Data Literacy is increasingly becoming a critical imperative for decision-making. To succeed today, c-suite executives in particular need to become comfortable, conversant, critical and confident in the understanding of their organizational data and use the knowledge for making decisions.
The growing roles of Big Data, powerful analytic platforms and the need for predictive dashboards are driving this need. Human Resources is no exception to this requirement.
For too long, HR has been clichéd as a paper-based organization. The truth is that HR is the custodian of an organization’s vital talent data. People and their skills are at the center of any business and everything about the employee force is integral to any decision making. Organizations who understand this importance treat their HR data with utmost importance. The first step towards this is to be able to quantify the data so that their metrics and analytics could be used make better decisions.
HR can no more be paper-based and about being nice. HR is more about applying business acumen and aligning the entire talent force to culture and strategies. All this begins with becoming data literate first and Data Literacy starts with having data to be literate about!
Realizing the vital role of HR data and its unexplored applications, more and more companies are beginning to incorporate robust metrics systems by using digital technologies. These platforms are expected to measure and report valuable analytics on aspects such as time-to-hire, cost-to-hire, attrition rates, performance by department, leadership pipeline and training impact.
Data literacy is the ability to read, create and communicate data as information and has been formally described in varying ways.-
As a recent Forbes article noted, data literacy is about looking at data and being able to "ask the right questions and seek the right assistance to accomplish the goal."
1)Transformation: Analytics aggregate, quantify, compute and analyze data. They give comprehensive insights, make predictions and guide decisions with enriched information. For example: how rich is a resume in terms of skills and candidate experience?
2)Learning: Regression Analysis delves into the relationship between bits of data. In case of HR, especially this process is complex since we are dealing with unstructured data. For example: Much of HR data exists in the form of words whose exact relationships have to be discerned.
3)Predict: Simulations and dashboards help test models and what-if scenarios to determine which selections to make from a range of choices. For example: what decision to take with regard to an investment based on available skills and expertise levels?
A Boston Consulting Group survey of 3,507 participants revealed that top-performing HR offices focus on data literacy in several ways. Each of the following observations relies heavily on data literacy to drive more efficient and effective HR functions, including:
1)Better performance: Companies with strong HR capabilities in analytics, among other areas, have a stronger financial performance.
2)Seat at the table: HR departments that use analytics and metrics- based KPIs are more likely to be engaged in strategic organization-wide discussions.
3)Data decisions: HR departments with analytics develop better strategies and make better investment decisions. They also use data to prioritize how to address the most urgent HR challenges.
HR data is tricky. Why? Because it exists in unstructured form; unstructured because existing technologies cannot comprehend quantify nor comprehend it well enough due to the fact that it exists in various formats. For example: talent data such as resumes, job descriptions, professional experiences, performance evaluations, etc. exist in narrative forms such as word docs, ppts, pdfs, txts, images, audio, video, comments, tweets, blogs and an array of digital footprints. This form of data cannot be contained in spreadsheets and tabulated assessments. The challenge is to decipher this ocean of multi-format data and generate meaning out of it. As one can guess, this is easier said than done.
Contextual technology has the unique capability to comprehend unstructured data and analyze it contextually. This is because it has the power to give narrative text or any form of data its ‘context’ which is similar to how a human mind discerns words. Contextual technology can break down HR data of any type and from any source. It drills down, sorts, analyzes patterns, quantifies, computes and gives in-depth analytics full of valuable insights. Contextual talent analytics arm CXOs with hard evidences necessary for informed decision-making.
The Spire contextual talent platform has proven to result in -
1)50% cost savings
2)40% time saving
3)9% increase in revenue
Make the most of HR data by using a contextual technology platform.