Digital Transformation — time for a new paradigm?
Introduction
Three years have passed since the first conversations with QA about a Digital Transformation Consultant role. I have never been a fan of job titles, but recently mine has changed. It is a good time to capture some observations and consider the implications.
In many of the early conversations as I started with QA, I would introduce myself by giving my job title — Digital Transformation Consultant. Then quickly suggest that we took away the word consultant — they do not have a great reputation! Transformation was next to go because that was about change; few of us like that. Finally, since no-one could define digital, we crossed that out. There was a blank space where a title once stood. The punchline being that the blank sheet was a pretty good place to start our conversations. The value I brought to that person was not my job title. Value was from insight, perspective, and creative solutions.
In the rest of this article, I will:
· recap on the four stages — technology, edge, core, and business models
· explore developing people capability at each stage
· discuss the evolution of the stages
· introduce dynamic skills development
In a world of commoditised technologies, it is people that are the differentiator and source of competitive advantage.
There is no single plan, and the article ends with suggestions for you to consider.
From Digitisation towards Digitalisation
Words matter. Sometimes we get hung up on specifics, other times we miss important nuances. Digitisation and Digitalisation were used interchangeably and without an agreed definition.
Based on the work that I had been involved with, there are four stages of transformation. The first three were about creating a better version today and classed as digitisation. The final stage involved reimagining the way the organisation created value. This is best considered as digitalisation — a better version of the future possibility based on what technical innovation now enables.
I illustrate the four stages below –
Transformation for many organisations started with changing underlying technology that was used. This was first seen at scale with virtualisation. As the world became increasingly mobile and we had ubiquitous connectivity, then it was the ‘edge’ of the business that needed to change -the customer facing elements. Typically, new products designed for a mobile interface and service design became the new focus.
For many, edge transformation was like ‘putting lipstick on a pig’ — it looked good, but it was a thin veneer. It quickly became clear that the internal systems (and ways of working) prevented greater change in products and services. The legacy systems became a blocker for change. To make significant further progress required a lot of heavy lifting in back-end systems, which was time-consuming, expensive and had long lead times to achieve impact.
As a result, much of the early ambition for transformation faded away. I gave in 2015, titled “The Shattered Dreams of Digital Transformation” that hinted towards this barrier to progress. For many, the cost and pain of transformation would only result in survival. My argument was that if you are going to endure the cost and pain of transformation, then the outcome should be to set the pace for others. This would only happen if new business models — the final stage — could become a reality.
My role had focused much of my thinking on the role of Government and its opportunity to move from addressing market failure to creating value. I linked this to the emergence of a platform economy.
In 2015 I quoted Chris Yapp — the more certain you are about the future, the more likely you are to be wrong — and therefore am not surprised that stage 4 has not happened as fast or in the way I suggested it might.
The reality is more complex than that and the time that it takes for new models to appear and for large shifts to be achieved takes significantly longer than we may expect (or believe happens).
As a result, I think we will continue to see a more complex ecosystem in which many traditional companies continue to survive whilst some next-generation businesses set the agenda for growth. What is true is it would be a mistake to think that survival is a good outcome — that is the bare minimum.
Impact on People Capability
Had COVID not hit so dramatically only a few days into me starting my new role, then the next stage of thinking may never have occurred. An illustration that even when we think we have good noise signals about future change and disruption, we need to keep the flexibility to change considering new and emerging data.
Simon Wardley and his mapping technique increasingly convinced me we were going to see the rapid commoditisation of innovative technologies. If this happened, then the barriers to access disruptive technology would be significantly lowered as would their impact on competitive advantage. The true source of competitive advantage would be the ability of people to understand and apply technologies into new situations.
My hypothesis was that the way that we approached developing capability (taken to be knowledge, skills, behaviour, and experience) would need to be different. Just as there was a journey in transforming the organisation so there would be a shift from the ‘just-to-late’ vendor led training that had been the focus for many IT professionals earlier in their career towards much more anticipatory learning.
There would be an emergence of a more complex system of change that, if used, would create a flywheel effect. I illustrate this in the following diagram -
The thinking was that the changing world and the organisation’s transformation would create a need for a future ready capability. This would drive out a learning requirement. However, there was a shift in the approach to learning as people understood the benefits of adopting a growth mindset, which would itself become the fuel driving change. As you raised the capability of the workforce and invested in learning so the ambition and creativity leading to transformational change acceleration.
I developed this model, having seen the approach to developing capability across the four stages of transformation set out previously.
The traditional approach to technology change was focused on skills conversion, typically following the chosen vendor curriculum. Many organisations took a ‘just too late’ approach (buy the technology, train the people) that saw the IT team attending three-day training sessions every couple of years.
As the transformation moved into the edge and core stages, then the focus became on ‘just-in-time’ training. However, the reality was often a lot of ‘tail feather pruning’ took place — lots of new skills and way of doing things had certificates and badges to go with it. This stays a challenge today with branding being put over the top of core skills to create differentiation — the buyer needs to remain aware and avoid the emperor’s new clothes trap.
Where the flywheel effect would really make a difference was when there was a significant shift towards anticipatory fast learning and the adoption of the ‘eternal newbie’ mindset. The biggest barrier to progress here is mindset. Both the individual learner and the Learning and Development function. As seen earlier (circa. 2008) with the IT function, L&D was trapped in order-taking mode and seen as a cost. There needed to be a significant transformation whereby it would become a strategic partner and a source of competitive advantage. Post COVID, there are signs that this transition could take place, but it will take strong leadership to succeed — many IT teams did not make fast enough progress after the financial crash to secure themselves in that value creator space.
