Targets Deconstructed

“Eliminate numerical goals, posters, and slogans for the work force, asking for new levels of productivity without providing methods.”

— Point No. 10 in Dr. W. E. Deming’s 14 points for management as written in “Quality, Productivity, and Competitive Position.”

A few weeks ago I had an excellent exchange on Twitter with UK Police Inspector Simon Guilfoyle on the topic of setting numerical targets. He asked “How do you set a numerical target without it being arbitrary? By what method?” Unfortunately, Twitter’s 140 character limit isn’t sufficient for adequately answering his question. I promised him I would write a post that explained my thinking.

When I was working for Samsung Austin Semiconductor (SAS) as a quality assurance engineer, one of my assigned responsibilities was to manage the factory’s overall nonconforming material rate. Over the course of my second year, the factory averaged a four percent* nonconforming material rate. The run chart for the monthly nonconforming material rate showed a stable system of variation.

As the year drew to a close, I began thinking about my goals for the following year. I knew I would continue to be responsible for managing the factory’s overall nonconforming material rate. What should I set as my target for it? Not knowing any better, I set it to be the rate we achieved for the current year: four percent. If nothing else, it was based on data. But my manager at the time, a Korean professional on assignment to the factory, mockingly asked me if I wasn’t motivated to do better. He set my target at two percent*; a fifty percent reduction.

What was the two percent number based on? How did he come about it? I had no insight and he didn’t bother to explain it either. From my perspective, it was an arbitrary numerical target; plucked out of thin air. I remember how incredibly nervous I felt about it. How was I going to achieve it? I had no clue nor guidance. I also remember how anxiety filled and frustrating the following year turned out for me. I watched the rate with a hawk eye. I hounded process engineers to do something whenever their process created a nonconforming lot. It was not a pleasant time for anyone.

Since then I’ve worked at several other companies in different industries. Nevertheless, my experience at SAS seems to be the norm when it comes to setting targets. This is regardless of the role, the industry or the culture. And, as far as I’ve been able to figure out, this approach to setting targets is driven more by tradition and arrogance than any objective thoughtful method. “Improve performance by 50% over last year!”, so the mantra goes. Worse still, no method is provided for achieving such arbitrary improvement targets. I’ve been told “You’re smart. You’ll figure out how to do it.”

So it’s not a surprise for me that folks like the good Inspector have become convinced all numerical targets are inherently arbitrary; that there is no objective and justifiable way to set them. Having been on the receiving end of such targets many times, I used to think the same, too. But just because people don’t know of a different way to set a target, one that is objective and can be justified, doesn’t mean there isn’t one. I believe numerical targets can be set in an objective fashion. It, however, requires thoughtfulness, great effort and understanding on the part of the person setting the target.

One way to set a target is to use the performance of a reference for comparison. In my case, the SAS factory I worked at had a sister facility in Korea. It would have been reasonable, albeit crude, to set my target for the nonconforming material rate to that achieved by the sister facility (if it was better.**) An argument could have been made that the target was achieved elsewhere, so it can be reached.

As part of our Twitter exchange, the Inspector made the point that regardless of whether these factories were defined to be sisters, there would still be differences between them. Therefore, they will generate a nonconforming material rate that is a function of their present system architecture. He is absolutely right! Setting a target for my factory based on the performance achieved by its sister facility alone will do nothing to improve the performance of my factory. It’s already doing the best it can.

But that’s not the point of setting the target: to operate the same system and expect an improved performance. The point of setting the target is to trigger a change in the system, a redesign in such a way as to achieve a level of performance that, in this case, has been achieved elsewhere. The sister system can be treated as a reference and studied. Differences between systems may be identified and eliminated. Along the way we may find out that some differences cannot be eliminated. Nevertheless, by eliminating the differences where possible the two systems are made more similar to one another and we will have improved the performance.

In the absence of a reference, simulations may be used to objectively define a target. The factory’s overall nonconforming material rate is the combined result of the nonconforming material rates of its individual processes. Investigating the performance of these inputs can help identify opportunities for improvement for each: stabilizing unstable processes, running stable processes on target, reducing the variability of stable on-target processes. All of this can be simulated to determine what is ideally possible. A justifiable target for the nonconforming material rate can then be set with the results. Best of all, the method by which it can be achieved gets defined as part of the exercise.

Finally, targets may be set by the state of the greater environment within which a system operates. All systems operate in a greater environment (e.g. national or global economy); one that is continuously changing in unpredictable ways. City populations grow or shrink. Markets grow or shrink. Polities combine or fragment. What we once produced to meet a demand will in a new environment prove to be too little or too much. A change in state of the external environment should trigger a change in the target of the system. A change in the target of the system should trigger a redesign of the system to achieve it. In Systems lingo, this is a tracking problem.

Targets are essential. They help guide the design or redesign of the system. They can be defined objectively in several different ways. I’ve outlined three above. They do not have to be set in the arbitrary way they currently are. But setting targets isn’t enough. Methods by which to achieve them must be defined. Targets, even objective ones, are meaningless and destructive without the means of achieving them. Failure to achieve targets should trigger an analysis into why the system failed. They should not be used to judge and blame workers within the system.

