As a service organization, Save the Children wants to know the impact of its programs.

And the information it needs to gather to make that judgment differs from data typically collected by reporting software, says Sarah Angel-Johnson, the UK-based NGO’s CIO and vice president of business and technology solutions.

Using traditional measures, around project outputs, was serving neither the workers nor the children they aid as well as the organization wanted. So Angel-Johnson and her IT team have been reframing their thinking, drawing on the principles of human-centered design. They’re creating personas, including one representing children, and considering scenarios from their perspectives, asking, “What do they need?”

“It has revolutionized how we approach technology and data,” Angel-Johnson says.

Angel-Johnson, herself a practitioner of human-centered design, says she started cultivating the discipline within her technology team soon after joining the nonprofit in 2020, believing that conventional IT has often missed the mark in what it delivers.

“My view of tech is it’s a ‘how’ and we’re often missing the ‘who,’” she says. “Everyone wants to adopt tech without asking, ‘Who will use it?’”

She compares that approach to making a car engine first, without considering what the driver actually needs from the engine. “In most organizations that I’ve seen, we start with tech and it’s the wrong place to start. We need to flip it,” she adds.

Human-centered design on the rise

Angel-Johnson describes human-centered design as “a mindset that puts people at the heart of any work; it’s around empathizing with people.”

But she and others note that human-centered design is also a discipline that brings specific skills and techniques to the process of building a product or service.

Technology teams build better, more robust products and services when they have a true understanding of individuals, their needs, and their journeys, Angel-Johnson says.

“I find my results are more robust. They’re closer to what’s actually needed, and I have higher returns,” she says, adding that leveraging human-centered design principles also helps technology teams deliver faster and at lower costs — mostly because they’re hitting closer to the mark on their first delivery.

This focus on the individual — the human element — happens not by chance but by intention.

Angel-Johnson established a human-centered design approach as part of her overall transformational agenda and her digital and data global strategy. She created teams that included practitioners of human-centered design (new hires as well as upskilled employees) who are “empathizing with the users” and working with product managers and software professionals using agile development principles to turn ideas into reality.

Case in point: A team recently created a child-centered tool, which sits on Salesforce, that gathers and consolidates data to illustrate whether all the projects supporting an individual child helps meet his or her needs — something that informs Save the Children not just on a project output but on overall outcome and impact.

Although specific figures are hard to come by, analysts, researchers, and CIOs say there’s a growing interest in and adoption of human-centered design. And with good reason, as adding this discipline to technology shops creates more useful and useable products and services, they say.

To those unfamiliar with the practice, human-centered design may seem similar to user interface design or more broadly to user experience concepts. But human-centered design goes further by  putting the human at the core of the entire process, not just the interface or the experience.

That’s a change from traditional IT thinking, which historically starts with the technology, says Lane Severson, a senior director at research firm Gartner. “The prominent form in IT is machine-driven or tech-centric,” he explains.

In contrast, human-centered design starts with personas and questions around the personas’ needs, wants, and ambitions as well as their journeys, Severson says.

That, according to practitioners, is what sets human-centered design apart even from user-centered design, as user-centered design still starts with the product and then asks how users will use and experience it — rather than starting with people first.

Research shows that a shift to starting with individuals and putting humans at the heart of innovation and ideation produces measurable results. Severson points to Gartner’s 2021 Hybrid Work Employee Survey, which found that employers with a human-centric philosophy across the business saw reduced workforce fatigue by up to 44%, increased intent to stay by as much as 45%, and improved performance by up to 28%.

Despite such findings, Severson and others say many CIOs and technology teams — and organizations as a whole — have yet to adopt the approach. CIOs often have more immediate challenges to address and other workforce changes to make, such as the move to agile development.

Yet Severson says more technology shops are bringing in human-centered design and seeing good returns for their efforts.

Human-centered design in practice

Katrina Alcorn, who as general manager for design at IBM leads the software design department and design thinking practice, has been a human-centered design practitioner for more than 20 years and says it’s not only a mindset and discipline but common sense.

Still, she acknowledges the approach has been slow to catch on. “You’re creating something for a human, but more often than not we have a tendency — especially with highly technical solutions — to start with the core tech and then figure out how to get people to use it,” she says. “That’s just backwards.”

