Powering talent decisions with data

Companies can use data and analytics to improve decision-making around their most valuable business assets: talented employees. Here’s how.

Using data to shape talent decisions opens up new and sometimes unexpected insights that can be exploited to gain a competitive advantage.

Most companies already hold large volumes of talent data in their organisations, often only superseded by financial data. Just think of the mountains of human resources (HR) data companies hold, such as recruitment analytics, career progression, training, absenteeism, productivity, personal development reviews, competency profiles and staff satisfaction data.

In addition, companies now have access to the ever-expanding amount of data that is generated via social media, the internet and mobile devices, among other things. This article takes a look at some real examples of how companies are using data to power their talent decisions.


Google wanted to know whether better and more talented managers really made a difference in the way the company and its employees perform. It first looked at existing data by correlating staff satisfaction, employee turnover and productivity with findings from managers’ performance reviews and the results of 360-degree assessments. The analysis showed that the employees who worked for top-performing managers were happier, less likely to leave and more productive. This triggered another question: What makes a good manager at Google? It is all well and good knowing that better managers make a difference. But the company can only really act on this if it understands the differences between good and bad managers.

As Google people analytics manager Kathryn Dekas explained in a 2011 presentation, the company set about to interview the managers who fell into the top and bottom quartiles (without disclosing which category they belonged to) and asked about their management style and the things they emphasised and struggled with. Google also introduced a management award that allowed employees to nominate good managers. As part of the nomination process, the company analysed the text of interview transcripts and nomination forms to identify key themes.

Google isolated the following eight behaviours that make a great manager in the company:

  1. Is a good coach.
  2. Empowers the team and does not micromanage.
  3. Expresses interest and concern for team members’ success and personal wellbeing.
  4. Is productive and results-orientated.
  5. Is a good communicator — listens and shares information.
  6. Helps with career development.
  7. Has a clear strategy for the team.
  8. Has important technical skills that help him or her advise the team.

In addition to the eight behaviours that make a good manager, Google identified the top three reasons managers struggle in their role:

  1. Has a tough transition (eg, suddenly promoted or hired from outside with little training).
  2. Lacks a consistent philosophy or approach to performance management and career development.
  3. Spends too little time on managing and communicating.

Google started to measure managers against these behaviours through twice-yearly feedback surveys. The results were fed into an early-warning system to detect both great and struggling managers. Google also revised its management training, induction programme and recruitment activities in light of these findings.


Business performance management (BPM) is generally a key role of accountants in business. Modern BPM systems should help to identify and measure the key drivers of future financial (or other) performance outcomes. Tools such as Balanced Scorecards help to create BPM systems that link people performance and talent to overall business performance.

A large UK retailer I work with has been able to quantify how elements of staff satisfaction drive operational performance, customer satisfaction and, ultimately, financial performance. The company is able to predict the extent to which a certain increase in specific elements of staff satisfaction drives a certain percentage increase in revenue by square foot in their shops. The key staff-related performance drivers include:

  • Staff find their job interesting.
  • Staff have an opportunity to advance.
  • Staff have a manager who helps.


Small and medium-size entities (SMEs) are now more than ever before able to access and analyse data using public and cloud-based solutions. There are so many new ways companies can access and analyse data either for free or at very low costs using software-as-a-service (SAAS) solutions that essentially “rent out” data analytics capabilities.

SMEs can now perform many of the talent analytics that in the past only large companies with big IT infrastructures could. This, to some extent, democratises data and data analytics.

Take this small and upcoming fashion retailer I work with as an example. While its ambitions are great, the IT budget is small. A new and trendy fashion outlet with only a few shops but with the goal to grow into a well-recognised brand had an objective to recruit popular and trendy people to work in its shops. The rationale is that these trendy and popular employees will attract and influence their friends to shop in their stores.

In the past, the company had to rely on the judgement of interviewers to identify the most popular and influential individuals. Now, the company is using the Klout score, which measures one’s influence based on an analysis of one’s social media activities — the number of “likes” on someone’s Facebook status updates, for example, or how many people re-tweet or reply to tweets. For the first time, and for free, the company can use data to make an objective judgement about how influential someone is or is not.

The company runs its talent management on a SAAS-based HR solution, which allows it to access analyses that until recently were reserved only for large corporations that could afford to install such systems in-house.


This brings us to the new world of Big Data analytics as well as the use of unstructured data such as text, photos, videos and voice to inform our talent decisions. If you are using social media networks such as Facebook, Twitter, LinkedIn or Pinterest, then you shouldn’t be surprised to learn that companies and recruiters use the information you upload there to understand you a little better.

In addition, we are increasingly surrounded by sensors, cameras and other data-collecting devices, which generate data about what we do. Just think of the smartphone you are carrying around and how it is logging where you are and how fast you are going. The use of this type of data (sensor, machine and unstructured social media data) is only just taking off and will become more sophisticated as the months go on. But here’s a look at some real-life examples that show how newer forms of data can be used to inform and improve talent decisions.


A competitive cycling team I work with uses bikes that are fitted with sensors that collect data on how much acceleration every push on the pedal generates. This allows the team to analyse the performance of every cyclist in every race and every training session.

