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.
"What gets measured gets done!" That's the saying and we've all heard it before, but what exactly to measure is amongst the most critical questions we can answer in relation to our lean six sigma projects. Lean six sigma is a data driven approach of improvement. With that in mind the data that we choose to establish in our improvement projects must be measurable and aligned with project goals.
There are three general categories of metrics that almost any lean six sigma (CTx's) objective will fall under: Quality, Cost and Time. However, these metrics are quite broad inherently and can still leave us wondering how "improvement" is defined. Which brings us to the most important point of project development, defining up front what "improvement" means.
Before any project kicks off or mapping begins all parties associated should know exactly:
1. What measurements will be used.
2. How those measurements constitute a win.
3. Why those measurements constitute a win.
Defining what metrics will be used to play the game helps employees to stay aligned with objectives and ensure that both the team and the organization get the results they want.
Like the game of basketball teams also need to understand how their metrics constitute a win. For instance an employee with a goal of reducing defects could simply show a traditional yield measurement. Although this measurement may show reduced defects and an improved yield, it may not be exactly "what" the organization wants as traditional yield often creates a hidden factory scenario. For this reason, teams, should understand clearly "how" the measurements align with project goals.
The team who puts the ball in the hoop on any given day more times than their opponent is the winner. The reason why is that there is correlation between a team’s skill, conditioning and teamwork and the amount of points they score. Understanding why they want to score more points helps the morale, motivation and dedication of the team. Going back to our yield calculation example it becomes clear that using a first time yield or a rolled throughput yield is a much truer measurement than a traditional yield would be. After all, why would anybody want 100% yield if there were months of rework involved?
While we sometimes end up on the short end of the stick with projects because what, how and why aren't clearly laid out up front many organizations may find that the wins they wanted were much bigger than what they actually saw. Establishing upfront what, how and why the "game" is being scored the way it is makes it much easier for both the organization and the teams to end with a winning score that aligns with everyones needs.
The last slide clicked, with jitters in his arms the young man set his clicker down. He knew something had gone desperately wrong. A loud voice soon called out " Okay, So what's the return?" For a moment the freshly trained black belt sank back into his suit. After a deep breath he replied "we have a faster process and everyone on the floor is much happier."
When looking to calculate metrics for a process one of the best performance metrics that you can use in relation to yield is Rolled throughput yield. Rolled throughput yield is the probability that a process with multiple steps will produce a defect free unit or service. RTY is often referred to as "True throughput yield" because it quantifies the cumulative effects of inefficiencies that often plague processes and drive hidden costs. Like we mentioned in our previous post entitled: First time Yield (FTY) most processes are linked together in a series so that tasks can be accomplished easily. As you can see in the flowchart shown for my friends unique pizza orders there is a series of interlinked processes.
In the first string of processes we pull ingredients, then assemble the pizza, next cook the pizza then ship to the customer. For processes that are more systematic like the one shown here, we use a measurement called rolled throughput yield.
What is Rolled Throughput Yield?
Rolled throughput yield is a percent that measures the probability that a unit can "roll through" a process without defects. This measure takes into account rework and scrap providing an organization with a more accurate assessment of internal waste and the cumulative effects of poor quality.
Why use RTY?
Traditionally yield calculations take place at the final step of a process. The thought is that rolled throughput yield measures the effectiveness of the overall process. Here is an example, Let's say we were evaluating my friends unique order pizza's. In our batch of pizza's we had 50 to start with, and out of those first 50 our first process step provided a yield of 78%. Our second process steps yield was 98% and our third was 93%. Finally we are ready to ship to the customer which gave us a throughput yield of 90% in our 4'th process step. When we calculate our RTY we see that the probability of a unit passing through the entire process defect free is 64%.
Now had we used a more traditional method of calculating our yield we would have a final yield percentage of 90%. While the numbers certainly look great, they are not accurate. The reality is that using the wrong yield measurement will hide inefficiencies by placing a mask over the waste in the process. These "hidden wastes" are often referred to as the "hidden factory." Rework and scrap both eat up time, resources and capital. The worst part about it is that you're left wondering why do I have 90% yield but my efficiency is terrible? The first way to begin dealing with these hidden factory measurements is to make them visible. Using Rolled throughput yield makes these hidden factory metrics much more visible and takes into account rework that might be performed at each process step. It will also expose the cumulative effects that poor quality has on a unit's probability of being produced defect free.
