Revolutionising Business: The Synergy of GBS, AI, Cloud Transformation.

In recent years, I’ve witnessed a shift in the business environment especially in relation to Global Business Services (GBS). At a fundamental level, GBS is evolving into the transformation engine of organisations. Technologies like artificial intelligence (AI) are providing a platform to harness new growth opportunities.

But first, let’s take a step back and look at what sets Global Business Services apart from traditional Shared Services. Simply put, Shared Services typically focus on consolidating and standardising back-office functions. In contrast, GBS takes a more holistic approach, integrating these services with core business processes and strategies. This difference is pivotal, marking GBS as not just a function but a strategic partner in driving transformation across organisations.

From a company perspective, we’ve noticed an interesting trend where automation hasn’t been delivering the seismic shifts many anticipated would happen. Of course, automation will be important in the journey ahead. But decision-makers are realising that it is just one piece of a much larger and more complex puzzle.

Our journey into the cloud is a testament to this. With the cloud comes more dynamic elements that we haven’t encountered before. The exciting part is that it is shifting how transformation is happening at a company level – not just for us, but others as well.

Despite what many people believe, the likes of automation, the cloud, and AI are not about replacing jobs. Instead, it provides human resources with the tools they need to augment their skills and fulfil more strategic roles. While repetitive tasks will be managed by technology, human skills will always be necessary to manage the process.

We can’t forget AI and how it must still be seen as a work in progress. While we're making significant strides, it's a journey of learning and adaptation. What's becoming increasingly clear is that it's less about expanding functional scope and more about enabling capabilities – think Data, Reporting & Analytics, AI & RPA, and Cloud support.

One fascinating evolution in GBS is how we're building services around journeys and users. Generally, the transformation begins with identifying the needs of the joiners, movers, and even leavers within a company. Each of these touchpoints provides fresh insights to help ensure the GBS services are efficient and user-centric.

Companies who grow into new segments are good examples of GBS in action. For instance, a medical aid provider might tap into insurance and banking segments as the means to diversify its product offering. However, this requires an organisation to consider how best to optimise its back-office functions. It's a familiar story in the business world – growth outpacing the evolution of support functions. Often, it takes a catalyst – like a spike in back-office costs or a dip in gross margins – to trigger a re-evaluation and the realisation that a centralised back-office makes sense.

The journey to centralisation is often met with resistance. The perception of losing control is a significant hurdle for many. Yet, once overcome, the benefits are undeniable. We've seen massive improvements in efficiency and effectiveness with a centralised approach. The evolution from a purely functional focus to a comprehensive end-to-end business process integration is what we're calling Generation 5 of GBS.

In the UK, for example, the advancement of digital agents in real estate reflects how this shift is taking place in ‘the real world.’ Whether you're interacting with a human or a bot is becoming increasingly indistinct. These digital agents, powered by AI and automation, optimise back-office processing, scraping data from back-end infrastructure to inform real-time decisions.

Moreover, in call centres, advancements in AI enable real-time sentiment analysis, transforming customer interactions. This not only improves service quality but also enhances resilience and capacity management. By understanding patterns and redistributing resources accordingly, we're not just reacting to business needs – we're anticipating them.

The shift from functional expertise to an end-to-end customer (and employee) journey approach signifies a maturity in our outlook.

More than just about providing a service, GBS is putting in place a self-servicing ecosystem that moves a business and its people forward.

As GBS continues to evolve as the transformation engine of businesses, embracing technologies like AI, it goes beyond adapting to change. It’s about leading the charge and enabling organisations across industry sectors to redefine operations for the better.

What are the technology components that enable companies to fully embrace GBS in their organisational strategies. The technology ecosystem for GBS is quite broad in this regard. But the two aspects that continue to dominate the landscape is the move to the cloud and artificial intelligence (AI).

More than ever, technology is one of the central components when it comes to transforming business landscapes. Over the years, organisations invested heavily in on-premises systems. There was a strong emphasis on data security. The advent of the cloud has resulted in many business leaders being apprehensive about migrating data away from their established systems. These concerns have been mainly driven by concerns around data privacy and a perceived lack of control over what happens in the cloud. However, this mindset has started to change.

The initial step for many companies involves moving data to the cloud while managing inputs on-premises. This hybrid approach allows data to be pooled into a cloud-based data lake, enabling powerful analytics and insights. One of the catalysts that has accelerated the transition has been cloud-first organisations that can adapt quicker and more effectively to customer needs when compared to those companies still ‘limited’ by legacy systems.

