Organizations aspiring to become data-driven need to take a close look at their HR practices. If your company's hiring and retention standards aren't keeping up with the times, you may be losing valuable job candidates and employees. To minimize the pitfalls of building a data-savvy workforce, consider these tips.
7/7/2016
An article from July 2016 found at informationweek.com and commented on here. |
Cultivating a data-savvy workforce can be a challenging proposition if your company is not among the rarefied ranks of data-first organizations such as Facebook, Google, and Amazon.
For starters, attracting top talent is a competitive sport and becoming more data-driven over time. For example, HR departments are able to track and analyze more types of data than ever. Using sophisticated software tools, they're gaining deeper insight into job candidates, employee performance, and the overall effectiveness of their HR practice.
Yet, even as data-driven human capital management is becoming a core element of the hiring and retention process in HR departments, many companies don't seem to really understand what it means to build a data-savvy workforce. That's partly because doing so can involve complete organizational transformation.
"Data-savvy workers think differently, ask questions, challenge the establishment, and demand improvements," said Kathy Marshall, director of recruitment quality and client engagement at Decision Toolbox, a recruitment products and services company, in an interview. "If a data-driven employee isn't challenged, can't affect change, or isn't able to access the information they need to drive results, [they] will quickly move on to other opportunities."
To serve the company's best interests, HR departments should understand their company's data strategy and how becoming a data-driven organization affects everything from organizational structure and corporate culture to roles, skills, cross-functional collaboration, recruitment, and retention.
Meanwhile, some businesses are fine-tuning their structures, cultures, and operations to improve their ability to compete using data. One such example is GE, which is becoming a digital industry company. Its leaders understand how technologies, including data analytics, are fundamentally changing the way the company operates. And they are making sure the workforce understands how each aspect of the business is touched by digital transformation.
"Every employee needs [to understand] what it means to be part of a digital, datacentric organization," said Susan Peters, senior vice president of Human Resources at GE, in an interview. "Whether you're on the shop floor of a manufacturing plant, in a research lab, or at the corporate headquarters, everyone is responsible for a company's shift to becoming data-savvy."
Of course, not all companies have GE's vast resources. The company spends $1 billion a year worldwide on employee learning and development alone. Even without such resources, here are 12 things your company can do to effectively attract, build, and retain a data-savvy workforce. Once you've reviewed our tips, tell us what you think in the comments section below. Is your corporate culture ready for a data-driven workforce?
Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include ..
HR analytics is gaining momentum as organizations attempt to accurately manage their workforces. Using HR analytics, HR departments are gaining fine-grain insight into the subtle dynamics affecting recruitment and workforce effectiveness. In addition to understanding the role of data as it relates specifically to the HR function, HR departments need to understand how becoming data savvy affects other departments and the organization at large.
"In order to find the best-qualified candidates, HR departments and hiring managers should be data-savvy and be able to clearly articulate the new data-related roles and responsibilities. They should also be able to specify how these roles add value to the organization, and what these resources will be doing once they're hired," said Jay Zaidi, managing partner at management consulting firm AlyData and author of the forthcoming book, Data-Driven Leaders Always Win, in an interview.
I.e., consider the/this first barrier/filter in the hiring process - these gays and gals need to understance the importance of data themselves. |
Data-first companies have data embedded in their DNA, which spills over into their HR practices. In those companies, it's everyone's job to be data savvy, which affects interview questions, the interview itself, and the work environment. Other organizations now are under competitive pressure to follow suit.
"Just hiring technologists and implementing technological solutions or products isn't sufficient for corporate success anymore," said Jay Zaidi of AlyData. "A data culture is a prerequisite for succeeding with data. Therefore, senior leaders have to involve everyone within their organization to make that happen."
The trend of today and what will keep companies and organizations competitive tomorrow. Just look at the big companies and what they are really dealing with - Facebook, Google, LinkedIn, et c - it's DATA. |
Different companies are at different stages of data-driven maturity. If your company hasn't reached nirvana yet, it probably needs to put more emphasis on integrating data into its DNA, rather than bolting analytics onto existing business practices.
"You need to ask yourself: Is it part of the daily conversation? Is data used to determine your business strategy? Do you depend on data in your decision making? Are you publishing data dashboards that reflect key metrics? Are you using data to hold people accountable? Decide what questions you want to answer 100% 'yes' to, and work toward that goal," said Teri Calderon, EVP of Human Resources at freelance marketplace Field Nation, in an interview.
There are many reasons why so many talented people want to work for data-first companies, such as Google, Amazon, and Facebook. Aside from perks, stock options, and the chance to have a marquis company name on a resume, people attracted to such companies tend to be seeking opportunities to innovate, opportunities to make a difference, the freedom to explore data, the freedom to question everything, and the ability to challenge management's thinking without fear of receiving a pink slip.
"Data-savvy employees, perhaps especially Millennials, want interesting, challenging work environments, and they want to keep growing. A digital company's culture has to give them a place to do their best work," said Susan Peters of GE. "A datacentric, digital transformation of a company needs to become part of an organization's entire culture. Cultivating a digital workforce doesn't just come from a hardware perspective, it comes from a deep change in corporate culture."
