Productivity is affected by a variety of factors, from the equipment used to the attitude of the employees to the quality of the materials. Improving productivity requires that factors such as these be addressed and mitigated so that production develops into a predictable standard of performance.
Productivity can be said to have improved when more output is achieved for the same input or when the same output is achieved for the less input. To improve productivity, either the process itself, the equipment and machinery used, the workforce or the indirect processes affecting production must be addressed.
For productivity to improve, improvement must be seen as a continuous process. Many organizations have found that Edward C. Deming’s process management cycle is useful. Deming’s cycle is frequently represented as PDCA, meaning: plan, develop a course of action based on information collected; do, implement that plan; check, measure and analyze the relative success of that plan; and act, adjust the plan accordingly
Sometimes, brainstorming with members of an organization will result in the accurate identification of problem areas in the company. However, more frequently than not, companies tend to focus on the issues but not the underlying causes of those issues. As a result, plans are developed to address the problem (for example, order satisfaction and high incidence of backorders) rather than addressing the causes of the problem (for example, unreliable suppliers, high absenteeism, scheduling problems).
One useful tool in productivity improvement is cause-and-effect analysis. By identifying and analyzing the issues restraining productivity, you can create a diagram of issues, the immediate causes of the issue, the causes of those causes and so on. Also called a fishbone diagram for its appearance, cause-and-effect analysis can be applied using the Theory of Constraints, which basically states that a process is only as good as its weakest input. Many people make the mistake of trying to address the “effect” rather than the causes of that effect.
In developing a plan for productivity improvement, gap analysis is a useful tool. Gap analysis looks at where a company’s performance is and where it wants to be. By looking at the “gaps” in performance a plan can be developed which targets those gaps.
Statistical process controls (SPC) are a useful tool to obtain an objective, quantified measure of the state of a process or the effectiveness of improvements made. Examples of SPCs include company ratio analysis, control charts, process capability studies, etc.
Productivity improvement can be driven by results or activity. Activity-driven approaches, though they may be successful in the short run, generally target the issues themselves rather than the underlying causes. As a result, productivity may be seen to improve briefly, only to go down again.
In contrast, results-driven approaches take on a sort of "just-in-time" quality, meaning that innovations are introduced only when needed and effectiveness is measured straight off, producing a type of trial-and-error environment where the need for improvement is continually reinforced and successful results are built upon and frequently expanded.