July 21, 2026 Elementor #8833 July 21, 2026 Elementor #8833 By emgraficaJuly 3, 2026 Elementor #8354 Add Your

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The ORBIS Digital Railway Programme, led by Network Rail, was the largest digitisation programme undertaken in the UK transportation sector at the time. This multi-billion-pound initiative modernised the national rail network by replacing traditional trackside signalling with continuous digital in-cab signalling. The programme formed part of the UK government’s 10-year ‘Digital Railways’ plan, with DXC selected as the technology partner. At programme inception, many rail assets were still maintained through physical hard copies of track infrastructure and diagnostic records, with some original records dating back to the Victorian era remaining in active use. ORBIS was established to help Network Rail rebuild its data sources, define a new information architecture, design new products using geospatial interfaces, and create new symbology sets for rail network assets. The programme marked a step change in how rail assets across the UK were identified and tracked for maintenance. Its benefits were multidimensional, improving safety for track crews while increasing cost efficiency for engineers and maintenance planners. Network Rail gained the ability to monitor component lifecycles digitally, while geospatial mapping made features and components easier to locate. Maintenance costs for labour and replacement components also became subject to greater control and observability, based on the estimated lifespan of each component. I directed the research and product design for a complex portfolio of railway infrastructure systems and services within this major digital transformation programme. The customer’s objective was to geolocate and map every physical feature across the UK rail network, assign geospatial coordinates, and introduce a new classification system. My team researched track assets and evaluated them for inclusion within a new asset taxonomy. This taxonomy became the framework for the information architecture of Network Rail’s GeoRINM software product, developed by DXC in collaboration with EY, ArcGIS, Atkins Rail Consultants, and Network Rail personnel, including track maintenance officers, cartographers, and planners. I led the full system and experience design lifecycle, with responsibilities spanning research, stakeholder engagement, and close collaboration with Network Rail department leaders and an EY consultancy team. DXC and EY delivered a series of workshops and research engagements with engineering, works, and maintenance departments. I oversaw the design lifecycle end to end and acted as the primary point of contact for engagement with Network Rail’s design bodies. Governance was rigorous and strictly applied, with oversight from three separate groups: Ergonomics and Human Factors, the Design Authority, and ORBIS. My remit covered the design of digital systems, the visual representation of assets, and the development direction of the interactive experience, including interface design patterns, visual design systems, testing and validation cycles including UAT, and deployment adoption strategies.

As Global Design Lead for Workplace Services, I led the UX strategy and design for the DXC Virtual Agent product. Built on IBM Watson’s AI framework, the Virtual Agent represented an early conversational experience platform and a precursor to today’s RAG- and LLM-based technologies. At its core, Watson was designed to support question-and-answer interactions and structured conversational journeys. The DXC Virtual Agent integrated with customer applications and device estates, core systems of record, Azure AD, Graph API, and Microsoft IAM to ingest user identity, hardware, and ServiceNow ITSM data. By interpreting semantic conversational signals, the team established clear and consistent interaction patterns across the experience. I directed the architecture of these technical components, partnering with Enterprise Architects and AI Engineers to create a bot framework capable of industrialisation. Watson’s entities and intents, together with verb and noun synonyms, were trained by the DXC team using raw data drawn from ServiceNow ITSM tickets across the global support services account base. Access policies, approval models, and system-based controls were applied within the system of record, ServiceNow, and extended through to the Watson conversational front end. Initially deployed through Skype for Business in 2017, the experience rapidly expanded across web, mobile, and Microsoft Teams channels. I helped define and test the limits of rule-based algorithms in relation to language structures and the complexity of internationalisation—limitations that modern generative AI has since overcome. Within those constraints, the UX Research and Engineering teams under my leadership designed and built naturalistic, linguistic, and deterministic training models. These efforts contributed to integrated ServiceNow ITSM question-and-answer experience sets that brought an early AI-enabled solution to market. The conversational models were researched and designed with entities and intents managed locally within the product. As the functionality expanded across numerous workflows guiding users to knowledge articles, escalation pathways, and, where required, live-agent support, I defined the role of the Conversational Designer. In practice, the Virtual Agent became a conversational mechanism for collecting case data, improving context for support agents, and increasing service deflection. I led the team in operationalising IBM Watson’s language-based sentiment and emotional interpretation models, creating an extensive library of synonyms and relational terms. Although conversational experiences were still in their technical infancy compared with the advanced RAG and LLM capabilities now available through Claude, ChatGPT, ServiceNow, and Copilot, the team established core principles of experience design and conversational convention. These foundations enabled a range of use cases that supported the DXC global service desk by deflecting users to self-service knowledge articles and automating data collection for requests and incidents. In 2021, DXC introduced the UPtime framework and transitioned to Espressive Barista as its chat engine. While Barista was not based on RAG or LLM technology, its modular, cloud-based bot framework provided a more scalable approach to domain knowledge and conversational experience. Its lexicon and technology references, delivered through web- and cloud-based knowledge repositories, expanded the breadth of knowledge coverage and conversational detail, significantly improving the product experience over the earlier IBM solution. I led the exploration of use cases and experience conventions for Barista-based services, primarily building experiences that were more extensive and interconnected. Along with state management and continuation, features that were missing or clunky in Watson, Barista enabled an extension of interaction language patterns that were more naturalistic and nuanced. Whereas IBM Watson was a framework to build upon from the ground up, Barista provided a significant set of bundled common IT scenarios, and its internationalised translation services were delivered dynamically in the cloud. DXC productised this new technology as ‘DXC Digital Assistant’, and my role changed to unified experience ecosystem architect, with a more integrated, holistic vision for workplace services. This vision comprised all technologies and experiences within the new UPtime portfolio launched in 2021.

