The Challenges of Real-Time Data in WFM

There’s little doubt that in today’s rapidly changing business landscape, organisations can respond by making better use of real-time data to action more informed workforce and business decisions. However despite this, the fact remains that the majority of organisations, both large and small, underutilise the powerful insights from their data.

According to recent industry research from the US, 99 percent of organisations have invested in data initiatives and 92 percent report a gain in the pace of investment. Given these numbers, it would be reasonable to expect there to be a prevalence of data-driven organisations. However, that’s not the case with the same research revealing only 24 per cent of respondents report being part of a truly data-driven organization.

While companies are making significant, and ongoing, investments in data technologies for workforce management there’s still much room for improvement. Accessing real-time data has a big role to play in an organisation’s ability to respond quickly when unexpected demands are placed on its workforce or its ability to adapt how people are deployed across the organisation when markets shift.

However, few organisations are able to respond quickly or effectively because they have not designed agility into their workforce planning – or the data they rely on to do it.

Barriers to harnessing real-time data

Harnessing real-time data does come with an abundance of challenges, not least of which is the often manual, spreadsheet-based processes that we see used across finance, operations, human resources (HR), sales or elsewhere in organisations that need to provide forecasts to the business.

This can be because the analytics capabilities of systems for HR, sales, workforce management, rostering, and other business units have limited capability to yield the broader insights that the organisation needs to be able to anticipate or respond to workforce planning needs in a dynamic way. Organisational data can also exist in multiple silos across business units, but in completely different formats or to serve quite different purposes. The refrain of ‘too much data, not enough information’ is not an uncommon one.

Analysing data this way is a significant time-hog. Gathering, consolidating, and validating data from within business unit silos provides can consume considerable work hours across the organisation – and that’s before analysing the data can even commence. Aside from the obvious time issues, there is considerable risk with manual processes that rely on potentially questionable data quality, duplicated data, data decay, or poorly governed structures.

Aligning data analysis with organisational business goals is best achieved by integrating the myriad sources of data to enable data access, more efficient and effective data gathering, design reporting to the need, and ensure proper data governance is in place.

Integration exposes underlying data challenges

One of the typical things we see when clients start to connect data sources to analytics tools is the exposure of underlying data issues.

As systems such as Success Factors, PeopleSoft and other platform data sources are connected to a planning and analytics tool, it is very likely that issues such as incomplete data sets, incorrect mapping of data, or redundant data are going to be found.

However, far from being a problem, it’s an opportunity to address data quality issues – ideally in the source system – so that the data being used in forecasting and analytics provides both useful and trusted results. Fully understanding where the data is sourced from, how it is classified, what content is contains, and how it is being used across the organisation is an essential part of maximising a planning and analytics tool.

Addressing these issues can achieve numerous benefits: the ability to trust data as it is pulled into the analytics view, confidence that it is connecting the right sources of organisational data, and that analytics tools can provide dynamic views for scenario planning and modelling.

Progress with planning analytics

As organisations increasingly incorporate new sources of data into the workforce management mix — and commit more broadly to becoming data-driven organisations – addressing the data quality and trust issues are vital for real-time data to be available to the business.

This is where sophisticated planning and analytics tools such as IBM Planning Analytics with Watson can turn data into a powerful organisational asset. Harnessing workforce and other organisational data sources to drive efficiency, the planning and analytics tools can yield new insights from data that enable business leaders to test new approaches to solving workforce planning challenges or validate opportunities to shift where headcount is utilised in the business.

Forward-looking organisations can built this capability into workforce management to support faster and more accurate responses when conditions demand it or foster better collaboration across HR, finance and operations with agile analytics that make reporting workforce ROI painless.

Cornerstone has delivered Workforce Planning and Integrated Planning solutions to both mid-size and enterprise customers in Australia’s as well as some of the world’s largest global brands. We partner with IBM to deliver Planning Analytics with Watson across many aspects of business performance management. For more information about our workforce management and planning capability, please contact us.