Predictive Analytics in HR

Lucy Hughes our consultant managing the role
Posting date: 2/4/2013 12:00 AM

Should you predict which employees will quit?

Turnover is a huge problem in any company. So what if you could predict, with reasonable accuracy, which of your team members were most likely to quit?

We found the following article interesting found on the CBS News website this month (© 2013 CBS Interactive Inc.. All Rights Reserved)

A number of companies have tried. Eric Siegel, a former professor at Columbia University, and founder of Predictive Analytics World, writes in his new book Predictive Analytics, about HP's Flight Risk program. This program used data to predict which HP employees were most likely to leave. Siegel says (in an interview) that such programs are "becoming increasingly common, especially with large organizations." In a pilot group, Siegel writes, HP was able to reduce turnover from 20 percent to 15 percent when armed with this knowledge.

When I first heard about this idea, I thought it sounded a wee bit Big Brother-ish, or like something out of Minority Report. But then I realized two things.

First, looking at which employees might leave involves the exact same process companies use -- widely -- to figure out which customers are most likely to defect. Of course, a person's livelihood seems like a more weighty matter than whether you're going to switch to a competing pizza chain, but as long as the data is used responsibly, it doesn't mean someone will be pushed out before they can quit or be denied promotions. After all, most companies want to keep their employees. Knowing someone you value is likely to quit could result in you, as a manager, giving that person a more interesting assignment or a raise. That's not a bad outcome for that team member.

And second, managers already make predictions about which employees are likely to quit -- some of which may not be fair. Notes Siegel, "In general, the point of making data-driven decisions is to move away from the gut and more toward empirically validated decisions." A manager who learns an employee is pregnant with her second child might assume she won't come back from maternity leave since that happened with someone else three years ago. But data could remind that manager that any person's decision to stay or leave is based on multiple factors that humans just can't weigh well. Data might tell that manager that an employee who goes out on leave for a bit is actually less of a turnover risk than someone who was just given a lot more responsibility -- but no raise. "The core science is about how to integrate multiple factors," says Siegel.

How do you decide which of your employees is most likely to quit?

Click here for the article on the web.

Related blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out the related posts below.

Weekly News Digest: 5th - 9th April 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.    The Drum: How data visualisation turns marketing metrics into business intelligence Gathering data is just one part of a marketer’s job but having the ability to turn this data into something visually stunning, informative and easy to use is another skill completely.  Marketers, on the whole, are extremely visual learners along with around 65 per cent of the population. Most of us are able to absorb data more effectively if the information being presented to us is done in such a way that is pleasing to the eye. And this is why Data Visualisation exists; it allows us to group, organise and represent data sets in a way that allows us to analyse larger quantities of information, compare findings, spot patterns and extract meaningful insights from raw data. Not only does Data Visualisation allow us to learn more effectively, but we can then turn this understanding into much broader and deeper Business Intelligence.  To read more on the positives of Data Visualisation and how to translate this into meaningful Business Intelligence, click here.  ZDNet: The five Vs of customer data platforms According to ZDNet, Customer Data Platforms (CDPs) are the hottest marketing technology today, offering companies a way to capture, unify, activate, and analyse customer data. Research done in 2020 by Salesforce showed that CDPs were among the highest priority investments for CMOs in 2021. If you’re planning to invest in a CDP this year, what five critical things do you need to think about when developing a successful strategy? ZDNet tells all.  Velocity - Your systems need to manage a high volume of data, coming in at various speeds.Variety - Every system has a slightly different main identifier or "source of truth," and the goal is to have one. This starts with being able to provision a universal information model, or schema, which can organize all of the differently labelled data into a common taxonomy. Veracity - Companies must ensure they can provision a single, persistent profile for every customer or account.Volume - It has been theorized that, in 2020, 1.7MB of data was created every second for every person on Earth. If you want to use those interactions to form the basis of your digital engagement strategy, you have to store them somewhere. Value - Once you have a clean, unified set of scaled data – now’s the time to think about how to derive value from it.  To learn more, read the full article here. Towards Data Science: How to Prepare for Business Case Interview Questions as a Data Scientist When you think of Data Science, the first thing that comes to mind will be technical knowledge of coding languages and fantastic statistical ability; softer skills such as communication and exceptional business knowledge may be overlooked. However, this is where many budding Data Scientists trip up. It is these softer skills and business acumen that sets brilliant candidates apart from others.  But how, when not usually taught at university, do you gather the business knowledge that will set you apart from the competition and showcase it in interview? Towards Data Science shares a few key pointers. Build a foundation – Brush up on your business basics. Research project management methodologies, organisational roles, tools, tech and metrics - all are crucial here. Company specifics – Research your company and its staff. Make sure your knowledge is tailored to the company you’re interviewing for. Products – This is where you’ll stand out above the rest if you get it right. The more you can know the ins and outs of products and metrics at the company, the more prepared you will be to answer business case questions. Read the full article here.  Harnham: Amped up Analytics: Google Analytics 4 Joshua Poore, one of our Senior Managers based in the US West division of Harnham, explores Google’s new and improved data insight capabilities, predominantly across consumer behaviours and preferences.  This exciting new feature of Google was born in the last quarter of 2020 and has now fully come into its infancy, and it’s an exciting time for Data & Analytics specialists across the globe. Joshua explores four key advantages of Google Analytics 4.0. Combined data and reporting - Rather than focusing on one property (web or app) at a time, this platform allows marketers to track a customer’s journey more holistically. A focus on anonymised data - By crafting a unified user journey centred around machine learning to fill in any gaps, marketers and businesses have a way to get the information they need without diving into personal data issues.Predictive metrics - Using Machine Learning to predict future transactions is a game changer for the platform. These predictive metrics for e-commerce sites on Google properties allow for targeted ads to visitors who seem most likely to make a purchase within one week of visiting the site. Machine Learning driven insights - GA4 explains it “has machine learning at its core to automatically surface helpful insights and gives you a complete understanding of your customers across devices and platforms.” Machine Learning-driven insights include details that elude human analysts.  To read Joshua’s full insights on GA4, click here.  We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at  info@harnham.com.   

