Data Science and the Art of the Possible
What is Data Science, and why should it matter to financial services firms?
A purist will tell you that Data Science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.
But here at Mudano, we go one step further. Data Science is a complex and fascinating field, but critically, it must solve business problems.
Most organisations intuitively know that they need Data Science. It is the discipline required that will allow them to unlock the magic in their data. But many organisations simply don’t understand it. This can lead to confusion, differences of opinion and sometimes even heated debates amongst decision-makers. This feeds through to employees and can therefore undermine the commercial case for implementing a firm-wide data-centric approach.
Data Science, when used properly to hypothesise and qualify experiments, can lead to profound positive change within your organisation. But simply hiring data scientists does not create a data-driven company. Nor does collecting data without systematically thinking through how you use it can drive actionable insights that lead to commercial results.
One way to bridge this organisational gap was to create ‘data translators’ who would act as a conduit between the business and the science. But this added unnecessary layers of complication and protracted the creation of silos within an organisation. A better approach is to educate stakeholders throughout the business value chain so as to increase organisational data literacy with data champions and citizen data scientists embedded throughout the organization – not just in structural silos.
Where then to start on your journey towards becoming a data-centric organisation? Applications of Data Science are practically endless, which is really exciting. But the possibilities can also be daunting.
The art of the possible
Before embarking on the journey, it’s essential for organisations to take a step back and consider the bigger picture. “The art of the possible” is a phrase that we use when discussing Data Science, and it’s helpful in conceptualising the topic and emphasising the creative element that underpins good data management.
Data Science is a somewhat esoteric and at times, seemingly impenetrable subject. Here at Mudano we relish the opportunity to guide decision-makers towards a level of understanding that enables them to make qualified commercial decisions. That’s why we offer Data Science education to help business leaders discover the possibilities and create well-defined use-case experiments. It’s about embracing the spirit of experimentation, before finalising an approach, obtaining key stakeholder buy-in and taking determined action to scale data practices, for example, data management.
‘Education’ is the keyword here, not only to increase data literacy – especially among the C-Suite and throughout the executive team – but also to educate about potential and possibility. Because understanding AI means understanding the microscopic view of your business, the telescopic view of your industry and the crystal ball of the future. It is difficult to do and we’re conscious that it can be hard to visualise the impact that data and AI can have on an organisation. So let’s consider a couple of examples of how we have helped clients prioritise data.
Training and education- Understanding the value of data
We offer a fast-track, immersive and interactive Data Management Experience for leaders to get hands-on with key data management concepts and challenges. The aim here is to help you develop a real understanding of data and the value it can bring to your organisation, so you can become a data advocate.
This is exactly what we did for a global asset manager who sought our help to educate members of their board and senior leadership team on why making the best use of data is key to commercial success. Like many organisations, they had begun some data improvement initiatives but were struggling to obtain executive support to implement and embed a firm-wide data vision and strategy.
The firm’s CEO, CFO and several business heads attended a full day Data Management Experience event and came away equipped with the knowledge needed to foster trust and confidence in data, enabling them to return to their colleagues and play a part in the journey to embed a culture where data matters to everyone. They were imparted with a greater understanding of the value of data, and initiatives they could undertake to improve data management in their organisation.
We also helped a large UK retail financial services client to build a sustainable internal Data Science capability.
The starting point was a team of enthusiastic, but technically inexperienced, analysts. In addition to designing personal development and career progression frameworks, our remit also covered the design of a bespoke training programme to take beginners in Data Science to expert level, so that they could apply their skills with the confidence to solve even the most challenging real-world problems.
Our approach yielded dramatic results. In just 18 months, the client doubled the size of their specialist Data Science team, with all team members sufficiently confident in core modelling techniques to fly solo on even the most difficult projects.
Beyond your business now
The point is, that knowing and understanding Data Science allows for greater identification of what to build today and where it can be used in the future. And data science, in a modern integrated business context – needs to be understood by business stakeholders to truly accentuate the value it can bring to your organisation.
You cannot simply keep employing data scientists and other practitioners and hope – which is why the art of the possible cuts across so many business functions and data propositions -data strategy, org structure, the function of the Chief Data Office and more. It is only by understanding what is possible that building the future of AI in your business can take place.
Ultimately, building a sustainable Data Science capability does take more than investing in analytics tools and hiring data scientists. It means building the right team and culture. And it requires training, technology and processes to set up a capability that is sustainable and creates long-lasting business value.
If this sounds relevant to you and your organisation, then please do get in touch. We’d love to talk you through the possibilities and help you get started on your journey.