The Disadvantages of Operations Research
Workflow is a work in progress, and if you're engaged and interested, you'll always be figuring out new and better ways to run your business. Operations research digs into the data so you can track efficiencies and adjust to solve inefficiencies.
Operations research gives objective data, telling you which aspects of your business are cost effective and profitable and which use more time and resources than necessary. The numbers are clean and clear, and they give you information that isn't always apparent when you've got your nose down and you're just doing your work.
For example, tracking worker productivity relative to pay grade and equipment upgrades could help you to calculate whether an extra investment in payroll or in infrastructure pays off in increased output. Similarly, examining the correlation between the number of people on the production floor, the types of products being produced and the amount produced per person per hour provides information for determining the optimum number of people to schedule at once for different products.
Operations research evaluates your business in terms of the numbers. However, intangible variables such as kindness and quality of life also play into business decisions, and operations data typically doesn't capture their importance. The importance of operations research in modern business management can make business decisions impersonal, emphasizing the numbers at the expense of the human element.
Some operations research is also quite sophisticated mathematically. This is an advantage because a skilled and knowledgeable researcher can draw nuanced conclusions. However, if you're mostly concerned day to day with the nuts and bolts of your business, you may have neither the resources nor the interest in using complex mathematics to solve tangible operations issues.
- Linear programming: This approach builds out a model that reflects both objectives and constraints. For example, you may be looking to create a scenario that shows how you can earn as much money as possible, with the limiting factor that your business lacks access to capital for equipment it needs. Linear programming uses software to play out the consequences of different combinations of functions, or desired outcomes, and different limiting factors that could interfere with an ideal outcome.
- Nonlinear programming: Although linear programming gives you the clarity of seeing direct outcomes from changing specific variables, not all outcomes are linear. In fact, nonlinear outcomes are more common than linear ones, as with scaling up a cookie recipe that requires less baking soda relative to flour as the batch size increases. Similarly, economies of scale are nonlinear, and it's tricky to accurately predict when you begin to reap their benefits.
- Simulation: Operation simulations project possible outcomes by cycling through possible random variables as if these random variables were known. By playing out many possible scenarios, simulations help you to develop a plan based on the statistical probability of having to deal with particular circumstances.
- Judgement phase: This part of the process sets up the scope of the research. At this phase, researchers outline the problem to be solved as well as the objective the inquiry is expected to achieve. Outlining the problem includes specifying its origin, causes and potential solutions.
- Research phase: This part of the process is dedicated toward gathering the data generated by the study's parameters. Once the data is collected, it is organized and analyzed to create mathematical models, and then these models are evaluated for the purpose of making recommendations. Hypotheses are advanced, tested and adjusted.
- Action phase: During this part of the process, researchers and managers work together to craft solutions that use the aggregated information to offer solutions to the problem articulated at the outset of the study. Once these solutions are offered, they are put to work, and a new phase of operations research begins as a fresh set of problems are outlined and a fresh set of outcomes are defined.