The bias for or against point solutions ebb and flow over time. Broadly speaking, many software applications deal with large volumes of data, but have fairly narrow purposes. For example, time & attendance systems focus on paying each worker for time worked. The data collection is important, but at the end of the day the system is a transactional one and in general does not stray too far from its intended purpose. Scheduling systems, on the other hand, are engines that evolve from mathematics and operations research. The knowledge-base to create scheduling systems for complex, multiple constrained problems is different from business and data collection systems. This statement is not intended to disparage transactional systems – you would not want a mathematician build a payroll system – but the buyer should exercise great caution in assuming a time & attendance vendor has the expertise to craft a labor scheduling system suitable for complex work environments. Implementing the workplace rules is not a simple case of a string of “if-then-else” statements as found with simple staffing systems, but involves solving combinatorics with a possibility of a high number of interacting constraints. The market evidence is that with scheduling systems, point scheduling solutions remain the most robust for sophisticated applications.
