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This is a profile from the 2021 version of the DataIQ 100.

The latest list is available here.

Luca Zuccoli, managing director, Calculus Analytics

Luca Zuccoli, managing director, Calculus Analytics

How is your organisation using data and analytics to support the corporate vision and purpose?

 

Data and analytics are at the core of the services we are providing. They are, in very practical terms, our business. In terms of objectives, we focus on improving risk, marketing, pricing, supply chain and collection effectiveness among other things. A strong area of growth has been alternative data. Enriching traditional data with alternative ones is particularly important for segments/sectors that are not data rich. To this extent, finding and carefully evaluating data that can boost performance and broaden customer reach has been critical. Another important point is being able to estimate the potential impact of new data/algorithms to be able to prioritise scarce investment towards quick wins.

 

2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?

 

Most of my clients within the company made a priority to accelerate change and transformations by being careful with spending and more focused on quick wins. To this extent, innovation based on better algorithms without touching existing infrastructures or piggy backing on ongoing data integration were the most sought after. Pragmatism and fast actions have been at the forefront of everyone’s ask. Large investments have been re-evaluated and at times postponed. Hiring has been more focused on critical needs.

 

Looking forward to 2021, what are your expectations for data and analytics within your organisation?

 

Data and analytics are the core of our company. In 2021, we are expanding to develop more innovative products and services for a broader set of clients across new verticals.

 

Is data for good part of your personal or business agenda for 2021? If so, what form will it take?

 

Data is for good part of my life in 2021 and onward. The form is that of growing a successful high quality team to produce new, exciting services and products and impact society in a positive way. This is, was and always will be my personal and business credo.

 

What has been your path to power?

 

I started as a data scientist who enjoyed explaining the results of what I was doing. I always focused on pragmatic approaches and I found a good fit in consulting for more than ten years. This helped me develop a combination of technical background and strategic vision. Then I took on leadership roles in innovative businesses of all sizes, from start-ups to FTSE 100 companies and focused on change management and executional excellence. The common theme has been realising innovations with data and digital, with a strong and measurable impact on the business.

 

What is the proudest achievement of your career to date?

 

All my achievements have in common establishing top performing centres of excellence, where technical people could grow their career in multiple directions. So, this is really the thing I am most proud, in particular, when I provided the opportunity to grow into more business and communication-oriented roles. To date, with one such centre, launching a SaaS platform and developing award-winning products on it, has been my proudest achievement. We managed to achieve a great mix of ambitious vision, great execution and commercial success.

 

Tell us about a career goal or a purpose for your organisation that you are pursuing?

 

My current career goal is to develop my own data-driven organisation, so my goal and that of my organisation are aligned. That’s an important alignment! For both me and my company the immediate goal is to achieve excellence in our products and services and develop a clear and recognised advantage on specific types of data applications. We have a great team, and we want to grow it and continuously improve the learning experience for our talented people. The two are inexorably linked. At the same time, we are growing our eco-system of partners and clients to provide convenient and trusted solutions, impacting ever more people.

 

How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?

 

Our business is fully based on data and analytics by its own nature, but when I look at an industry level and at other organisations, there are important gaps to close. The most important is about communication and planning.

 

Often what is feasible within which timeline and with what investment is not sufficiently clear. Having clear use cases to aim at before starting infrastructural/investment work is critical. Thinking about the level of detail required to achieve a successful end-result of any product, are we sure that we start with sufficient guidelines to get there, at the desired speed?

 

This gap is typically due to both the technical side and the business side. Are we spending the right amount of time and effort to achieve clarity from both sides or we are rushing towards ambitions that are not sufficiently clear without considering your starting point? There is trade-off between time, investment and achievable results.

 

To align these elements, we have to speak a common language and accept constraints and trade-offs upfront. There has to be the acknowledgment that best practices and benchmarks are context dependent and that every company has to follow its own path.

 

What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?

 

This is the most important challenge for organisations in the 21st century. A data-first mindset requires a DNA level of acceptance that important decisions have to be taken and discussed through data at all levels. This will always be a work in progress, and it should be the priority. Data literacy at its most effective provides a minimal shared knowledge and a common language to understand if we are really taking data into account or not, and how to do that.

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