Workplace Performance Analytics — Next Generation Performance Improvement Technology

Contributed by 2017 Conference Speakers Timothy R. Brock, PhD and Enderson Miranda, MBA. Learn more about their session when you read about our 2017 Speakers & Sessions.

As performance improvement professionals, we apply our 10 international standards to improve organizational performance by improving the performance of people at all levels of the organization.  Organization leaders are well aware that human capital and organizational development performance improvement professionals have been experiencing new, unprecedented workforce development challenges caused by increasingly volatile, uncertain, complex, and ambiguous (VUCA) environments.  Our profession should flourish in this environment.  However, the demand for greater speed, focus, agility, and accountability to produce worthy performance and sustainable results is further compounding our challenge to successfully diagnose and proactively remedy workforce performance vulnerabilities, deficiencies, and opportunities within such VUCA environments.  Unfortunately, our current human performance technology toolkit is missing a crucial VUCA-sensitive analytics capability that other professions currently possess. What we are missing is a next generation human performance improvement technology capable of generating workplace big data performance analytics.

During our presentation, “Workplace Performance Analytics? Next Generation PI Technology”, we will examine an industry in the midst of overcoming VUCA challenges where most of us have had some type of experience. The US healthcare system has been undergoing substantial changes and healthcare providers have had to re-invent themselves to survive.  Healthcare organizations are applying workplace big data performance analytics to respond to their VUCA environment and higher accountability requirements mandated by the Patient Protection and Affordable Care Act (PPACA), also known as ACA or “Obamacare”.  One of the major impacts is the shift from a “Fee-For-Service” model (FFS) to a Value-Based Reimbursement (VBR) model. The VBR goal is that “by shifting a significant percentage of clinical and financial risk from payers to providers, VBR programs can help reduce costs significantly, improve the quality of care, and increase efficiency”1. Consequently, healthcare executives are leveraging human performance big data analytics technology to help offset this added financial risk.  Here are a couple of lessons we can learn from the healthcare profession and why it is important to our performance improvement profession.

The Institute of Medicine (IOM) conducted a study to address nurse-related performance deficiencies   required to satisfy ACA mandates.  One conclusion of their report is that the healthcare profession must develop nurses to practice to the full extent of their education and training2.  This study found that uneven performance on nurse-sensitive outcomes was a symptom of confusion about nurse role accountability, responsibility, and authority resulting in a task-based focus vs a profession focus.  This role confusion was considered a root cause to explain the variation in practice and lack of consistency of care, which decreases the quality of care, creates potential harm for patients, and wastes resources due to inefficiencies and errors.  This lack of professional role competence is a barrier to optimizing the RN Scope of Practice, a key variable to practice excellence.

A growing number of healthcare executives are expecting performance improvement professionals to do something about inconsistent nurse behaviors, practices, and outcomes.  A similar expectation trend is occurring outside of healthcare, as executives realize they are facing the same dilemma regarding inconsistency of results and variation in workplace practice at all levels of their organization.

Multiple human capital trend studies reveal a growing shift in the way executive-level decision-makers design and measure their human capital strategy.  Big data analytics technology that provides descriptive, predictive, prescriptive capabilities is becoming significantly more common.  For example, two independent 2015 studies published by Deloitte and The Conference Board reveal human capital has been the top issue of executives around the globe for multiple years.  A 2015 Harris Poll reveals that ninety percent of executives expect those of us in the human capital profession to be proficient in workforce analytics with 35 percent saying it is absolutely essential.  Yet, the Deloitte report reveals that only 8.4 percent of executives believe they possess strong human capital analytics capabilities. In addition, a 2014 Oxford Economics study reports that 53 percent of executives indicate that workforce data is a key competitive differentiator yet only 38 percent of these executives believe they have ample workforce data to understand their organization’s talent strengths and vulnerabilities.  Finally, according to the World Economic Forum, of all the human capital domains, talent development is the most critical factor “linking innovation, competitiveness and growth in the 21st century”.

A growing number of executives are no longer willing to accept the unnecessary risks associated with guessing or assuming the strengths and vulnerabilities of their staff to remain competitive.  Executives and managers expect credible evidence of actual workplace competence so they can make data-driven human capital development decisions. This is especially true for their substantial leadership and staff development investments (reported as high as $50 billion per year worldwide) that are failing to meet their leadership quality, bench strength, and growth expectations and needs.  Organizations want a quantifiable and sustainable impact results and Return on Investment (ROI).  Furthermore, they want to avoid making costly resourcing mistakes.  Ultimately, they want to dramatically reduce human performance system costs and lower sustainability risks.  Organizations are concerned about the capability of their performance improvement professionals to diagnose and remedy of addressing their daily workforce behavior variation challenges. Effective 21st Century performance improvement professionals are expected to uncover meaningful human capital insights through the use of the right tools and resources that give them a scalable, enterprise-wide perspective to optimize workforce performance at the individual, team, and organization levels. Big data analytics gives us that capability.

Big data analytics technology is changing the performance improvement landscape.  This business intelligence capability has become a common practice in many functional areas but has been lagging in our performance improvement profession.  It is incumbent upon performance improvement leaders and practitioners to recognize the implications of this changing landscape, thus integrating workplace performance analytics into our needs assessment and evaluation programs.  This means going beyond learning analytics that uses data about each learner gathered from end-of-course survey ratings/comments (Kirkpatrick/Phillips Level 1) or assessment scores typically extracted from a traditional Learning Management System (LMS) (Kirkpatrick/Phillips Level 2).  Performance analytics will allow us to make our own value shift to diagnose and remedy hidden workplace behavior (Kirkpatrick/Phillips Level 3) and practices that later reveal themselves in improved outcomes/results (Kirkpatrick/Phillips Level 4), thus effectively quantifying that our investments in performance improvement interventions are working as planned.

Our presentation will also show how performance improvement professionals at various healthcare systems are currently transforming their delivery value stream by using human performance analytics technology to diagnose and remedy costly daily practice inefficiencies.  We will also provide examples of how to leverage data analytics to impact workplace role competence and ensure practice at highest level of licensure and scope of practice. We will further illustrate how performance analytics technology is helping organizations to swiftly identify and correct hidden and costly behavioral variations using leading competency indicators, rather than waiting for lagging business indicators.

In addition, we will also discuss how to evaluate the effectiveness of the solutions to make sure each intervention or development program is working optimally and as desired. This model helps define value for all key stakeholders, as well as align the activities and metrics required to satisfy all stakeholders.  The analytical demonstration of the success rate of each activity, based on desired outcomes for each stakeholder, contributes to measurable transparency and managerial best practices that include the calculation of the financial ROI, a variable that  executives in all industries are expecting to see.


Deloitte. (2015). Global human capital trends 2015. Retrieved from

Harris Poll. (2015). New era in ceo-human resources relationship. Retrieved from

Institute of Medicine. (2011). The future of nursing: Leading change, advancing health. Retrieved from Washington, DC:

International Society for Performance Improvement, 10 International Standards,

Kellerman, B. 2012. The End of Leadership. New York: HarperCollins.

Kuhn B and Lehn C. Value-Based Reimbursement: The Banner Health Network Experience. Front Health Serv Manage. 2015 Winter;32(2):17-31.

Oxford Economics. (2014). Workforce 2020: The looming talent crises.

Sinar, E., R.S. Wellins, R. Ray, A.L. Abel, and S.Neal. 2014. Ready-Now Leaders. Bridgeville, PA: Development Dimensions International; New York, The Conference Board.

World Economic Forum. (2015). The human capital report 2015: Employment, skills and human capital global challenge insight report. Retrieved from: