FRAMEWORK : Human Resources Analytics

HR Goes Agile

Traditional human resources (HR) models made sense when companies had annual goals and annual performance appraisals to measure employees’ progress toward these. But as business models change, HR must reflect the new reality.

The agile approach tears apart long-term strategies into manageable pieces. In our current world, employees need immediate feedback. Leaders need to know what’s happening in teams—and who knows this better than other team members? Particularly when the person an employee reports to may not be on that team.

See where some of the biggest changes are happening:

  • Performance appraisals are becoming an ongoing dialog.
  • Managers are receiving more real-time coaching to sharpen their people skills: from human coaches and virtual coaching programs.
  • Work is organized around teams: with multidirectional feedback, decision-making pushed to the front line, and managers in charge of handling complex team dynamics.
  • Compensation is being linked to near-term behaviors and results.
  • Recruiting is influenced by the teams on a project that determine the characteristics of who should be hired.
  • Learning and development can be directed by artificial intelligence (AI) programs. These monitor employee performance and direct the person to the virtual training programs needed for improvement.

FRAMEWORK : Human Resources Analytics

Co-Creating the Employee Experience

This Q&A with IBM’s Chief Human Resources Officer Diane Gherson demonstrates how the company is doing something too rarely seen. Management understood the quantifiable connection between employee satisfaction and its performance. Research indicated that employee engagement accounted for two-thirds of its client experience scores, and each five-point improvement in employee satisfaction added an extra 20% in revenue. That created a compelling case for investing in the employee experience.

Because IBM develops sophisticated tools, the company already had what it needed in-house to execute this strategy. Management took analytic methods it was using to measure and enhance the client experience—such as the net promoter score—and applied these to do the same for employees (I’ve encouraged organizations to do the same since giving a presentation on this at the Talent Science Conference in 2014). In overhauling talent management, Gherson focused on strengthening three employee experiences: learning and development, performance management, and sentiment analysis. She and her team also encouraged employees to speak up during the process to improve the result.

Here’s one example I loved. When IBM eliminated the compensation for its rideshare program, HR was flooded with negative feedback—monitored by its AI system. Gherson was alerted. Within 24 hours, she acknowledged what people had said and reinstated the original policy, showing employees they had the power to make change happen.

Explore how IBM is combining AI with good judgment to create a more attractive and rewarding environment for its people.

FRAMEWORK : Human Resources Analytics

One Bank’s Agile Team Experiment

This “experiment” was the most game-changing among the companies profiled in these articles. ING leadership decided to make three fundamental changes: 1) better focus on delivering “Banking on the Go” services to its 30 million online customers, 2) redeploy its internal resources to support this, and 3) simplify its organization and speed up its response time. To do that, it implemented an agile team-based system of tribes, squads, chapters, product owners and coaches. (There’s a simple and useful graphic in the article that illustrates the structure under the heading of “Tribes, Squads and Chapters.”)

In the past, customer issues could go unsolved—or fall between the cracks—as different departments took or didn’t take ownership. ING developed smaller teams that would provide end-to-end project management. They were given permission to try new ideas and, more importantly, were rewarded rather than punished when something failed. The philosophy became “fix it and move on.”

To prevent teams from wandering down the wrong path, every quarter there are strategy meetings. Tribes look at their biggest successes and failures, review what they learned, and spell out their goals for the next three months.

Here is the result:

  • ING has empowered small teams to set up and resolve customer issues.
  • It has domain experts across the franchise that support the agile teams.
  • Its business management and leadership ensure strategic direction is aligned to the corporate strategy.

How does this apply to you?

The idea of marrying talent and technology to create a better business—culturally, operationally and financially—is a worthy goal. By diving deeper into the articles and breaking them down into “chunks,” identify what is important to your company and open the dialogue across the organization.

“Change is hard because people overestimate the value of what they have and underestimate the value of what they may gain by giving that up.”

— James Belasco and Ralph Stayer

FRAMEWORK : Human Resources Analytics

Finding Context for CHROs and Data Analytics

What exactly is the CHRO’s role today?

Neeraj Sanan’s People Matters article, “How contextual intelligence is empowering CHROs,” contends that today’s businesses demand more  strategic direction from HR that requires “an assertive, data-driven CHRO.”

Research shows survey respondents expect Human Resources to focus on aligning their function with the overall business strategy rather than their traditional role.

However, Sanan cites research that shows a “large gap” between the requirements for this strategic role and “analytical data skills” of many CHROs today, and this is where “contextual intelligence” enters the discussion. Yet, the article fails to explain exactly what “contextual intelligence” is and how it is “empowering CHROs.”

This is where the disconnect occurs.

Confusing terminology aside, we all agree that businesses need to better understand and promote the use of data analytics in HR. For further perspective and insight, I asked my colleague Eric Sandosham to join me in a discussion about questions the article raises.

What follows are excerpts from our conversation and discussions with my Editor. Our reflections focus on the meaning of “contextual intelligence” and data analytics’ role in Human Resources.

Marcia Tal: The term “contextual intelligence” is often used by global organizations for redefining roles for both people and leadership when moving talent, services and products from one market to another.

