Man has been measuring work as long as he has applied organized methods to building or manufacturing anything of substance. Henry Ford was, of course, sensitive to work measurement in order to produce an affordable automobile. Undoubtedly, the builders of the ancient pyramids of Egypt also measured work in order to calculate schedules and allocate the use of resources effectively. The work of W. Edwards Demming is legendary in how it helped revolutionize post-WWII Japan. The need to measure work should be obvious: to maximize productivity, minimize costs, and to seek new and improved methods to expedite development. It involves analyzing such things as development methodologies and tools, monitoring quality and costs, and the amount of effort required to perform a given task.
One of the most common mistakes made in work measurement though is to focus solely on the output of a process. For example, in the Information Technology field, there is concern with the process of entering data (aka, "data entry" or "data conversion"), which is typically implemented by keying or some other technique. Banks, insurance firms, and other companies are known to have large groups of data entry clerks, not to mention government. Here, emphasis is placed on such things as the number of keystrokes against time. This may be rather simple for computer vendors to record, but it fails to consider if the keystrokes were truly necessary or if they resulted in errors. Other people consider the simple recording of time as a means for studying productivity, particularly "Man Hours" (a common invalid concept for measuring time). Again, this may be easy to do but there is no consideration for the necessity of the task and if any errors were made. This is like running a race without a frame of measurement; is it 50 yards? 100 yards? A mile? We may have spent considerable time running, but we cannot know how fast we are trule going without knowing BOTH the starting and ending points. There is little point in measuring how fast workers shovel without knowing what they are shoveling (amount of dirt) and how they are doing it (good or bad).
As another example, distributors of parts and products must make timely shipments to customers. Quite often productivity is measured by the number of shipments in a day. However, the materials being shipped should also be considered; e.g., a small item will likely take less time to process than a larger item; quantity ordered also impacts shipments. If you are only measuring the number of shipments in a day, then you are mixing apples with oranges and will inevitably arrive at some false conclusions regarding the productivity of your shipping department. Here, we should consider the types and volume of items to be processed (the inputs), how they are stored, picked, packaged, boxed and labeled (the process), and the number of shipments (the outputs). By studying the entire process carefully, we may consider improved ways for storing and picking materials, packaging assembly (manual versus automated means), and delivery.
If we want to determine the speed of anything, we must know the distance between two points, and what route to take. This means studying everything from start to finish, which involves not only the end product of the work process (the output), but the materials going into the process as well (the input). In the data entry example, it is necessary to know the volume of input to be keyed, as well as the amount of time necessary to complete the task, and the number of errors made in the process (if any). Only when all of these variables are known can we determine work load capacity. This is a subtle but significant difference on measuring work. Although we are using data entry as an example here, this approach is applicable to any repetitive task.
One of the biggest benefits from this approach is the development of standards. Arbitrary standards for work load are simply not realistic and can be quickly dated. By measuring the input/output elements for each worker, it is possible to develop realistic standards, not just for an individual, but for a group of workers, thereby providing the means to analyze the performance of one worker against another, or an individual against the group. By summarizing the numbers of a group, it is possible to then analyze the performance between groups.
The ability to measure work is a relatively simple endeavor, but requires a total perspective on the problem, not just one part of the puzzle. Doing so will inevitably lead to erroneous conclusions. Knowing the amount of true effort required to build something leads to better estimates, better schedules, more effective use of resources, and may even lead to new development processes. Just make sure you are measuring the right things: both outputs AND inputs.
Keep the Faith!
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Tim Bryce is a writer and the Managing Director of M. Bryce & Associates (MBA) of Palm Harbor, Florida and has over 30 years of experience in the management consulting field. He can be reached at firstname.lastname@example.org
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Copyright © 2012 by Tim Bryce. All rights reserved.