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The first part of this article requires a little imagination.
Imagine a stream of water in a meadow. The water starts in the hills above the meadow, slowly flowing from a small lake out of sight. The stream is not large, only about a foot wide between three- to four-foot-wide banks as it passes through the meadow.
How would you describe the flow of the stream? Peaceful? Slow? Perhaps relaxed?
Now imagine that same stream in a raging thunderstorm, the kind that throws down more than an inch of rain in an hour. Imagine there is so much water from the rain that the stream is full from bank to bank, some water spilling out in some of the lower spots. How would you describe the flow? Angry? Raging? Chaotic?
What changed in the stream that caused our our descriptions of the flow to change?
Volume. Falling rain collected and increased the volume of water in our stream. Some places in the stream are narrower than others, restricting the velocity of the water, creating backups that increase the pressure of the water in the narrow spaces, making the water move faster through the restriction.
In those narrow places, the water moves with more turbulence, scouring away at the dirt and rocks that form the bottom and sides of the stream, eroding the banks. If the restriction is soft enough, the higher water pressure and turbulence erodes the restriction. As the water erodes the restriction, its velocity slows and the turbulence abates. Eventually, the stream erodes the restriction away.
Imagine the wide sections of the stream. The banks are wide-set in this section, so that as the volume grows, the water gets higher, but meets with little resistance. There may be little eddies of turbulence, but the water flows with nowhere near as much velocity or point pressure as it does in the narrows.
Now, imagine we put a little dam in that stream. Not a big dam, just something that holds back the water a little. In the storm, the water does not back up; it just flows over the dam, which acts as nothing more than a speed bump. After the storm passes, the volume of water drops, and at some point the overflow becomes only a trickle.
What does the dam do? It restricts the flow of water, capturing the water until it overflows the area behind the dam. The overflow may go over the top of the dam, or it may find a different low point, creating a different path to follow. Hundreds, thousands of variations in terrain, wind, rainfall, ground cover; all will affect the flow of water.
Water always seeks a way to go lower, pulled by the never-ending power of gravity. It goes not only downhill, but through the bottoms of the lakes and streams, soaking into the ground to nourish the plants and trees that grow along them. In some cases, the water makes it to underground aquifers in porous stone and sand, 0r into caves that have been carved out of limestone over millions of years.
Have you noticed that information has a flow? Like water, there are many factors influencing the flow of information. This flow depends on the structure and culture of the organization, and the proximity of leadership to operations. Then thousands of smaller variables can influence the flow in small but sometimes critical ways.
Unlike water, which gravity pulls in just one direction, information flows across a network of people, each of whom has gravity and pulls information out of a deluge of data that flows by.
Notice the difference between data and information. Data is just some number measuring something. Information is data that answers the questions I am asking.
Imagine the flow of knowledge available in a large concentration of people, like a corporate office. Now think of the information flow in a smaller regional office. Which office do you think has a tighter flow of information, the kind of flow that changes direction in the operations?
Who is going to have better information? Remember, data is only information when it answers the questions we ask. Imagine that the data systems are a stream, and each office pans the stream for the gold nuggets of information they are seeking. Knowing how to find the nuggets is the trick.
These offices communicate as entities and as people. Sales, production, order, and inventory management data flow up to corporate through machines. People talk on the phone or use e-mail to transmit operations and management instructions, status, and hundreds of other factors that influence the flow of information. If you look closely at the operations, there are direct channels of influence between the central office and the field offices, channels between the clerks and managers who execute the work.
There are restrictions in the flow of information. Just as hard rock mountains influence the flow of a river, there are walls and floors in any data structure. Water erodes barriers with natural friction. In an organization, people are restrictions. As the information flows, it changes.
Imagine how water tastes as it comes out of a glacial stream. How does it taste?
Now imagine you are inside of a drop of glacial water. The water off that glacier flows down through the mountains, picking up minerals and animals on the way down. Other streams of water flow into this one, and this stream, no longer a stream but a river, flows into an even bigger river. What is the chance that you are still in a drop of pure glacial water?
Above, I asked a question about the chance that a drop of pure glacial water could flow in a river. Moving thousands of miles after dropping off the end of a glacier, that drop of water is just as saturated with pollutants as every other drop of water in that river.
Making my point clear, like the drop of water that picks up various compounds along its journey, information changes in the course of its journey with each exchange from person to person. Sometimes the change is good, sometimes it is benign, and sometimes it is bad. While data flows along wires and in reports, data does not provide an answer, only an opportunity for an answer. Information changes as it moves from person to person, each exchange altering the information slightly.
