Why it’s unacceptable to be unsure if your employee benefit programme is succeeding.

By Graham on 

Employers often spend hundreds of thousands, if not millions of pounds, on providing workplace benefits to their people.

While there are many good reasons to do so, the justification to support such a significant investment should be objective and demonstrable. Instead, decisions are too often based on “similar experience” and “anecdotal feedback”. With budgets coming under scrutiny like never before, there is increasing pressure to evidence the effectiveness of benefits programmes. Now is the time for reward professionals to embrace the power of data or end up finding themselves exposed.

Employers that understand the needs and motivations of their workforce are best placed to create meaningful reward packages. The more accurate and granular this understanding, the more targeted reward packages can become in supporting wider corporate objectives.

For example, reward packages that increase the number of applicants from specific high performing talent pools can help improve business productivity. Alternatively, benefits that help reduce absence and attrition across critical client facing functions can help improve customer experience and reduce recruitment costs.

“Reward packages that increase the number of applicants from particular high performing talent pools can help improve business productivity.”

However, in order to craft a meaningful benefit programme and measure its impact, reward professionals first need to have access to reliable, accurate and consistent data. Unfortunately, many employers fall down at this first hurdle. Almost 40% of organisations are still using spreadsheets to administer their benefit schemes [Rewarding Tomorrow’s Workforce, 2018], while over 20% of employers use multiple benefit-specific platforms with differing reporting capabilities [Rewarding Tomorrow’s Workforce, 2018]. This prevents employers from gaining a single, complete picture of their benefits schemes. Without high quality data, it becomes almost impossible to set benchmarks and identify patterns across departments or demographic groups.

“Without high quality data, it becomes almost impossible to set benchmarks and identify patterns across departments or demographic groups.”

We’re rapidly moving towards a world where machine learning will automate the analysis and interpretation of large data sets, which will enable employers to accurately model the outcome of proposed changes to their benefits programme. Imagine being able to directly and accurately correlate attrition rates within a specific subset of your employees to changes made to their benefits package, before making a commitment to introduce a new benefit.

Better still, machine learning will enable platforms themselves to recommend changes that best support specific corporate objectives, based on detailed knowledge of the workforce demographics and current workplace dynamics. This analysis will call on anonymised data from across entire sectors, at a scale that would be impossible for a single benefit consultant to comprehend. Although it will take time for algorithms to learn and provide reliable results, the potential is mind-blowing.

This improved intelligence will be welcomed with open arms by progressive HR functions, keen to evidence their role in supporting corporate objectives. However, it will also cause nervousness for others, with HR Directors able to openly scrutinise the effectiveness of existing, long running and costly benefit schemes, without relying on consultants that have often been involved from the outset.

“We’re rapidly moving towards a world where machine learning will automate the analysis and interpretation of large data sets.”

For the providers of benefits technology, the opportunity will also be viewed as a double edge sword. For some, who focus primarily on benefits technology and continue to invest in their platform, machine learning will be seen as another exciting new capability that will help clients deliver better and more engaging benefit programmes. The good news is that some providers, such as Zest, are already embracing this challenge.

However, for providers that have failed to invest in their platform and opt to continue providing costly manual services, increasing automation will erode their revenue as the value of those services diminish. This will be welcome news to employers, who have long complained about their reliance on additional services to get the most from their benefits technology.

Many leading employers are already embracing technology to improve the way in which employees engage with their reward package and reduce the administrative burden of administering their schemes. This has become a benchmark itself of those employers that invest in their people. Those employers that have all their data in a single benefits platform will be better positioned to measure the effectiveness of their programme, using these increasingly powerful analytic tools.

As the battle for talent continues to intensify, the role of reward functions is likely to take on increasing importance. Reward functions that can demonstrate how their benefits programmes supports their corporate objectives will continue to be viewed positively by those that control the purse strings. Those that continue to manage their benefits programme in a fragmented manner and fail to evidence their contribution will likely find it much harder to secure the ongoing investment they require.

When the CEO comes and asks what you’ve delivered with that generous budget they provided you, be ready to show them the great results you’ve achieved.