In the leadup to FutureNet World (3 & 4 May, London) we caught up with Sam Keys-Toyer, Head of Business and Portfolio Development, Managed Services Networks, Ericsson to get his thoughts on how CSPs can overcome operational complexity, the barriers to operational transformation programmes, the need redesign operations to support AI, and much more.
- Organisation, structure and culture: why is this still a barrier to driving through operational transformation programmes?
[Sam Keys-Toyer] It is certainly true that a key to successful transformation is in the hearts and minds of the people affected. A new functional and organization model is required to enable this digital transformation to service-centric and data-driven operations. If they embrace the vision and journey the chances of success increase exponentially. On that basis a smart change program is paramount supported by strong and active communications, with visible leadership involvement that engage people to propel the transformation forward.
Transformation cannot be solely focused on amending what is happening today, the real challenge lies in how to get there – it must be based on a clear vision on what the organization wants to achieve and deliver in the future. Defining this clear vision anchored on tangible and measurable business outcomes and a solid investment plan, supported by executive sponsorship must be the starting point.
Also, cultural norms for how people collaborate, especially between functions or teams, must evolve. A proactive mindset and cross domain working become default behaviors. There is a need to promote agility, speed up decision making, minimize bureaucracy and liberate peoples’ problem-solving capability.
When we analyzed our functional structures, accountabilities, governance, skills & behaviors, and ways of working, we revealed significant gaps between our needed culture and the reality on the ground, not only necessitating a redesign of the people blueprint to a flexible model but to also execute a very effective organizational change program. Big bang approaches typically don’t work, especially when technology adoption is part of the mix.
- There is a clear need to build intelligent operations for a 5G world: do you think there is a need to redesign operations to support AI?
[Sam Keys-Toyer] As 5G becomes more common and eventually 6G is introduced, network management will become more complex and require greater agility and minimal manual intervention to ensure complexity is simplified for operations. It’s important however to have the right focus. The goal of implementing AI techniques in network operations is not for the technology itself but to deliver tangible business benefits that CSPs will be able to extract only if they consider a number of keys parts of any operating model redesign or transformation, and which from experience should be addressed:
Ericsson´s holistic approach to transformation
It is important though not to be distracted by the “shiny new things”. While key enablers, automation, analytics & AI are techniques or enablers and not the solution to digitalization in isolation. Business value must be front and center to all automation and AI ideation, development, and deployment.
- In order to unlock the 5G opportunities in both enterprise and consumer markets, CSPs need to overcome operational complexity at speed: How can they accelerate the adoption of new operating models to leverage these opportunities?
[Sam Keys-Toyer] The next evolution of the Operating models must support a self-optimizing network driven by intent and underpinned by hyper-automation. This involves transitioning from people managing the network to people managing the machines that manage the network. For this to work, data/knowledge, policy, automation, assurance, analytics, machine learning and reasoning, and security must be integrated into a true Intent-Based Network.
This in turn will enable a wider variety of applications and use cases for consumers and businesses with CSPs aiming to provide configurable services with detailed agreements on functional and non-functional characteristics that require dynamic adaptation to the network. With this increased flexibility and dynamic adaptation, the network must be managed in real-time to deliver on these requirements. Concepts like “autonomous networks” and “intent” are needed to drive new propositions and automate the network’s state to meet performance KPIs, SLAs, and business outcomes.
We see three main drivers for intent in building and operating new services:
- The complexity and cost of operating 5G networks and beyond require a new level of automation – a level beyond even AI/ML today’s automation
- The need to transform operations to better meet the needs of the business
- The need for transparency and AI explainability – so that we can trace back all decisions recommended and actuated on by the system.
- The industry is well aligned on the need to transform operations to better meet the needs of the business: can you give some indication to the tangible business benefits gained by the adoption of automation and AI?
[Sam Keys-Toyer] Automation & Artificial Intelligence are essential to get the most from our data driven operations approach. The massive scale we manage enables global feedback loops that we leverage to constantly evolve our processes, grow our closed-loop automation & AI use case libraries, making it possible to handle a global network of more than 710 thousand sites and 6.4 M RAN cells with highly focused human intervention. To illustrate, the aggregated level of close loop automation within our today’s network operations is above 88% and in 2022 we reached 36 M of AI recommendations.
This has a significant tangible impact on CSPs operations business outcomes. From a network performance perspective, data-driven operations reduced network unavailability by 34 percent while decreasing customer complaints by 21 percent. On the network efficiency side, the transformation led to a significant 12 percent reduction of work orders (WO) and 24 percent less truck rolls per node and up to 8% reduction in energy consumption which has an important impact on CO2 emissions.