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Bridge the gap between data modernization and data monetization.

Back Data and AI

Bridge the gap between data modernization and data monetization.

Pedro Martins 1
Pedro Peres Martins 2 minutes Share

In the past three years, our lifestyles, the way we work and the day-to-day life within companies radically changed. An unprecedented and ongoing transformation on a global scale, that has been leveraged mainly by technological innovation.

One of the areas of technology that’s been promoting this change the most is, undoubtedly, Data & Analytics, with plenty of notable examples - the rise of the public cloud as the default model for analytic workloads, the consequent end of on-premises legacy in big data ecosystems and its replacement by native cloud alternatives, as well as the rise of Artificial Intelligence.

With such a high focus and level of investment in modernizing data ecosystems, we could expect a rapid progress and little resistance to this new paradigm. However, the reality turned out to be quite different. The weak understanding of how these technologies impact businesses, the lack of articulated strategies, which define the role of data and integrate it in the business ecosystems, as well as the numerous gaps that exist in the management of these transition processes all show that there´s still a long way to go to reach a true democratization of data&analytics within organizations.

Despite all these challenges, there’s also a rising need to overcome them in order to leverage data assets. The result? A growing demand from companies on their Data & Analytics teams to realize all this potential, in order to improve customer experiences, product portfolio performances across multiple channels and to optimize synergies between physical and digital ecosystems.  

So, what advice can we give to companies to help them build a gradual and sustainable bridge between data modernization and data monetization?

1 – Business results are your starting line. 

Realizing the data strategy behind monetization initiatives will bring the use cases and associated ROI, that will later be needed to justify the investment in data modernization projects.

2 – Make sure the Business and IT teams are in tune.

Business teams will lead the data monetization initiatives and IT teams will lead the modernization component, but a shared vision and roadmap needs to be created in order to drive alignment and, ultimately, success.

3 – Promote internal collaboration through the Data & Analytics program.

There are few initiatives that impact as many areas of a company as data-centric transformation. If your company is used to working in silos, this is a great opportunity to get together and to create a culture of sharing ownership and collaboration.

4 - Measure progress along the way and expect a slow start.

Starting these programs always implies a greater initial effort, due to the alignment of teams around new processes and strategies. In order to keep track of progress and to help reduce with the initial frustrations, consistency and, above all, perseverance are key. 

Data-centric transformation is picking up speed, but it remains an early concept for many companies. All the collaboration required for this to happen adds complexity but also creates a great potential for positive transformation within organizations, a transformation that will ultimately leverage the wealth of data that companies have accumulated, though the modernization of data platforms and though advanced strategies.

A truly revolutionary phenomenon within the business ecosystem, that may yield priceless benefits for companies and help set them apart from competition, provided it is implemented correctly.

Pedro Peres Martins

Head of Data & Analytics at NTT DATA Portugal.

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