Category Archives: Logistics

Keep Your Procurement On PACA with FSMA with Procurant!

We don’t cover specialist Procurement providers much here on SI because many don’t have much in the way of domain specific product functionality (and differ primarily on domain knowledge, terminology customization, and service offerings), but some, like Procurant, go beyond the basics and offer domain specific functionality of relevance that the market needs to take note of. Especially when such functionality can help an organization be compliant with current and, most importantly, incoming regulations they are not ready for.

Procurant, marketing itself as a strategic platform for perishables that does Procurement AND Food Safety, offers the following core functionality:

  • P2P (Procure to Pay) for Perishables
  • Inspections (recording and auditing)
  • Traceabillity that is mobile-enabled and FSMA 204 compliant
  • Market Intelligence
  • Food Safety (workflow and remote sensor integration) (not covered in this article)

It’s the one-stop solution for retail grocers, especially those with US operations, that need to manage their perishable supply chain in a manner that is both PACA and FSMA compliant. (And if you’re a grocery retailer that does NOT know what those acronyms stand for … Uh-Oh! Better find out and give Procurant a call ASAP — because failure to comply can not only result in fines but [supply chain] shutdowns.)

Procurement/Procure-to-Pay wise there isn’t much that’s unique in core functionality (as the uniqueness is with the integrated support for the perishable space), but it’s all there, and we’ll start with the core so you can be confident the core is on par with other best-of-breed Procurement solutions.

With respect to quote management, the platform contains integrated RFQ / price request that makes it really easy to not only request (updated) quotes from suppliers, but get a commitment on that price (for a certain time or volume; i.e. one week or 100 pallets). When you get a commitment, the system tracks orders against that commitment, and then lets you know when the quote has expired because the commitment has been used up (and if you still need more product, you need a new quote with a new commitment).

With respect to order management, the solution makes it easy to select products for orders from the built-in catalog, from order templates (guides), or from demand forecasts (which can pulled in from the forecasting/demand management system OR created natively in Procurant using weighted average outbound for the last 12 weeks, with more forecasting algorithms coming in a future release). The platform even supports the definition of automatic (replenishment) orders, should the organization choose that functionality. Once the order is assembled, it’s very easy to send it to the supplier for fulfillment.

Moreover, as Procurant ‘s P2P also contains integrated support for carriers and logistics (due to the need to monitor the entire produce supply chain and ensure food safety every step of the way), in Procurant, you can also assemble orders by truckload, as you don’t want to be under-shipping if not absolutely necessary (as it takes the same amount of energy to maintain the temperature when refrigeration is necessary whether the truck is almost full or almost empty) and it’s easier to trace when you decide who is shipping what, when, and on which truck. One great feature of the platform is that it’s super easy to assemble an order for a carrier. It’s just a matter of dragging and dropping order line items until the platform notifies you that the last line won’t fit in the truck (as you can encode a max # pallets, weight, and volume by truck and as soon as one limit is reached, the platform lets you know). No complex training on a sophisticated TMS required.

As a result of this deep support for logistics and carriers, purchase orders can be incredibly detailed and include shipping dates, carrier, load reference number(s), and even cross docks.

Also, order management is multi-state and the system will track and notify if there is an:

  • order modification by the buyer
  • order modification by the supplier
  • order cancellation by the supplier
  • order reconciliation by the supplier (on being notified the goods received didn’t match the PO)

and all changes by any party are maintained in a secure, unalterable, audit log.

With regards to order management, the buyers can choose whether or not the supplier can split orders, remove items, or add substitute orders. Whether or not they can change prices (or just quantities to match availability), and even when modifications will be accepted. Similarly, the administrator can determine the order creation capability the buyers have access to … whether or not they have (to use) guides, whether they can create cross-dock orders, etc.

With respect to invoice management, it’s super easy for a supplier to flip a PO to an invoice. All they have to do is enter the actual quantity shipped by line item and submit. The invoice then goes into a wait state until a receipt is entered, at which point if there is a discrepancy, the invoice is sent back to the supplier for correction before it goes into the normal processing queue, where it would be held up until the discrepancy was resolved, which could delay payment considerably if the organization has long approval chains for corrections and exception processing.

The platform also tracks supplier fill rates, so you can quickly see which suppliers are fulfilling the POs they accept and living up to your expectations and which suppliers are not. It also has price watch capability, and can alert you whenever PO or quote prices exceed current (or historical) prices by a certain percentage.

And, of course, there’s a dashboard which summarizes current tasks and open orders and great search and filter functionality to find just the orders, invoices, or quotes you are looking for.

The platform also integrates the inspection reports from their inspection app and, for any fulfilled order, you can quickly bring up the full report that summarizes the inspection (packaging, appearance, condition, flavor, and quality) on each item delivered as well as the number of items rejected. Also integrated with the Procurement platform is the Inspection Module that contains the overall inspection summary dashboard, dill downs by supplier, scorecards by supplier, and other key reports and data points on inspections. The inspect application is a mobile app that workers can use at the warehouse on or the dock to inspect the quality of goods as they come in and, if necessary, reject them on the spot.

