Four Ways High-Performing Organizations are Adapting to the Age of Data
Apr 24, 2019
By Cliff Stevenson, i4cp
Only one-quarter of participants in i4cp's latest report, The Age of Big Data: A Progress Report for Organizations and HR, indicated that their organizations are equipped to meet today's analytics needs—prompting an urgent call for analytics skills and acumen across organizations. Top-performing companies are not content to play catch up; these companies are building analytics capabilities mostly through training, but also through recruitment.
Report findings show that high-performance organizations (HPOs) are not only embracing the data-driven business world, but are outpacing their peers in the use of information now available to them in four key ways:
1. HPOs have embraced the analytical mindset.
It starts with an analytical way of thinking. HPOs drive analytical methods and approaches from the top down, with executive teams that are rated much higher in analytical ability than struggling organizations (64% rated as advanced or expert in analytical ability as opposed to 32% of lower performing organizations).
2. HPOs have greater analytical ability across job functions beyond the obvious ones.
The example set by the executive team is reflected in all other job functions at HPOs and not just in the departments traditionally associated with data analysis, such as R&D and finance. Human resources, operations, marketing and even sales at HPOs all have higher rated analytical ability. In general, it seems that HPOs simply have more analytically minded employees across the entire enterprise.
3. HPOs build analytical strength through hiring and training, with an emphasis on training existing employees.
How do HPOs build analytical capabilities? When asked, most indicated that the major source of increased analytical ability was training. These organizations were more than two-and-a-half times more likely to use training over hiring to increase overall analytical skill.
There has been plenty written about the widening gap between supply and demand among data scientists—with the increase being on the demand side. The lack of exceptional data experts has produced a cost increase among these workers, which makes the training option both now and in the future more financially sound.
4. HPOs are prepared for the use of Big Data to help with HR decision making.
The Big Data phenomenon, which refers to the exponentially increasing size of datasets used in some businesses, is becoming increasingly relevant to an expanding range of businesses. HPOs are ahead of the curve in understanding and applying Big Data principles and techniques and are using Big Data for workforce decision making. Strategic workforce planning, recruitment and productivity measures are all areas in which HPOs see an opportunity to exploit Big Data.
From Understanding to Action
HR professionals have a critical role to play in creating and shaping the new analytical workforce. The lessons learned from today's market leaders provide the following sound guidance on how to get started:
- 1. Identify analytical needs in your organization.
Assess your workforce for analytical capabilities and use that data to determine where to focus first. Any departments that fall well below the acceptable level should obviously be dealt with first, but, if all else is equal, work on increasing the analytical abilities of top leaders either through executive development or recruitment.
- 2. Build analytical strength.
To build analytical acumen, training should focus on using data to make better decisions rather than on specific tools and data-crunching techniques—although those are still important for some jobs. This type of training will help employees approach problems from a more empirical point of view. Some functions within your organization may already have the needed skills and can be tapped as subject matter experts to help educate others.
- 3. Prepare to manage the flow of Big Data.
The hubbub regarding Big Data is mostly about that first word: big. If organizations are planning on making use of the enormous datasets available to them, infrastructure must be in place beforehand. Enterprise-wide HRIS may or may not be able to leverage the massive amounts of data collected, so it's important to understand what you are hoping to find before plunging into the overwhelming current of Big Data.
- 4. Embrace the analytical decision-making mindset.
Changing from an instinctual, experience-based decision making organization to a data-driven one isn't as simple as increasing your organization's analytical abilities. The very way in which problems are viewed has to be changed, which is why it is so important to have leaders who understand and use data-based/evidence-based decision making. Merely having more data accomplishes nothing if that data isn't used to make better, more fact-based decisions. Ignoring the shift to data-based decision making is done at one's own peril, as this is no passing fad. The only thing that has changed is the amount of data available to us. To not use this data to drive strategy is irresponsible and financially unsound.
Computers, the Internet and datafication: This new way of doing business isn't arriving; it's been here for years. Organizations that take their time catching up to a data-based world will soon become statistical data themselves.
Nonmembers of i4cp can download a summary version of the study.
AMA has a comprehensive portfolio of Analytical Skills seminars. Consider these:
Data Analysis Fundamentals: A Hands-on Workshop
Developing Your Analytical Skills: How to Research and Present Information
About the Author(s)
Cliff Stevenson, i4cp, is a senior i4cp research analyst and the lead researcher for the i4cp Performance Management Exchange and the Evidence Based Human Resources Exchange. He was previously the head of HR for a Boston-based consulting company.