Developing Internal Capabilities To Drive HR Analytics Across The Enterprise
Data analytics spearheads organizational effectiveness
Organizational development lies at the heart of any successful modern enterprise, many of which are currently reviewing their services to lead the charge towards more effective global performance. A crucial target is the ability to gain access to real-time data on important information like the global employee base.
Getting to ‘one version of the truth’ will mean far more effective deployment of international human resources for enterprises that are struggling to work out a global growth strategy based on making the right decisions around talent.
Many of the HR transformations are massively technology-led with a focus on end-to-end, "cradle-to-grave" services so at the early stage process mapping is important to ensure that the solution will fit the whole world, not just individual markets.
To lead an effective initiative, the HR head needs to own all HR data, processes, technology and strategy globally. And while the transformation doesn't have to hinge on data and analytics capability, delivering greater efficiency across the enterprise relies heavily on easy access to real-time data, and trusting ‘one source of the truth’ at its core.
For organizations that need to know exactly what their headcount is, and what's driving it, a robust approach to data management is key. Many companies confirm how difficult it is to report globally on human resources because of insufficiently reliable data – whereby the key challenge tends to be multiple sources of information. Technology capability lies at the heart of a new solution.
If the data is all in one place than we will have one source of data and one main record of truth for all employees globally," explains a European head of a global HR service. "Right now we have nothing like that. The big differentiator is that we will be able to manipulate this data faster, and we will be able to access it real-time, as opposed to requesting information from country offices."
The implication for making the right resource and personnel decisions is huge.
Technology is #1 Enabler of Analytics
Most enterprises have a wide range of technologies across their business units. From SAP to spread sheets to locally built systems there is often little to no standardization. Moving away from on-premise legacy systems with their high maintenance costs and which are hugely resource-intensive, towards a cloud-based environment, is a big step towards standardization. The big challenge, according to many practitioners, is that there is no one single provider that can provide the vast majority of HR services as well as offer the languages and geographical scale that is needed. By necessity, therefore, most solutions turn out to be a combination of different providers, often including interim processes and solutions as workarounds.
Given the very broad remit of HR services – ranging from talent management to learning and development, resourcing, international assignments, reporting and analytics, employee relations, etc. – making enterprise-wide decisions on the basis of real data, instead of generic strategies, will catapult HR into a valued business partner.
With more insight to real-time HR data companies will be able to make more effective decisions on important issues like:
- Talent acquisition and management
- Compensation and benefits
Facilities and location
To build up this capability, many SSOs are already targeting people skills that are increasingly going to include data awareness, if not data analytics. Others are "borrowing" these skills from marketing departments, more familiar with analytics. Considering whether the necessary skills are already present somewhere in the organization is an easier way to leverage them quickly.
One thing that is not uncertain is that every HR function will be called upon to make more intelligent decisions going forwards, and be more intelligent about HR operations. Technology can lead that strategy – and people, up skilled in the language of data analytics, will follow.