Industrial data scientists are in a unique position and time

Industrial data scientists are in a unique position and time

Organizations around the world, primarily industrial ones, are undergoing rapid, large-scale digital transformations, sometimes it can be easy to focus on the tree, even a branch, and miss the forest, losing sight. When a company takes a deep dive into the undergrowth of artificial intelligence, machine learning, big data, predictive analytics, the cloud, and edge computingthey forget at the end of the day of the goal.

The goal is to use these new technology solutions to empower employees, make their lives easier, and configure them to more efficiently and effectively deliver new value and innovation to your business. It is about the people and their organizational culture, not about the benefits for the organization; Engaged, culturally cohesive employees on a technology platform naturally drive better results.

One of the principles of the theory of constraints, which prompted Goldratt’s book, The Goal, preaches that the speed of a project lies in the pace of the slowest of the individuals participating in said initiative. The same applies in the case of digital transformation, including process automation; a small portion of users will go faster, a large number will go at normal speed, and some will go slower. Unless the company culture is to leave someone out, no one can be left behind.

This should definitely be considered by industrial data scientists. Relatively new to industrial and process engineering, this role has emerged to meet a growing need in the transformation industry: to marry traditional data science with localized domain expertise in the digital realm, while not forgetting that the The success of these projects depends on the people who make up the organization and the culture that prevails in the group.

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We know that the industrial sector was one of the first areas to adopt automation and robotics. Following the philosophy of the industrial revolution, decades ago, this sector began to implement all kinds of technologies in order to make industrial production more efficient; this brought as a consequence a large amount of data, with the data came the first engineers in charge of analyzing it and implementing improvements, and with the evolution of humanity towards science, came the first industrial scientists.