On-demand technologies, the numbers don't add up

Increasing the ability to innovate, improving operational agility and strengthening competitiveness: a dogma for millions of companies engaged in the digital transformation process and which see public cloud services, Software as a Service (SaaS) applications and generative artificial intelligence tools as the technologies of choice to achieve this goal. But while the advantages of adopting these solutions are objective, a recent study by Capgemini Research Institute ('The On-Demand tech paradox: balancing speed and spend') also reveals their dark side, made up of poor cost visibility, management complexity, underutilised resources and governance holes. All factors that, combined with a mentality still tied to the logic of the past, risk compromising the scope of these advantages.

Companies, reads the report that Il Sole24ore had a preview of, are progressively shifting from capital-intensive investments to more flexible and consumption-based models, fuelling a trend that has seen the weight of on-demand technologies on IT budgets grow from 29% to 41% in just twelve months. In more detail, 82% of the 1,000 or so executives of very large companies surveyed on a global scale report a significant increase in spending on these solutions, 76% of companies have exceeded their public cloud budgets (by an average of 10%) and 68% have overspent on Gen AI, paying tariffs for underutilisation of resources and lack of centralised purchasing. Finally, only 29% of companies have achieved expected cost savings from SaaS and only 38% have truly accelerated innovation with Gen AI tools.

"These technologies," observes Ernesto De Ruggiero, Managing Director Cloud Infrastructure Services of Capgemini in Italy, "have transformed the way companies operate, but they have inevitable economic repercussions, with expenses set to double in the next three to four years. This is a clear summary of a scenario that calls on CEOs and CIOs to make important decisions, and in which those companies that are able to align their cloud migration strategy with business objectives (thanks to more mature and evolved FinOps practices, which are still underdeveloped at the moment) and to design scalable and modular architectures, exploiting AI-based automation to optimise processes and reduce inefficiencies, will be those most ready to generate value from their investments. Indeed, the majority of surveyed managers (77 per cent to be precise) consider the scalability and performance provided by cloud computing to be crucial for growth, as it enables them to accelerate transformation and reduce time-to-market, but there are many cases of companies finding it difficult to keep the management and operational burden of these solutions under control.

There is therefore a sort of paradox that hangs over companies, linked to the risk of having no returns from on-demand technologies, and to overcome it - according to De Ruggiero - there is basically only one way, and that is 'a holistic approach in which strategy, solution design, corporate culture, governance, tools and operational processes are aligned and dialogue with each other in a coherent manner'. Businesses that have been able to maximise the benefits of adopting SaaS and cloud-native solutions by following this path are not lacking (even in Italy) and an example comes from the manufacturing sector, where Capgemini and Google Cloud have implemented for a large multinational a Gen AI solution (composed of a chatbot and a forecast engine) capable of providing real-time answers and accurate forecasts on demand, obviating the ineffective management of orders in warehouses and creating the conditions to optimise stocks and reduce costs. Another virtuous example is that of National Gas, the UK's leading gas network operator, which has moved many of its processes to a fully automated cloud environment on Microsoft Azure. In general, concluded the Capgemini manager, 'we need to go beyond simple technology implementation and develop a data-driven strategy supported by IT investments based on solid business cases and clear, shared metrics, as well as integrated cost planning from the early design stages'.