Be cautious when there’s some, be cautious when there’s none, and be cautious when adding more than one.
What do the heck does that mean???
Let’s take these correlation cautions one by one.
Be cautious when there’s some. Suppose you did a study and found a correlation between job performance and high school grades. Does this mean that if we simply increase everyone’s high school grades that they will perform better at work??? Clearly not!
Every part every interval (EPEI) is my favorite lean metric for high mix/low volume (HMLV) value streams and probably the least known. It’s especially helpful when changeovers are a significant portion of capacity as frequently is the case with machine-oriented operations.
As some of you may recall, I launched a new blog called Lean Math back in February with a couple of my buddies. In my humble opinion, I think that the ever-growing content is pretty useful stuff for lean practitioners.
In any event, I just wanted to share some basic holiday lean math...
On behalf of Michael O'Connor, Larry Loucka, and myself, I would like to thank you for investing your valuable time this year reading our posts and sometimes sharing your thoughts. We truly appreciate your readership and we hope that we have, in some way, provided assistance in your lean journey.
In that spirit, some basic holiday lean math follows...
PEACE ON EARTH + GOODWILL = HAPPY HOLIDAYS
We are coming to the end of the year so it is a good time to reflect on where we have been and start thinking about next year. And to make the thinking definite, let’s suppose that you estimate that 85% of your customers will stick with you next year and 10% of your competitor’s customers will switch and become your customers. Is it time to open the champagne and give everyone a big holiday bonus???
And just to make the math easy, let’s just suppose that you presently have 1000 customers and your competitors have a total of 1000 customers as well.
Heijunka, also known as level-loading, production-leveling or production-smoothing, is a foundational element of the Toyota Production System. It facilitates system stability by addressing workload unevenness (mura) through the leveling of both volume and mix over time, see Figure 1. Heijunka also serves as a pacing mechanism for operations, often reflected in the use of heijunka, leveling, or schedule boxes, which are typically designed using pitch intervals, see separate pitch post.
OK, I know that what I’m about to say may sound cynical, but 20 years of personal, hard knock lean experience tells me that this is reality. And most folks I think would, or at least should (I hope), agree with me. The majority of companies pursuing a lean implementation do so superficially. (Did I just hear you yawn?!) Many fail to understand the transformational lean principles, much less have the will to rigorously live them.
Accurately determining the appropriate stocking levels of perishable items is very important. Stock too few items and you will have disappointed customers. Stock too many and you’ll have unsold product - which has a high probability of turning into a loss.
A number of industries face this dilemma each and every day.
The WIP-to-SWIP ratio is a simple comparison of a process, line or cell’s actual work-in-process count versus its standard work-in-process inventory (SWIP). Among other things, a process’ target condition reflects the consistent execution of standardized work, including SWIP maintenance (which is why it should be a leader standard work audit point). No SWIP maintenance, no standardized work adherence. Accordingly, the target WIP-to-SWIP ratio is 1.
Weighted average cycle time (Tcwa), also known as “average weighted cycle time,” provides a representative average cycle time (Tc) within a mixed model environment. Varied models or services in a given cell, line or work area often have varied work contents due to different steps, duration of steps, sequence of steps, etc. Accordingly, the Tc‘s vary.