I am leading the strategy for the Workplace Experience programme, supporting deployment of an Experience Management framework including XMO structure, XLAs, satisfaction survey processes and continuous improvement mechanisms. The programme operates under a Unified Experience Data Management strategy that integrates subjective (X Data), operational (O Data) and technological (T Data) experience sources. Sources of data are consolidated into an abstracted ‘meta model’, with a consolidated data model utilising AI tools for NLP, NLU and sentiment analysis. ML features are used to recursively analyse user behavioural patterns across user segments within the ECB. User segments and operational units are monitored for experience underperformance or technology degradation, which is then addressed in real time through advanced service automation or retrospectively through XMO governance.

I established the internal UX product team for requirements evolution, workplace service research and logic, journey mapping, rapid prototyping, POC development, and prototype development, sustaining an active feedback and user-testing function within the Agile development cycle. The team also led visual design and design system development using React UI Library components, the Muuri.js layout grid, Storybook.js, and Figma design tokens and layouts. UI elements were managed and versioned using tokenisation and release versions.

I facilitated and conducted workshops for DXC’s global leadership team, active demonstrations, and show-and-tell sessions for investment leadership, while also introducing cross-organisational stakeholders from sales and operations to the mental models that underpinned the ‘unified experience strategy’. My introduction as leader to these groups also meant that I was called on to meet with customers to present user-centric product deep dives and conceptual data-driven elements.

I acted as Senior UX Architect for the product and led a team of workplace domain User Researchers, Knowledge Managers and Article Authors, ITSM Service Designers, ServiceNow Engineers, UI Designers, and Front-End Engineers. The pace of design and development was the most extreme I had established to date within the product design and development lifecycle. With absolute backing and trust from DXC leadership, I was highly effective as a cross-functional leader, translating concepts into designs and designs into development across the intensive product lifecycle.

I served as senior UX architect for workplace mobility in enterprise, collaborating with global technologists, architects and developers within the HPE and Microsoft partnership programme “Cloud, Productivity & Mobility”. I established and operationally managed a distributed UX department supporting the app factory model, spanning offshore teams across Northern Africa, India and South Asia. I evangelised user-centred design across governance, architecture and business teams and created a library of UX materials and templates to enable use-case-centred design practices.

I led the development, industrialization and global scaling of DXC’s Workplace Experience Management services, establishing a distinctive capability at the intersection of employee experience, digital workplace operations, experience analytics, service design, user experience, workforce profiling and continuous service improvement. In this leadership role, I shaped the strategy, operating model and market narrative for Experience Management (XM), Experience Level Agreements (XLAs) and Experience Management Office (XMO) services across DXC’s Modern Workplace business, helping reposition workplace services from commodity IT operations toward measurable, human-centred business outcomes. My leadership combined product strategy, commercial enablement, customer engagement and delivery governance. I worked directly across pursuit, solutioning and execution phases, supporting sales cycles and senior customer engagements with CXO-level stakeholders, including Chief Experience Officers, CIOs, digital workplace leaders, service owners and executive sponsors. I translated complex experience management concepts into practical commercial propositions, helping customers understand how workforce sentiment, service quality, operational data and technology performance could be converted into measurable contractual outcomes and continuous improvement programmes.

