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- Employers can use flexible benefits scheme data to assess how well their scheme supports their organisation’s business objectives.
- But they need to ascertain from their flex providers and benefits consultants the range of data that is available on their scheme, plus the format in which it can be provided.
- Flex providers may charge for data analysis.
Flexible benefits scheme providers hold data on every aspect of their employer clients’ flex schemes, from the frequency with which their employees take up particular benefits to how they flex these up and down, based on factors such as their age, location, marital status and whether or not they have children.
Benefits professionals can use this data to monitor the effectiveness of their flex scheme in, say, supporting their organisation’s talent management strategy by tracking scheme engagement levels among employees that have recently left their organisation.
Employers could also use their data to monitor any correlation between employees’ engagement in their flex scheme, particularly in any health and wellbeing benefits on offer, and their sickness absence levels, to help measure the effectiveness of the scheme in boosting staff wellbeing.
Employer interest is low
But employers’ interest in, and requests for, flex scheme data is currently low, which Alex Tullet, head of benefits strategy at benefits consultancy Capita Employee Benefits, attributes to cultural issues surrounding many benefits professionals’ approach to flex scheme design.
“A lot of decision making has historically been based on the gut feel of HR departments and benefits consultancies and very little on data, but now we have the data to test [these instincts],” he says.
This gut-instinct-based approach to benefits selection helps to explain why so many employers struggle with flex scheme issues such as low take-up.
Tullet recalls one employer that suffered low scheme take-up because of its inappropriate benefits offering, based on what it thought that staff wanted. The organisation offered private medical insurance, life assurance and a workplace pension to a workforce with an average age of 31 and an average salary of around £25,000.
“Employees at that level are interested in where they can save money, such as through gadget loans; they are not interested in insurance,” he says.
“Because of that, the employer had low engagement, so we had to get it to re-engage with its employees with a revised benefits package based on an understanding of what it is that its employees will be interested in, and [teach it] how to communicate effectively with those employees off the back of the investigatory work that we did with the data we have.”
Large employers dominate data queries
The majority of the current interest in flex scheme data is dominated by large employers, which are particularly interested in benchmarking the take-up rates of their flex benefits with those of their industry peers.
Terry Gostelow, an account director at flex benefits software provider Staffcare, says: “At the end of an enrolment window, employers will be interested in the take-up rates of benefits, so they can see whether or not their staff are actually interested in the benefits that they provide.”
He adds that employer clients are increasingly demanding analytics around scheme usage, so that they can understand the journeys motivating their employees’ benefits selection.
And benefits consultants are helping to drive employers’ interest.
”Consultants might provide advice on whether [organisations’ take-up rates] fit within industry benchmarks, which informs employers’ decisions for the following scheme year.”
Manesh Patel, senior benefits consultant at Aon Employee Benefits, says: “If a scheme has already been in place and the employer is going through a renewal cycle [around its enrolment window], we have a review session explaining the trends we are looking at for the following years and which benefits to consider. We use this as a basis to provide any recommendation, because employers do not necessarily know what is happening [in the benefits market].”
He adds that employers typically want analysed information rather than raw data to work with.
Tullet believes that now, in light of the UK’s economic recovery, is the perfect time for employers to start sourcing the data underlying their flex scheme, whatever their preferred format.
“Post 2007, there was a massive switch away from some of the more luxury-type benefits, such as wine clubs and concierge services, and into defensive benefits, such as retail discounts,” he says.
“We are now looking at whether or not we are starting to see the tail-off of that trend, and whether employers are starting to move back [into luxury-type benefits]. It has not happened yet, but that is our prediction.”
How to source flex scheme data
Employers that are keen to use data to help shape their flex scheme should start by talking to their flex providers about the data that they can, and are willing to, provide, as well as the format in which they can provide it.
Organisations should also consider the level of support that they may need to analyse their data, whether a provider can deliver this and at what cost, as well as how their provider can help them to manage potential risks such as data protection breaches around employee data access, if at all. (See column).
Employers that are currently considering introducing a flex scheme to their organisation should ask these questions during the due diligence process that they undertake when selecting a flex provider.
Employers should ask their flex providers to help identify any trends around employee scheme usage; whether they can break down employees’ benefits take-up based on their salary, grade and location; and how they can help them to segment their communications campaigns for different groups of employees.
