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Barriers to HR Data Analytics Success Part 1

Posted by Mathew French

12 August 2014

Last week's blog looked at the big picture for big data analytics, HR and talent management. This week's two part blog will dive more deeply into the big data analytics landscape. The life-cycle of developing the necessary data analytics capability in any organisation, first requires a thorough understanding of the current status quo. Any roadmap for implementing organisational change, requires some deep contemplation of current capabilities and all the things that might stand in the way of future success. This blog will outline the potential barriers that stand in the way of a fully integrated HR function that harnesses integrated data and analytics potential to create future business excellence.


The Big Data Landscape

First, let’s get clear on the continuously shifting, but important parameters that enable us to contextualise the ‘big data’ landscape. That can be done by considering how the following four elements, fed by the increased sohpistication of technology and the Internet, resulted in the current data explosion.

  • Today, more data crosses the Internet every second, than was present across the entire Internet in 1993.
  • The 'Cloud' facilitates a massive increase in storage capacity (meaning ever increasing amounts of data to process and analyse).
  • Faster data at higher speeds than ever before, even in remote locations. Information and relevant data traffic is moving at warp-speed (and getting faster).
  • Real-time data means delay has disappeared, there is no longer any excuse not to have a virutally 'live' data set, for everything.
  • More data on more aspects of life and work, being integrated at ever increasing levels of sophistication.
  • Data is being captured across greater range of devices and channels, from smartphones, to tablets, to laptops, to embedded chips.
  • Is becoming increasingly predicated on integrated systems / solutions and structures.
  • Requires the ability to build the skills and smarts for analysis.
  • Requires collaboration and connectivity around data and information.
  • Necessitates the ability to use data as a transformational tool.

So, what does all this mean for HR Professionals contemplating a departmental skills upgrade to keep pace with the big data analytics driven future?

CIPD’s HR Outlook report for winter 2012–13, indicates that despite 63% of HR leaders thinking that they draw insight from data, only about a fifth of their non-HR business counterparts share and reflect that level confidence. The research clearly illustrates that there is real value in these data analytics skills and the insights around people they produce. These skills and insights are also most definitely valued by leadership. However, what’s also clear is that without the ability to have disciplined data sets and organisationally consistent analyses, such insight loses its integrity and inherent value.

The actual value of data in its current form, is potentially limitless because it facilitates a new set of insights around deep and complex organisational issues. The value of mining organisational elements such as culture, change and learning, helps 
to optimise the way in which
 the transactional elements of HR can be delivered and assessed. However, evidence suggests that the HR function within most organisations may be less ready than 
it needs to be in order to take advantage of such opportunites. Significant barriers still exist in HR’s ability to both explore and exploit, talent analytics and big data, for value-added people insight that can be leveraged to contribute to organisational excellence.

Let’s look at the highlights from CIPD’s 2013 report on ‘Talent Analytics and Big Data’ for an overview of the barriers that potentially stand in the way of HR Professionals being able to effectively acquire and embed appropriate data analytics capabiliies.

Potential Barriers to HR Data Analytics Success

The Barrier of Structural and Systems Silos

When organisations seek to develop a talent analytics perspective, they often face a number
 of issues. The main issue is usually whether they can access the data they need: data that 
is systematically organised, reliable and well defined. The problem is, that data in most organisations is often diffuse and difficult to access because of internal silos.

The first of these silos are structural; that is, structural barriers between the HR functions themselves, between the people who own data sets, and potentially also between performance operations.

Structural Barriers
  • HR 'compartments'
 that don't share data collaboratively.
  • Business unit isolation
 (lack of information integration).
  • Projects and programs that operate outside regular channels of communication, or aren't integrated with business-as-usual activities.

Within HR teams, there is often 
a solid separation between HR functions and a lack of productive collaboration. For example, learning often operates in a silo of its own, as does reward and recognition, and so on. Subsequently, data silos are common and often each individual HR 'compartment' will have its own data set, captured in its own format (excel, a custom built system etc).

If you consider that active sharing is one of the most important facets of being able to harness the insight available in stored information, current structural habits make it difficult to achieve such sharing. Access to data is a great reason for collaborating across teams, however it’s often not clear if data produced in different HR silos is being actively integrated.

Data sharing protocols across business units also suffer from the same type of silos, as well as the problem of a shared data approach across projects and programs. This is then compounded by management structures, organisation charts and reporting lines, all of which disrupt the free flow of data, inhibiting an effective, cohesive, holistic, analytics approach.

The other type of silo can be
 described as a systems silo; in 
other words, having systems
 which are incompatible and poorly integrated. Many organisations operate with either hybrid data systems, or have linked their existing systems together inappropriately. This can lead to a conglomerate of solutions that are incapable of ‘talking’ to each other, rendering the data they contain almost useless.


