According to the France Num Barometer published last September by the Directorate General for Enterprise, 81% of VSE-SME managers believe that digital represents a real benefit for their structure. However, despite costly investments, management teams sometimes struggle to see the benefits of a successful digital transformation. Thus, 19% indicate that digital technology wastes them more time than it saves their organization (compared to 12% in 2021). For Ash Finnigan, Head of Digital Transformation at Conga, digital transformation, and in particular artificial intelligence (AI), is nevertheless a major challenge for companies. According to her, it can be a real differentiator, especially within financial services, provided it is properly integrated and exploited.
What is the main pitfall for financial services when embarking on digital transformation?
The primary contribution of digital transformation to financial services is revenue operations transformation (RevOps), which involves streamlining internal processes to improve overall business function and optimize revenue streams. However, it can be very complex and costly if it is poorly orchestrated. Financial services are well aware of the added value of the latest AI and automation technologies, which give them a real competitive advantage. However, their integration is often done in a hurry, without having really identified or taken into account the needs of the other potentially impacted departments. This is a real barrier to enterprise-wide adoption of new technology, and can even delay future transformation plans.
Concretely, what are the factors likely to jeopardize the development of an AI technology?
AI is too often implemented without clear objectives having been defined upstream, and without precise information on the consequences of its implementation. Therefore, a large deployment of this technology can represent a risk for the organization. In particular, this can lead to such operational complexity that most of the tasks that are supposed to be automated ultimately fall into the hands of the teams, who enter the data manually themselves.
AI is certainly a promising technology, but it is not a magic solution. If bad processes have been implemented upstream, then it will simply amplify the existing problems. Similarly, if some data is poorly structured or not taken into account, leaders will not be able to rely on AI to guide their strategic decisions and grow their structure. In addition, the quality of this artificial intelligence depends on the data provided. All systems, data and processes must therefore be aligned before its implementation. Finance teams are required to ensure that all workflows are well-structured and optimized before embarking on an enterprise-wide transformation program.
When is the right time to embark on digital transformation?
In general, it is essential to take a step back in order to analyze the situation before starting any transformation, whatever the size of the structure. Banks and financial institutions, in particular, need to be able to assess their digital maturity before getting started. This inventory will allow them to have a precise vision of the way in which the data circulates between the systems, the teams and the various services. From there, leaders will be able to identify areas for improvement, maximize data flows, and optimize RevOps cycles. It is on this condition that AI can bring real added value.
What should be considered in the RevOps transformation process?
Any digital transformation project must take into account three essential elements: people, processes and technology. Every leader considering implementing a RevOps transformation program, regardless of system size or density, must first focus on better connecting these three variables. The objective: to optimize the company’s operational model, for example by improving customer service, reducing response times or even automating the management of contracts and invoices. However, the diversity of the teams, processes and systems involved can lead to operational complexity and inefficiencies over the long term.
In view of budgetary constraints, it is essential that financial organizations focus on solutions or services that are useful to them and improve their overall performance. Of course, it’s hard to know where to start. This is why a detailed analysis of data is essential: understanding the way in which it is stored, managed and how it circulates is essential. Indeed, siled or disconnected data can impact operational efficiency and lead to a significant loss of revenue.
Can this transformation take place overnight?
No, and you have to be aware of it, without getting impatient. The most important thing is to start small and slow, because RevOps transformation is an ongoing process. Rather than trying to do everything at once, it’s better to consider change step by step. In addition, the structures must involve the employees whose work will be affected. Together, they can identify a key operational process, the optimization of which will bring a better return on investment.