Data analysis objectives are crucial
But employers should first identify what they want their data analysis exercise to achieve.
Matthew Gregson, consulting director at benefits consultant Thomsons Online Benefits, says: “Employers have to consider how much better informed their decision making will be as a result of their data analysis.”
And in the process they should carefully consider the challenges involved in the exercise, such as how to analyse their findings, because poor scheme take-up, for example, may not necessarily be a result of poor benefits provision, but because of poor communications around these benefits.
Similarly, benefits take-up rates do not necessarily indicate whether or not employees subsequently use the benefits, or if they do whether it is for a sustained period of time.
Finally, employers need to consider the resources required to ensure the accuracy of their data to optimise the value of their analysis.
But these challenges should not deter employers from embarking on their project as soon as possible, because data analysis around flex is a growing trend that they cannot ignore, particularly in light of the potential cost savings.
Capita’s Tullet, who believes that flex data analysis is more about behaviourial economics and HR analytics than it is about ‘big data’, which refers to terabytes of data, claims to have helped 15 employers generate around £15 million in savings.
“This is just by redirecting their benefits spend so it’s more effective,” he adds.
Case study: Sky uses data to tailor benefits
Sky uses the data underlying its flexible benefits scheme to ensure that its benefits package is fit for purpose for its workforce.
The home entertainment and communications provider works with its benefits consultant, Capita Employee Benefits, to analyse data on, for example, its workforce demographic broken down by employee location and age profile.
John Whitaker, benefits consultant at Sky, says: “We can then start to make some informed decisions in terms of the benefits that we should be introducing, the benefits that we should be archiving off because they are just not adding value and the benefits with really low take-up and some of the reasons behind that.”
One particular exercise involved the organisation investigating whether or not there was any correlation between the number of benefits employees select and the likelihood of them being employed by Sky a year later, which proved to be the case.
But Whitaker says: “You can come up with up with all of these correlations that may be interesting, such as employee engagement versus benefits spend, and it looks pretty on a graph, but it is really important [for employers] to identify what it is they want to achieve.”
Employers should embark on a data analysis exercise by understanding what they are trying to achieve and ensuring that they have accurate data.
Sky attempted to analyse its scheme data in-house, but found the process too difficult because of its lack of resources, the proliferation of systems on which data was held and the way in which data moves around.
Whitaker says: “Trying to analyse data is really, really difficult.”
He adds that Sky’s benefits, which include childcare vouchers, health screening, retail vouchers and bikes for work, offered through its ‘Anytime benefits’ package, constitute the employer’s own form of flex.
“We have salary sacrifice, but I don’t see it as a flexible benefits scheme with a massive enrolment window every year and then lock it down for 11 months.
“We offer rolling, monthly benefits, so if an employee wants to take [one of the aforementioned benefits], they are free to do that throughout the year.”
Jim Lister: Employers must consider the potential risks involved in data mining
The mining of staff data raises data protection issues, although in-house mining is usually much less problematic than wider big data projects.
Any third party that employers use to mine their data will be considered to be a ’data processor’ for the purposes of the Data Protection Act. That means that employers will need to tie them up to a data processor agreement, which commits them to good data protection practices.
A data mining report is unlikely to create new personal data. It will usually identify trends, but not name individual staff members. But any data trawl is itself considered to be ‘processing’, even if it is automated, and that processing must be conducted lawfully and in accordance with the eight data protection principles in the act.
Data mining associated with incentive schemes will usually involve processing both ‘ordinary’ and ‘sensitive’ personal data. Information relating to sickness and maternity leave, for example, will be ‘personal data’ and must be handled accordingly.
Consideration must be given to whether the individual consent of staff members is needed before a data trawl is undertaken. It is strongly arguable that the general consent wording appearing in most modern contracts of employment, which permits processing for normal HR purposes, would be sufficient to allow data mining of both ordinary and sensitive data. Most organisations will proceed on that basis, without seeking specific consent, perhaps taking comfort that the exemption in the act relating to processing data to facilitate management forecasting is also likely to apply.
The issue that could really hurt employers is data security. Fines for breach of data security can be very substantial, up to £500,000 in serious cases. Employers should therefore ensure that only staff who really need to, if any, are able to access mined data.
Jim Lister is a principal lawyer at Pannone, part of Slater and Gordon