I was working on a challenging project. The deadline was just three weeks away, but there was about six weeks of work to do to finish. I came in late in the game.
There was a lot of bad flow on this project. Good information about many aspects of the project just did not flow. Leaders and managers made hasty decisions about changes to the plan, and then faced the unintended consequences of their actions. Each move focused on the consequences of the previous move, creating only more unintended consequences.
This behavior, a bout of “Whack-a-Mole”, is the “Fixes That Fail” Archetype, (see Fixes that Fail – System Archetype 9 ). If an operation or a project is heading for disaster, the organization falls into a systematic loop, making repairs that only lead to more repairs. An overly complex system or a set of overly complex business rules can bring about the "Fixes That Fail" loop.
On a DC start-up project that went awry, we examined the order fulfillment process to figure out where the bottleneck was. We found an overly complicated process that held orders in staging until someone inspected the order. Inspection triggered the clerical staff to print customer custom bar code/UPC labels. Next, the order moved to label tables, where people peeled the printed labels and stuck them to the product. We did not understand the extra audit at the start of the process. Managers wanted to prevent errors from reaching the label tables.
We did not agree. Our approach focused on the concept of flow. We eliminated the initial audit, flowing the picked orders directly into the staging in front of the label tables. Label printing moved forward in the process, to when the order dropped to the floor, not when we started picking the order.
Preprinting helped picking accuracy. In some cases, an order could pull stock from 12 different zones, each zone requiring different equipment. Order pullers worked in teams of two, one person on an order picker truck, the other on the floor with a picking cart. The split between truck and cart picking depended on the order and the stock locations of the product. The WMS used a floating pick logic; once the pick location is empty, the next pallet, wherever it is, becomes the pick location. An order line for one sku could pull product from several locations.
Discrete orders from multiple zones, custom ticketing, packing, and shipping — not that complex a flow, once we removed the useless steps that failed to add value. Picking errors was the biggest challenge, except that the label tables could call the pickers in to correct errors. While the pickers corrected an error, the label tables worked on labeling other products. The material continued to flow while the team corrected picking errors.
Completed order velocity tripled as we removed the "Fixes that Failed" in the process, stripping out what waste we could. We made no change to the systems or the equipment, only to the process. When we first arrived, the management team thought that picking was the issue. When we changed the labeling process, eliminating the unnecessary inspection, picking, labeling, and packing were no longer the problem. The system constraint moved to shipping.
The "Fixes that Fail" cycle can spin fast. It is normal for cycles to spin out of control quickly. The best way to control them is to slow the process down, creating a time before making the fix to assess the options. This is hard to do when the general contractor, the customer, or the operations group are screaming for you to do something. "Fixes that Fail" always address the symptom of a problem, not the root cause. It takes time and thoughtful effort to figure out what the root cause of a problem is, then more time to fix the root cause.
Back to the challenging project I was working on. I was thinking of the "Fixes that Fail" systems archetype as I watched conveyors move from one installed location to another installed location and then back again. The correct information was available on site, but none of the project managers had access to it. Engineering failed to consider a critical dimension, and in the end, a conveyor line moved four feet so that support legs landed off the platform where they should have gone.
The information just did not flow to the people doing the work.
Water flowing in a stream. Oil flowing through pipelines. Gas flows through pipelines too. We typically use the word "flow" to describe the movement of water or gasses. But what about the flow of a crowd? How about gain flowing from a hopper? Flow is a description of movement, the movement of liquids, a bunch of solid objects, of work, of people, of ideas. If it moves, it can flow.
I like to think of a logistics network as a system of pipes in which the products flow from one connection to the other. Logistics networks are like pipelines, a physical network of pipes, compressors, and tanks that move liquids and gases from production to consumption. With pipelines, the size of the pipes limits the flow, the direction of the pipes limits the flow, the actual pipes used in the line limit the flow. Compressor stations create pressure, pushing the gas or liquid along the pathway. The valves control the direction. Tanks provide holding storage, acting as buffers that allow change in the flow.
In most supply chains, trucks, trains, ships, and planes serve in the role of the pipe in the system. Warehouses are like the storage tanks. Pipelines have central control centers, system control centers, where managers control all pipeline operations from a single point. In most supply chains, the concept of control is much more fluid, not as defined or centralized. Unlike in the pipeline, various people and entities control the “pipes,” i.e., the trucks, trains, ships, and planes. Different companies own these pipes, making strong central control a difficult proposition.
