Big Data - Turning the Data Deluge into Strategic Value

December 3 2013 - 2013 may have been the year of big data, according to research firm Gartner, but is the business seeing any value? While the focus in many companies is on long term projects to improve customer understanding, there are other areas of the business, most notably employee recruitment and development, where big data should be making a real difference. So how can a business turn big data into usable insight that can support both operational and strategic requirements?

While rapid and unprecedented access to candidates globally is compelling, as Stephen Blackmore, Head of Sales at DaXtra Technologies, explains, to really exploit the value of big data organisations need to step back and use analytics internally to gain real insight into the short to medium term talent requirements.

New Recruitment Processes

The concept of big data analytics has been around for a decade yet opinion as to what it is, what it should be and how it should be used to deliver business value continue to differ widely.

The current surge in interest is fuelled by two key trends: recognition that there is a mass of information now publicly available on the Internet that should be exploited; and the maturity and accessibility of supporting technologies.

The problem is that the vast majority of organisations are still unsure what big data means and where business value can be attained. There are some obvious areas: big data analytics is already being used to understand vacancy scraping - assessing vacancy information to identify areas in which a requirement for particular skills quickly appears. It is also enabling organisations to search across geographic areas to identify candidates, significantly extending the breadth of candidates under consideration.

However, this reinforces the impression that the value of big data is only about rapid access to a new breadth and depth of candidates. Certainly, the ability to search the Internet, capture and analyse vast amounts of unstructured data is beginning to open up new recruitment processes. In addition to vacancy scraping and geographic search, companies can also use publicly available social media information not only to gain further insight into the quality of active candidates via their Twitter activity, LinkedIn profiles or blogs. They can also identify high quality individuals that are not actively seeking a new job but could be tempted into a move - the sought after passive candidates.

Strategic Value

However, while this mass of social data has the potential to provide additional insight to recruiters and offer day to day operational benefits in identifying and interacting with candidates, its long term value may be questionable. Individuals, especially highly skilled and in demand individuals, are increasingly security savvy and restrict access to online information.

In the medium term, and certainly in the case of corporate in-house Talent teams, there are likely to be more strategic benefits to be derived from the analysis of existing internal data. Those technology companies that provide analytical tools developed to explore and exploit Internet based big data, often also have the ability to provide similar tools that should first be deployed internally to determine a business's talent requirements and capabilities over the next two to five years.

Using analytics to explore internal data can not only identify gaps in the current skills landscape, but also predict potential shortfalls in Talent required to service a company's business objectives in the medium term. Once Corporate Talent Departments have established where their gaps are and quantified their weaknesses as a department, they can then begin to explore and exploit the new options for locating, attracting, training and communicating with candidates.

Data Verification

Once the correct tools have been put in place organisations cannot simply rush in and gather this mass of Internet based data without putting in place robust processes for managing, extracting and analysing external data. These data sources are valuable, but their value is unverified and unsubstantiated - unlike the internal database of candidates that most organisations have invested heavily in creating. Organisations cannot risk compromising internal data in the race to explore the depths of external information.

While there is clear value in building a more colourful candidate profile that links internal and external resources, it is vital to avoid contaminating the internal database with incorrect or corrupt external data.

Is the internal existing candidate the same person as the sourced external candidate? Current technology should be comparing multiple record fields to guarantee an accurate match before records are merged to ensure the candidate information remains robust, resilient and clean.

Furthermore, big data can only deliver great insight when used in conjunction with a workable analytical tool; any technology must have an interface or method of turning vast amounts of retrievable data into something that is commercially useful and operationally relevant.

Conclusion

There is no doubt that big data has the potential to deliver real benefits. At an operational level, linking Internet based search data to existing candidate database records extends the potential pool of talent and enables interaction with candidates not responding to traditional means of communication. The value should be improved candidate quality and reduced costs. In the longer term, however, big data's true value will be the provision of new insight into trends that can inform strategic decision making not only in recruitment but also in business direction and development.

There is unlikely to be a one size fits all solution - at least in the short to medium term. The process of adopting a big data solution is likely to be bespoke and will demand clear corporate vision, measurable objectives and an understanding of the impact on day to day processes.

2013 may have been the year of big data, but managing and exploiting complex, extended data sets remains challenging. Organisations need to understand just how this data can be used to deliver commercial and operational benefit and deliver a return on investment.

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