Businesses are right to be optimistic about the potential of Generative AI to fundamentally transform how we work and operate. However, before attempting to develop new products and services based on AI, they also need to be realistic about the challenges and implications that come with rethinking core operations, organisational design, and advanced analytics.
In terms of Gen AI, it has yet to be proven what companies can achieve. What is clear, however, is that there are multiple foundations that need to be established before Gen AI can generate value and solve complex business problems.
Thinking Enterprise Data
If we take a closer look at advanced analytics, Gen AI requires vast amounts of curated data, semantics, knowledge, and methodologies to learn effectively. A modern enterprise data platform built on-cloud with a trusted and reusable set of data products is essential to meet these requirements. Such platforms are cross-functional, providing enterprise-grade analytics and data stored in cloud-based warehouses or data lakes. This allows data to break free from organisational silos and be democratised for use across an organisation. By analysing all business data together in one place or through a distributed computing strategy like a data mesh, businesses have the potential and capability to obtain deeper and greater insights.
In the pre-generative AI era, companies could still get value from AI without having modernised their data architecture by taking a use-case-centric approach to AI. That’s no longer the case. This realisation makes solving the data challenge an urgent priority for every business, meaning companies will need to invest in their proprietary data, technology platforms, and core operations. Creating a foundational operating model can be a complex, compute-intensive and costly exercise. To succeed in a core operations transformation, this needs to be a CEO agenda item, orchestrated by leadership, mobilising cross-functional teams and business-led adoption.
Transforming Core Operations
When considering a radical overhaul of your company's operating model, it's imperative to begin with a comprehensive assessment of current state organisational design, capability, process, and data strategy. This evaluation should include an analysis of how these elements are performing, as well as how they connect and share value across functions and the wider organisation. Based on our experience, most companies excel in certain aspects but face challenges in others. Rather than attempting to tackle all issues simultaneously, it's advisable to prioritise the areas where improvement is most needed and approach the transformation in a phased manner. But whatever your starting point may be, now is the time to act.
A foundational operating model has the ability to overcome the common frictions of "lines and boxes", which include duplicative work, isolated decision-making, and a lack of cross-functional collaboration. It optimises the allocation of tasks and establishes seamless, cross-functional ways of working, resulting in increased speed, agility, and better use of scale. In our research to date, we have found that traditional and siloed ways of working are breaking down; these ways of working will now be obsolete as all roads lead to Generative AI.
Focus on Simplicity
Steve jobs once said on focus and simplicity. “Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it's worth it in the end because once you get there, you can move mountains.
I have no doubt that Gen AI will indeed, move mountains; however, to generate value in the here and now, it is pivotal to build the right foundations and make this a CEO top-down objective. Companies that prioritise a core operations transformation in 2024 will have a compelling opportunity to achieve the extraordinary.
If you need help breaking some ground with transforming core operations, we would be more than happy to help.