Productivity is defined as bringing you closer to your goal. Every action that brings you closer to your goal is productive. Every action that does not bring you closer is not productive, even if it seems so.
The Goal of every business is to make money. Likewise, activities that do not bring you closer to making money are not productive.
Organizations can be measured by 3 metrics: Throughput, Inventory, and Operational Expense.
Ideally, your activities improve all three at once.
The bottleneck of the system determines the throughput of the entire system.
Increase capacity at the bottleneck through a variety of interventions.
The non-bottlenecks should be synchronized with the bottleneck, which means idling at non-bottlenecks is acceptable. If both the bottleneck and non-bottleneck go full steam ahead, the non-bottleneck will produce surplus inventory, which adds cost and causes traffic jams.
To coordinate this, use Drum-Buffer-Rope
The Goal is a classic management text, and on Jeff Bezos’s short-list of books recommended to new managers.
The Goal is written in the form of an allegory, where a manufacturing plant manager has to reduce a large backlog of orders and improve factory throughput. Its management lessons are interwoven with the manager’s epiphanies. Because we felt the lessons were more important than the narrative, we’ve focused on the teachings and theory, and we’ve summarized the narrative in a chapter at the end.
What can you apply the lessons in this book to? It’s an easy leap to apply The Goal to manufacturing, operations, supply chain, and automation problems.
It takes a bit more thinking to apply it to knowledge work, larger projects, or your personal life, but the principles are generalizable. To really get the most out of this The Goal book summary, think constantly about how you can apply it to your own situation - whether that’s closing sales clients, creating software products, managing a team, or writing books.
Take the advice of Ray Dalio in Principles: view yourself top-down as a machine, digesting inputs and creating outputs. From this perspective, you’ll be capable of studying and optimizing yourself.
Productivity is bringing a company closer to its goal.
Defining the Goal is critical. The Goal of every business is to make money. Without money, the company is dead.
If you improve efficiency at one step without increasing overall output, you are not being more productive. You might even be causing an excess inventory and increasing cost per good sold.
What is the minimum number of measurements you need to know if you’re making money?
How do you convert these highest-level metrics to ones that are more actionable day-to-day?
If you make a subpart more efficient, you do not raise your competitive advantage if it does not increase output or reduce cost.
Says the mentor in The Goal: “A plant in which everyone is working all the time is very inefficient.” There must be a bottleneck along the chain; idling the rest of the chain prevents inventory from piling up.
Make sure you’re focusing on the right output and not just wasting time.
What is your big Goal? What is the ultimate purpose of your work?
What is the minimum number of measurements to know if you’re hitting your Goal?
What activities do you do each day that drive you toward your Goal? List the most important ones.
In manufacturing, a balanced plant tries to match average capacity of every resource exactly with market demand. Any resource beyond the average rate is seen as extraneous, so it is either put to use or eliminated. This is the traditional mode of thinking at the protagonist’s company in The Goal.
However, two interconnected concepts make the balanced plant backfire, thus decreasing throughput, increasing inventory, and increasing carrying costs:
Fluctuations happen regularly at each part in the chain. However, each downstream part can only catch up to the extent that the upstream part permits it to. Negative fluctuations bring down every later step of the chain; positive fluctuations are constrained by the next bottleneck. Over time, this causes a lower than expected average throughput.
As explained in the next sections, the solution is not to balance average capacity with demand, but rather to balance flow or throughput with demand. The way to do this is a drum-buffer-rope system, where the bottleneck determines the throughput and inventory of the entire system.
We’ll explain all of this with an analogy.
Imagine a troop of 10 boys hiking single-file on a narrow trail in the woods. The leader of the pack sets a comfortable pace that everyone on average should be able to meet.
Every boy is only able to catch up to the boy in front - he can’t pass the boy in front. Thus, the speed of each boy is constrained by the boy in front.
Analogy to manufacturing: the first boy is the most upstream step; the last boy measures throughput; the distance in between is inventory.
Here’s an example of a negative fluctuation
Let’s say to relieve these pesky dependencies, you order all the boys in speed, with fastest leading the pack. All boys can now move unconstrained and operate at their individual peak efficiencies. However, the distance between the first boy and the last boy will incrementally grow, unbounded.
To solve this accumulating gap, let’s try a new solution: order the boys with slowest first and holding up the line for all other boys. On the surface, this seems very inefficient - the other boys are nowhere near their peak efficiency, and they’re all running into the next boy.
However, there are a few key advantages:
This wonderful analogy should make clear the flaws of defining the average of all steps, without regard to the overall throughput and the bottleneck steps. In the next chapters, we’ll discuss how to identify the bottleneck and improve it.
