Digital continuity across the value chain: the right information, where needed, when needed, for as long as needed
Smart everything
Xlifecycle Ltd provides digital continuity and business transformation consulting services, helping organizations make the most of their digital strategies in order to:
ADAPT to change
Discovering and aligning requirements from new technologies, products and market attributes, customer expectations, to sustain competitive advantage, while continuously managing total cost of ownership
ADOPT digital continuity solutions
Aligning people, data, process and technology across the business change roadmap, managing complexity and cross-functional stakeholders, defining critical success factors, from RFQ definition to project service transition, including vendor & partner delivery and relationship management
TRANSFORM operating models
Defining fit-for-purpose operating practices and new organizational structures to maximize value from digitization and IT modernization, aligning skills and talents to education requirements to enable effective deployment and operational transition to minimise time-to-value realization
Digital transformation is not just about throwing technology at the problem; successful implementations often (always?) relate to business change and alignment across multiple perspectives: from people to data, processes, tools and technologies.
Unless there is a change and an adaptation blended across all pillars, there is no or little transformation. Cultural alignment is vital for digital transformation to work, so getting people on board should be the first concern.
Prioritizing digital transformation initiatives requires continuous capability development and digital roadmaps, coupled with a robust understanding of how much change the business can deal with, in a given period of time.
Digital transformation – towards smart everything: products, engineering, operations and industry 4.0
Lifecycle of thingsThe rapid pace of technological change brings both opportunities and challenges for businesses, across domains and industries. As a matter of fact, every organizations increasingly rely on technology to differentiate their products, services, user experiences and operations, seeking for effectiveness and efficiency across their “X" lifecycle, where X = product, application, asset performance, talent, technology, data, process, material intelligence, etc.
Each of these things follow their respective lifecycle maturity change stages, as they coexist concurrently and evolve in iterative and interlinked loops.
A digital transformation occurs when a business uses digital technology to change the way it operates, particularly around customer interactions and the way value is created; it implies business transformation, rather than IT transformation.
Digital transformations require challenging the status quo and experimenting with new ways of working, new operating models and new technologies. They are contextual to each and every organization; this is mainly due to cultural and contextual factors, but also to industry and organizational maturity.
ASSESS
Is this a technical upgrade, a business transformation, or both?
ENGAGE
Are the teams engaged and committed to the change?
EXTEND
Who will benefit from the change and how will value be realized?
FOCUS
Are priorities aligned across the business and support functions?
MEASURE
How to track and measure progress with business owners and change leads?
EVOLVE
Is the organization ready to operate effectively once the change is implemented?
SCALE
What are the next steps in the transformation roadmap?
LEARN
What are the lessons learned to feed into next improvement steps?
A common definition of digital maturity which applies to every context can be hard to pinpoint, hence it can be difficult to benchmark one organization with another. It is critical to communicate extensively about the digital strategy internally - especially in the language that the current leadership team can relate the most.
Successful transformations require more than executive awareness (necessary but not sufficient requirement); it is enabled by a combination of active business engagement, fostering continuous attention to deliver impactful and relevant messages at all levels, including C-level and B-level decision makers.
Regardless of the industry, organizations manage common pressures from profit margins, competitive advantage, customer expectations, sustainable performance, compliance, customer differentiation and technology requirements which drive the need for digital transformations.
The proliferation of new technologies has opened the door to new business opportunities, enabling organizations to align and create new business models to improve their operations, from their value chain to their value system. It is important to understand why companies seek to transform digitally, both from a content perspective and in what context, as well as how they formulate and implement their business transformation strategies.
The value chain includes the various activities within the organization's boundaries, from inbound logistics to services, and also consists of supporting activities to facilitate the end-to-end production process. The value system, on the other hand, extends to suppliers upstream and also to channels and end-customers downstream.
1. ASSESS
Is this a technical upgrade, a business transformation, or both?
1. ASSESS
How is change embraced? What is the training and communication culture? What are the anticipated hindrances? What mitigations are required?
2. ENGAGE
Are the teams engaged and committed to the change?
2. ENGAGE
How will the change be implemented? Who will drive what? Who are the supporters and detractors? How to influence them? How will they be managed? By whom?
3. EXTEND
Who will benefit from the change and how will value be realized?
3. EXTEND
How will continuous benefit realization be tracked? How can value be maximized across the enterprise What is the speed of value creation?
4. FOCUS
Are priorities aligned across the business and support functions?
4. FOCUS
How is the scope controlled? What are the technical and business dependencies? How well is the deployment plan managed? When will early benefits be realized?
