Improve your talent

It is widely accepted that the value of a business lies mainly in people, brand and reputation. To say that value is created by people is a no brainer. However when it comes to measuring Human Capital Value reliance on historical data is no longer adequate. By the time historical data is gathered the world has moved on and more significantly many talented people will have moved on.

How many organisations are able to predict with any reliability the significant risk of attrition, the resultant loss of productivity and the costs of replacing lost skills? What if an organisation’s brand lags behind other more attractive employers? For a lesser employer brand the task of replacing skills is challenging enough and is made harder by increasing attrition and intense competition for skills.

This is a real issue for businesses today. In a recent report by PwC the availability of skills was said to be the main concern for business leaders across the UK with 63 per cent of respondents describing it as a “serious concern” for their organisations. The report went on to say that most of the companies surveyed considered that they were under prepared to respond this very real challenge.

Further evidence that employers are under prepared to tackle skills gaps can be found in the CIPD’s autumn 2013 HR Outlook survey. In that survey the highest priority for HR was identified as “building relationships with colleagues and understanding their priorities”. The survey pointed to the prevalence of open and collaborative HR functions, a sign that HR is still operating in the area of relationships and organisation building. Whereas developing the ability to use data to inform decisions came fifth. Interestingly, addressing talent shortages did not feature in the list of top HR priorities.

The CIPD survey reinforced a need for executive sponsorship of data led approaches in HR so that such initiatives are driven as transformation projects. Given the serious issue of skills shortages, a transformation that should be given the highest priority is the development of talent analytics.

Talent analytics

In this article I intend to focus on the key issue of skills shortages. The powerful insight offered by big data and predictive analytics could have a major impact on skills gaps by helping employers to plan and execute recruitment and retention programmes more effectively. As a minimum, data should be procured on the availability of skills and the competitive landscape for recruiting those skills. Looking ahead, the use of algorithms to predict attrition would enable early intervention before skills gaps start to impact on revenue and profit. Below I have provided thoughts on data that could make an enormous difference:

Forecasting attrition:

In the past I have been involved in programmes to address attrition. Here is a typical scenario. An employer gathers historical process data and surveys employee and leaver attitudes. Over time an understanding evolves of the key reasons for attrition. Having addressed the root causes of attrition and improved recruitment and branding strategies, too many people are still leaving the company. Why? Because the employer still does not fully understand external factors such as structural skills shortages and the competition for those skills.  Employers need to align internal analysis with a comprehensive understanding of external factors in order to predict attrition and take early preventative action.

Using big data and algorithms can provide the answers needed to tackle the issue of attrition. In this field organisations such as Google lead the way. Internationally known HR thought leader Dr John Sullivan in his research Talent management lessons on algorithms, showed that out of the entire list of Fortune 500 firms, there was only one algorithm driven HR function and that firm was Google.  Dr Sullivan commented “not only is Google the leader in algorithm driven people management decision making, but is literally the only function where all people decisions are based on data and analytics.”

Demographic skills data:

Examples of this type of data include the concentration of skills by geography, the number people graduating from preferred schools, colleges and universities and the numbers of experienced and qualified professionals in business locations.  Armed with such data the employer can make informed decisions such as where to recruit and whether to recruit or train.

Take engineering for example. There is already a critical shortage of engineers in the UK. This problem will only get worse if as widely expected the number of retiring engineers will exceed the numbers joining the profession during years ahead. Under such circumstances it might be better for employers to concentrate on training graduates and school leavers for the next few years rather than spend a lot of money attempting to recruit experienced staff. Before making such a strategic decision however employers would be wise to gather data on the availability of engineering skills internationally. This is a profession where international mobility is prevalent and where demand exceeds the supply across the globe. Using big data on the international availability and movement of key skills elevates resource planning from tactical guesswork to strategic decision making.

Root cause analysis and eradication of errors using Six Sigma:

An employer might find that it is competing at the top of its game for talent and that its retention rates are optimal. But there are still material skills gaps in the organisation.  With persistent shortages of highly skilled people, the consequences are potentially significant in terms of lost revenue and profit. Here are two typical symptoms – vacancies remain unfilled for too long and the quality of candidates is deemed to be poor.