The critical concept in the book is identifying the bottleneck, or the key constraint that holds back throughput. While this sounds like common sense, it can be hard to objectively identify your own bottlenecks when you’re in the thick of work.
Relationships between a bottleneck (X) and non-bottleneck (Y) can be summarized in the following 4 diagrams:
Y → X
X → Y
X → Assembly ← Y
X → Product A | Y → Product B
In all these blocks, Y never determines throughput for the system. Throughput instead is determined by bottleneck X, or market demand.
Any time that the bottleneck isn’t working is lost time forever that cannot be made up at any other part in the system.
An hour lost at the bottleneck causes a loss in total throughput equal to the hourly capacity of that bottleneck. This is an important concept.
In other words, a loss in the bottleneck means a loss to the entire operation, and should be viewed with such gravity
Other losses in effective throughput are also similarly costly. For example, feeding low-quality parts through the bottleneck will cause rejection later, leading to effectively lower throughput.
While time lost from the bottleneck can be made up for by hurrying non-bottlenecks, any extra effort here typically adds to operational expense (eg overtime pay). Ideally, the bottleneck is simply maintained at peak capacity at all times.
The bottleneck is any resource whose capacity is equal to or less than the demand placed on it. Here are a few ways to find it.
Identify the bottleneck by seeing where you have the greatest upstream inventory piling up, and low inventory at the next step. If the non-bottlenecks are producing at equal rates (eg 100 parts/hour), the slowest step will have the largest upstream inventory.
Alternatively, see which downstream steps are most in demand of upstream parts and are idling. If you decrease inventory sizes, you will see which work center, if stopped, halts the whole line.
Alternatively, in a more brute-force comprehensive way, define your market demand (by sales), then compare the productivity of each step of the chain to this demand.
Find the bottleneck that’s decreasing your total throughput.
In what step do you have the greatest inventory piling up in front? Where is your largest backlog?
What you defined above is your bottleneck, and every other step is not a bottleneck. What are other steps you thought were important to optimize, but actually aren’t bottlenecks?
What is the cost of your bottleneck per hour? Remember, this is the loss in throughput of the entire system per hour.
Now that we know the bottleneck is hugely significant, we’ll learn how to improve the bottleneck’s capacity.
In The Goal, Goldratt describes the 5-step process for continuous improvement:
We’ve discussed identification in the previous chapter. We’ll now dive more deeply into improvement.
The protagonist of The Goal book undergoes multiple iterations of increasing capacity as his bottleneck to increase overall throughput. Without detailing every struggle, in this book summary we’ll cover common causes of reduced capacity at bottlenecks, and fixes to increase capacity.
(Shortform note: This is a good point to consider your own work or life in this context, and to construct effective ways to relieve your personal bottlenecks.)
We can divide this into a few themes.
Improve the Bottleneck Itself
Improve What the Bottleneck is Working On
Optimize the System for the Bottleneck
(Shortform suggestion: take some time to consider how to apply these to your own life. For example, say you’re a manager who wants to improve your throughput. Consider the above fixes directly applied to a manager, whose time can often be the bottleneck of an organization’s throughput:
Ideally, the flow through the bottleneck should match market demand. Producing more than this will increase inventory of finished product. Too much inventory will hinder flexibility through sunk cost fallacy - you’ll be reluctant to adapt to new market demands, because it would mean writing down your old inventory.
Instead, when you have surplus capacity, try to increase sales to make use of this capacity. Because you’re already paying for the fixed costs, you can lower prices to above material (marginal) cost to simulate more demand. This will decrease your overall cost per product.
If you do your work right, you’ll find that the constraint is no longer holding up the system, and the constraint has moved somewhere else. Here are a few tips on how to deal with this.
Different constraints can require very different optimizations. Don’t assume that what you applied to the first constraint can solve any other constraint.
Don’t overcorrect for the constraint you just fixed. Overcorrection can be counterproductive. If you obsess about preventing the bottleneck from idling and exceed market demand, you’ll produce surplus inventory.
While The Goal is literally concerned with manufacturing, its principles are generalizable to any work system in which multiple parts contribute to a single goal.
Consider asking yourself these questions:
Are you refusing profitable work because you don’t have enough throughput? If so, find your bottleneck and alleviate it.
How can you cut batch size to increase efficiency?
Where is the weakest link in your chain?
Are you currently the bottleneck for any throughput? How can you tell?
Try to increase capacity at your bottleneck. This might not be a machine in an assembly line, but also your knowledge work or personal life.
