What Operations Management Is and Why It Matters
Operations management is the discipline that designs, manages, and continuously improves the systems and processes that transform inputs (labour, materials, capital, information) into the outputs (products, services, customer outcomes) that the organisation’s customers value. The operations management function is present in every business — the manufacturing plant that produces physical goods, the professional services firm that delivers expertise, the technology company that develops and maintains software, and the hospital that provides healthcare are each managing the specific operational processes that most directly determine whether their outputs meet the quality, the cost, and the timing requirements that their customers expect. The quality of operations management most directly determines whether the organisation can consistently deliver on its customer value proposition at the cost that the competitive market requires.
The operations management competitive advantage that most clearly distinguishes the organisations with superior operations from those with adequate operations: the specific operational capabilities that enable the organisation to serve customers better, faster, or at lower cost than competitors while maintaining the quality consistency that customer trust requires. Toyota’s production system that produces automobiles at lower cost with higher quality than most competitors, Amazon’s fulfilment system that delivers most orders faster than most competitors at costs competitors cannot match, and McDonald’s kitchen system that produces consistent food quality at consistent cost in thousands of locations simultaneously are all examples of the operational capability that has become the durable competitive advantage that marketing, pricing, and product alone cannot replicate.
Process Design and Improvement
The process design principle that most clearly guides the development of the efficient, scalable operational processes that deliver the organisation’s value proposition: the flow optimisation that minimises the time and effort required to transform the input into the output by eliminating the waiting, the transportation, the over-processing, and the rework that add time and cost without adding value. The process map that traces the actual path of the work — from the moment the customer request is received to the moment the customer outcome is delivered — through every step, every handoff, and every waiting period reveals the process reality that the idealised process diagram obscures and identifies the specific steps where the waste elimination would most reduce the total process time and cost.
The process improvement methodology that most reliably produces the sustainable process improvement that the one-time process redesign exercise does not sustain: the continuous improvement culture that embeds the expectation that every person who performs a process is simultaneously the first-line observer of the process’s performance gaps and the primary contributor to the ideas that address those gaps. The operations management system that creates the mechanism for front-line process observations to be shared, evaluated, and implemented — the kaizen suggestion system, the daily team huddle, the improvement board — and that responds to those contributions with the specific action that demonstrates the observations are valued and acted on is the system that most sustains the continuous process improvement that episodic redesign projects alone cannot maintain.
Capacity Planning and Management
The capacity planning approach that most effectively balances the cost of excess capacity (the fixed cost of the capability that is not fully utilised) against the cost of inadequate capacity (the lost sales, the customer service failures, and the quality compromises that occur when demand exceeds the ability to serve it): the demand forecasting that most accurately predicts the volume and the mix of work the operations must handle in each future period, combined with the capacity model that translates the demand forecast into the specific resource requirements that the predicted demand volume and mix imply. The capacity plan that is built from the specific demand forecast rather than from the historical average avoids both the systematic over-capacity that the average demand creates in peak periods and the systematic under-capacity that peak demand creates when the average is used as the planning basis.
The capacity management decision that most significantly affects the operational cost structure: the make-or-buy decision for the capacity that the demand forecast indicates will be needed only intermittently. The permanent capacity investment in the equipment, the facility, and the workforce that serves the peak demand creates the fixed cost that must be recovered across the full period including the off-peak periods when the capacity is underutilised; the variable capacity arrangement (the outsourced production, the temporary workforce, the rented equipment) that can be activated for peak demand and deactivated for off-peak demand maintains the cost variability that the intermittent demand most efficiently justifies. The capacity strategy that combines the permanent capacity for the base load with the variable capacity for the peak demand most efficiently manages the cost of serving the demand variability that most operational environments produce.
Quality Management in Operations
The quality management integration with operations management that most effectively produces the consistent quality output that the customer’s experience requires: the quality specification that is built into the process design rather than inspected into the output after the process has completed. The process step whose completion criteria include the specific quality verification that the output meets the specification before the work passes to the next step is the process step whose quality problems are identified and corrected at the minimum cost — before the non-conforming output has accumulated additional processing cost and before it has potentially caused problems in the downstream processes that received the non-conforming input.
The quality performance measurement approach that most effectively drives the continuous quality improvement that the customer experience requires: the real-time quality data display that makes the current production’s quality performance visible to the production team as the production occurs — rather than the end-of-shift quality report that reveals the quality performance after the opportunity to correct the in-process quality problem has passed. The production operator who can see the real-time defect rate for the current production run, who receives the specific alert when the rate exceeds the control limit, and who has the specific authority and the specific knowledge to make the process adjustment that most commonly corrects the trend is the quality management system at its most effective — the one that most prevents the non-conforming product from being produced rather than the system that most efficiently identifies the non-conforming product after it has been produced.
Technology in Operations Management
The operations management technology investment that most improves the planning, the execution, and the performance visibility that effective operations management requires: the enterprise resource planning (ERP) system that integrates the financial management, the inventory management, the production planning, the procurement, and the customer order management into the single system of record that provides the real-time operational visibility that disparate, disconnected systems cannot support. The ERP system whose implementation is designed around the organisation’s specific operational requirements — rather than forcing the organisation’s processes to conform to the software’s default configuration — provides the operational planning and execution capability that most improves the operations management effectiveness.
The advanced planning and scheduling (APS) technology that most significantly improves the manufacturing operations planning quality beyond the ERP system’s standard planning capabilities: the optimisation-based planning engine that simultaneously considers the multiple constraints (the machine capacity, the labour availability, the material availability, the customer delivery requirements, and the inventory targets) that the standard ERP planning module addresses sequentially rather than simultaneously, producing the feasible, optimised production schedule that the sequential planning approach cannot reliably generate. The APS implementation that is integrated with the ERP system’s demand and inventory data produces the planning optimisation that most directly reduces the inventory, the overtime, and the expediting cost that suboptimal production scheduling generates in the complex manufacturing environment where the standard ERP planning module’s sequential approach most consistently produces the infeasible schedule that the shop floor must improvise around.