HR organisations are embracing talent data. The tools and technologies to collect it, analyse it and make course corrections based upon it do exist.
Yet most organisations are struggling to use data effectively. What is the difference between companies that have best practices and those that do not?
Lack of infrastructure investment
Lower performing companies consistently under-invest in the infrastructure needed to perform analysis at a high level. Because analytics have historically been largely underutilised in organisations, it can be difficult to justify the necessary investments when other parts of the company, such as IT, finance, sales, marketing and operations are all a step ahead of HR in demonstrating the ROI of their own system needs.
Further, the infrastructure isn’t a stand-alone application.
It’s integrated with other systems so that data can be transferred rather than rekeyed, which is what often happens at laggard companies. Finally, the lower performing companies were inconsistent in using any system for recruiting throughout the organisation, making a holistic analytics solution difficult to implement.
A siloed approach makes the data more difficult to access, while avoiding inconsistencies and inaccuracies.
Lacking HR analytics acumen
Typically, HR departments lack a wealth of analytical talent. Instead, they tend to be supported by other departments with that capability. But to achieve real analytics maturity, HR personnel are needed to implement and at least initially run the programme. Training in Six Sigma disciplines is ideal, though not required for this initiative, at least during the early stages.
Then the programme can be turned over to dedicated resources in HR who have an analytics background.
Over-reliance on spreadsheets
In project management, this is called “managing the GANTT chart, not the project.” When we talk to lower performing companies, we asked about the systems and processes used to supply talent acquisition data. Virtually all answer the question with something like, “Well, we have a spreadsheet…”
To be fair, top performers used spreadsheets as well, but they’re more of a means to end rather than the end itself. Visibility into valuable talent data can be hampered by widespread use of spreadsheets to manage talent and data. The over use of spreadsheets is indicative of a poor analytics capability and a lack of investment in systems.
The use of spreadsheets, particularly for large enterprises, is inefficient, costly, and likely to introduce errors and inconsistencies. Over reliance on spreadsheet use is a major obstacle to improving performance management and talent management, and addressing this issue is essential if organisations are to mature in managing the performance of talent management.
Doing so requires using systems that are less error-prone, deliver data in real-time and are easier to audit. This is particularly true when companies are trying to measure the effectiveness of talent management strategies, which requires information from multiple sources.
End goal not clear
Also symptomatic of non-top performing companies were respondents who could not identify what decisions were being made as a result of the data provided. No analyst can provide actionable information without some understanding of how the information can or will be used. Important trends can be missed, and improvements never initiated because of the siloed approach to conveying the data.
So why not measure the value of talent management initiatives? Basically there are three reasons; we don’t know how, we don’t have the time, and don’t have the money.