In today’s business environment, transformation is a constant. With these shifting sands, an organisation’s propensity and readiness for learning can be the difference between floundering or flourishing.
My recent experiences show that cloud native migrations acutely increase the learning curve, and that younger employees often learn faster than their more experienced colleagues. With the right engagement and support, a more informed (and more refined) approach to learning can be brought to bear to overcome some of the biggest migration challenges for enterprises.
Helping people make the leap
NTT DATA UK is delivering some large transformation programmes and on-prem to cloud native migrations, all of which involve a significant amount of upskilling and change management as the users adapt to new processes and technologies.
Was it their openness to new technologies and lack of scepticism that helped them progress quickly, and laid the foundation for the next levels of knowledge?
But it is in knowledge transfer that one of the biggest challenges lies. For one client, their transformation journey began with pilot projects, before the larger migration kicked off. Knowledge was concentrated in the platform team, limited to operational staff. Self-guided training exercises were provided along with guidance on using the new platform, but engagement was lacking.
As the pilot continued, we changed tack and started to present the new technologies, demonstrating them in the future target state. But feedback from the client was that their staff were struggling to keep up with topics. Some felt left behind; others felt the leap was too big from their current ways of working. The majority of the staff are highly experienced, professional engineers – it was not expected that it would be difficult for them to learn these new technologies.
The next phase of the migration will only introduce more change into the environment and require a fast rate of learning; we had to refine our approach.
Understanding patterns of learning
Working alongside me at the same client were a number of graduates from the NTT DATA Tech Academy programme. Two were assigned to work with me on a cloud native build-out last year. They had limited IT experience, and little or no experience in cloud or in the Kubernetes platform; so we started with some basic training, but soon moved on to pair programming and working on real-life requests and issues.
Initially, the emphasis was on experimentation and learning – not on delivery. They quickly immersed themselves in the technologies and have progressed faster than their senior colleagues. During this period, the graduates were also asked to constantly reflect on their learning, playing it back to me as their mentor, and their peers in the Academy. This reflective process consistently helped them reset for the next set of tasks, and ensure they got the feedback they needed.
The nature of cloud native technologies is that they are constantly changing. The best solution for the problem at the start of the project might be obsolete by the end of the project.
We considered what it was that resulted in the quicker adoption by the younger cohort than by the veteran employees. Was it their openness to new technologies and lack of scepticism that helped them progress quickly, and laid the foundation for the next levels of knowledge? Perhaps more experienced engineers, overvaluing their existing knowledge, were blocking themselves from letting new information in and potentially ‘washing out the old’. All we know is that this phenomenon is very real, and can be crippling to large enterprises unless addressed head on.
Recognising and accounting for complexity
Using the Cynefin framework, if we were to categorise the challenges set out in this cloud native programme, they largely fall into the Complex domain. This is a domain of tacit knowledge – difficult to transfer, difficult to learn. As this domain is also likely to be unclear in direction, there is a greater risk that people will struggle to buy in.
The nature of cloud native technologies is that they are constantly changing. The best solution for the problem at the start of the project might be obsolete by the end of the project. This domain leads heavily towards collaboration, and encourages prototyping for fast feedback loops to help decision making. If decisions can’t be made now, take a short-term direction and iterate.
This is naturally how the graduates started working. They had the freedom to prototype and feed back with little pressure on them to deliver.
Advocating engagement and reflection
Taking time out to focus on training or a new skill while you are performing your existing role is very difficult. The context switch takes time. Using immersive methods can help engage people when they are on training exercises, so they are more likely to focus and learn effectively.
Similar to DevOps simulators, cloud native simulators and scenario-based learning can enable organisations to play out real-world examples in a safe environment. The next level in immersive learning, in the new remote working world, could very well be VR-based simulation training, which would be ideally suited for simulation style training. Introducing the graduates to a live project early in their training helped them develop their real-world experience.
If decisions can’t be made now, take a short-term direction and iterate.
Recently on a leadership course, an exercise encouraged us to openly reflect on each other’s leadership qualities. It struck me how powerful reflective feedback can be in a learning environment. It is not uncommon in more formal training environments to have these reflective periods to write down or play back what you have learned, but it is rare to find this in a more unstructured learning format.
Taking critical reflection on your work and learning has an important part to play in transformation, particularly in unlearning no-longer-useful old habits. The sheer act of writing it down, and allowing others to critique your interpretation requires humility and courage. Perhaps, the more experienced we are, the harder it can be to critically reflect on our own actions. Straight out of the Tech Academy, the graduates were more open to continuing this style: keen to share, and accepting of feedback.
…
The agile organisation is always learning, and with every crisis or unexpected situation comes the opportunity to revisit old assumptions, and make a change that affects everyone positively. Through my experiences, I’ve learned that when it comes to knowledge transfer, teams must adapt their approach to communications as they go, always taking on feedback and adjusting to maximise engagement, buy-in and ultimately, chances of success. Equally, time and care must be taken to account for the different learning styles of different cohorts. In a complex organisation (and a complex world), distributed decision-making and collaboration is the only way to prevail. And lastly, for learning to be as effective as it possibly can be, leaders must create time and space for reflection and honest self-assessment, if they are to cultivate the environment that best promotes personal – and company – growth.
