Region is a fundamental element of any logistics or supply chain digital product. The geographical location defined and abstracted into code is what I define as region. How should one define a region when designing a product in this domain? Should it be a pair of co-ordinates that show the location? Should it be the boundary of the facility plotted on a map? This is pertinent especially in an era where GPS is accurate upto few metres, precision is not an issue. So, why in the last 10 years of working in this domain, I still keep tripping over problems surrounding region as they become the root cause of many solutions being stuck from [[Execution, growth and product market fit|scaling]]^[Scale and growth are two sides of the same coin. Often times the growth of the product is restricted by its lack of universality in theory.Hence, not scalable. ]. I have spent too many hours distilling the overall framework of region to be considered when designing the backend architecture of a product^[Every time I spend time doing it, teammates always find it over indulgent. And everytime once we progress little further down the line it starts making sense] ### Why it turns into bottleneck ? The quick job of getting a functional prototype to show value results in people inheriting the logic of region defined by the mapping provider. In terms of solution, it is just capturing the address from the map and storing it in our database. This reduces the complexity of the product. In the address, you can get all the details needed but address is made up of administrative categorisation and many times it deviates from the business logic. A simple illustration of where it deviates is always surrounding borders. Two facilities are on either sides of a border, so they fall in different administrative blocks. For a person, the spacial representation of these facilities allows them to understand why they are being treated under the same region. But this will not be the case for code if the logic doesn’t exist. We will have to define it or else it won’t factor it. In these scenarios we write the custom logic to abstract the physical representation of the facility to the contextual representation of the facility in the process. And these logic get convoluted as the product grows. ### Why is it relevant ? I see this as a challenge that would make many agents stumble as they are tasked with executing workflows on people’s behalf. The region abstraction layer would be key context that the agent needs to comprehend for it to contribute meaningfully. If not contextualised properly, the loss of trust on the agentic framework will be swift. This is not a single product but a function of lack of theory. The problem persists because the simpler abstraction is easier to understand even if it not effective. [Let us take the case of spot(open) full truck load market in US(we can extrapolate it across geographies )](http://supplychainmit.com/2015/04/30/the-myth-of-a-single-market-truckload-rate-part-1/) > Many supply chain executives believe in, and hope for, a single generally accepted truckload (TL) rate for any given lane. This is typically referred to as the market rate for a lane, and is found by taking the average or median of a sample of TL rates from a common origin and destination. > **Chris Caplice** There is no such lane. When cargo owners moving goods from one location an another abstract to a postal code and define it as a lane and then they are faced with rates that are not the same. This paper from 2015 goes on to say that there is no single rate per lane for FTL (Full truck load) yet > An econometric-based model does not compare lane rates; it separates out the individual effects, to include the origin and destination locations. While shippers have very low lane overlap, they have very high region overlap. We exploit and leverage this by calculating the impact of loading (unloading) in different geographic regions. The model is able to accurately estimate the geographic cost impact of each 3-digit postal code region. Yet this is not the prevalent narrative in the Full Truck load market. I still stumble with the question why is region or abstracting region so important? And I want to use this post to answer the question. ## How should we define a region ? Here is my basic framework for [[Defining a region|defining a region]] : > ![[Defining a region.png]] The logic behind how we define a region comes from the bounded by region framework. ![[Pasted image 20241013104934.png]] For example, let us go back to the full truck load spot (open) market. The society is determined by carriers and shippers. The economy is determined by the transaction ecosystem whether we are in a tight spot market or soft(capacity vs demand balance). And the domain is determined by the spot market components (short term, transactional and commoditised service). So, the region we develop should encompass all these components into them. From our example, a region in truckload market should focus on abstracted geographical regions where density of shippers is robust(radius of the region). It should also have flow of traffic between regions(economic conditions). And lastly, it should have list of counterparty organisations working in the region (society). A manifestation of this is hotspots in delivery apps where they rush delivery drivers to ensure demand is being met. Region over here is created dynamically basing on supply and demand flows and plotted on the map.  ## Region is the highest order bit Many of the logistics services are commoditised. You don’t pick a carrier to move your freight because they move it better^[I am generalising for affect but there are few commodities that require special equipment and service. They represent a fraction of the total market]. The level of service differentiation is minimal compared to price. If there are two carriers quoting two different prices with varying service levels. Even if the difference is equal for both dimensions, the carrier with the lower price gets precedent. I wrote about it in [[3Cs of Logistics|3Cs of logistics]] post.  So getting the region right allows participants to grade each others performance. For example, a shipper can grade two carriers if they operate in the same region. This is similar to competitive exams, you don’t need to be the absolute best to succeed but you need to be relatively better than rest. When we compare inaccurately things only seem worse than they actually are. And when you are building a product in this domain (a platform of sense), getting this region (reference) accurate becomes the [highest order bit](https://dinesh.eth.link/notes/highest-order-bit/).  The inherent expectation that a digital product will help scale is often restricted ill defined region model. Scaling systems are micro interactions that can be replicated in multiple setups across different set of customers. This is the inherent sentiment of what scale means in logistics as well. And setting up the region accurately helps products become scalable. If we define it too concrete for a specific geography , it sometime doesn’t translate well to a different geography. In the end, time spent defining the region will enable the product for scale. Region alone will not solve all scaling issues but it will help in geographic expansion if we get it right. **** `Original Published date` : 28-07-25 `Tags`: #logistics #product