How Are Life Science Analytics Innovating For A Post-Pandemic World?

As COVID-19 unfolded, the Life Science discipline was thrust into the spotlight. The pandemic has shown the extent of the Life Sciences industry’s ability to innovate and collaborate. When facing a new disease, Life Sciences adapted quickly. The rate at which pharmaceutical companies successfully developed COVID-19 vaccines was unprecedented. Approaches that may have previously been labelled risky, were implemented to manage changing demand and deliver increased throughput. Embracing digitisation and innovation enabled organisations to adapt and accept constant change. The pandemic has shown just how well the Life Science industry is able to innovate and develop according to changing demands. As the world looks to the future, how can Life Sciences continue to remain dynamic?  Cloud data The cloud is becoming a CEO agenda item for Life Sciences. The cloud has the potential to enable more effective and profitable ways of doing business throughout the life science industry. It offers a powerful, secure platform for innovation and collaboration, with immense transactional power and data throughput. The cloud is necessary for creating data enablement, ensuring the right data is in the right place at the right time. It enables companies to innovate faster, work at a greater scale and increase collaboration.  Virtual communication According to Accenture, sixty-one per cent of healthcare professionals now communicate more with pharmaceutical sale reps than before the pandemic. 87 per cent now want either purely virtual or a blend of in-person and virtual meetings post-pandemic.  New means of virtual communication have created new opportunities in the industry. Digitisation allows for increased communication with trial participants and new opportunities to educate people about their conditions and care. There was already a growing trend for virtual healthcare interactions, but the pandemic has shifted this is into becoming the new normal. Collaboration ecosystem COVID-19 has led to increasing collaboration between companies. The race for a vaccine has seen cooperation evolve at an extraordinary pace. Companies who usually compete are now coming together to share data and cooperate. Organisations have created collaborative agreements in a matter of weeks; partnerships that pre-pandemic would have taken years to create.  The industry is now seeing the value of ecosystem partnership. The success of organisations post-pandemic relies on this continued collaboration.  AI and blockchain technology COVID-19 has increased the focus on AI in Life Sciences. Yet, Life Sciences have only scratched the surface of AI capabilities. AI has the potential to transform the industry; it can design novel compounds, identify genetic targets, expedite drug development and improve supply chains. The use of AI in Life Sciences is expected to continue to grow and organisations will need to focus ever more on merging human knowledge and AI capabilities.  Blockchain is also becoming increasingly trusted in Life Sciences. Its ability to create tamper-proof records makes it a key resource in increasing patient trust in remote clinical trials. As more of the industry understands the skills needed to use blockchain and increases collaboration, blockchain has the potential to become ubiquitous in Life Sciences. The pandemic has shown the importance of digital technology in Life Sciences. Digitisation increases efficiency and, collaboration, and also helps create a framework for future scientific discoveries. As we look towards a post-pandemic world, a successful Life Science industry must continue to embrace this mindset of innovation, collaboration and dynamism.  If you’re in the world of Data & Analytics and looking to take a step up or find the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.

RELATED Jobs

Salary

£300 - £400 per day

Location

London

Description

INSIGHT ANALYST £300-£400 PER DAY (INSIDE) 1 MONTH ROLLING CONTRACT AGENCY REMOTE

Salary

€40000 - €50000 per annum

Location

Eindhoven, North Brabant

Description

A data-driven scale-up in Eindhoven that works within the computer vision industry is looking for a data engineer to join their team.

Salary

£25000 - £40000 per annum + Comprehensive Benefits Package

Location

Bradford, West Yorkshire

Description

I'm recruiting for an Analyst with strong SQL skills to drive insight into portfolio and business performance in the financial services space

recently viewed jobs