What's said on paper holds less and less value as employers look for new hires who can demonstrate their problem-solving prowess. Theoretical knowledge is important, but employers are wise to pay more attention to a candidate's ability to affect positive change in real-world scenarios. Some organizations involve technical and non-technical people in assessing job candidates in order to accurately ascertain the balance of technical and "soft" skills.
"What better way to assess a job candidate than to ensure they can demonstrate the skills of the job? [One way] is to have them complete an assessment that measures that skill. Another way is to walk through a scenario with enough detail to show they have the expertise," said Teri Calderon of Field Nation. "If you have a technical expert participate in the interview process [that person is] going to be able to 'call bluff' on a candidate who doesn't actually have the knowledge required."
Data-savvy job candidates will likely include more metrics in their resumes than their less data-savvy counterparts. According to Kathy Marshall of Decision Toolbox, employers should identify people who ask thought-provoking questions and ask datacentric questions.
"If a new hire asks datacentric questions, [it's] a strong indicator this is how that person's brain is wired. Look for questions like 'How will success be measured in this role?' and 'Are there any benchmarks I can use as a baseline for measuring success?' "
Look for stated - and quantified - achivements in resumes. |
Many of today's data-related job descriptions are poorly conceived and written because the hiring manager, HR department, or both either don't know or can't articulate exactly what it is they need. The side effect is a job description listing far more skills than a even bona fide superhero can possibly possess. Alternatively, job decriptions may include potentially unnecessary "requirements," which only serve to keep away perfectly qualified candidates.
"Keep only the most important qualifications in the posting. You'll quickly realize which skillsets can be taught, versus which are a necessity," said Mike Stringer, co-founder of data science consulting company Datascope, in an interview. "Some companies say Ph.D. required [or] Master's preferred, but that misses a wide array of talent. Just because a person has a Ph.D. in machine learning, doesn't mean that person will be good at your specific machine learning processes."
Technology and the global business environment are changing so rapidly some skill sets are becoming at least partially outdated within a year or two. To stay on track, companies are investing in employee education and training to keep their workers, and their companies, competitive.
"The pace of change is faster than ever before, and our educational systems are not keeping pace. It's the responsibility of the C-suite to prioritize continuous learning programs that teach their workforces the skills they need to drive the business forward," said NV "Tiger" Tyagarajan, CEO of global process management and services company Genpact, in an interview. "CEOs should think of reskilling as a business-critical mission, versus a nice-to-do."
CFO asks CEO: What happens if we spend money training our people and then they leave? Richard Branson has said: "Train people well enough so they can leave, treat them well enough so they don't want to.” |
Universities, industry associations, vendors, and opportunists are busy rolling out new data-related educational programs. Navigating the maze can be confusing and even frustrating. Nevertheless, it behooves HR departments and hiring managers to understand the differences. Some curriculae emphasize real world problem-solving considerably more than others, some are tailored to specific industries, and some are more valuable than others.
For example, Heinz College for Information Systems at Carnegie Mellon University is blending technical and managerial classes so its students can learn to manage large, diverse technical teams while partnering with different departments across an organization. Because data has become integral to what businesses do, students now have access to new educational opportunities in healthcare informatics, digital marketing, cloud-based consulting, entertainment, the arts, and more. The curriculum emphasizes experiential learning.
"The Heinz College collocates two different programs - Public Policy and Information Systems. This allows our students to understand the implications of data strategy on organizations and society," said Ari Lightman, a professor at Heinz College, in an interview. "Our students have not only a deep understanding of the different techniques to collect, store, and analyze data, but what the ramifications associated with these practices might be, especially culture, privacy, and security."
Management gurus have been harping about "leading by example" for decades. By now, workers expect it. Meanwhile, boards of directors are pressuring executives to get smart about data, but not all of them are doing a good job of leading by example. If becoming more data-driven is the company's goal, then the C-suite needs to step up.
"Currently, most leaders only harness about 25% of the available data in their decision-making process. Those leaders harnessing 60% to 70% of data when making decisions are innately creating a data-savvy culture," said Karthik Krishnamurthy, head of Global Analytics and Information Management at global business and technology services provider Cognizant, in an interview. "Executives need to ensure data and analytics are incorporated into all parts of the business. Metrics must also be established and managed to drive overall performance management."
One way to tell if a company or an employee is making progress is through monitoring. Field Nation has an "Objectives and Key Results" (OKR) culture which started with establishing the OKR vision for the company as a whole, breaking it down by functional areas, and ultimately to individual contributors. Other companies have been tracking KPIs for years. Given the breadth of KPIs which can be tracked now, and the necessity to focus on the metrics that matter most, companies are necessarily thinking about aligning KPIs with business objectives, as opposed to only department-centric goals.
The analytical capabilities of an organization are often limited by barriers to information flow. Often, the information fiefdoms are relics of yesteryear's culture, and no longer serve companies well. And, it's problems like this which cause good workers to seek employment elsewhere.
"Many companies are still thinking of data analysis as an IT issue when, in reality, it's make-or-break and must be embedded across the organization," said Tiger Tyagarajan of Genpact. "To get the most of data, we have to break down organizational silos and ensure that all employees are working toward the same goals. Otherwise, efforts will be wasted."