A few months back I received a phone call from an old friend. After we had finished catching up for a bit he began describing to me how he had his employees calculate the yield of his pizza's. each day the employees would mark how much came out and how much was put in. The employee would then divide the out number by the in number giving him the yield percentage. Sound familiar? The method that was being used to calculate yield is known as traditional yield calculation. Out of curiosity I asked him, "what is your yield percentage?" He then shared with me that his yield for each day was always right about 96%. So what was the issue? 96% production rate is not the best, but it's not the worst either. That's when he mentioned that things didn't seem to add up.
So where do we start? Let's look at the process right! First I asked him to give me a run through of the process that was being used to make the pizza's. As it turns out he had two separate processes, one for popular orders and one for unique orders. We will look at the "popular order" process here.
What is First Time Yield?
The first time yield, first pass yield or throughput yield is a metric used to determine how a process is performing in relation to the number of good units or services it produces. In other words it tells us the number of good units to the total number of units excluding wasteful activities like rework and scrap on units that can not be fixed. In the case of our pizza we actually have a 90% first time yield not 96% as the traditional calculation showed us.
How is it Calculated?
6% change in a measurement is quite significant. Can you imagine if that change was in car parts, airplane parts or computers and not pizza's? The way we calculate first time yield, throughput yield or first pass yield is simple by dividing the number of GOOD UNITS (excluding any rework or scrap) by the THE TOTAL NUMBER OF UNITS GOING THROUGH THE PROCESS. If you are interested in a template the bottom of the page will give you a free download.
Why use First Time Yield?
So why do we use first time yield instead of traditional or final yield? The most obvious reason is that using final or traditional yield methods keeps the "hidden factory" hidden. The final yield only divides the number of acceptable pieces by the number original number, or what comes out in comparison to what went in. Looking back on our pizza's we can understand now that the yield was not really 96%, in other words using the traditional yield calculation hides wasteful activities like rework, lost time and many other forms of waste. However when a metric like first time yield is used we take into consideration only process steps that yield good parts or services and exclude rework (first pass). This gives us greater insight as to what is actually going on in the process. Using metrics such as first time yield also helps combat the famous, it's just the way we always do it behaviors by exposing rework and other wasteful activities so that they do not get built into future processes.
In the case of my friend he was losing 6% on every 100 pizza's which could turn out to be a significant opportunity to improve his process and gain additional resource time in the near future. Ultimately first time through yield is a significant step in the right direction, however most processes are linked together in order to create a systematic way of accomplishing tasks along the way. When there is a string of processes involved FTY is not the ideal way to measure. These cases like we will see in our "unique order" pizza's are better suited using a rolled throughput yield. So stay tuned as we calculate the complex unique orders of our pizza process using rolled throughput. Don't forget to download your free template by clicking on the link below.
Have you ever gotten into a discussion of why? because. Why? because. Last weekend I had the great pleasure of this discussion for what seemed to be the first time. I never really put much thought into it but asking why never really was a difficulty for me.
Oftentimes when we want to use the 5 whys to drill from issue to root cause we end up in a pattern of why, because. Why, because. Or, we conduct a long analysis only to find out that none of our levels of causation matched at all. One of the best known examples of a 5 why analysis was performed by the master Taiichi Ohno. He used the example of a welding robot stopping in the middle of its operation. Like a sensei does he naturally went from initial issue to root cause with almost no difficulty at all. So, how do we begin developing this level of mastery with regards to root cause analysis? Here are a few important things to keep in mind when looking for the ROOT cause.