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Month: February 2018

How Today’s Analytics Change Recruiting

HR is late to the analytics game by modern standards, and yet, HR metrics is not a new concept. The difference is that modern analytics enable HR professionals and recruiters to measure more things in less time and derive more insight than ever before.

Rosemary Haefner

Rosemary Haefner

“If you’re looking at recruiting, there have always been metrics such as time to hire and cost per hire, but you’re seeing other channels and avenues opening up,” said Rosemary Haefner, chief human resources officer at online employment website, CareerBuilder.com.

The “time to hire” or “time to fill” metric measures how many days it takes from the time a requisition is posted until the time an offer is accepted. The longer a position remains open, the higher the cost of talent acquisition. In addition, if a position remains open, an intervention may be necessary to ensure the work at hand is getting done.

If time to fill were the only measure of success, then, in theory, the faster a position is filled, the better. However, as most working professionals have experienced, the person who can be hired the fastest isn’t necessarily (and probably isn’t), the best candidate.

On the other hand, moving too slowly can cost organizations sought-after talent.

“There’s the time to fill, the cost of the person you hire, whether that person is high-potential and what their expected tenure in the organization is. That’s an example of four interrelated metrics,” said Muir Macpherson, Americas analytics leader, People Advisory Services at EY. “HR needs to stop thinking about individual metrics and consider the problem they’re trying to solve and how to optimize across a set of metrics simultaneously.”

Beyond keywords

Talent marketplaces and talent acquisition software made it easier to navigate a sea of resumes using keywords and filters. In response, some candidates stuffed their resumes full of keywords so their resumes would rank higher in searches. If one’s resume ranked higher in searches, then more people would see it, potentially increasing the candidate’s chance of getting interviews and landing a job.

Masterful keyword use demonstrated an awareness that the recruiting process was changing from a paper-based process to a computer or web-based process. However, other candidates who might have been better fits for positions risked getting lost in the noise.

The whole keyword trend was a noble effort, but keywords, like anything else, are not a silver bullet.

With today’s analytics tools, HR departments and search firms can understand much more about candidates and the effectiveness of their operations.

“You can use a variety of big data and machine learning techniques that go way beyond the keyword analysis people have been doing for a while that integrates all of the data available about a candidate into one, unified prediction score that can then be used as one additional piece of information that recruiters and hiring managers can look at when making their decisions,” said Macpherson.

Data impacts recruiters too

Recruiters now have access to data analytics tools that enable them to better match candidates with potential employers and improve the quality of their services. Meanwhile, HR departments want insight into what recruiters are doing and how well they’re doing it. The Scout Exchange marketplace provides transparency between the two.

“We can look at every candidate [a recruiter] submits to see how far they got in the process and whether they got hired. We use that for ratings so [companies and the recruiters they use] can see the other side’s rating,” said Scout Exchange CEO Ken Lazarus.

The site enables organizations to quickly find appropriate recruiters who can identify the best candidates for a position. HR departments also allows HR departments to see data and trends specific to their company.

Bottom line

Analytics is providing HR departments, recruiters and business leaders with quantitative information they can use to improve their processes and outcomes.

“Knowledge is power and having that data is helpful. For me, the first step is knowing what you’re solving for,” said CareerBuilder’s Haefner.

Right now, HR analytics tend to emphasize recruitment. However, attracting talent is sometimes easier than retaining it so it’s important to have insight throughout the lifecycle of employee relationships. EY’s Macpherson said HR departments should think in terms of “employee lifetime value” similar to the way marketers think about customer lifetime value.

“[HR analytics represents] a huge opportunity because for most companies, people and compensation are their biggest costs and yet there has been very little effort put into analyzing those costs or getting the most out of those investments that companies are making,” said EY’s Macpherson.

How the IoT Will Impact Data Analytics

IoT devices are just about everywhere, in cities, on oil rig, and on our wrists. They’re impacting virtually every industry, and their growth is outpacing organizations’ ability to make the most of that data.

To give you an idea of scale, IDC expects global IoT spending to reach nearly $1.4 trillion by 2021, up from $800 billion in 2017. The IoT is all around us, in many cases fading into the backgrounds of our homes and lifestyles, all the while generating massive amounts of data. The trick is driving value from that data.

The Balance of Data is Shifting

Over the past decade, we’ve witnessed several shifts in enterprises’ ability to deal with data. While different companies and industries are at different stages of maturity, we’ve seen and continue to see analytics evolving, whether it’s adding unstructured analytics capabilities to structured analytics, third-party data sources to our own, or IoT data to enterprise data. Slowly but surely, we’ve been seeing the balance of data shift from internal data to external data, particularly as more IoT devices emerge.