Of course, moving from on-premises to the cloud is not without its challenges. There is no ‘one size fits all’ approach to follow. For businesses with extensive legacy portfolios, this shift can be protracted and complex. Even though cloud environments are not as customisable as on-premises systems, they do provide businesses with the means to quickly adopt new technologies. The past decade in South Africa has seen a significant push to the cloud signalling a meaningful change in perceptions around use cases and their importance.

Unfortunately, the regulatory environment often struggles to keep pace with the rapid advancements coming from the cloud. Over the past year, this has been particularly evident when it comes to AI. The technology moves faster than our ability to regulate. This is something that we have seen happen with cryptocurrency when it exploded onto the scene with regulation struggling to keep pace. AI, especially when it comes to its ethical considerations and inherent biases, is likely to follow a similar path.

Even with cloud computing, regulatory challenges persist, especially around data privacy. At EY, we have developed the largest secure ChatGPT system in the world. It harnesses public data without disseminating sensitive information to the public cloud. We anticipate that more companies will adopt private ChatGPT systems that better balance the need for innovation while still maintaining privacy and security.

Going forward, the line between human and AI-generated content and interaction will become even more blurred. From a GBS perspective, this will result in both opportunities and challenges. The opportunity lies in harnessing these technologies to deliver more efficient, personalised services. The challenge is in doing so responsibly, ethically, and in a manner that aligns with regulatory standards.

The evolution of GBS is not just about adopting modern technologies. Rather, it is about approaching business transformation in new ways. By embracing cloud computing and AI, GBS is not only adapting to the changing business environment but is also driving it.

We started by discussing the evolving role of GBS and followed that with a look at its technology underpinnings. Now is the time to map out the practical steps essential for embarking on the path to GBS.

The key to a successful GBS transformation lies in identifying and capitalising on opportunities that balance effort with impact. Companies must meticulously assess their portfolios through the lens of customer and employee journeys. This will enable them to pinpoint exactly what creates value and what causes friction. An effective starting point is to streamline processes for joiners and leavers, which are typically low effort yet have a high impact on the company’s functioning.

One common oversight is underestimating the friction in existing processes. Take recruitment and onboarding as an example. This is often a person’s first impression of the company. Organisations must therefore analyse not only the customer journey but also the employee one to identify high-value, high-friction areas. Once this is done, they can strategically redesign processes to improve internal efficiencies and ensure the right first impression is made and consistently managed through an employee’s ‘life cycle’ with the business.

The key to GBS transformation is not just about scoring quick wins. It is about making strategically sensible changes. This involves spending considerable time, sometimes up to nine months, redesigning processes and making sense of the underlying data. Today, the era of the 'big bang' approach to change is behind us. The focus has shifted from optimisation of specific functions, like finance, to fully integrated process design that take shared services from a cost centre to a value generator.

The evolution from shared services to business services is significant. Often, this entails a cycle of outsourcing, insourcing, and reevaluating to identify more cost-effective solutions. Throughout this, it is essential companies remain focused on what their core identity is and not get sucked into the wants and needs of individual business units. The emphasis should be on solving business problems and enabling capabilities, rather than just expanding functional scope.

Take, for example, the hype around the metaverse which has not yet delivered on its promise, and compare that to the more enduring potential of AI. The real value lies in the capabilities that GBS can unlock, such as data science and visualisation. There is a growing demand for these skills, highlighting a significant gap in the market. Companies must recognise this and work towards attracting this talent, potentially through partnerships with universities.

The cornerstone of any GBS transformation is data, which often presents a challenge due to its volume, inconsistency, and age. AI can play a crucial role in cleansing and hypothesising this data. However, the skills needed to manage and interpret this data are rare. For instance, there are only about 20,000 people globally skilled in testing large language models like ChatGPT. Companies seeking to upskill their workforce in these areas must be proactive, tapping into emerging talent pools.

GBS can indeed be a transformation agent, especially given its access to vast amounts of data. However, successful transformation requires a systemic approach, focusing on the most critical data points and balancing the capabilities of AI with the irreplaceable insights of the human brain. It is therefore not about replacing people but rather augmenting their capabilities to visualise and strategise more effectively. As we move forward, GBS stands not just as a function within businesses but as a cornerstone of strategic, data-driven decision-making and innovation.