With the real time data that is available from all ATS and ERP systems the DMAIC approach to process improvement (define, measure, analyse improve, control) used in Six Sigma programmes can be applied to great effect in identifying errors such as delays in recruitment and their root causes. Using three key metrics: process speed, candidate quality (% of candidates interviewed deemed to be at “offer” standard) and competitiveness (% of offers accepted), it is possible to speed up recruitment processes significantly and address any perceived lack of candidate quality.

I would also suggest that in general the quality of candidates is not actually poor at all.  Many candidates are overlooked in recruitment processes due to the volumes created by online access to vacancies and recruiters’ reliance on inaccurate key word search tools for selection. Innovative technologies are available to address error prone recruitment processes. These include artificial intelligence and other technologies that automate and significantly improve the evaluation of candidates.  An example of this was illustrated in Recruiter Magazine in November 2013 featuring our successful introduction of one such technology, ResumeSort into the UK: http://oro-solutions.co.uk/blog/wp-content/uploads/2013/11/Recruiter-Magazine-November-1.1.pdf

Such technology innovations and Six Sigma process improvement together offer a truly leading edge capability in recruitment process management. The end result is high quality candidates being identified and selected with remarkable speed and reliability, giving the employer a great competitive advantage.

Talent attraction

Big data also enables effective marketing of the employer brand and career opportunities to passive candidates i.e. people who are not actively looking to move jobs but could be tempted if a great career or job opportunity was put in front of them. This has the benefits of significantly extending the employer’s reach into the market for talent and enabling better targeted recruitment campaigns. My business ORO People Solutions works with Jobs The Word Ltd a provider of Big Data talent attraction services.

Final thoughts and references

The HR profession and service providers such as my own business have a great opportunity to make a real difference using big data and talent analytics. In support of this view I would refer to the report produced by The CIPD in partnership with Oracle: Talent analytics and big data – the challenge for HR:

“Big data is essential to HR and L&D because it allows the conversations and connections which have tended to be in the realm of the immeasurable to be captured and leveraged”.

Some of the approaches and methodologies I have pointed to in this article have been in existence for some time. However the availability of real time data and the advancement of technology mean that predictive talent analytics can now be developed to achieve real gains in Human Capital Value. I expect that predictive talent analytics will become essential tools and will be embraced by the HR profession and service providers alike.

Jim Whelan, May 23rd 2014

Download our latest newsletter : Newsletter May 2014

True innovation is not purely in the efficiency that technology brings to the recruitment process. It is also in the competitive advantage won by creating a great candidate experience through technology.

This will become all the more important as economic conditions continue to improve, intensifying competition for talent. If you plan to recruit professional people during the next few years it is likely to become increasingly challenging. In a 2012 CIPD survey it was noted that 71% of organisations had reported an increase in the numbers of unsuitable talent. Recent reports indicate that the growth rate in vacancies has overtaken job applications for the first time in 5 years.

Hiring has long been identified as the number one strategic function impacting future revenue, company earnings and competitive advantage. McKinsey’s War for Talent, which surveyed 410 highly ranked executives, found that top performers delivered 40% more productivity, 49% increased profit and 67% more revenue. Later exhaustive studies reconfirm the opportunity cost of not hiring the best.

Yet over recent years recruitment processes have become time consuming and cumbersome for candidates. Hardly the best way, you might think, to build employer brand value and attract the best talent. This has been compounded by growing numbers of candidates and short listing decisions increasingly being made using unreliable key word search tools. As a consequence the process efficiency brought by technologies such as applicant tracking systems has been offset by an eroded candidate experience.

And there is a bigger downside in that suitable candidates can often be overlooked. Optimistic studies in the US show that even experienced recruiters find “the perfect resumes” 12% of the time.

It should be no surprise therefore that recruitment often fails today. The majority of people simply don’t apply to job advertisements anymore and the task of dealing with large numbers of unsuitable applications is very onerous for employers. The result is a widely reported shortage of talent even with large numbers of candidates available.

To attract suitable talent employers must create a great candidate experience. This is eminently possible with the advanced recruitment technologies that have emerged in recent years, for example in the fields of semantic search, big data marketing, video interviews and online psychometric profiling at the time of job application.

Organisations must market their employer value proposition effectively and deal thoroughly with every candidate they attract. The outcome should be prompt and informed selection decisions and engaging communications with all candidates particularly if they are not successful. Employers that can achieve this win a significant competitive advantage by heightening their reputation and brand value with prospective employees.