Alcorn says IBM has been strengthening its muscle in design thinking. The company now offers training and certifications, which give not only designers but others working with them a common understanding of the concept and its principles as well as the language.

“What I call discovery you might call the observe phase, so we do have to align our language to be successful,” she says, adding that technologists who are good listeners and who are curious, empathetic and open to new ideas are already demonstrating key elements of human-centered design.

But that isn’t enough to succeed — at IBM or elsewhere. “It’s not enough to hire designers and say, ‘We do design thinking,’” she says. “If companies want to be successful with human-centered design, they have to create the conditions for designers to thrive.”

Here, embedding human-centered design within the product and service teams is key. As is building out those teams with staff who are familiar with the principles, value the approach, and allow time for research and other parts of the process to happen.

“You want to bring your designers in early, in the problem-framing stage,” she adds.

Delivering human-centric results

Joseph Cevetello, who brought the approach with him when he joined the City of Santa Monica in 2017, is one such CIO doing that.

Cevetello, who had learned about human-centered design during his tenure in higher education, is a fan of the approach. “There’s no better way to get to the needs of the people, the customers,” he says. “I can’t think of any better way to approach innovation than to have that human-centered mindset.”

Cevetello, who models the approach to help instill its principles within his IT team, had staffers work on a project with the Cal Poly Digital Transformation Hub using the human-centered design approach to ideate solutions. That effort paid off, as Cevetello saw his team use that approach in early 2021 when developing a mobile app aimed at making it easier for citizens to connect with the city.

Like others, Cevetello says the human-centered design process all starts with empathy. “To me, empathy is the key to all of it, empathy meaning really trying to engage in a robust inquiry into who the customers are and what their challenges are,” Cevetello says, adding that one of his first tasks was getting his IT team to think in these terms. “I had to get them to think about citizens as customers and these customers have needs and desires and they’re experiencing challenges with what you’re providing. It sounds simple, but it’s very transformational if you approach it from that perspective.”

Sathish Muthukrishnan, the chief information, data, and digital officer at Ally Financial, also believes in the value of human-centered design and the need to start by asking, “What do people really want?” and “What do customers need from banking?”

“We have moved from problem-solving to problem definition,” he explains. “So we’re sitting with marketing, sales, internal engineers, finance and figuring out what we’re really trying to solve for. That is different from building something for people to buy.”

To build the capacity to do that, Muthukrishnan created an innovation lab called TM Studios, whose workers engage directly with customers, handle external research and review customer feedback. (Technology team members rotate through TM Studios to gain and enhance their human-centered design skills, Muthukrishnan notes.)

Muthukrishnan also looks for new hires with experience and skills in human-design thinking, and he offers training in the discipline for employees. Furthermore, Muthukrishnan expects his team to put human-centered design to use, starting with the inspiration phase.

“That’s where you learn from the people you service, immerse yourself in their lives, find out what they really want, emphasize with their needs,” he says. That’s followed by ideation — “going through what you learned and how Ally can use that to meet their needs” — and then implementing the actual product or service.

Muthukrishnan says these tactics ensure “what you’re delivering is most useful and extremely usable for the consumers you’re building for,” adding that the approach enables his team to consider all potential solutions, not just a favored technology — or even technology at all.

Ally’s conversational AI for customer calls is an example of the results. Ally Assist, as it is called (“We don’t trick people into thinking it’s a person,” Muthukrishnan says), will transfer customer calls about Zelle money transfer issues to a live person because Muthukrishnan’s team recognized through its focus on customers “that those are issues that need a human interface.”

“That,” Muthukrishnan adds, “is human-centered design.”

Design Thinking, Software Development

New collaboration-enhancing technologies are transforming three-dimensional (3D) design and accelerating content creation. The film industry used to require years of work from hundreds if not thousands of visual effects (VFX) artists to create a single 3D movie. In the case of 2009’s Avatar, over 900 VFX artists on separate design teams spent three years creating otherworldly flora, fauna, humans, aliens, and machines.

Though 3D design technologies have matured since then, many tools used by today’s design teams lack interoperability. Heavy 3D production pipelines are becoming increasingly complex as artists, designers, engineers, and researchers integrate technologies like global illumination, real-time ray tracing, AI, compute, and engineering simulation into their daily workflow. Compounding these challenges are a growing, diverse and increasingly remote or hybrid design workforce that must contend with arduous workflows and increasing expectations for physically-accurate, photoreal simulation.

