Chief Information Officer, Chief Data Officer, Chief Scientist Officer… Great. However and paraphrasing Tom Cruise’s shout in the movie “Jerry Maguire”: Show me the data! … Or even better… Show me your data strategy!!!
This noble effort of becoming a data-driven organization is not new. Corporations have been devoting time and resources -enough?- to this objective for the past years, but with mixed results.
Information and communication technologies -mainly fueled by data- are GPTs, general purpose technologies, a term coined by MIT professors Erik Brynjolfsson and Andrew McAfee in their book “The Second Machine Age”; namely, technologies that “disrupt and accelerate the normal march of economic progress”. Technologies that have extended their reach into many corners of the economy and radically altered the way we live and work.
We do need and want to foster these technologies. Nonetheless, there is a bottleneck in this evolvement and it’s not related to the technology per se, but to human beings: the biggest hurdle for corporations concerning a proper data strategy is related to cultural change. Becoming data-driven is about the ability of people and organizations to adapt to change. And we have gone through this reluctance in every single technological paradigm shift. For instance: the adoption of the Internet has played out over the course of the past quarter century.
The current incumbents of the positions Chief Data Officer, Chief Information Officer or Chief Scientist Officer, are they performing well? Are they being successful?
Today, before having a clear data strategy, we are already talking about data lakes, because it’s the new buzzword. But data lakes, what for? How are you going to retrieve data from those lakes? -watch out since they might be too deep. Are you going just to pour data in the lake without any schema? Are we talking about structured data or unstructured data? Too many questions, and very few vague answers.
We all know that every second millions of terabytes of data -sensor data, videos, audios, texts, signals, pictures…- are generated, perfect. But let’s not get confused by astronomic figures. Let’s focus on our needs and from there let’s do or redo our data strategy. Do not try to encompass everything: sometimes less is best. We need to have a different mindset to draft a proper data strategy and face this data avalanche: critical thinking, human judgement, and creative innovation.
Last but not least, our data strategy must be wrapped by a proper layer of ethics. Gradually users and customers have been aware about the importance of keeping the privacy of their data. They do know that if something is free, it’s because the end user is the product and they do not want to keep on bartering their personal data for just some flashy beads and Likes.
Becoming data-driven is a holistic long-term process and bet. Now that the use of data intensive technologies, such as artificial intelligence, is being democratized, we should devote proper attention to our data strategy and the positions around it, since the twenty-first century fuel is going to be data, properly curated data.
Written by:
Domingo Senise de Gracia
Founding Partner & CEO hAItta
Domingo is an AI entrepreneur and advisor. For the past 10 years his career has been focused on artificial intelligence -firstly, holding management positions in different organizations, and eventually setting up and leading his own AI start-up, hAItta. Currently doing his PhD in AI, he holds a MSc in AI, an MBA, and two MAs -Linguistics and Conference Interpreting.
