HR: Applying Business Judgment to Data Science

Most organizations place too much emphasis on data science and data management at the expense of driving business decisions and actions.

To improve the impact of talent data, HR is increasingly seeking individuals with advanced statistical degrees and experience working with statistical tools and models.

However, analytics expertise is only part of the equation. Business judgment— the ability to use business and organizational knowledge to draw conclusions from talent data—is far more influential on business outcomes.

CEB research has shown that, on average, business judgment activities have up to a 32% analytic impact compared to 18% for data science activities. (‘Analytic impact’ is defined as the extent to which talent analytics improves decisions and provides actionable support to key stakeholders.)

HR executives at the best organizations focus less on advocating for talent analytics and more on building the function’s ability to:

• Set a clear vision and objectives for analytics staff that are oriented around business judgment;


• Hold all HR staff accountable for applying data to business challenges; and


• Establish accountability and connections between analytics staff and the business.

For example, Telefonica Europe, a telecommunications company, has refocused the role of the HR analytics function toward inspiring, influencing, and shaping business decisions using three key steps:

Step 1: Align the hiring process to overall analytics goals. Although Telefonica hires candidates with advanced degrees, they assess for strong judgment skills critical to driving business decisions, as shown in real-world simulation tasks.

Step 2: Reinforce the need for analytics to support action. Telefonica ensures HR analytics employees have opportunities for internal networking and best practice sharing at every step of the HR analytics project cycle.

Step 3: Establish mutual accountability for analytics results. Telefonica’s HR analytics team lead engages with business stakeholders before the start of any project to establish clear business expectations—what HR analytics will do for the business and what the business unit will do to support the HR analytics team. Early collaboration and consensus ensures HR analytics will be trusted and used by the business.

via HR: Applying Business Judgment to Data Science | CEB Blogs.

HR: Applying Business Judgment to Data Science

Next Wave HR Tech Part 2: HR Data

You don’t need to read the latest story about NSA leaks to understand that people today leave an increasingly wide trail of data as they work their way through life. There’s the data found in HR systems, the data that is compartmentalized in departments (like sales or production), and external data channels like social media. Is there an opportunity for HR to harness people data across the entire spectrum of data sources to find the best utilization of people?

 Integrating Non HR Data

Like most functions, organizations and people, the HR Department is buried in new somewhat relevant data. The organization’s management will waste little time before they mandate the discovery of uses for this external data. Recruiting, which is always the most competitive of the HR silos is already trying to make sense of a world that violates our preconceptions.

What used to be private is now public. What used to be assumed is now measured. What used to be implied can now be made literal.

Today’s data tsunami seems to get much of its volume from social media. Services like Dice’s Open Web (or Gild, Entelo, TalentBin.com, HiringSolved, Swoop, RemarkableHire) aggregate social data much the way that Indeed aggregates job data. Relentlessly scraping social sites for information about people, these services claim to give the Recruiter deeper and better access to insight about a particular candidate.

LinkedIn sells the data. Monster, CareerBuilder and even Indeed sell data about candidates. The problem isn’t new or is it? We think that the volume of data coupled with our lack of ability to digest it all means that this is more than a bigger version of an old issue.

And, data about our people or their connections is just the beginning. The contemporary HR Department has to be prepared to incorporate data like the following:

• Investment data (including a clear picture of which employee owns how much of the company)


• Industry market trend data (for workforce planning)


• Labor Market Data (who are the competitors and what does supply look like?)


• Free or low cost Training available through various sources (YouTube, Khan Academy)


• BYOD device data (to assess risk when circumstances require it)


• Aggregate health data (from suppliers like Kaiser) to fill in Workforce


• Social Media data about current employees (not to mention the spillage from internal collaboration systems


• Supply Chain people data (for the management of the health of the ecosystem)

And, that’s just the beginning. Individual employees will increasingly be a part of the development of learning modules and/or figuring out what works from the marketplace.

In order to blend the flow of external data with the material we already have captured in our systems, new concepts will have to be forged. In order to fully deploy our people, we’ll need to know more about them. At the same time, we’ll be taking more of their input.

The mechanics of data integration are currently up in the air. Providers like Broadbean develop integration tools that give recruiting departments a multidimensional view of their performance. The process harnesses data that’s been lying around as well as data from new sources.

Data makes its own gravy. That means that each of the new data flows will also kick off powerful metadata (like anonymities health care data to help uninsured companies cover their employees). The more that external data is intertwined with internal data, the better our prognostics will be.

HR Data for Other Departments

As long as an organization is a comfortable tribal size (say, under 150 employees), it’s possible for everyone to know everyone. The distance between the top and the bottom is not great. Job descriptions are not work rules. Departmental lines are fuzzy.

