When it comes to the digital transformation and business intelligence arena, José Luis Lopez is a well-versed strategist who draws on his years of industry expertise gained through managerial and consultancy positions, to help organizations with their digital transformation needs. In 2005, while serving as the CEO of Nimbus Systems, Lopez saw an opportunity to help companies adopt digital transformation and business intelligence, through a differential approach and smaller teams, in less time, with better results—Bluetab was born. A multinational company that offers services focused on data analytics as well as sector-specific solutions, Bluetab assists enterprises to keep pace in today’s data-driven world. With its ‘do it right the first time’ approach, Bluetab is a valued partner for major market players across the US, Spain, México and Colombia, in the banking, telco, utilities, and education sectors.
In an interview with the CIO Applications, Lopez, the co-founder and managing director of Bluetab sheds light on the expertise and value proposition that the company delivers to its clients.
What are some of the challenges that your clients face when it comes to the Business Intelligence arena, and how does your organization address these problems?
The major problem that many firms constantly encounter is that they really lack an agreeable culture in their companies while dealing with data. We help them gain some quick wins in order to gather support from the rest of their organization. On the other hand, we find that there is a need to follow a careful and disciplined approach to ensure that organizations have the proper sets of data to drive positive outcomes; this is something that many customers tend to overlook. In a hurry to drive results, they often forget the need to curate and clean the data before moving to the next stages. They require a well-organized data culture and approach in order to make it work and sustainable within the time frame. Many of our clients usually raise aesthetics-related issues. They do not necessarily understand the scientific approach involved in the process, and that one must strictly adhere to a set of laid rules. Beyond just playing with the data and getting results, organizations have to ensure what they are doing is right to reach meaningful conclusions.
How do you customize or tailor your solutions in accordance to your clients’ business needs? And, is there an approach that you take in understanding their requirements?
Firstly, what you need is a functional knowledge; we must understand the specific requirements of the customer.
We offer our own products that clients can use free of charge as well as leverage other technologies or solutions to resolve their business problems
Could you please elaborate on a case study, where you helped one of your clients address their discrete business requirements?
We worked with an International Bank that had to roll out advanced analytics solutions in their offices across different countries. While each country has a different set of technologies, information sources, and more, it was challenging for the client to deploy a centralized platform and get the same results in all their offices. To begin with, we ensured that the entities spoke the same language, agreed on the same objectives and worked in the same direction. This was not an easy task, as multiple problems required a centralized definition and a common dictionary to attain that. The second part was creating a common infrastructure platform that supports a variety of data sources, different from one other. We created a platform that empowered the client to uphold the independent jurisdiction in each country and allowed them to make changes to each data set as per their requirements.
This was a huge effort as it involved attaining centralization on a global landscape while dealing with different sources of data, different languages, and different understandings. We reached the middle ground to translate all the changes and different viewpoints into one. Besides solving a technical problem, we also addressed functional issues and process changes; as a result, transforming their culture.
Please shed some light on how Bluetab differentiate itself in the marketplace and stay ahead of the competition?
Our uniqueness lies in our mixed approach, whereby we offer our own products that clients can use free of charge as well as leverage other technologies or solutions to resolve their business problems. We believe that data is not the problem; instead, organizations should run off its value with their functional knowledge or using the technology from other people. Unlike many of our competitors who offer license-based solutions, our solutions are open-source, and anyone can use them.
Where do you envision Bluetab in the future in terms of technological advancements or geographical expansions?
With the rise of self-service BI, we are planning to use machine learning to substantiate the analytic tasks of our clients. With a deluge of data, managing the influx of information to design business models becomes complex and requires tools to pinpoint our priorities. For example, imagine that you have a data dictionary with thousands of entries. You are going to take a long time without an assistant to find what you want. Besides, you must work and think very hard to keep the complex sets of data related to each other or go back often to behold these relationships. We aim to use machine learning to ease such redundant tasks, such that an assistant will let you know what you are working on, how it is related to another entity, and more. People today demand the taxonomy of data, which is complex and difficult to master; Bluetab is perfectly positioned to tap into this opportunity and deliver results. We are going to push our bundle offering mainly in Spain, Latin America and the US.