Edge analytics helps separate meaningful data from all the noise, which usually means identifying, and perhaps reacting to, exceptions and outliers. For example, if the temperature of a piece of industrial equipment rises beyond a threshold, maintenance crews may be alerted, or the equipment might be shut down.

Organizations attempting to manage IoT data using their traditional data centers are fighting a losing battle. In fact, Gartner noted that the IoT is causing businesses to move to the cloud faster than they might move otherwise. In other words, when so many things are happening in the cloud, it makes sense to analyze them in the cloud.

Data and Analytics Strategies: Top-down and Bottom-up

The sheer amount of data organizations must deal with increases greatly with the IoT, and there are still philosophical debates about how much data should be kept and how much data should discarded. Gartner strongly advises its clients to be smart about IoT data, meaning that one should not save all the data hoping to drive value from it in the future, but instead focus on strategic goals and how IoT data fits into that.

We often hear how important it is to align analytics efforts with business goals. At the same time, we also hear how important it is to uncover unknown opportunities and risks simply by allowing the data to speak for itself. Some of the most sophisticated companies I’ve talked to over the last several years are doing both, with machine learning identifying that which was not obvious previously. In Gartner’s view, “data and analytics must drive business operations, not reflect them.”

One major challenge organizations face, practically speaking, is operationalizing analytics — with or without the IoT. The core problem is moving from insights to action, which can’t be solved completely with prescriptive analytics. It’s a larger problem that has to do with company culture, stubborn attitudes and the very real challenges of integrating data sources.

Meanwhile, some organizations are pondering how they can use the IoT to improve customer experience, whether that’s minimizing transportation delays, improving environmental safety or otherwise eliminating friction points that tend to irritate humans. Humans have become fickle customers after all, and each touch point can affect a brand positively or negatively.

For example, Walmart placed kiosks in some of its stores that retrieve online orders, scan receipts and trigger the conveyor belt delivery of the items a customer purchased. The kiosks address a customer pain point which is walking all the way to the back of the store and waiting several minutes for someone to show up only to be told the order can’t be located.

Now think about what Walmart gets from the kiosk: trend data about customer use and experiences that may impact staffing, inventory management, marketing, supply chain. Clearly, the data will also indicate whether the kiosk idea is ultimately a good idea or a bad idea.

In the pharmaceutical industry, GSK has been working with partners to develop smart inhalers that track prescription compliance and dosing. The data helps inform research, and it also has value to doctors and pharmacies.

Similarly, enterprises can use IoT data to develop predictive models that help improve business operations, logistics, supply chain and more, depending on the nature of the sensors and the device.

Are Media Relationships Dead?

question-mark-160071_640Strange as it may seem, PR pros used to spend incredible amounts of time cultivating relationships with the media. It wasn’t an email here or there or a social media ping. It was face-to-face time with editors of the target publications at events, on the road, and elsewhere.

I don’t know how many lunches, dinners, and media tours I went on when all of those things were fashionable.  While my PR clients were more interested in “hits” and cover stories, my agency was more concerned about the relationships we established because relationships transcend any client engagement.

In today’s highly fragmented world, things are very different.  PR people have to multitask on entirely different levels and in doing so, they sacrifice focus – focus on relationships, focus on targeting pitches, focus on learning what their clients really do.

I believe it’s still important to develop actual relationships with the media.  I can’t speak for all journalists on this point, but I can tell you that if we’ve established a relationship, your pitch will be placed at the top of the virtual pile, and I’m less inclined to delete it in the first place.  Also, if I have to do outreach for a story, I’ll probably contact you first.

One time, I spent 30 minutes on the phone talking to a PR person about his client’s product strategy simply because every time I needed him to cut through the red tape at that client’s organization, he did it.

PR success requires a confluence of many things, some of which are in your control and some of which are not.  One thing you can control is the way you approach and work with the media.  If you want to have more influence, stop looking at your job as a series of rat-tat-tat news announcements and start looking at the bigger picture.  Cultivate actual relationships with people, because there will be times when you need them, and vice versa.

Remember:  actual relationships transcend clients and publications.  You or I may move tomorrow.  If one or both of us does, you can count on me to point you in some kind of helpful direction, even if your client does not fit within one of my beats.

Why Privacy Is a Corporate Responsibility Issue

Many organizations have Corporate Responsibility programs that focus on social issues and philanthropy. Especially in today’s Big Data era, why is privacy not part of the program?

Today’s companies are promising to lower their carbon footprints and save endangered species. They’re donating to people in developing countries who have far less than we do, which is also noble. But what about the fact that American citizens are a product whose information is bought, sold, and obtained without consent? In light of recent events, perhaps the privacy policies deserve more consideration than just two linked words at the bottom of a website home page.