Over the past 12 months, market interest in DXC XM services has doubled. In response, DXC developed a DEXOps-integrated experience architecture to harvest, analyse and consolidate experience and consumption data across the service landscape. The model now supports sales cycles, XMO technology solutions and field operations. As of April 2026, 87% of DXC Intelligent Workplace customers have active XLAs. Experience data is captured through monitored feedback loops including comments, post-call surveys, voice analytics, sentiment analysis and CSAT campaigns, with governance and performance controls where required.

I directly led or supported XMO and XLA customer programmes from pursuit through execution, including Uniper, Philips, Vale, the UK Department of Health and Social Care, Kaiser Permanente, Intermountain Health, Nestlé and the European Central Bank. These programmes demonstrated how DXC could operationalise XM at scale, apply experience analytics to real-world workplace environments, and create referenceable customer outcomes linked to service quality, employee sentiment and workforce productivity. My XM leadership was instrumental in helping DXC win, expand and reference major customer engagements. I supported the activation of the Unified Experience Service in UK Government, including the Department of Health and Social Care, which became a new reference account and was nominated for a UK public sector innovation award. I contributed to Vale Mining’s award-winning XLA strategy in Brazil, supported the deployment of XLA services at the European Central Bank, completed a 12-month engagement to establish an XLA framework at Intermountain Health, and helped incorporate the XLA solution into the Nestlé workplace deal as part of a broader global customer engagement. I also supported strategic pursuits and developing opportunities across accounts including the US Army, ADNOC, ExxonMobil, If Insurance, Urenco, Mondelez and Procter & Gamble. In these engagements, I helped translate XM, XLA and XMO concepts into customer-specific value propositions, aligning DXC’s workplace services with the business priorities of executive stakeholders and the operational realities of large, distributed workforces. My work contributed to measurable maturation of DXC’s experience management capability. By April 2026, 87% of DXC Intelligent Workplace customers had active XLAs under DXC’s expanded definition of workforce experience data collection, monitoring and governance. Across the wider account base, DXC reported 214 accounts with XLAs, 70 accounts using sentiment analytics, 114 global parent companies using CSAT, 1,435 support experience segments, 29 global parent companies using post-call survey data, and 271 global child companies with post-call survey data. These figures reflected the increasing industrialisation of XM as a standard component of DXC’s workplace operating model.

I was instrumental in building the XM services team and capability base required to support this growth. I expanded the team from an initial group of 3 people to a maximum of 16 practitioners trained across XM methodologies, experience analytics, workforce profiling, service design, UX research, service improvement and XLA governance. I created the conditions for a multidisciplinary operating model in which analysts, designers, service managers and workplace specialists could collaborate around evidence-led experience improvement and customer-specific service transformation. I directly led or supported XMO and XLA customer programmes from pursuit through execution, including Uniper, Philips, Vale, the UK Department of Health and Social Care, Kaiser Permanente, Intermountain Health, Nestlé and the European Central Bank. These programmes demonstrated how DXC could operationalise XM at scale, apply experience analytics to real-world workplace environments, and create referenceable customer outcomes linked to service quality, employee sentiment and workforce productivity.

I am leading the strategy for the Workplace Experience programme, supporting deployment of an Experience Management framework including XMO structure, XLAs, satisfaction survey processes and continuous improvement mechanisms. The programme operates under a Unified Experience Data Management strategy that integrates subjective (X Data), operational (O Data) and technological (T Data) experience sources. Sources of data are consolidated into an abstracted ‘meta model’, with a consolidated data model utilising AI tools for NLP, NLU and sentiment analysis. ML features are used to recursively analyse user behavioural patterns across user segments within the ECB. User segments and operational units are monitored for experience underperformance or technology degradation, which is then addressed in real time through advanced service automation or retrospectively through XMO governance.