5. MEASURE
How to track and measure progress with business owners and change leads?
5. MEASURE
What are the CSFs and KPIs to define and track progress towards successful change? Who are the business owners and champions?
6. EVOLVE
Is the organization ready to operate effectively once the change is implemented?
6. EVOLVE
Who are the early adopters? How will the change agents operate? What decisions will be required when? How will production impacts be handled?
7. SCALE
What are the next steps in the transformation roadmap?
7. SCALE
Does the deployment strategy require refinement? Have business priorities change? Which capability and / or business function will be deployed next?
8. LEARN
What are the lessons learned to feed into next improvement steps?
8. LEARN
What worked well and not so well? Was the organization ready and able to adapt? What is likely to happened next time and are risks mitigated?
The above framework can help define new operating model enabling organizations to move through transformation roadmaps while accounting for a period of significant change, both internally and externally.
where X = product, application, asset performance, talent, technology, data, process, material intelligence, etc.
Digital thread: a path to adopt innovative and transformative capabilities – connecting talents and digital twins
Following the digital thread across the extended enterprise, connecting data across multiple functional capabilities, including product innovation, enterprise execution and asset performance value chains.
The digital thread encompasses all meaningful relationship connections across business functions, between all product’s digital assets – and their maturity over their respective lifecycle – including (albeit not limited to):
- Version iterations of Bills of Materials (BOM)
- Mechanical materials
- Electrical materials and electronics
- Software
- CAx models
- Marketing and technical requirements
- Product and process simulations,
- Service manuals
- Technical publications
- Component applicability for product variants
- Non-geometrical data such as color or weight attributes
- Cost and budget models
- Asset performance (machines and products in operations)
- Etc.
Delivering value from digital twins, as well as any digital assets for that matter, requires a combination of business change, lean operations, pragmatic delivery and continuous improvement upon service transition from a strategic initiative into business-as-usual maintenance and support.
Robust Business Change
Robust change business case leadership and ongoing maintenance throughout benefit realization
Lean Operations
Lean and effective implementation governance, data and people focused deployment; stakeholder management
Pragmatic Delivery
Technical delivery management; vendor and third party performance coordination; operations and PMO
Continuous Improvement
Continuous requirement alignment and technical solution architecture principle leadership
A digital twin is a conceptual model representing the digital equivalent representations of a physical asset, or asset-to-be, driving innovative and lean developments and operations through their entire lifecycle.
Digital twin technology: why and how it matters?
Digital twins are live digital representations of physical assets (which exist or are yet to be created in the real world). In other words, they are virtual models of the real thing, and can be either related to a product or process. Multiple, yet different, virtual / digital twins are used throughout the product lifecycle to simulate, predict, and optimize the product and production system before investing in physical prototypes and assets.
Effective dataDigital twins are multi-purpose representations of the real; they coexist across to product maturity development stages; all digital twins do not serve the same purpose, they range from product concept to industrialization and operations. They include CAD, CAE and other CAx models, but also non-geometrical data and mathematical models. Digital twins also include predictive twins which are to model future state and behavior of a device, product or service.
Their scope moved beyond manufacturing and into the merging worlds of the Internet of Things, Artificial Intelligence and data analytics. As more complex things become inter-connected, predictive models, advanced digital hubs and platforms provide business analysts, data scientists and other professionals with the ability to optimize operations throughput efficient collaboration, scenario planning and simulations.
Concept
Aligning start-up virtual twins to carry-over strategy: concepts are architected based on product and platform-based virtual models, including cost models, concept BOM, market and technical attributes, CAD carry-over, make or buy strategy, technology benchmarking, virtual product definition, cost base and virtual build requirements.
Industrialization
Gearing development digital twins towards seamless delivery: products are developed and industrialized while the enterprise is concurrently getting ready for start of production; aligning product and platform requirements to achieve economies of scale and scope across the extended enterprise and including design and manufacturing partners.
Operations
Providing in-field operational digital twins for continuous service: from connected products, asset optimization and shelf life extension, on-air embedded software monitoring and updates, asset performance optimization using machine learning, leveraging IOT, big data and AI to extend the product lifecycle.
Each function, business or technical domain requires different types of models, whose virtual twins are digital representation of the real, tailored for specific context and boundary condition validation. In the concept and industrialization stages, digital twins aim to simulate the physical product or, to be more precise, represent a subset of its behaviour.
During the operations phase, digital twins leverage the Internet of Things (IoT), product and infrastructure connectivity, support and enhance the way products are used and maintained, continuously embedding new requirements while minimizing disruption and improving customer experience.
Tweets by lionelgrealou