How to use RTY
Assuming our same pizza baker had measured his yield with the rolled throughput yield, we then would be able to quantify the cumulative effects of inefficiencies found in our pizza making process. This is done by figuring the FTY for each process step and multiplying the numbers. Let's give it a try. You can download the excel sheet here and follow along. Today our worker is required to bake 100 pizza's.
1. So in process step 1 we input or pull ingredients for 100 pizza's. The output again yields only 90 pizza's good giving us 10 "scrapped" or in our case that can not be made and 5 needing rework.
2. Now we have 90 pizza's going into process number two. However, when we look at the output we see there is again 10 scrapped and 7 needing rework.
3. By the third process step we input all 80 remaining pizza's. Our output shows us that 5 more pizza's will need to be scrapped and only 3 can be reworked.
At this point our rolled throughput yield is 62%, which is much different than the 90% yield we would have seen had we used the traditional yield method.
4. In our final process step of delivery we send off or "input" of 75 pizza's but 5 need to be scrapped and 10 can be reworked.
So why did we end up with 95% yield on our traditional calculation and 50% on our rolled throughput yield? Looking back on my friends pizza shop we can see that much of the factory was hidden. Probably not because anyone intentionally hid the amount of scrap and rework going on but simply because calculating yield alone only takes into consideration what goes in and what comes out. That would mean that if 100 pizza's went into the process and 100 came out you would have 100% yield. But what if 40 pizza's needed rework, is it still 100% yield? Hopefully not. Using RTY exposes those wasteful activities. The other benefit to using a rolled throughput measure vs. a first time yield measure is that first time yield measures what goes into a process step against the number of good parts produced, but it does not provide a cumulative view of the effects on an entire process series.
When it was all said and done at the pizza shop many opportunities were discovered simply by changing the way yield was measured. At the end of the day our improvement opportunities are only as good as the measures we use, but no measure will ever be as good as a "true measure."
DPU, DPMO, DPO and DOE. Sometimes it's hard to keep track of six sigma acronyms which makes it even harder to remember what the heck they do. DPMO is the acronym for defects per million opportunities. So, why do we need to know that. Well roughly because six sigma is in large part based on 3.4 defects per million opportunities or 3.4 DPMO. That's right, in order to reach a six sigma rating a company must have no more than 3.4 defects per million opportunities or 99.9997% yield. To put it simply DPMO is the average or ratio of the number of defects in one million opportunities. Lets first understand an important concept before moving forward.
Defect and Defective
We want to be sure that defect and defective are not confused before diving into DPMO. If a part is said to be defective it may have more than one defect associated with it. For example we may have one defective shirt but the shirt may have a rip in it, a loose button and a stain. That means our one defective shirt has three defects associated with it. When we calculate DPMO we use the number of defects to figure our calculation.
How is it calculated?
The easiest way to calculate DPMO is to multiply DPO by 1,000,000 which will then give you your DPMO. As a reminder for calculating DPO visit our recent post in Listen to the Gemba titled Calculating Defects Per Opportunity (DPO).
Pretty easy right. In short DPMO is the measure used to gauge business process performance. By calculating and monitoring DPMO you will have a better understanding of how to improve processes.
Choosing between DPU and DPO can be a bit tricky but as a general rule of thumb DPU is usually used when there is only one performance measurement available. DPO is used when there are more than one available. So how exactly do we calculate DPO? These few steps will help you in obtaining your defects per opportunity measurement.
Step 1 - Assuming you have your total number of measurements or sample batch or lot size figured out already, you will need to gather your team together and brainstorm a list of potential defects that customers might be concerned with. There is not much risk involved in this step but be cautious that you do not repeat "opportunities" as it could skew your data.
