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The Pensions Regulator recently stated that only 46 per cent of those staging in 2017 were aware of their responsibilities.
Many of the nearly two million small employers approaching their pensions auto-enrolment staging dates are in danger of missing deadlines by underestimating the amount of data needed to complete the process, an advice firm has warned.
Lighthouse Group said tens of thousands of SMEs and micro employers are now “starting to grapple with the complexities of employer pension schemes for the first time”.
The Pensions Regulator recently stated that only 29 per cent of those staging in 2016 were fully aware of their date and only 46 per cent of those staging in 2017 were aware of their responsibilities.
Roger Sanders, managing director of Lighthouse Group Employee Benefit, said: “We are finding many businesses lack the accurate, up-to-date information on employees vital to completing enrolment smoothly. Firms that leave their enrolment preparation too late will be in for a shock when they discover years of payroll and employee data needs to be sorted before they can properly begin.”

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Lighthouse advised employers who use a payroll bureau to ask whether their systems and software are geared up to deal with auto-enrolment, assessing if they can extract needed information easily, in a suitable format, and on a regular basis.
The firm explained that a payroll bureau generally holds information such as an employee’s full name, their salary or wages and National Insurance number, but may not have the employee’s address and other contact details such as email, which is often held by the employer.
However, under auto-enrolment all this information needs to be brought together each time an employee is paid, whether monthly, fortnightly or weekly.
Mr Sanders said: “The data challenge doesn’t end once everything is in place. Businesses also need to run a data check for every pay period, to verify employees’ eligibility criteria, new joiners and contribution levels. This will ensure that any employees who become eligible later are enrolled, for instance because their earnings have increased or they have reached the age of 22.
“Automating as much of the data gathering, collating and transmissions as possible will significantly lower both the margin for error and the overall cost to the business.”

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