In addition, the team started to integrate data from wearable devices, such as smart watches. These devices collect data on calorie intake, sleep quality, air quality and exercise levels. The latest innovation is to integrate the analysis of social media posts to better understand the emotional states of athletes and how this might impact track performance. If this kind of analytics is being applied in elite sports, how long will it take companies to adopt similar practices?


Michael Lewis’s book Moneyball explains how the Oakland Athletics (A’s) baseball team applied analytics to detect talented players who were often overlooked by talent scouts applying traditional ways of spotting the best players. Trusting statistics, the A’s were able to assemble a successful team for a fraction of the cost of spendthrift rivals such as the New York Yankees. The A’s spent about $41 million on salaries in 2002, while the Yankees spent more than $125 million that season. Each team won 103 games during the regular season that year.

So, one thing that analytics can help companies do is find the right talent, hopefully for less money. An example comes from one company I have worked with that always believed its best-performing employees would be the ones with excellent grades from Ivy League universities. However, analysis of actual job performance showed that this wasn’t the case. Instead, candidates from non-prestige universities outperformed the top university candidates. This kind of insight allows the business to recruit the right talent for less money, as graduates from the Ivy League universities tend to demand much higher starting salaries.

Another client of mine is constantly developing more sophisticated ways to predict staff turnover. In particular, it is trying to pick up signs that its most talented employees are considering whether to leave the company so that they are able to intervene early on. The one obvious indicator is the changing use patterns of social networking site LinkedIn as well as updating profiles on job-seeker sites.


Especially valuable are unexpected findings from our analysis. These are obviously not generalisable and apply only to the specific job profiles of the companies concerned. Here is what some organisations found and didn’t expect:

  • Call centre sales staff with a criminal record performed better than those without a criminal record.
  • Sales people with more Facebook connections performed more poorly than those with few connections.
  • Candidates who completed their job applications using browsers that were not pre-installed on their computers and instead used other browsers that they had to install (such as Firefox or Chrome) tended to perform better.


One could argue that the analysis of talent data is the role of the HR team in the organisation. However, management accountants bring certain skills about numbers and data analysis that are often lacking in HR departments. Management accountants also bring the understanding of the overall business performance framework and should be able to help create the link between talent analytics and overall business performance outcomes (eg, financial results). A close working relationship between the finance team and the HR department can ensure that complementary skills are brought together to deliver enhanced business benefits.

People with the right talent are the most important asset for any organisation and generally also represent the biggest costs. Advances in data generation and analysis capabilities allow us to harness existing HR data and supplement them with newer forms of big and unstructured data analysis to gain real business insights and competitive advantages.

The key to making talent analytics work is ensuring the business leaders identify the key business questions about their talent. Once the questions are defined, data can be collected and analysed to answer the question.

Real business questions addressed in the examples here include:

  • What makes a good manager in our company?
  • What difference can happy employees really make?
  • How can we best recruit the talent we need?
  • What are early warning signals that some of our key people are thinking about leaving?

But you can come up with many other key business questions about the talent in your organisation.


Analytics aren’t just for data-savvy companies seeking a competitive advantage. Individuals can also use data to ensure their careers stay on track. Here are three tips for using data to power your career:

1. Ensure you have what employers are looking for.

When it comes to your career, you want to make sure that you stay in touch with the latest developments, newest tools and general trends. This information is vital to ensure you spot the best career moves to make as well as the top development and training opportunities. Three really good ways to keep up with trends are:

  • Google Trends: A free service that allows you to map out how the worldwide search volume for these key terms is changing. You can also compare a number of terms to see the relative trends.
  • Topsy: A social media search engine that features a Twitter analytics tool. You can compare up to three subjects to understand which one is trending the most.
  • Google Alerts: Set it up so you get the latest news about your industry and job directly to your inbox.

2. Find the job opportunities.

Many websites provide job offers and alerts. One I particularly like is It helps you find relevant jobs but also provides a look inside the company. The site provides information about salaries and interviews at the company as well as reviews of what it is like to work there. allows you to set up a profile once and alerts you about relevant openings. Having this setup allows you to regularly read the relevant job offers and see what companies are looking for in their job specs.

3. Make yourself interesting for a potential employer.

LinkedIn is my preferred tool for business networking, and if you are not signed up yet, do it right now. It is the best place to grow your network, find and interact with like-minded people and market yourself to a potential employer. Sites such as LinkedIn allow you to collect data on how your network is growing, how many of your skills have been endorsed and how many people have looked at your profile, among other things. Used well, it can provide valuable insight about how attractive you are for potential employers.

Here are some key tips to increase your attractiveness on LinkedIn:

  • Grow your network: Send personalised invitations to key people in your industry asking to connect. Even if you don’t know them personally, I find that if you make it personal and explain why you would like to connect, you generally get a positive response.
  • Ensure your most relevant skills are listed and endorsed: Don’t put all your skills on the list. Pick the ones you believe employers are looking for. Then ask your network to endorse those skills.
  • Seek recommendations: These are great ways to show potential employers that you are doing a good job.
  • Engage with the community: Join relevant LinkedIn groups and participate in conversations. This will show that you are actively involved in your industry and will help to boost your score on Klout, which measures influence by analysing one’s social media activities.

Bernard Marr ( is an author and authority on organisational performance and business success. He is founder and CEO of the Advanced Performance Institute, a research, consulting and training organisation in business performance.

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