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Big Data and Mid-Level Managers

While most information technology professionals and many senior executives may already have well-developed analytical skills, experts say more middle managers need to hone their big-data skills to make the most insightful -- and impactful -- decisions for their organizations.

Monday, August 5, 2013
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As more organizations realize that decisions can be best made after gleaning

"actionable insights" from the information within their internal databases, external market research and social media, more middle-level managers will be under the gun to build their big data analytical skills, according to a survey of nearly 800 respondents from more than 50 industries, conducted by the Seattle-based Institute for Corporate Productivity.

While senior executives and functional experts are thought to have the most highly developed analytical skills, "the broad mid-levels of today's organizations still have a way to go," according to the study, which was released last month.

About a quarter (23 percent) of the respondents said their leaders were "expert" in their analytical skills, and 26.9 percent said their functional leaders were at that level. However, only 14.4 percent said their managers were expert, 7.8 percent said their supervisors were expert and 11.3 percent said individual contributors were at that level.

To best compete in today's business world, managers at all levels need to have big-data skills, says the American Management Association's Senior Vice President Robert G. Smith. (The AMA sponsored the survey.)

"No longer do the skills for understanding data reside solely in IT and marketing – mid-level managers also need such skills because they are closest to the sources of the data," Smith says.

"And, increasingly, decision-making is being pushed down to this level," he says. "Tens of thousands of people will visit the company's website and click on several pages. In addition, on social media, people will be making comments about their products and their competitors are making inferences from that. Middle managers are seeing all of this information."

So just what are the big-data skills that are the most critical for middle managers to know? Smith says managers should be able to glean insights from a variety of data sources, including third-party research and social media, as well as information about customer behavior and prospect behavior. As such, they need to have critical-thinking skills, problem-solving skills and they need to be able to communicate and present their findings persuasively.

"The ability to analyze data is critically important," he says, "but so are the 'softer' skills of presenting and persuasively communicating the findings and insights to others."

These types of skills are most often learned through mentoring, training and self-study, Smith says. Information-technology professionals can teach middle managers how to use data analytics tools, but it takes people who have a real grasp of the overall business to teach middle managers how to think critically about the business impact.

The challenge to teaching such skills is tied to the learner's level of confidence -- or lack thereof -- as Smith says many middle managers are intimidated by the concept of big data.

"The way we describe big data – volume, velocity and variety – that description can be exciting, as well as instill some fear," Smith says. "But with appropriate training to make people feel comfortable, and demonstrating how one can get their arms around data and turn it into useful information, middle managers can become more confident in data analytics."

To support the growing demand by business, the AMA in June launched a new portfolio of "Analytical Skills" seminars, more than two dozen online and classroom seminars, including "Improve Your Analytical Skills: Making Information Work for You," "Managing Chaos: Tools to Set Priorities and Make Decisions Under Pressure," and "Strategy Execution: Getting It Done."

Training on such skills is necessary as big data is only going to get bigger and more complex, Smith says.

"The definition of big data has been morphing over time," he says. "Years back, it really was just an IT term to define the databases that house data, but now it's morphed into how organizations take increasingly varied data and turn it into actionable insight. The amount of data is only going to increase over time and it will be an incredible challenge for any business to make sense and use it strategically to make better business decisions in areas such as getting and keeping customers."

Brian Levine, partner and U.S./Canada leader for workforce analytics at Mercer in New York, says that middle managers not only have to understand how to best leverage data analytics to determine the impact of specific actions, but they also must have "higher-level conversations" with senior executives to explain the impacts and opportunities to generate business value.

"This is becoming part of the decision-making process," Levine says, "and it's the middle managers who are creating the business cases which the executive group will evaluate."

The most critical big-data skills are the ability to ask the right questions and know what data to pull together to answer them, he says. Managers need to be able to reduce a lot of data to the core elements, and they need to be able to leverage new technology "to tell the story." Business-intelligence tools have become the norm, and they need to combine data sources appropriately to make sure they can tell the story accurately and completely.

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"It's not enough to have complex associations pop out of a program," Levine says. " 'Do the following 20 things to get this outcome'; they need to be able to understand what it means. To be effective, they also have to engage executives in the interpretation of data, to ensure that at the end of the process they accept the information being presented to them."

Over the last year, Mercer partnered with the AMA to co-sponsor the development of a curriculum on workforce analytics.

"Organizations need to build capacity, therefore they need to get smart on how to use data to drive insight," he says. "The C-suite is clamoring for it, and HR needs to develop that capability, and because of that, we developed a curriculum to help organizations get to where they need to go."

The challenges to getting middle managers to embrace big-data skills are the type of challenges "you would expect when you engage people who are used to making decisions based on their gut," Levine says.

"They are going to be more skeptical about what the data can tell them, so part of the process is getting them to change their thinking – to see how different strategies play out based on data analytics," he says.

But training middle managers on big-data skills is only part of the task for HR leaders and other managers – they also need to ensure that cross-functional teams of such managers are structured appropriately to achieve the most effective actionable insights, says Gene Tange, CEO and founder of PearlHPS Inc., a cloud-enabled predictive analytics software company in Pleasanton, Calif.

The firm's software focuses on "execution" analytics, of which HR leaders and other managers can use to predict whether a cross-functional team will be able to achieve desired business outcomes. The software analyzes three variables: team leadership competence, team goal alignment and team continuity.

"If you look at each of these variables individually you get insight, but if you combine them, they predict business outcomes of the team up to 12 months out," Tange says.

He refers to a 2012 Gartner report on analytics, "Predicts 2013: Business Process Improvement Leaders Need to Stop Tackling the Tactical and Get Strategic," which states that, by 2016, 70 percent of the most profitable companies will manage their business processes using real-time predictive analytics or "extreme collaboration."

"This alone should be compelling to learn and become more comfortable or be left behind when senior line executives ask for predictive solutions," Tange says.

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