The Data Conundrum And HCM Applications
HR professionals know where the next great leap in true value lies. They know it is not in the day-to-day, transactional data processing that happens behind the scenes. Don’t get me wrong! That is important too. It boosts efficiency, drives up engagement and frees up qualified resources to focus on the really important stuff, which is: delivering on the talent agenda for strategic impact -that’s what HR professionals want to do; it’s what the business expects!
Candidly, it is what the HR function has been laser focussed on for years with varying degree of success. It is the state of their people data that brings them crashing down to reality in most organisations, the state of HR data is so inadequate and so fragmented that it is extremely difficult to extract meaningful information and develop insights, let alone execute on the talent agenda.
Introducing the HCM software
And this is where the HCM applications vendors come in with their shiny, ‘all in one’ core HR systems and with an army of consultants, all part of their strategic (strategic for them, not for their customers) partner eco-system, trying to convince organisations that their application is just what the doctor ordered.
It is the classic catch-22 situation. Most organisations are being told they will have to go for one of these brand new shiny HCM application because their data is all over the place. That is what the vendors and the consultants will have them believe. But then, most of these new deployments – that’s what you have to do, by the way, once you buy a shiny brand new HCM application – fail, because – you guessed it – data issues!
Given this, it is strange that organisations continue to fall for that old chestnut that the ‘sophisticated’ data structures embedded in new generation HR applications will solve all their data woes; that these ‘sophisticated' data structures will impose an enforced discipline which will provide the much-needed governance layer that they so obviously lacked and all their data troubles will be a thing of the past.
Unfortunately, it does not quite work out that way.
The ‘enforced discipline' imposed by so-called mature core HR systems, doesn't work because it is a technical constraint, specific to the product and external to the organisational dynamics and sometimes contrary to the ethos that makes the organisation click.
And so the inevitable always happens. The biggest reason HCM system deployments are delayed, often abandoned is because organisations are not able to provide good HR data in the required format (remember those ‘sophisticated’ data structures) in time. Organisations that manage to provide the data either make ‘pragmatic’ choices and cut corners so that the data, though sufficient to ‘Go Live’, is not adequate for generating insight or for strategic initiatives. The very few organisations that meet the stringent data requirements of these applications fail to sustain the process and the governance needed and in two to three years’ time their data quality begins to go downhill.
It is déjà vu all over again! Didn't the same thing happen before when instead of SaaS, client-server technology was all the rage?
Organisations will do well to remember that it is seldom an HCM application or even the lack of one that is to blame for poor data quality. Poor data is seldom a system issue, it is almost always a process issue, a governance issue. An HCM application can help alleviate the data problem but will never solve it. To get their data right, organisations will have to start working on their data well before they issue an RFP for a new HCM application. The heavy lifting has to be done up front.
The organisation should start by clearly establishing a meaningful and manageable scope - the lean, the clean and the necessary- by finalising data elements which are truly critical for the organisation, e.g., organisation data, job data, compensation data, talent data and demographic data. Then they should establish a consistent definition of these key HR data elements across the organisation, categorise them as global or local requirements and document how these data elements are created and who will have access to these and for how long. Last, but not the least, they should establish clear governance parameters including regular data quality checks and audits, accountability and ownership backed up by legal guidance around GDPR and other local regulatory guidelines.
Only after they organisations put these in place and are in control of their people data, should they start looking for HCM software to automate, optimise and deliver insight.