How could you improve work at the bottleneck itself? (Remember: skip unnecessary steps; add supplements to increase capacity; increase time the bottleneck is active.)
How could you improve what the bottleneck works on? (Remember: focus the bottleneck only on critical parts needed today; allow parts to skip the bottleneck; add analytics to study bottleneck operations.)
How could you optimize the system for the bottleneck? (Remember: ensure excess inventory in front of the bottleneck to prevent idling; redistribute load to non-bottlenecks; outsource the bottleneck work.)
Once you identify the bottleneck and improve its capacity, you may find other problems arising that decrease throughput. In the narrative, the team goes through multiple iterations of solving problems, yielding the below principles.
In the story, the team identifies a robot as the bottleneck. They devise a system whereby all parts destined for the bottleneck are always worked on at highest priority at non-bottleneck steps. This increases throughput temporarily, until they discover that at final assembly, suddenly there are shortages in non-bottleneck parts while there is massive inventory upstream of the bottleneck. How could this be?
They discover that they were running non-bottlenecks at full-speed and cranking out bottleneck parts far in excess of what the bottleneck could process. In turn, the non-bottlenecks had insufficient capacity to produce their non-bottleneck parts.
To avoid this, you must synchronize the non-bottlenecks with the bottleneck, to prevent massive deviations. Goldratt proposed the Drum-Buffer-Rope method, as follows:
The bottleneck dictates the pace of production of non-bottlenecks.
Analogy: the slow boy scout beats a drum, and others take steps with the drum beat. If the boy scout beats more slowly, everyone else steps more slowly.
Similarly, a machine may regularly report its production rate, and the non-bottlenecks adjust their own rates up and down accordingly.
Release starting materials to the non-bottlenecks strictly at the drumbeat rate.
The bottleneck should have surplus inventory upstream so it doesn’t idle.
Analogy: non-bottleneck boys can scout ahead, clear brush so the bottleneck boy can keep walking at normal pace without having to stop.
This buffer allows for “good enough” scheduling rather than needing to be perfectly accurate.
Goldratt suggests choosing a time buffer equal to half the current lead time, then decreasing or increasing as deadlines or hit or missed.
When non-bottlenecks exceed a certain surplus level, they idle.
Analogy: tie a rope between the boy in the front and the bottleneck boy, and limit the maximum distance between the two.
Similarly, prevent work-in-process inventory from exceeding a threshold level.
In addition, production requires prioritization - complicated chains require more parts to be worked on in the correct order to avoid queue times. As a simple heuristic, prioritize batches by time elapsed since its release - the longer parts have been waiting, the higher the priority they get worked on.
Each piece of material spends time from when it enters a plant to when it leaves:
All types of time add cost to the system and lower throughput.
For parts going through bottlenecks, queue time is dominant. For non-bottlenecks, wait time is dominant.
Traditionally, larger batch sizes are seen as more efficient per part. However, this decreases agility and increases inventory.
Imagine cutting batch sizes in half, and the benefits that result:
But wait - won’t cutting batch sizes increase setup time at non-bottlenecks? This isn’t really an issue. Remember, an hour saved at a non-bottleneck is a mirage. Reducing an hour at a non-bottleneck doesn’t increase throughput, because the bottleneck determines throughput.
(For what it’s worth, cutting batch sizes also decreases idle time, since non-bottlenecks are kept busier rather than waiting for the big batch upstream.)
When you increase capacity at the bottleneck, you may start seeing shortages in non-bottleneck parts that hold up other parts of the chain.
While by reflex you might think this is a new genuine bottleneck, be wary - often production has so much extra capacity that it takes a huge increase in throughput before this really happens.
For example, in the plot of the The Goal, a non-bottleneck is producing two parts - part Y that goes through a non-bottleneck chain, and part X that goes through a bottleneck. If you focus the non-bottleneck entirely on part X, then you create a scarcity of the non-bottleneck parts Y - which creates an artificial bottleneck.
Instead, ideally you synchronize all parts that run through all chains so that the right number of parts reach the last step at the same time to meet market demand (with some buffer).
Similarly, taking on more orders may reduce spare capacity on non-bottlenecks, depleting inventory in front of the bottleneck and starving it of work.
As the protagonist of the narrative finds, productive practices can lead to virtuous cycles and increased competitiveness.
By adopting lean manufacturing principles like bottleneck alleviation, small batches, and Drum-Buffer-Rope systems, a cascading series of benefits happens:
In contrast, Goldratt points out how poor practices can lead to aggravating policies that cause further problems. Focusing on cost-accounting and local efficiencies:
Measurements like financial accounting should induce the organization to do what’s good for itself. But as you improve throughput, traditional accounting measures may make your situation look worse than it really is.
