Are you a “PLM doctor” involved in fixing #PLM implementation challenges? Let’s share on what it takes to make sense of typical symptoms, investigate root causes, mitigate business deployment risks and deploy successful remediations https://t.co/ttoGmSrMaP 30/10/2020 11:21 PM The #change equation as described by Beckhard and Harris (1987); does it make sense, and how can it actually be used in practical terms when initiating #businesstransformation journeys? https://t.co/PjsuMnGCSY​applying-the-change-equation-to-business-transformation-journeys 29/10/2020 9:25 PM Quote: the need to develop a #transformation story that creates lasting connection to the #change you want to see https://t.co/ZktEPszV0t 28/10/2020 9:48 PM The Product Owner is the #agile business relationship manager, the guardian of the vision and protector of the voice of the #customer: prioritizing #requirements, influencing the #business on making value-driven #decisions https://t.co/LCBGgptjeo 27/10/2020 9:26 PM Given the prevailing fuzzy definition of #digital, it is not surprising that business #leaders are often unsure how to evaluate the myriad #technology-enabled initiatives being proposed to them and how much #value they may create https://t.co/25P7CGyKB5 22/10/2020 6:27 PM

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 transformationCultural 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

The 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.

Lifecycle of things

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?

Provided as an example, frameworks like the above 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. 

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.

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 client requirement alignment with leadership of solution architecture and technical deployment


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A digital twin is a conceptual model representing an equivalent digital replica of a physical object or future asset, driving innovation, streamlined developments and operations throughout their lifecycle.
Adapted from Dr Michael Grieves (2011)

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.

Digital 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 these things become more complex, they begin to be used in largely interconnected predictive models. In addition, digital platforms allow operational performance optimization, enhanced collaboration, scenario planning and effective simulations.

Effective data

Concept

Aligning initial virtual twins to carry-over product strategies: 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.