I have established and led experience strategy and product design teams across global organisations. A characteristic of all the teams I've led is the shared objective of reducing the complexity and effort of achievement for end users of systems and products. The fundamental practices involved have hardly changed across decades, or even centuries. The practice spans a universal interest in the needs of human societies and the interaction of groupings and individuals with the worlds they find themselves in. The practices are concerned with three areas: Discovery, Insight and Action. 1. Discovery and understanding of sequential interconnected, systemic or ecosystemic events and the laws of cause and effect. A fascination with the contradiction or paradox in human experience, or the seemingly random, consciously registered timelines and journeys that provide resolution or achievement in overcoming a worthy challenge. 2. Exploratory insights into narrative complexity that can be attained through empathetic enquiry and analysis. Then communicated through a framework of storytelling to give definition to components and contexts, characters and catalysts. Empathy is imbued into systems and value is formed, by addressing the needs and goals of a people and defined within the eternal format of the story. 3. The ability to formalise practices to support the translation of ideas and needs into interactive features and services. Constant iteration and solution refinements to multiply the value provided to service customers and product consumers. A repeatable and scaleable framework for conducting the necessary actions to make the value tangible in product.

The workplaces of contemporary globalised economies share values and cultural norms with the societies they source their workforce from. Understanding how the microcosm of the workplace is represented, within the mental model of the citizens of those societies, influences the balance between positive or negative outcomes a service can have for end users. The definition of one, or multiple, mental models within a workforce, acts as a fundamental driver for beneficial experiences. This practice influences adoption rates and learning curves, by constructing a reflection of how elements such as roles, technology, business assets and information relate to each other. A mental model provides a powerful resource which can be used as a reference structure in the shared mind of the workforce.

The study of megatrends was something I began during my undergraduate studies continued to support my understanding of factors which impact technology and societal evolution. Megatrends impact generational or multi-generational populations and once prevalent will likely impact the entire global populations, directly or indirectly. Megatrends exist in many domains and are impacted by the limitation or availability of raw materials, the constant discovery and progressive nature of new technologies and disruptive ecological or biological impacts to human societies. As a design strategist and technologist, the subjects greatly interest me as they have enabled me to understand the past, present and range of potential futures I am working under.

Driving adoption is synonymous with managing and controlling change. In my career as a leader of technology experiences for the Workplace, I have discovered that understanding how communities, distinct groups and individuals adopt or reject change is key to achieving success for my customers.

Network Rail Asset Information’s ORBIS Programme is a technology enabled business transformation programme delivering intelligent solutions designed to collect, join and exploit accurate asset data on the UK’s rail infrastructure. Combining spatial data, information technology and operational technology, ORBIS harnesses the value of mobile devices, apps, GIS network viewers and decision support tools to enable access to quality asset information – improving the ability to make quicker, more cost-effective decisions to operate a safer, more reliable railway.

I am leading experience design for DXC in our productisation of Microsoft Copilot for M365. This work is being conducted in collaboration with Microsoft and the DXC M365 practice.

I have led the Modern Workplace organisation in the transformation our portfolio from a set of technologies and platforms to a set of interconnected experiences.

In the spirit of innovation, I encouraged every member of the group to work in a deeply cross-collaborative model across research, design, technical architecture, and development engineering. Because the full product had to be prototyped and imagined, innovation was not treated as the preserve of one discipline; instead, it became part of the team’s operating culture that every question was worthwhile and every use case should be considered for evaluation. This culture of open creativity, trust, and respect permeated the group and created synergies that influenced customers, who wanted either to become part of the story or to engage DXC because of a dynamic innovation culture willing to take both calculated and uncalculated risks when the intended outcome was valuable enough. In this environment, vision was critical: it unified the group around a shared pursuit and created a willingness to experience and accept failure as an intrinsic part of the creative process. I evaluated hands-free wearable experiences designed to reduce cognitive load and organized user testing with technicians in mechanical and industrial environments. One engagement led to a targeted automotive industry solution in which motor technicians were provided with a digital twin of components, while car diagnostic information was connected via API to the cloud for HoloLens to use in real time. The solution improved safety for workers in industrial contexts, reduced cognitive load through progressive disclosure of information, and created a direct physical representation within the user’s field of view. AR and XR workplace solutions supported flow-state entry and continuity by enabling users to consume and interpret information without interruption, using interactive digital twin feedback alongside mechanisms and physical infrastructure visible in the user’s field of view.