real data. For instance, with a digital twin, organizations can study and predict the ways a hurricane could impact the position of mobile antennas on a telecommunication tower. These predictions can inform engineers of individual towers that will need maintenance in advance of such an event. Moving from reactive to predictive maintenance can save organizations from downtime and support greater efficiencies of business operations.

Evaluating drone use in your organization

Automate inspections and reducing manual effort with drones will drive significant growth in the coming years. The global drone services market is projected to grow from USD 9.56 billion in 2021 to USD 134.89 billion by 2028 at a CAGR of 45.9% in forecast period 2021-2028. As this market grows, these industries will demand more specialized drone services.

Source: ibm.com

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Three mega-trends shaping the data economy

Data Economy - A European Perspective

I recently had the pleasure of chatting with Vilmos Lorincz, Managing Director of Data and Digital Products for Lloyds Banking Group in the United Kingdom. Data is a fundamental currency in financial services, and so developing new approaches for banking protocols is critical to formulating progressive solutions for both clients and industry colleagues.

In response to a demand by the U.K. government for more transparency in financial services, the Open Banking Implementation Entity (OBIE) was set up in 2017 to deliver architectures that give customers more control of their data within a secure framework.

Lloyds Bank undertook a decisive transformation by moving their big data to the cloud and advancing data literacy for its employees, upgrading their capacity to provide benefit to clients. “We had to design the new agile operating model for more than a thousand colleagues,” said Vilmos, “helping them land in their newly defined roles, making the right technology investment choices, while engaging with more than 20,000 people.”

Vilmos emphasized that ethical behavior is absolutely critical to gaining and maintaining client trust, establishing a company’s brand as honest and responsible partners.

When asked about mega trends that are shaping the data-driven economy, Vilmos suggested three fundamentals.

1. Customer awareness: As citizens become more digitally sophisticated, they are keenly attuned to privacy and security issues. They rightfully want control of their data, expanding their ability to explore and select personal options.

2. Maturing corporations: The corporate world is advancing its ability to adopt new processes that keep pace with emergent technologies to add value to their business models and to benefit their customers.

3. Regulatory bodies: Regulators and governments are playing active roles in adjusting to new market realities, both protecting individual rights and positioning their nation to take full advantage of the opportunities of the rising data economy.

“Organizations are realizing that data is a mission-critical competitive factor and a must-have to meet and exceed customer expectations,” Vilmos explained. “They are becoming much better at deploying machine-learning and artificial-intelligence capabilities as an increasing part of their data estate.”

Vilmos advises business executives to prepare for a fast-evolving future by establishing frameworks that can accommodate the growth of the data economy and by planning how to deliver their products within the data-driven landscape.

Source: ibm.com

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