Growth creates the need for policies, procedures and structured governance. It’s not long until the various boundaries between people and sub groups start to get rigid. By the time a company reaches 1,000 people, it’s the big time. It’s no longer possible for everyone to know everyone. Hierarchies are established to navigate the problems caused when most members of the organization are strangers to each other.

One of HR’s central roles is policeman. Someone has to enforce the governance structures required by size. While it would be great to have a world where strangers immediately understood each other’s boundaries, we build our organizations with human beings who have a limit of about 150 connections that they can manage well.

Much of HR’s work is designed to overcome the communications problems demonstrated in the telephone game. Just like any form of copying, the clarity of a message declines each time it is transmitted. (Basic internet protocols are designed to overcome this problem by including additional information so that the message content remains intact.) HR’s job (in interpersonal matters particularly) is to ensure that the organizations rules and boundaries are enforced and reinforced.

Social tools (like Honey, Yammer, Chatter and a host of others) are restructuring the way that communications work inside the company. (Here are the stories about that.) As a result, cultural norms form like crystals around seeds discovered in the social flow. The really interesting thing is that these social tools seem to impact the degree to which the telephone game disrupts communications.

What used to be delivered in a stale memo is now communicated in the flow/context of other data. It turns out that the more personal the data, the more it sticks. The memo was used to reinforce the message of policy; to prevent telephone game-like degradation. Much of that function can now be accomplished socially.

This is a significant unintended consequence of using social media in the organization. It enlarges and extends the span of control without resorting to enforcement or coercion.

So, HR needs to be a good bit smarter about using influence (think of peer pressure, not Klout) to move ideas through the organization. The interesting question here is whether or not social media creates too much homogeneity. The fact remains that social media reduces the work required from HR.

Meanwhile, the other departments in the company are getting hungry to use social data about employees as a way of getting things done. HR seems like the logical receptacle for the organization’s data on its people, doesn’t it? Since forever, individual departments have only been able to know a lot about the people within their boundaries. Today, they can easily discover things about the rest of the organization through social channels.

While you could be forgiven for forecasting a chaotic reality in which HR never stepped up to this responsibility, that future isn’t very likely. The forces that drive the requirements for HR in the first place haven’t been voided. HR’s opportunity horizon has expanded.

Here are some of things the rest of the organization would like to know about the workforce:

• Which employees are also customers? Which are not? Why


• Which employees are also investors? Which are not? Why?


• Which employees are stakeholders in the community (from elected to volunteer leadership)?


• Which employees would be good for beta testing programs? Who has already done this and what were the topics?


• Which employees would be good for focus groups? Who has already done this and what were the topics?


• What do we need to know about the people on the other department’s softball team?


• Which employees might be useful (by virtue of education, experience or avocation) in times of talent shortage?


• Which employees have connections that might be useful in a particular sales process?


• Which employees have connections that should be converted to leads?


• Is there something about our department that is causing communications problems? (see how our beliefs and values line up with another department)

And, that’s just the beginning. As more data about employees becomes available, there will need to be a central repository for the information and useful ways to sift through it.

In the very near term, HR will become a net publisher of data to other departments. By helping the organization know as much as it can about employee likes, dislikes, affiliations, hobbies, connections and other interests, HR will be able to step up to its mission of finding the best utilization of people.

via Next Wave HR Tech Part 2: HR Data | HR Examiner.

Next Wave HR Tech Part 2: HR Data

How Important Is Data Analytics to the Future of HR?

Having discussed harnessing social media, enabling internal knowledge creation and leveraging social capital in previous articles, it seems a logical topic to cover next is to address one the key players in this debate and how they interplay with advances in data analytics and technology: Human Resources.

Big Data remains big news to HR so why is it (as was recently noted by the CIPD) “such a big ask for HR”? What is getting in the way? Is HR’s work too tied up in the ebb and flow of day to day business issues? How does HR achieve sophistication of operation if they are caught up in administrative tedium? It seems more than this though as the CIPD recently reported that organisational silos, insufficient internal skills sets, suspicion and scepticism from HR professionals, all surround the use of innovative and contemporary data sets.

HR analytics plays a key part in getting to grips with the challenge of containing costs while developing a high performing workforce; the primary issue facing most companies today. But do organisations know enough about their workforce to optimize its success? We all know how HR analytics can benefit talent sourcing and recruitment however it can also add to the wider HR remit including measuring and managing: retention; learning and development; sickness absence and performance data. Looking at the bigger picture, branding, marketing, social media, CSR and the creation of how HR can contribute to operational effectiveness can all be supported by gathering the right HR data in the right way.

