The Data Challenge (Big or Not)






HR already is grappling with the challenges of out of date, incomplete or potentially inaccurate about corporate employees. Analytics teams are addressing issues of data cleansing and the creation of data dictionaries to solve the linguistic and data model incompatibilities across the organization. (Note the great variation in what constitutes an “employee,” or how “attrition” is defined across a company).


However, in the current flood of attention paid to analytics in human capital management, we as practitioners need to keep one more point in mind: thatbusiness-relevant (not just HR relevant) analytics will stem from the combination of HR data with production and financial data. This creates an immediate challenge for the HR professional.


The challenge for HR becomes to better understand the intersections between the workforce in total, and the mission and vision of the organization — current and future. Furthermore, HR will need a firm grasp of the comparative costs of workers of all types: not only competitive salary data and benefits;, employer costs of labor; and workforce overhead, for example,  but also the costs related to an increasingly contingent workforce.


The analytics required will need to assist the HR team in the hiring and development of a disparate, global workforce such that the team has the data necessary to deploy just-in-time talent where and when it is required.

New data types abound within HR: video and telephone–derived candidate interviews and the job applications themselves are just one example. Capturing text communication between recruiters and candidates or employees and customers is another. We can anticipate that these and other data types will proliferate across the other areas of the business as well. This leads to the bigger challenge of synthesizing, extracting meaning, and storing unstructured data; data gathered from all parts of the organization. How will HRIT and IT professionals derive standard data models from these more recent types of data? How will it integrate with the structured data in the employee profile and system of record today? 

The focus on business-relevance leads to cross-disciplinary analysis; the added requirement for managing new data types is an added challenge for both HR and HRIT. Begin building your analytical skill sets now! And download Karen O’Leonard’s High–Impact Talent Analytics: Building a World-Class HR Measurement and Analytics Function for more details!


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Christa Degnan Manning

Vice President, Solution Provider Research Leader / Bersin, Deloitte Consulting LLP

Christa leads technology and service provider research for Bersin, Deloitte Consulting LLP. In this role, she helps businesses align their workforce support strategies with appropriate third-party software developers, service partners, and governance models. A 25-year technology industry veteran, Christa’s expertise assists organizations in creating functional capabilities and employee experiences that increase productivity, engagement, and workforce efficiency. Frequently cited by business and trade media, she has presented market research on business to business trends, leading practices, and expected challenges and benefits at industry and user conferences globally throughout her career. Christa has a bachelor of arts in English from Barnard College, Columbia University, incorporating studies at University College, University of London. She also holds a master of arts degree in English from the University of Massachusetts and has completed executive coursework on business metrics at the Wharton School, University of Pennsylvania.

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