Step 2 - Once you have all the opportunities the team can come up with you need to calculate the total number of defect opportunities. This is done by multiplying the number of units in your sample lot or batch by the number of opportunities the team came up with.
Step 3 - Divide the total number of defects in the sample lot or batch by the total opportunities for defects, which was the answer you came up with in step 2. This will give you your DPO.
This number can now be used to calculate your Defects per million opportunities.
The Alarm Clock goes off, you hit the snooze button and go back to sleep for a little bit, then it goes off 5 minutes later and you realize, "Oh my goodness, I'm Late!" So you start to rush panicking that you might show up late for the "big meeting." Finally you arrive at the office, jump out of your car and reach for your briefcase, your briefcase? Oh no, you've forgotten your briefcase. Well hopefully this wasn't the start of anybody's morning but to be quite honest it happens all the time in Kaizen Events, Projects or daily work activities. Nobody Keeps Takt of the time.
Takt time is the rate at which we need to complete our work, but most importantly it is the rate in which we need to complete our work according to the Customers demand and there needs. In essence Takt time can be compared to the way a heartbeats; the heart keeps pace or beat in order to provide our body with the necessary blood and oxygen it needs. What happens when it falls off pace? You get light headed, miss a step or worse yet come to a complete stop. Just like our body falling out of beat if we have no Takt time or precise interval of time it becomes much harder to tell when something is not operating at quite the rate it needs to be. Here are a few simple tips for Calculating and using Takt time to your advantage.
1. Assess where you are at
It goes without saying but if you are doing work there is a time figure you can use to assess the current situation. You may be able to pull data from your ERP/MRP system or take the Gemba approach; Grab your stopwatch set up an excel sheet and start gathering some times (cycle, process, lead). Be sure that the data you gather is in alignment with your objective.
2. Where is it you need to be?
This is the exciting point where we ask ourselves at what rate does our Heart need to beat in order for the customer to continue circulating a healthy amount of blood into the organization? Let's start with how we figure out the Takt Time. You will want to find out exactly what the customer demand is Per day (internal or external) and you will need to define how much "available time" there is in the work day (i.e. 1 shift 8 hours, 2 shifts 16). Once you have these two pieces of Information you can now figure the Takt time.
Let's look at an example of How we can figure Takt. Let's Say Our Customer wanted 100 pieces per day(keep in mind the pieces don't have to be actual materials they may be services or activities that are not so tangible) and our shift was exactly 8 hours or 480 minutes with no downtime and no breaks or lunches (breaks, lunches and downtime should be figured into your available time if you have them, and we hope you do) that would mean that each piece needs to be made in 4.8 minutes to keep up with the customer demand.
3. If there is a Gap identify it If not Support it
Now you can probably tell it would be very clear if we were meeting takt time or not (compare current as is situation to the Takt time). If you are not meeting the Takt time we suggest Identifying the Gap and any of the Contributing issues so that you can make a plan in order to reach the Takt time. As with anything else set your team up to win try to give them goals they can meet and inch your way to meeting the Takt time. If there is no Gap continue to support the crew's efforts and reward their hard work and labor.
4. Post It
Once you have defined the rate at which you need to complete activities, it will be to your advantage to make everyone aware of the Takt time, You can post it on Huddle boards attach it to a meter or any other way you want, the point is make it Visual. The purpose of making the Takt time Visual is that you can remove barriers as they pop up, remember we are here to "Support" the team in accomplishing their goal not monitor, spy, or tattle on one another. One way you can do this is by observing when the activity has fallen off pace, you can then identify the contributing issues and remove the Root Causes.
Not having a Takt time can cause you to be late for work, forget items in the hurry to make up time or place unnecessary burdens on individuals. Though it may not be quite as obvious to you if you are not involved in the activity, having a Takt time established will allow you to identify abnormalities and see lines or processes that may be out of balance. Just like any other Origin of Waste once we identify those abnormalities we remove them. Well you all better get back to work; If you need any support in keeping Takt of time feel free to email email@example.com, we would be happy to support. Let's make this week the week where you establish and keep Takt of at least one of your times. We would love to hear about your experience in doing it.