Enter virtual desktop infrastructure (VDI). Specially developed VDI environments for 3D design enable authorized users secure from-anywhere access to a desktop environment containing the digital tools they need to do their jobs. The result is real-time collaboration across dispersed teams, more design iterations for higher quality work and faster production.

Enable Immersive Visualization and Accurate Simulation

VDI is built for speed, collaboration, and stringent security from cyberthreats from the data center to the endpoint. And it’s already revolutionizing 3D workflows across industries. Even before the pandemic and social distancing, the VDI market was growing. A recent study forecasts a blazing compound annual growth rate (CAGR) of over 20% between 2022 and 2030, when the global VDI market will be worth over $78 billion.

VDI connects design teams on a single, interactive platform fueled by powerful servers and virtualized GPUs. Teams can do their very best work in a shared virtual space integrated with leading design, animation, and visual effects software. Creators, designers, researchers, and engineers can work together from anywhere, on any device, without having to deal with importing and exporting massive files. 

Workflows are simplified as near-instantaneous updates, iterations, and changes with no need for data preparation.  With real-time application interoperability, infinite iterations are possible at no additional cost. Design teams are empowered to take creative risks to achieve new heights of quality and innovation with faster time-to-market.

VDI for 3D Design

It is no small task to provide access to high-performance compute power to a geographically distributed team in a way that enables collaboration without compromising security. But to remain competitive and retain top talent, organizations have no choice but to provide a virtual platform that enables designers and reviewers to work together in real-time across leading software applications in shared virtual 3D worlds from anywhere. 

Dell Technologies and NVIDIA are working together to deliver a powerful GPU-accelerated VDI solution that is available anywhere for collaborative immersive 3D design workflows. Dell Validated Design for VDI with NVIDIA Omniverse™ Enterprise fundamentally transforms complex design workflows for organizations of any size and 3D projects of any scale. VDI helps streamline delivery, protection and management of 3D collaboration applications for remote workers. NVIDIA Omniverse™ software on Dell hyperconverged infrastructure provides a reliable and repeatable foundation for remote 3D graphics. The solution unites teams, assets, and software tools in a shared virtual space, enabling diverse workgroups to collaborate on a single project file simultaneously.

3D Design Collaboration in Different Industries

3D workflows are now an essential component of every industry. Everything that will be built, will first be designed and simulated in virtual worlds. Here are some of the ways diverse teams across different industries are leveraging a shared virtual space using VDI to revolutionize 3D design workflows.

Media & Entertainment: Content creators can leverage VDI to operate in real-time using a variety of industry‑standard applications and bring together internal and external tool pipelines from multiple studios, enabling multiple personnel to collaborate, render final shots in real‑time, and create massive virtual sets.Architecture, engineering, construction, and operations (AECO): Building design products can be handled from any location. The VDI environment can be used, for example, to create a digital twin to simulate a construction project and then to monitor and optimize it throughout its lifecycle for maximum efficiency, quality, and cost savings.Manufacturing:  Geographically distributed design and engineering teams and third‑party contractors and suppliers can seamlessly connect and collaborate throughout the production design process, from early‑stage ideation concepts to smart factory automation and robotics workflows.

VDI offers enhanced collaboration amongst innovators in nearly any industry. Learn more about how Dell Technologies and NVIDIA are enabling remote 3D design with Dell Validated Design for VDI with NVIDIA Omniverse

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Intel® Technologies Move Analytics Forward

Data analytics is the key to unlocking the most value you can extract from data across your organization. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Just starting out with analytics? Ready to evolve your analytics strategy or improve your data quality? There’s always room to grow, and Intel is ready to help. With a deep ecosystem of analytics technologies and partners, Intel accelerates the efforts of data scientists, analysts, and developers in every industry. Find out more about Intel advanced analytics.

Collaboration Software

Developing and deploying artificial intelligence (AI) solutions efficiently and successfully in businesses requires a new set of skills, for both individuals and organizations.  In a recent study, over half of companies that have successfully deployed AI applications have embraced an enterprise-wide strategy that is inclusive, open, and pragmatic, using homegrown AI models 90% of the time. They have spent time understanding and documenting consistent and effective ways of rolling out projects and processes to drive efficiency. 

AI is Booming. Wanted: More People & Best Practices.