Systems Barriers
  • Incompatible technology, including systems that can't talk to each other.
  • Permission problems
 for sharing data and systems 'owned' by other parts of the organisation.
  • IT skills capability issues, where only a small number of users have the knowledge to use a system.
  • Legacy systems which can be costly and difficult to upgrade or replace.

Generally, for talent analytics to be of value and for big data to be harvested, the approach needs robust but permissive security across the entire organisation. Restricting access to just a few 'owners' limits the ability to gain insight from stored information. Solutions already exist to help overcome these problems in many of the integrated Human Capital Management solutions available. Even though implementation of these types of solutions is increasing, there is still a long way to go to for HR Professionals to be able to proactvely harness the data insights they make possible.

IT and database skills issues can
 also so get in the way from a systems perspective, with the ability to use database query languages, or to programme, often a prerequisite to run some fairly basic data enquiries. This can create skills problems often requiring the resourcing of extra capability. Linked to this are the legacy systems issues and the systems transition problems, evident when organisations 
inherit older solutions and need to integrate and use them alongside newer technology.

For whatever reason the systems silos arise, they need to be tackled, and soon. Some examples of how this can be done include:

  • Having integrated HR and IT systems which allow the data 
to be stored consistently and allow everyone who needs and warrants access to the data, to be able to do so with appropriate safeguards for data integrity and security.
  • Choosing the appropriate software and tools for analysis, allocating permissions/access for all who need them; these tools should also be integrated with wider systems for both HR and general management.
  • By creating 'ecosystems' where all technology solutions can communicate and transfer data seamlessly, from one solution to another.

CIPD’s research demonstrates that if these systematic approaches are undertaken, silos relating to sharing data and information currency, can be broken down.

Their research also emphasises the importance of having a level 
of senior sponsorship and a commitment to drive the talent analytics and big data initiative, along with a change management focus that ensures the issue of silos is addressed.

The Barrier of Skills Capacity

Many HR Professionals who lack a consistent training in data and analytics, tend to feel less comfortable with numbers and data, and have a bias towards more qualitative approaches. There is also a continuing tension between leadership seeking richer insight about people and culture, versus solving immediate and ongoing business challenges. Historically, talent analytics is more commonly associated with solving business challenges, and HR functions tend to rely on intuition and inductive reasoning skills to address people issues, without the perceived need to use analytics.

CIPD’s research identifies two possible pathways to increase the needed skills and aptitude of the HR function in the sphere of HR data analytics.

Make and Migrate

  • Tap existing analytical capabilities across the organisation through a collaborative exchange of skills and information.
  • Build out skills from the initial / existing talent pool.
  • Develop centres of excellence / expertise with direct engagement in HR teams.

Make and migrate is often an improvisational early-stage approach in which organisations seek to find a few analytical individuals within the existing HR team or wider organisational talent pool. As an example,
 these individuals are likely 
to come from a reward, or workforce planning background. Or they might be business analysts tasked with tracking sales and marketing opportunities. Generally, such individuals tend to be analytical and used to dealing with numbers, and some have advanced skills, for example using spreadsheets to their fully functional capacity, as well as databases, and possibly with the ability to write queries and code.

Buy In and Build

  • Hire analyst talent and encourage early involvement in key data driven analytics programmes.
  • Integrate and align capabilities to business objectives, and then embed capability within the HR team.
  • Source integrated platforms and technological solutions to help translate and transform data capabilities across the entire organisation.

In some organisations, analytics capability needs to be launched at warp speed in order to fill the current gaps and remain competitive. This may be because the business drivers for people and performance data have become more acute, or because leadership places a renewed priority on the issue. It could also simply be because existing capability 
has not been able to fulfil the need. Or, sometimes it’s due to an organisational shock, where exposure of inadequate data insight has been identified as an issue in competitive disadvantage.

Generally, the individuals acquired purely for their data analyst capacity, are from a natural science background and are known as data scientists. As HR starts to get access to good data that can be used to develop real insight to support the organisational business activities, this is often the catalyst to establish a dedicated team.

Once data capabilities start to ramp up, 
the HR function will need
 to think about developing a coherent strategy to consolidate their approach. Often, people insight and strategy has been integrated with marketing and finance, simply because these areas are where the analytical skills reside. Such integration can lead to significantly enhanced value across the entire organisation.

In part 2 of this blog, we will look at the other barriers CIPD's report identified, that also have the potential to inhibit data analytics capabilities within HR, and across the entire organisation.

In the meantime, if you would like to learn more about how Subscribe-HR's solutions can enable you to harvest your organisation's stored information, sign up for a free trial below.




Credit: The image used in this blog is taken from CIPD’s 2013 report on ‘Talent Analytics and Big Data.'

Topics: HR, Big data, Big Data Analytics

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