We encounter frequent symptoms with our supply chains. One reason is our supply chains are large in scope. Supply chains start from the source (e.g. mining of raw materials, harvest of agricultural crops), pass through a multitude of activities that supposedly add value (e.g., procurement, storage, manufacturing, handling, dispatch, transport), and end with our target markets of many users and consumers.
The symptoms we encounter with supply chains happen enough times to keep us busy and preoccupied. These include:
- Delayed deliveries of materials from vendors
- Customers complaining about product quality
- Customers rejecting products delivered
- Unscheduled shutdowns of production lines
- Delivery trucks not showing up as scheduled
- People not showing up for work
- Pilferages
- Losses
- Equipment breakdowns
- Items out of stock
- Service provider asking for higher freight rates
- Sales & marketing asking why their new products aren’t delivered yet
- Finance managers insisting we lower inventories today
We spend a lot of time addressing symptoms. We do a lot of quick fixes. We stock up (or draw down) inventories, we hire (or fire) staff, and we buy from multiple vendors rather than relying on just one.
We attempt to permanently prevent symptoms via investments in automation & sophisticated information software (e.g., robots, artificial intelligence), via additional capacities (e.g., more warehouses, more manufacturing lines, more trucks), and via negotiations for more favourable terms & conditions in contracts with vendors & service providers. We outsource operations to offshore locations, or we build facilities to near-shore our supply chains closer to home.
We sometimes just bear with the symptoms and hope they will go away. That’s what many enterprises did when international ocean freight prices skyrocketed in 2021. Prices eventually plummeted from late 2022 to early 2023. Many business firms just rode with the wave. Some increased prices of their products while others simply cut back on orders of items from abroad.
We sometimes are satisfied just working day-to-day mitigating symptoms. We’d rather not spend any more capital for our supply chains. Many of our bosses just don’t like the idea of spending any more time or resources for supply chains versus allocating money for marketing or research & development.
Many executives, who are our superiors, spend a lot of time developing strategies. To many executives, we should start with a strategy before we think of improvements to our supply chain operations. A strategy, after all, helps us plan what resources we need and how we will use those resources to reach our desired destinations, i.e., our goals.
We can’t, however, think about strategy and the goals we want to accomplish when we are bugged by symptoms. We can’t improve our operations if the symptoms are like burning platforms. We find ourselves putting out fires instead of contemplating longer-term changes.
We, therefore, improve our supply chains by starting with symptoms. As long as we feel them, we likely are suffering in terms of higher costs, lost productivity, and wasted cashflow.
Symptoms are effects of problems. We start with symptoms to identify causes and define the problems. To identify causes, we diagnose.
A diagnosis is not an audit. Audits aim to assess conformity to mandated rules, standards, & policies. Diagnoses determine the root causes of unwanted symptoms via the examinations of operations.
A typical diagnosis of a supply chain consists of four (4) steps:
- Mapping
- Data Research
- Analysis
- Identification
Mapping
Mapping helps us see and appreciate the operations of supply chains. Maps show us the activities, and present how functions work and relate to each other.
Mapmakers usually favour flow charts. Flow charts are either simple, i.e., basic shapes (e.g. circles, triangles, squares, arrows) or complicated, i. e., intricate in detail (e.g., value-stream maps, engineering schematics, critical path method [CPM] charts).
Maps can also come in the form of diagrams such as the fishbone or Ishikawa diagram and the Force-Field Analysis diagram.
The point of whatever mapping method we use is to visualise the supply chain so we can find out where we are feeling the symptoms and where to start our research.
Data Research
We research to catalogue bits of information and their sources. Data Research isn’t just data mining, which is about gathering as much as information as possible about a subject or individual. Data research is about reading and comprehending information from the data gathered. It includes interviewing people and comparing different versions of whatever stories they tell.
The finished product of data research is an organised report about the operations in which it explains where the symptoms are emanating from and where they are having an effect. Data Research provides the foundation for analysis.
Analysis
Analysis is the study of the research from which we draw conclusions.
We analyse via different means, such as:
- Scientific
- Statistical
- Financial
- Subjective
- Comparative
So-called experts would tell us to analyse scientifically, in which they imply we should be objective, and not subjective. In a scientific analysis, we often use reductionism, in which we break down what we’re studying into its parts or components. The objective of such an analysis is to find out what specific part or component could be the root cause of an issue.
In a statistical analysis, we grind data to find mathematical correlations via parameters such as averages, standard deviations, probabilities, and trends. We look for where these statistical numbers lead to or originate from. And then draw conclusions from these numbers.
In a financial analysis, we assess the impact of the research on the wealth of our enterprises. We compute factors such as rates of return, depreciation, cashflow, and income derived from our supply chain operations. We then determine if the symptoms are worth addressing.
A subjective analysis is the opposite of a scientific analysis, in which we base our conclusions on our points of view and intuitions. We gather comments or suggestions from peers or teams based on the information we gathered. Or we make up our minds ourselves based on “gut-feel,” in which rely on our hunches or what we would call calculated guesses based on experience or even, emotion.
A comparative analysis checks our research between similar operations or between data from what we gathered in the present to what we recorded in the past. We use scientific, statistical, financial, or subjective methods as we compare varying scenarios.
Whatever analysis we do, we come out with our findings and conclusions. We identify the root causes of our symptoms.
Identification
In the final step of diagnosis, Identification, we articulate our conclusions and pinpoint the root causes of symptoms.
Root causes may be outright obvious, as in, for example, we see the cause right away from a fishbone diagram.
Sometimes, however, they are not so obvious even after analyses. This can happen if our analysis’ conclusions imply several causes.
For example, salespeople at a snack foods corporation complained about late & incomplete deliveries of pending orders. The salespeople cited empty shelves at supermarkets & convenience stores as an effect. Data research, however, showed that the logistics department was delivering orders efficiently, like 95% completely and on-time. Analysis concluded that:
- Salespeople were submitting orders late, like up to one (1) week after customers called in their orders;
- Items salespeople said were out of stock were often in-stock and available at the central warehouse, up to 90% of the time.
It turns out there is really one root cause: the ordering system was not in sync between the sales department and the orders processing department. The system’s functions of receiving, validating, and allocating inventories for deliveries were working separately than together.
Identification as a diagnostic step is a form of post-analysis of root causes. It puts together the conclusions and pinpoints articulately what’s the cause of the symptoms.
We often start from the symptoms when we want to improve our supply chains. As engineers, we diagnose our operations by focusing on where we are feeling those symptoms.
Diagnosing involves mapping, research, analysis, and identification. We map our operations to see how functions work & relate with each other and look where the symptoms are having an impact. From mapping, we research not only by mining data but also by reading, comprehending, and organising them. We analyse via the methods we think are best applicable to our diagnosis and we conclude by identifying the root causes of symptoms.
A diagnosis is not a tool. It’s a method or procedure built into our problem-solving approach especially for our improvement of supply chains.
And it is the first thing we supply chain professionals do before we define and solve problems.