AI in business is advancing at a brisk pace. The market is forecast to grow at a Compound Annual Growth Rate (CAGR) of 36.2% between 2022 and 2027, when it will reach $407 billion, according to a recent study by MarketsandMarkets. But the report cautioned that: “The limited number of AI technology experts is the key restraint to the market.” The same lack of enough skilled personnel, along with established processes for deploying AI, was also cited in a recent global study of 2000 businesses by IDC.

Thirty-one percent of companies surveyed were actively using AI while the others were still in prototyping, experimentation, or evaluation stages. Significantly, companies using AI – considered early adopters – have integrated their AI platforms with the rest of their data center and cloud environments instead of running AI in silos used by separate groups. They have defined holistic, organization-wide AI strategies or visions along with clearly defined policies, guidelines, and processes. 

Another characteristic of these early AI adopters is that they use internal staff instead of external vendors to deploy AI applications. They also prioritize training line of business managers to use outcomes from algorithms and to tap these stakeholders to help guide new projects. This connection between IT and business leaders results in a high degree of support from C-level executives on down. 

AI Environments are Complex

To provide the massive compute power and data storage resources required for AI applications, businesses typically use systems with graphical processing units (GPUs) that accelerate applications running on the CPU by offloading some of the compute-intensive and time-consuming portions of the code. High-speed storage, parallel processing, in-memory computing, and containerized applications running in clusters are other techniques that are part of AI solution environments. 

Working with such complex technology requires the right training and experience. According to Datamation, there are 55,000 jobs currently listed under “artificial intelligence” on LinkedIn. Many if not most of these jobs (e.g., AI engineer, data scientist, AI/ML architect, AIOps/MLOps engineer) require years of education and advanced degrees. Yet the IDC study makes clear how much more effective AI projects are with these personnel designing models and collaborating with stakeholders in-house.

Scaling an AI Environment for Critical Healthcare Diagnoses

A leading pathology diagnostics firm in the U.S., that works with top biopharmaceutical and medical organizations around the world, has developed its own best practices for designing and deploying AI applications. Project teams at the firm include IT professionals, machine learning engineers, and data scientists who specialize in the biomedical industry.  Line of business managers also help guide the development of algorithms, 90% of which are developed based on the use of inhouse models. 

Many team members work primarily alone, then collaborate to deliver complex projects. With fluid, continually evolving project requirements, the company uses the Agile software development process that anticipates the need for flexibility in a finished product. To ensure that the technology they use (including GPU-based compute with high-speed and object-based storage and file-based access to Kubernetes clusters) is kept up-to-date and future proofed, the firm relies on close partnerships with vendors to review product roadmaps and anticipate and incorporate new features.

Agile development requires a pragmatic approach. IT managers at the firm insist that developers evaluate their work critically in the design phase and be willing to start from scratch if an approach isn’t working. In IDC’s survey, the companies actively using AI take an average of three months to build machine learning and deep learning models where AI laggards commit a fraction of that time. Deployment in AI early adopter companies like the pathology diagnostics firm, however, is accelerated because developers have already done their homework and obtained buy-in on models and validation from data scientists on technology purchases. 

Summary of Best Practices for Effective Use of AI 

As more C-level and line of business executives recognize and prioritize the use of AI as an effective tool to enhance competitiveness and drive efficiencies, the barriers to adoption have also become clear. Companies achieving success with AI have invested in people with skills and expertise. They have established vendor partnerships to future-proof solutions by staying up-to-date on evolving product roadmaps. They have fostered collaborative and highly flexible development environments that can alter course based on changing business dynamics. Using mostly homegrown models, they are committed to taking the time required to get the design of algorithms right before moving to well-defined established deployment processes.  Finally, AI development teams mentor business stakeholders, working with them to uncover and apply actionable insights from data analytics. 

Download the new IDC report to learn more about what is separating AI leaders and laggards. 

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Intel® Technologies Move Analytics Forward

Data analytics is the key to unlocking the most value you can extract from data across your organization. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Just starting out with analytics? Ready to evolve your analytics strategy or improve your data quality? There’s always room to grow, and Intel is ready to help. With a deep ecosystem of analytics technologies and partners, Intel accelerates the efforts of data scientists, analysts, and developers in every industry. Find out more about Intel advanced analytics.

Artificial Intelligence