In this case, using data and analytics helps understand attitudes, belief systems, mental models, how people adjust to change, and to what degree people are open to new ideas.

Eric Sandosham: “Contextual intelligence” is a very big, even bombastic word. In the case of HR, the way you use experiences, the nature of different cultures, different occasions, different personal contacts—all of that is contextual. All analysis has no value until you contextualize it.

The real pressure point is that many organizations are feeling that HR may be the weakest link. And I mean weakest link in the sense that the quality of decision-making is not keeping pace with what’s required.

Marcia Tal: I think we all agree that data and analytics can provide the capabilities to better understand people. HR can use that understanding to determine that we have the right people. The right job. And the right skills and mindset. With that combination, we can design strategy and drive new business practices to deliver on business results.

Eric Sandosham: Commentators often talk of “contextual intelligence technology” and the idea of big data—in all the work that I’ve done in HR, there’s very little big data. What data we have in Human Capital Analytics is instructive. You have profiles, performances, productivities, and there are some great examples of using digital applications to monitor employees. This data may be available, but it’s not being curated to allow CHROs to be able to map an employee’s journey. That’s the challenge.

Marcia Tal: I think that CHROs don’t have to be the analyst themselves. What they need is access to analysts within their organizations or a budget to acquire external sources for data analysis. There’s such a big gap—between what organizations expect and the capabilities of CHROs— because this analytics discipline is very advanced. CHROs should be savvy enough to understand what they need and to find the right specialists, but they don’t have to be the analyst.

Eric Sandosham: In all the data work that we do, data only has meaning when it’s phased into context. It may be unique to a particular situation, or unique location attributes, or specific problematic attributes. Of all the data that we use, we never use it generically. It’s never a universal set of data—because it’s people.

Often it’s the exact opposite. In our experience, HR business partners resist using data. Their decisions have largely been based on customized, contextual information. HR is so used to making decisions that are individual or departmental, they may see data as robbing them of that contextualization. Does the data homogenize the approach? Does HR lose what’s special about their case-by-case approach?

Marcia Tal: In the end, there needs to be an organization-wide culture that is open to data… and recognizes the individual… and embraces that people and organizations are driven by something larger than any single one of us.

Eric Sandosham: Without saying, it’s people that move the needle. Technology comes very much later in the process. Technology itself doesn’t lead to discussion or to transformation; technology comes in at the end to optimize and automate.

If you want to know how to fix things on a human capital level, look to people rather than technology. You can crack it with people—with good old-fashioned thinking and framing.

Intelligence, contextual or universal, comes from human mental strength.

Marcia Tal: Exactly, it’s the framing that provides context. The solution comes from human understanding.

FRAMEWORK : Human Resources Analytics

How to Create Your Own Superconsumer Associate Program

In “The Benefits of Hiring Your Best Customers,” Eddie Yoon has an interesting take on the idea of superconsumers.

He’s a big proponent of the “superconsumer strategy: find, listen to, and engage with your most passionate customers; understand their tastes, emotions, and behaviors…and then tailor your decision making, coordinate, concentrate your cross-functional investments, and innovate—both your product and your business model—to give these consumers what they want and need.”

Yet, he finds that it’s not only the superconsumers outside organizations who are passionate about a company’s products and services; it’s the “superconsumers who are inside your organization, working at every level.”

Talking about corporate culture, Yoon notes that culture is critical but often hard to quantify. “But,” he concludes, “unleashing a culture of superconsumers has clear benefits.”

To make his point, he quotes an article, “Manage Your Energy, Not Your Time” (Schwartz and McCarthy)— “To effectively reenergize their workforce, organizations need to shift their emphasis from getting more out of their people to investing more in them, so they are motivated—and able—to bring more of themselves to work every day.”

This is an astute observation.

How can you take this idea and turn it into something tangible and systematized across your organization so it transforms your culture?

If you are familiar with Management Associate Programs—mostly large corporations’ career development tracks—you may have a hint of my idea…

What would you need to create a formal data-driven Superconsumer Associate Program within your company?

Think a two-year rotation program created for employees that constantly exposes your “in-house superconsumers” to all facets of consumer-facing operations within the company.

Imagine how a program like this could, over time, transform a culture.

But how would the program work?

Creating a Superconsumer Associate Program would look something like this sketch:

  1. Identify your “in-house superconsumers”
  2. Model on premier Management Associate Programs
  3. Establish a corporate budget for required investment
  4. Specify the outcomes, metrics and impact of the program
  5. Build a set of criteria for Superconsumer Associates
  6. Plan a two-year rotation, placing SCAs in consumer-facing positions where they can best express their passion to fuel growth of the company’s products and/or services
  7. Form an internal marketing communications program to promote the program and encourage applications
  8. Develop a culture around the program – and a formal yearly class (“Class of 2017”)
  9. Implement Superconsumer Associate Program
  10. Measure program, improve and iterate

Those Superconsumer Associates who complete the program would go onto further customer-facing positions and challenges in the company and become mentors for the following SCA classes. Of course, your new superconsumer culture would be measured for its effect on predictable long-term growth and return on investment.

In this way, we invest in our superconsumer culture, our own super employees, our customers, and our future.