The one other aspect of learning and people development during this time is a focus on roles and capability frameworks. Long seen as the enabler for career progress, I would suggest they have become too rigid and difficult to apply to have had impact. Many career pathways are mapped out with progression happening in steps and people experience barriers along the way. The reality for most people is that careers are an organic journey and that the frameworks do little to recognise this. The diagram below illustrates this -
In the last section of this article, I will review this change in skills development and how we can enable a move from steps and jumps towards a more natural skills-based progression, recognising the transition state as part of that change.
Evolving Digital Transformation
This then leads to the situation today. My observations (and they are more that than extensive research) is we see fragmentation across the transformation journey. A spiral effect is starting to occur. The one consistent is that the gulf between the dreams and reality stays and few organisations are successfully able to reimagine themselves and set the benchmark for next generation growth.
The three stages tech-edge-core have become less of a sequence and are a set of continual changes in their own areas as shown in this diagram -
Technology becomes Cloud Next (avoiding the 2.0 tag), edge becomes experience, core is interoperagiliy (to be explained) and finally a recognition that future business models are likely to be created within a platform ecosystem.
I predict that we will continue to see evolving progression across the four stages combined with transformation within each stage. The overall ambition of the organisation and its ability to create a cohesive strategy will determine if they can unlock the full value available. Those that do will set the pace, others will have to continue to struggle in survival mode.
The following section explores each stage. I will also consider the implications for the approach to building people capability within the same section. I do this in recognition of the convergence of the skills approach with the transformation change.
Progressing towards dyanmic skills
For the technology domain, then there is a realisation that the ‘life and shift’ approach taken to cloud migration has not achieved the full potential and there is a need to re-architect applications and consider a multi-cloud approach. This is leading to a situation where you have an expert-novice community. People have undertaken extensive vendor-aligned training and certifications, but it has not translated into changes in workplace practice. There are many factors for this, but it shines a spotlight on what we consider is the ‘finish line’ for training — it is not the ability to complete the training but the ability to do something different or with improved performance in the workplace.
The edge, which for many organisations transformed with a thin veneer of mobile apps and other “lipstick on a pig” features, is starting to creak. The need to create a consistent customer experience across the whole organisation is forcing a rethink of end-to-end service design. Organisations need to have a single view of their customer and being able to trust the data they hold is critical to future growth. As a result, there is a need to undertake more contextualised training to grow capability. It is not sufficient to know the tools and techniques. People need to have confident application developed through experience.
The third domain was the core of the business — all the aspects that make things happen but not normally seen by the customer. I am creating a word for this domain — interoperagility. This is the shift organisations are making towards being product-centric but recognising that they will still have operating functions that exists in their own space and so they need to be able to reduce the tension between them and make it easier for things to flow but also have the agility to change the cross-company flows (including with partners, etc.) as the world around them changes.
Anyone who has made any attempts to adopt an agile delivery approach will have uncovered it is more often the mindset of the people than the method used that underpins success. When transforming the interoperagility domain, we need to adopt a mindset that is open to change, supports collaboration and is comfortable in a liminal state — that is not the old but not yet the new.
As before, the last domain brings these things together to create the next-generation business that can thrive in the platform ecosystem. I expect that many variations of thriving organisation will appear in this complex ecosystem, but they will have some key characteristics. At their heart they will be fluid, driven by clarity of purpose, balancing genesis and commodity components within their value chain, and hypothesis led in their growth ambition.
To be able to execute in this domain, there will need to be an understanding and balance of the perishable and non-perishable skills that underpin the capability the organisation has. The pace of change mandates that there is a focus on the non-perishable skills that persist over time and act as the gateway skills to being able to develop the (often technical) perishable skills that must constantly evolve.
We should note that none of these domains exists in isolation nor are the approaches to people capability development exclusive. The labels given to each are typically where the emphasis will be, but there is a recognition that we will find elements of each across the stages.
The diagram below connects the approach to capability (skills, knowledge, behaviour, and experience) to the four domains.
The last aspect to draw out will be the movement from creating a static role framework within the business towards a more dynamic skills ontology. Specific steps that traditionally exist between roles will be smoothed to create fluidity within the workforce. Using artificial intelligence will better support the identification and predication of knowledge, skills and experiences needed and it will guide individuals to develop in more incremental steps.
As the earlier diagram (repeated below) illustrates, career progression has historically been steps and jumps. This creates barriers to progression and often traps people within specific pathways. A danger of this model is that people’s identity is tied up within their job title and career pathway, increasing the perceived barriers to change. If we can remove these (artificial) barriers and enable a gradual uplift of skills over time and fluidity within career progression, then new opportunities for workforce planning will exist.
In considering this picture, there is also a recognition that we are holding in tension three futures — future work, future skills, and future society. I am specific in saying that this is ‘future’ and not ‘future of’ and will explore that further in a later post. For now, it is sufficient to recognise that there is not a single future state and that not all jobs, or skills, will develop in the same way at the same pace. The extreme position of a fully decentralised and commoditised workforce where all skills are sourced as a transaction is not something I expect to be achievable for all industries, though it should be considered within the overall workforce planning model.
Key considerations
Based on this view of the state of digital transformation then I would make the following recommendations:
1. Understand the progress that your organisation has already made and its ambition for the future. The four stages (and their evolving state) are a useful way to explore this. Being clear about where you are allows you to make informed decisions about people capability.
2. Review your approach to developing people capability for the future. There may be a requirement to think more holistically not just about skills and knowledge, but also behaviour and experience.
3. Explore the barriers to transformation internally and the points of friction that exist and prevent higher degrees of interoperagility from taking place.
I will finish with my much-used phrase — all models are wrong; some are useful for conversation. It would be great to hear your own experience of digital transformation and reflections on the future.