Big Data and HR analytics are key to HR achieving sophistication and delivering a broader impact. The CIPD recently celebrated its’ centenary and asked HR professionals to comment on how HR can be future focussed. Central to the debate was how HR meets the demands of being strategic in contribution to the business. So how can HR help create lean efficiency in operations and play a pivotal role in a business? Human Resources need to be Innovators and Integrators in organisations; quite simply HR leaders must stay on top of the latest developments in their field and ensure their teams do so too. It is not simply a case of considering how analytics technology can help HR carry out their work more easily. They should also take a broader view, exploring ways they can use technology to better connect people with the company and also HR with their role in strategy.

It seems that organisations are now at different stages of the analytical journey. Organisations such as Royal Bank of Scotland, Unilever, Nestle and Transport for London are leveraging people metrics and insights to improve business performance, employee engagement and satisfaction. Ultimately it does come down to Data vs. Insight – to fully leverage the strategic benefits of HRIS data and human capital analytics, HR Analysts and HR leaders must be able to understand the data themselves and then to communicate the story it tells. The skills of uncovering “insight” and being able to communicate this effectively as a ‘story” that correctly influences human capital decisions, is of increasingly critical importance in the global economy.

via How Important Is Data Analytics to the Future of HR? | Mark Braund.

How Important Is Data Analytics to the Future of HR? 

Human Resources Tentatively Tries Predictive Analytics

Knowing the probability of important employee events before they happen can have a big bottom-line impact.

What’s the probability that employee X will leave in two years? Could predictive analytics supply an answer?

Accurately forecasting what any individual employee will do in the future is at the bleeding edge of the market, say human resources experts. What’s more common, and on the rise, is using analytics to better understand the patterns of large collections of employees, such as in a call center.

“Statistical techniques used for prediction tend to work with larger numbers,” David Gartside told InformationWeek in a phone interview. Gartside is managing director responsible for HR offerings and capabilities within the Accenture Talent & Organization practice.

In call center operations involving thousands of people, such analyses are being used today, providing, for example, predictions about the percentage of workers likely to leave in a month.

“If you have a good view of this, you can plan accordingly, ramping up or down recruiting,” Gartside says.

Three things are driving the use of predictive analytics in HR, Gartside told us. First, HR departments are getting much better at using operational processes and technology with an eye toward collecting good-quality data to make better decision-making.

“The second piece is social data,” he said, referring to the inclusion of both external and internal data. These rich data sources didn’t exist even a few years ago.

Finally, he notes, vendors of HR solutions are increasingly building analytics into their core platforms.

But predicting an individual’s future actions — think Minority Report-style “precrime” — raises a number of largely unanswered legal and ethical questions, too, which explains why HR organizations have been pursuing this application of predictive analytics with a great deal of caution.

In the context of NSA spying revelations and other privacy concerns, “people have a heightened sensitivity” about surveillance, said Mark Berry, vice president of Human Capital Analytics and Reporting at ConAgra Foods, during his presentation at the Predictive Analytics Innovation Summit in Chicago earlier this month.

Nevertheless, ConAgra Foods, which has only just embarked on some HR analytic programs, hopes the work will help it plan better and improve business outcomes.

 

 

“We want to know our employees as well as we know our customers,” Berry said, adding that the company has already developed a number of safeguards for what types of employee data it will and will not collect, as well as assess the impact, both positive and negative, of the project before proceeding.

Where to start
But how accurate is predictive analytics when it comes to forecasting individual employee events, such as a key vice president of sales quitting without notice?

“It is a very difficult science,” Accenture’s Gartside says. And like ConAgra’s Berry, Gartside urges companies to think about how these systems will be regarded by employees and the marketplace. Make sure these programs aren’t just cognizant of what’s legally allowable, he cautions, and make sure they are aligned with the culture and company brand as well.

Asked for advice on how to get started with predictive analytics in the HR function, Gartside offered the following:

• Start with a business problem, such as service quality, being impacted by employee attrition.


• Do a pilot with existing data and capabilities. “See if these analytics have value, and don’t wait for the data to be perfect.”


• Finally, put in a technical infrastructure that can make this kind of analysis repeatable and easy to do.

Will advanced, data-driven approaches to employee performance and outcomes become standard? Gartside thinks so.

“Look at how many people have a job title with ‘talent analytics’ in it. This title didn’t exist two years ago,” he said, adding that the Fortune 250 are carving out this executive role, “because people are finding value in it.”

via Human Resources Tentatively Tries Predictive Analytics – InformationWeek.

Human Resources Tentatively Tries Predictive Analytics