Data Science has become an immensely popular buzzword. The promise of data-driven decisions delivering us from the uncertainty of gut feel. Big data and cognitive computing freeing us from excel spreadsheets and graphs. An entire new function has emerged in many organizations with Data Scientists and chief data officers. To meet the demand universities now have Data Science degrees and a plethora of online courses exist. While we all want a Data Scientist on our team few of us know what they do or how to use their skills.
What is Data Science? While there is no consensus on an exact definition there are common themes across business and academia. Data Science is viewed as an interdisciplinary field, employing techniques and theories from math, statistics, and computer sciences often combined with specific domain knowledge and frequently combined with data visualization or business intelligence. Data Science is conducted with the purpose of extracting actionable knowledge from data. Data Science has been posited as a “fourth paradigm” of science (empirical, theoretical, computational and now data-driven).
While the exact definition is still up for debate, adoption and the impact on business is expanding rapidly. Data Science is transforming work across organizations from product development to marketing and sales. Within HR, new technologies are enabling organizations to bring Data Science to people data. The new field of People Science is emerging as organizations are finally able to go beyond HR metrics and reporting to apply Data Science to people data.
People Science is the extraction of actionable knowledge directly from people data through a process of hypothesis formulation and hypothesis testing within the context of achieving an organization’s business goals and strategy. It is a data driven approach to understanding the interactions between people and their environment, their resulting behaviours, organizational systems, and performance so an organization can make better people decisions.
People Science is not an end state but an ongoing journey. The journey starts with having accurate and accessible people data – a single source of truth. Good data is the cornerstone of People Science and enables an organization to start the journey. Analytic capabilities in business are often evaluated or discussed in the context of maturity with basic analysis considered lower maturity and predictive analytics near the higher levels. This maturity paradigm lends many of us to assume we need to reach full maturity and build predictive analytic capabilities. The goal of reaching the highest levels of analytical maturity should be balanced with the return generated from investing in more complex analytics and be considered independently for different people challenges. In People Science, the scope and context of the problem drives the method and complexity of the analysis. To meet the rapid pace of business today, extracting actionable knowledge from people data needs to be rapid as well. As business goals and strategies adapt and change the People Science journey and priorities should adapt along with the people strategy, all moving in lockstep together.
2nd March 2017