Examples:
However, these are usually temporary adjustments. Remember, what really matters is the total throughput of the system - increase that, and you’ll be able to make more sales. Over time you’ll enjoy lower inventory costs and faster lead times, which improve topline sales. The financials will look healthier in the long-term.
The manager’s job is to answer three questions: “what to change?” “what to change to?” “How to cause the change?”
Don’t delude yourself into believing the problem doesn’t exist. Management speak can disguise real problems and goals. Why do people use it?
If you successfully improve the bottleneck and increase capacity beyond market demand, a natural reaction of managers is to downsize the capacity. This punishes the workers who just helped the company improve, and makes the organization resist future improvement. Instead, to make better use of the now-increased capacity, encourage more sales to use the improved performance.
Collecting too much information without identifying the underlying intrinsic order leads to false patterns and bad decision making.
Before the periodic table, it was unclear how one should understand the chemical elements. By color? State of matter? Instead, Mendeleev organized the elements first by atomic weight, then by reactivity (eg sodium and potassium behave similarly when thrown in water). This even allowed prediction of elements that didn’t yet exist.
To find the underlying intrinsic order, start from simpler If-Then principles. Only then can you question, “if this is true, what can I predict to be true?” Then test these predictions and continue testing the hypothesis. (Shortform note: This section felt a bit shoehorned in by Goldratt as a pedagogical item.)
As an allegory, The Goal is explication of a philosophy with a fictional novel wrapper.
This has various effects beyond pure entertainment value. Portraying the protagonist’s struggle makes you empathize and absorb the teachings better. Unlikable characters stereotype critics of the philosophy (like Eddie, who doesn’t ever question the traditional way of doing things). Overcoming the struggle paints a vivid picture of how the strategy can work.
However, at times the dialogue and epiphanies in The Goal book can feel forced, and the conversations don’t sound natural.
Thus, we consider the plot to be a minor portion of the value of the book. Here’s the summary, for context:
Alex Rogo is a beleaguered plant manager in a small manufacturing town. They’re in a bad situation: large backlog of orders, all orders are late unless expedited.
Company policies are to blame. The division’s goal has been to increase cost efficiencies, so they focus on local efficiencies of production (like the fallacy, “we have to keep the robots running at all times or else the cost per part will go up and we’ll never make back the cost.”). Large inventories accumulate, and they add robots without increasing sales.
Their entire division has 3 months to improve performance or it’ll be sold.
He talks to his old physics professor Jonah throughout all this. Jonah feeds him insight piecemeal, and Alex uses it to solve each problem, only for another to appear.
Alex ponders the problem. Why didn’t adding robots increase throughput? Humbled, Alex is prompted to find the bottleneck of the plant.
On a boy scout hike, Alex realizes the fallacy of the balanced plant and how to identify and resolve bottlenecks.
At the plant, they identify two bottlenecks - the new robotic machine, and heat treatment.
But after identifying bottlenecks, it’s not clear how to increase capacity. They realize the bottleneck machine is idling at times because of union rules; also, the heat treatment inefficiently runs small loads.
They reorder the work queue so that the bottleneck is working only on the oldest unshipped orders. They clear the idle time with the union rep.
They run into an issue where the bottleneck doesn’t have upstream parts available. They learn the non-bottlenecks are working on non-bottleneck parts. They put red tags on bottleneck parts so that those always get highest priority.
They start filling their backlog and reduce their lead time. But it’s not enough to clear the backlog entirely.
New bottlenecks seem to emerge. It turns out they’re releasing too much upstream material and focusing on producing red bottleneck parts only, leading to a deficit of green non-bottleneck parts.
They reduce batch sizes, which decreases their lead times. Sales increase as reputation grows.
Alex’s plant gets a 1000-unit million-dollar order to be delivered within two weeks. They initially consider it impossible, but they cut batch sizes again and offer to ship the 1000 units in 4 weekly shipments, starting 2 weeks from then. They make this happen.
Alex’s boss gets promoted to headquarters, and Alex becomes division manager. He gets tasked with finding out how to become a manager. He realizes he needs to learn to figure out problems for himself, rather than consulting Jonah.
Throughout all of this, there is a secondary storyline with Alex Rogo going through marital turmoil with his homemaker wife. The stress over losing the factory makes him miss dinner dates, they communicate poorly, and his wife leaves for her parents. Over time they reunite as Alex turns his factory around and gains clarity.