“Privacy is a big issue for a host of reasons — legal, ethical, brand protection and moral,” Mark Cohen, Chief Strategy Officer at consultancy and technology service provider Elevate. “[Privacy] is an element of corporate culture [so what goes into a privacy policy depends on] your values and priorities.”

Problems with Privacy Policies

There are three big problems with privacy policies, at least in the US: what’s in them, how they’re written, and how they’re ignored.

One might think that privacy policies are tailored to a particular company and its audience. However, such documents are not necessarily original. Rather than penning a privacy policy from scratch, some are literally cutting and pasting entire privacy policies regardless of their contents. In fact, the people who are simply grabbing another company’s privacy policy might not even bother to read the content before using it.

The boilerplate language is also a problem. In-house counsel often uses freely available forms to put together a privacy policy. They may use one form or a combination of forms available to lawyers, but again, they’re not thinking about what should be in the document.

In addition, the documents are written in legalese, which is difficult for the average person to read. Businesses are counting on that because if you don’t know what’s in a privacy policy, what you’re giving away and what they intend to do with your information, you’ll probably just hope for the best. Even better, you’ll click an “I agree” button without knowing what clicking that button actually means. It’s a common practice, so you’re not alone if that’s the case.

Oh, and what’s stated in the documents may or may not be true, either because the company changed the policy since you last read it or they’re ignoring the document itself.

“After May 2018 when the new GDPR [General Data Protection Regulation] goes into effect, it’s going to force many companies to look at their privacy policies. their privacy statements and consents and make them more transparent,” said Sheila Fitzpatrick, Data Governance & Privacy counsel and chief privacy officer at data services for hybrid cloud company NetApp. “They’re going to have to be easily understandable and readable.”

Businesses Confuse Privacy with Security

Privacy and security go hand-in-hand, but they’re not the same thing. However, the assumption is, if you’re encrypting data then you’re protecting privacy.

“Every company focuses on risk, export control trade compliance, security, but rarely you find companies focused on privacy,” said Fitzpatrick. “That’s changing with GDPR because it’s extraterritorial. It’s forcing companies to start really addressing areas around privacy.”

It’s entirely possible to have all kinds of security and still not address privacy issues. OK, so the data is being locked down, but are you legally allowed to have it in the first place? Perhaps not.

“Before you lock down that data, you need the legal right to have it,” said Fitzpatrick. “That’s the part that organizations still aren’t comprehending because they think they need the data to manage the relationship. In the past organizations thought they need the data to manage employment, customer or prospect relationships, but they were never really transparent about what they’re doing with that data, and they haven’t obtained the consent from the individual.”

In the US the default is opt-in. In countries that have restrictive privacy policies, the default is opt-out.

The Data Lake Mentality Problem

We hear a lot about data lakes and data swamps. In a lot of cases, companies are just throwing every piece of data into a data lake, hoping it will have value in the future. After all, cloud storage is dirt cheap.

“Companies need to think about the data they absolutely need to support a relationship. If they’re an organization that designs technology, what problem are they trying to solve and what data do they need to solve the problem?” said Fitzpatrick.

Instead of collecting massive amounts of information that’s totally irrelevant, they should consider data minimization if they want to lower privacy-related risks and comply with the EU’s GDPR.

“Companies also need to think about how long are they’re maintaining this data because they have a tendency to want to keep data forever even if it has no value,” said Fitzpatrick. “Under data protection laws, not just the GDPR, data should only be maintained for the purpose it was given and only for the time period for which it was relevant.”

The Effect of GDPR

Under the GDPR, consent has to be freely given, not forced or implied. That means companies can’t pre-check an opt-in box or force people to trade personal data for the use or continued use of a service.

“Some data is needed. If you’re buying a new car they need financial information, but they’d only be using it for the purpose of the purchase, not 19 other things they want to use it for including sales and marketing purposes,” said Fitzpatrick.

Privacy may well become the new competitive advantage as people become more aware of privacy policies and what they mean and don’t mean.

“Especially Europeans, Canadians, and those who live in Asia-Pacific countries that have restrictive privacy laws, part of their vetting process will be looking at your privacy program,” said Fitzpatrick. “If you have a strong privacy program and can answer a privacy question with a privacy answer as opposed to answering a privacy question with a security answer, [you’ll have an advantage].”

On the flip side, sanctions from international countries can destroy a company from reputational, brand and financial points of view. The sanction under the new GDPR regulation can be as high as 4% of a company’s annual turnover.