Most supply chains, like pipeline systems, are repetitive. Ships operate on routine, pre-determined schedules, as do planes and many trucking systems. With repetitive networks, we can observe performance in each cycle, measure the performance, and make predictions about future performance. With enough data and time, we can observe the relationships between the different steps and different nodes in the network.
In these routine systems, there are three different flows in the supply chain. The obvious one is the flow of the physical product. There are two other flows, however, each of which exerts considerable influence on the material flow: the information about the material flow, and the flow of the money behind the trade that created the material flow. All three flows are basic requirements of any supply chain system. Without the money, the method of value exchange is missing. Without the information, we can’t control the flow, we can’t monitor the flow, and we can’t protect the physical and monetary flow.
If we look back into the history of global trade, we can see the original foundations of these three flows as broken loops, with each of the flows locked into step with the other two. In early trade, by sea or by long, land-based trade routes, the ship’s captain or the caravan leader took ownership of the cargo, taking title of the cargo and settling with the seller of the goods before loading. The seller signed the cargo over to the captain using a negotiable Bill of Lading (BOL) that gave the captain the title and rights to the cargo. The captain pledged to attempt to deliver the cargo to the consignee, the buyer of the goods, but he could sell the cargo if it became impossible to deliver it.
If the captain arrived at the port of delivery and could not find the consignee, or the consignee rejected the shipment, the captain could sell the cargo to another buyer for whatever price he could negotiate. Even if the original buyer wanted the cargo but could not pay the captain for it, the captain could sell the cargo to another buyer.
In that era of trade, the value, the information, and the material changed hands simultaneously and traveled together. This tightly integrated movement of cargo, information, and finance ensured that each trading partner received their value for the shipment.
The Bill of Lading defined the cargo — the terms of transit, the origin, destination, description, who shipped the cargo, who received the cargo, who carried the cargo, and the cost of the transit. Every shipment carried a Bill of Lading. The ship’s captain maintained a manifest that listed all the cargo carried on the ship by Bill of Lading number, and summarized the weight, value, and number of articles of cargo on board. The ship’s manifest was the captain’s inventory ledger.
It would take centuries of change in developing trade practice built on trust initiatives for the three flows to decouple.
Banking practice and technology helped to decouple the lockstep timing of the three flows.
Money was the first place the flow started to decouple. A Letter of Credit (LOC), is a contract between banks, pledging that the seller will receive payment as long as the trading partners meet the terms and conditions of the letter. The buyer establishes credit with a merchant bank with connections to other merchant banks in the seller’s area. The buyer’s bank documents in the letter that the buyer has established the credit, and pledges to pay the bank redeeming the LOC, subject to proper documentation.
Let’s assume we are buying 100 sheep from an Australian rancher. We go to our commercial bank and establish credit, mainly through a deposit of funds and some pledge of credit. The bank identifies its partner bank in Australia and drafts a letter that outlines our establishment of credit. The letter defines the conditions that the person presenting the letter of credit must satisfy to receive payment. In most cases, the letter will outline documents that the seller must present to the bank to satisfy. The conditions can vary, but may include the submission of an invoice that documents the monetary value of the transaction, a delivery receipt documenting that the shipper loaded the cargo, and the particular quantity of the goods.
In our example, the LOC could state that the bank will pay the credit once presented with a proper BOL for the loading of 100 sheep onto a named ship, or delivered to a named location for loading. The remote bank collects all the documents and forwards them to the bank that issued the LOC. Once presented with the LOC and the documents that satisfy the LOC, the issuing bank pays the remote bank.
Letters of Credit obviated the need for the ship’s captain to take financial responsibility for the cargo. Letters of Credit opened the door for other forms of maritime financial process, like cargo insurance. Ship owners and masters, the captains, no longer accepted open risk of loss because they did not take financial responsibility for the cargo. The bank’s Letter of Credit lifted that financial responsibility. In most cases, the buyers accept the risk of loss, risking the monetary value of the cargo if it is damaged or lost, or buying insurance to cover the risk of the loss.
Cargo insurance grew with the growth of Letters of Credit. Over coffee at Lloyd’s Coffee House in London, investors calculated the risk of the shipment, and for a fraction of the value of the shipment, ensured the safe delivery of the cargo. The captain’s history, the nature of the cargo, the destination, the trade route, and the weather on the route all influenced the risk and the price of the insurance.
Distributed credit and insurance helped decouple the financial flow from a direct relationship to the flow of the goods. Under the letter of credit, the flow of the money depended on the flow of documents, not the direct flow of the goods. The cargo could continue to move, while the documents that validated the physical flow triggered the flow of the money. Without this decoupling, modern trade on the scale we are accustomed to could not exist.