Sadly, people are like water, finding and using the path of least resistance. Setting arbitrary improvement targets is easier than doing all the work required to set objective ones. They have been successfully justified on the grounds of mindless ambition. No one questions the approach out of fear or ignorance. Positional authority is often used to mock or belittle the worker for not being motivated enough when the truth is something else: managerial ignorance and laziness to do their job.

* I’ve changed the numbers for obvious reasons. However, the message remains the same.

** As it turned out, the nonconforming material rate achieved at my factory was the best ever in all of Samsung!


3 responses

  1. Hi Shrikant,
    Thanks for taking the time to explain your thinking. However I’m afraid I still don’t agree ‘targets are essential’, as you put it. A few things that jump out at me are:
    – I agree there can be a lot to be learnt from studying how a similar facility performs; however, it is the learning and subsequent systems changes which achieve better performance, not the target.
    – In respect of targets acting as a trigger to make systems changes to improve, I understand what you are saying, but there should already be an ethos of seeking continuous improvement, i.e. aiming for perfection if possible. The Taguchi Loss Function illustrates this – effort is focused on achieving nominal value from the customer’s perspective, rather than arbitrary specifications determined by the organisation. Have a look at this blog, which contrasts the two approaches – Seriously, why is aiming for a fraction of might be achievable better than aiming for the best you can possibly be?
    – Targets do not provide a method or capacity for achieving purpose or even greater output (as you recognise).
    – Oh, and whether it’s a 50% improvement sought, or 34.7%, or something else, it’s arbitrary. No matter how much number crunching goes into establishing prior performance, predicted trajectories, external influencing factors, or what someone else is doing, the actual point of adjustment from the baseline to the designated target is arbitrary. It ignores variation for a start. You might be able to say, “If we change process ‘A’, take into account factors ‘B’ and ‘C’, compare how sister facility ‘D’ has performed in similar conditions, then we can predict output will be in the range of ‘E’ and ‘F’.” That’s fine, BUT…
    How can you determine where a precise target should be situation within this anticipated range? The data will be subject to variation. We may be confident output will fall within a range, but if it does, it will happen anyway – that’s nothing to do with the target, but the capability of the process. Have a look at the points made in this blog –
    All the best,

    1. Hi Simon,

      Thank you for your comment. I believe that the gap between what you and I are saying is due to a difference in how we are defining the word “target” rather than fundamentally different views.

      When I speak of a numerical target, I mean it in the same way as it is meant in Taguchi’s loss function: the location where we would like a stable process to be centered. That value has to be defined in some way. I attempted to identify a few ways how a designer might go about defining it in my post above.

      It won’t matter how tightly my expenses are distributed about the mean if the mean of my expenses exceeds my revenue. I will soon be out of money. That is just a mathematical fact. If I want to keep my affairs going, I will need to shift the mean of my expenses to be less than my revenue. The minimum amount of that shift can be objectively determined. That is the point I wanted to get across.

      Once you have defined a target, of course you want to operate your process as close to it as economically possible with as little variation as economically possible. I couldn’t agree more with you on this point of continual improvement. While Taguchi showed this mathematically, it also has an intuitive appeal.

      However, continual improvement cannot account for a shift in the external environment. When such a shift occurs i.e. the target in Taguchi’s loss function takes on a new value, the existing process that previously produced little loss will now generate huge loss. The existing process must be redesigned to operate around the new aim. I hope this point makes sense.

      Whereas my revenue exceeded my expenses when I had a job i.e. the mean difference between the two was positive, that difference turned negative when I lost my job. In order to keep my affairs going, I must adjust to the shift in the external environment by shifting my expenses in the direction that minimizes my loss.

      You and I share the same philosophy. I believe we were talking about different concepts that unfortunately use the same word. Please correct me if I am mistaken.

      Best regards,

      PS: I implicitly assume as understood that a stable process produces variable output about its mean.

  2. Hi Shrikant,
    Thanks for your clarification. What you seem to be describing is what Deming called a ‘fact of life’, i.e. if a company makes less money than it spends this clearly isn’t a good thing! I don’t believe that such considerations reflect the nature or use of targets however – companies don’t set a target of not making a loss, or positioning the Taguchi Loss function so that nominal value is the break-even point; they tend to aim for profit, setting numerical targets for sales, for example, such as “To increase profits by X% or X Million $”. Setting such precise numerical targets ignores variation (as described in my previous response), is based on an arbitrary adjustment from a baseline value, plus it causes dysfunctional responses and unnatural cycles in output, depending on whether performance is reported quarterly or annually.
    Regarding your other main point, adjusting to changes to the external environment is fine and is to be encouraged as a hallmark of an adaptive and responsive organisation, but that reflects environmental awareness and effective interpretation of data which lead to beneficial system changes- targets are not required to achieve this.

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