• TDF provides a suite of services and capabilities related to Data and Insight.
  • Our team has over 30 years of combined experience in building data warehouses, business intelligence, organizational data, relevant and robust AI, as well as framing ideas that transform ideas into keen insights for white papers and thought leadership.
  • TDF is also pioneering it’s own AI with specialty industry verticals. We focus on robust and transparent processes that support business growth and goals. 
  • TDF Champions and supports the business development of game-changing SaaS, business intelligence, data, and analytics, as well as AI that drives results.


Our commitment to driving best in class ESG practices and to the 17 UN SDGs has allowed us to partner with the Turnkey Group which is based in Singapore and the UK. TDF is involved in building out the algorithm of the Turnkey Group’s platform solution in the Americas as well as in other parts across the globe.

Read Turnkey’s General Presentation PDF from January 2020 > (PDF will open in new tab)

The Turnkey Group provides advanced sustainability software to help companies and their supply chains manage the environmental and social impact,
mitigate risk and improve profitability. Turnkey allows companies to collect, monitor and report on ESG data
(Environmental, Social and Governance) in a transparent, consistent and comparative manner. 

The Disruptive Factory in partnership with Turnkey offers best practices to build and support
the ESG framework and measurement of results. We also capture KPIs and map the UN SDGs.

Artificial Intelligence & Data Science: Our Synergistic Analytics Paradigm

The most important thing for businesses to realize about “artificial intelligence” is that it is often too broadly defined. After all, AI need not be “artificial” or “intelligent” at all, it can be both or artificial-only or intelligent-only. This seeming riddle is explainable by the fact that various scientific methodologies and practical algorithms operate diversely: from simple, inexpensive statistical or mathematical models to highly sophisticated, expensive deep learning black boxes. 

We understand there is more than one way to find the right set of answers. The most obvious approach may not always be the best one. The newly emerging landscape of data science too often follows a path that can be unnecessarily complicated with black box approaches that are executed by the unqualified. Or, data science can fall back on legacy tools that have been in use for decades even when newer methods offer better predictions, less chance of mistakes, and can handle all types of Big Data. 

1. Old and new-school approaches 

Data science may be new, but its roots as a discipline go back decades. We combine those time-tested approaches driven by the scientific method with a modern focus on artificial intelligence, machine learning, and big data. These newer approaches can respond to business challenges dynamically, rapidly adjusting to changing market conditions and other factors. By bringing the old-school approach together with a new-school perspective, our data science is more than the sum of its parts.

2. Tools from many branches of science

Business scenarios can often be approached with perspectives from a range of disciplines such as statistics, decision science, economics, or engineering. The most effective solutions can come from unexpected areas, and so we consider multiple approaches in every engagement, not just the ones that seem most obvious or are most frequently used.

 3. Insights from multiple industries

Whether it is financial services, beauty, telecommunications, or agriculture, every industry has developed an effective set of tools and techniques. We leverage these industry-specific approaches while bringing in diverse perspectives from other fields, leading to an out-of-the-box, thorough, and ultimately more effective work product targeted exclusively to you.