Background:
A local HR consultancy company that provides recruitment and payroll processing functions for their clients. As part of their business to perform an outsourced human resource payroll function to their clients, clients make submissions to them on a monthly basis. These submissions are made to their payroll team who are in charge of processing these submissions into their HR software to complete the payroll processing, followed by generating of the invoices, consolidating the documents including the person’s payslip to send over to their clients as proof of completion of the tasks.
Scope of Work:
Blacklight was contracted to look into optimising and automating their payroll process through designing an automated process that could be scaled as their client base expanded with time. This was in part fueled by their pain point of hiring and re-training payroll executives as their business scales. The objectives were thus to first study the process, and present portions of the payroll process that could be suitable for automation, and to suggest different approaches. As two of their staff were also going to be on leave for maternity, the management team also desired for the deployment of solutions to be completed as soon as possible.
Approach:
To meet the objectives of this project, Blacklight had to first work with the payroll team to understand their existing set up and processes, and then make a series of recommendations on what can be achieved. Thereafter, the expectation was for Blacklight to implement and execute the recommended solutions.
We commenced work through our 4-stage process of discovery, design, develop and deploy. The discovery phase for ST was three-fold.
The first task was to capture the as-is processes in process maps. During this discovery, we got our developers to shadow payroll representatives and IT personnels to understand the payroll systems and billing systems, and how they interfaced with the overall payroll process. These processes were captured in process maps, along with the estimated time taken for each client to be processed.
The second task was to collect quantifiable and non-quantifiable values that could be part of a multi-faceted value benefits analysis with results presented to the management team as productivity and benefits outcome. Along the way we also captured their anecdotes of pain points and challenges in completing the task at hand.
The third task during discovery was to test the RPA bot access into all the target systems used in the data process, to ensure that it could present a viable solution. With the completion of the discovery phase, we will then arrange to meet again with the client management team to present our findings and move toward the design phase.
The design phase is when we present the findings of the discovery to our client and co-create the desired ‘to-be’ process flows together. The importance of this co-creation process is to establish ownership and involvement as part of the change management process. It also ensures that we confirm our understanding of the impact of the final solution – such that it becomes a sustainable, meaningful solution for our client in the long run..
The completed and signed BRD is then taken to the development team for them to complete the development. During the development phase, there will also be a UAT conducted for each process automation sequence, which is showcase and approved by the client teams. Thereafter, Blacklight finally deployed the RPA solution, and worked closely with the client until the completion of the project.
Impact:
The implementation of RPA on data validation and entry processes, Blacklight has enabled the payroll team to function with 2 fewer persons (who were on maternity) from an original team size of 4 persons. If they had not embarked on this automation journey, the client would have hired at least 3 temp staff instead. Other than productivity outcomes, we also helped our client address stress levels of payroll manager to train and monitor new staff on a tight deadline, improve and increase accuracy of enable scaling of number of client companies, as well as address the longer term key person risk.
