2020 has not been an ordinary year by any measure. Covid-19 has impacted economic, social, and ecological structures in an unprecedented way. When one virus disrupts every form of life as profoundly as it has, people & businesses think, focus, and prioritize differently.
The financial services industry, too, is dealing with the effects of Covid-19. The industry was already reeling under several systemic challenges (costs, regulations, competition) for the past 30 years, and now they are faced with additional pressure to reinvent their operating model for the next normal (if there is one!).
Most financial institutions understand that the industry will transform significantly in the coming decade as it re-aligns its purpose to emerging global and societal needs and leverages the increasing datafication across processes and products to achieve this purpose. As such, the secular trends of digital transformation, customer-centric strategies, and operating model simplification will only accelerate.
At Bloom AI, we would like to support this transformation and have set a simple vision: Help financial institutions realize the economic value of data by scaling enterprise transformation to the last mile.
#financialservices: Need for differentiation, but there is growing frustration with the complexity
Generating meaningful value from data is challenging in banking and capital markets. The industry is highly data-intensive, complex, regulated, and multi-threaded. Increasingly though, a large percentage of financial firms believe that data & analytics is becoming the only source of differentiation in the industry. McKinsey estimates that AI can help generate an additional value of $1trillion for global banks.
The drivers and agents for generating economic value from data are continually evolving. At a macro level, our Economic Value of Data Framework indicates four key drivers: productivity, revenue, monetization, and sustainability and four agents: technology, computation, processes, and people.
In technology and computation, banks are placing big bets on the cloud, AI, and data, to systematize and automate data infrastructure. However, the real value realized thus far is still relatively low, and there is a growing frustration. For instance, in sales & marketing, the highest potential area for AI within banking, firms have invested significantly in CRM and mar-tech solutions. Despite that, less than 15% of firms have readiness for advanced marketing & sales strategies.
The drivers and agents for generating economic value from data are continually evolving. At a macro level, our Economic Value of Data Framework indicates four key drivers: productivity, revenue, monetization, and sustainability and four agents: technology, computation, processes, and people.
In technology and computation, banks are placing big bets on the cloud, AI, and data, to systematize and automate data infrastructure. However, the real value realized thus far is still relatively low, and there is a growing frustration. For instance, in sales & marketing, the highest potential area for AI within banking, firms have invested significantly in CRM and mar-tech solutions. Despite that, less than 15% of firms have readiness for advanced marketing & sales strategies.
A key reason for this has been the slow evolution of the last mile – people and process changes, and for the full realization of value, financial institutions will need to prioritize the last mile!
#returnonchange: ROI as ‘the metric’ to capture structural change is flawed, lessons from the Printing Press
There is a consensus that the operating model and practices within the financial services industry are going through structural changes, and the pace of change is likely to accelerate. How should banks think about transformation through this phase, as the standard ROI approach can be misleading?
If we go back in time to the printing press – it was one of the most pivotal innovations in modern information technology. Studies have found that cities that were early adopters of the printing press experienced a 40-80% economic advantage for almost 300 years compared to those who did not. The diffusion of print media led to new knowledge and ideas in people – leading to many first, second, and third-order effects that could not be captured in an ROI model.
The context for innovation & transformation is no different today. We find that less than 10% of data & insights currently generate value in financial institutions due to a lack of systemization, automation & context. Since we are still in the early stage of transformation, institutions should focus more on capturing the ‘return on change’ instead of ‘return on investment’ only. Imagine, what would be the productivity shift if each process and person in an organization were data-driven or data augmented?
#insightsbasedaction: From hidden data to integrated real-time action – The Fitbit Story
Bringing about change in the last mile is indeed the most challenging aspect of the data journey. Over the past ten years, visualization platforms have significantly increased data transparency and have also grown in complexity. The end-user is overloaded with information that is still very fragmented, technical, and lacks actionability. Embedding data-driven attributes into daily workflows requires new thinking, as well as a significant behavioral change.
Fitbit offers a great lesson here. By making health data (previously invisible to users) visible effortlessly and intuitively to the users, they started a health revolution. It provided you and me the ability to measure and act on our health every day.
Now imagine if this can be replicated by businesses also. For instance, our research indicates that there are at least 10-15 ‘insights moments’ for sales and marketing teams every day in banking and capital markets. These might be while engaging clients, planning GTM strategies, or executing campaigns. Unfortunately, many teams operate on heuristics as the insights may not be available, too dispersed, or too technical to action. What if there could be a Fitbit for your sales & marketing team?
At Bloom AI, these numerous possibilities inspire us, and we are here to help! Technology stewardship powered by machine learning, cloud, smart design, and technology will provide transformational capabilities to teams.
If you would like to discuss how we can take the first step towards this, please reach out to me on LinkedIn.