What’s really cool is the Track and Trace capability where, for any item, you can see the entire journey from the source lot to the warehouse or the store shelf, as appropriate. You just need a GTIN, lot number, order number, SKU, or product description and, optionally, a date range and you see the store shipments, receivings at your warehouses, vendor shipments, and base lots. And you can click into each store shipment, receiving, vendor shipment, or lot and see complete details (such as the ship to, date, and receiver for a store shipment; order #, sales order, Lot, shipper, shipment date, and cases for a vendor shipment; etc.). And with their next release, the (default) output report formats will be usable for FSMA compliance. (Again, if you do grocery retail and you don’t know why this is critical, you better find out soon!)

Finally, their Market Intelligence Capability in Procurant Connect provides Commodity Pricing, Weather, and Transportation analytics and tracking. The commodity pricing tracks price movements across all commodities by region; the weather pane integrates forecasts down to the county level; and the transportation analytics tracks average load fees by lane (defined by city pairings), as well as price changes and shipper / transportation availability (surplus, slight surplus, adequate, slight shortage, or shortage).

Procurant can integrate with your ERP and AP (payment) system, your TMS (or onboard carriers natively, which is something not many P2P systems can do as carrier management is critical in perishable supply chain management), and your supplier master (for supplier onboarding) if it’s not your ERP.

All-in all, Procurant is a fantastic solution for the perishable supply chain procurement and one that absolutely has to be on the short list of any grocery retailer that needs to get a handle on their perishable supply chain in a manner that will allow them to be fully PACA and FSMA compliant.

Coupa: Comprehensive Optimization Underlies Procurement Assurance: Coupa Supply Chain Solutions

We’ve never covered Coupa Supply Chain Solutions (for Design and Planning), formerly known as Llamasoft, here on Sourcing Innovation, but the doctor did contribute to some of the coverage over on Spend Matters, including the acquisition coverage (Functional Overview, Overlap Between Direct Procurement and Supply Chain, and Procurement, Finance, and Supply Chain Use Cases [Content Hub Subscription Required]) in 2020. Llamasoft / Coupa Supply Chain Design and Planning has also been more recently covered by Spend Matters’ Pierre Mitchell as part of his analysis of Coupa for Supply Chain Management overall. For those interested with a ContentHub subscription, see his pieces on Can Coupa manage supply as well as spend?, Coupa’s journey from Business Spend Management to Supply Chain Management: Assessing progress on seven key dimensions, and From Spend to Supply — Coupa’s direct spend management progress.

Coupa Supply Chain Solutions consists of four main offerings:

  • Supply Chain Modeller: the core solution, that can be used offline on the desktop (Supply Chain Guru) as well as online in the cloud, where you build network, inventory, and transportation models for optimization and exploration through the dynamic reporting and dashboard creation module; note that the online version can process multiple “what-if” optimization models simultaneously
  • Supply Chain App Studio: the online solution which allows users to build custom interfaces to the underlying model that can be, if desired, custom designed for different user types (procurement, logistics, demand planners, etc.) and then shared with those users who can use the app for regular analysis and what-if optimization
  • Demand Modeller: for demand modelling and forecasting — not covered in this article
  • Supply Chain Prescriptions: uses machine learning and AI to identify savings opportunities from changes to transportation and inventory models, as well as to identify risk mitigation scenarios, based upon the current supply chain design

In this article we are going to primarily cover the capabilities of the Modeller / App Studio and the Prescriptions which is the core of their supply chain (design and planning) solution suite.

The Modeller has three primary components:

  • Model : where you build the models
  • Explore : where you build what-if scenarios, that are then optimized
  • Results : the outputs of the what-if scenarios

Model building is quite easy. It’s simply a matter of selecting, or uploading, a set of data tables for each relevant supply chain entity. They can be pulled in from a relational database or from a CSV file in standard row-based column format. As long as the column headers have standard field names, the SCP solution can auto detect what entity the table represents (warehouse, lane, transportation mode, etc.) and what data is provided on the entity. It understands all the common elements of supply chain modelling, common names and representations, and appropriate business rules that can do all of the auto mappings.

When you pull in a table, and it does the mappings to the standard internal models, it also automatically analyzes and validates the data. It makes sure all entries are unique, key values required for the types of analysis supported are there (such as coordinates for warehouses, costs per distance for transportation modes, stock levels and associated product requirements for inventory), etc. and flags any conflicting, missing, or likely erroneous data for user review and correction.

When you go to build a scenario, it understands what is required in the base underlying model and validates that all of the necessary data is present. If data is missing, it warns you and gives you a chance to provide the missing data. (Furthermore, as you add constraints to the scenario, the platform understands the data is required and ensures that data is present as well before it tries to run the scenario.)

The application was designed for ease of use and speed, tailored for automating most of the model building process for standard network/inventory/transportation scenarios (including setting parameters and defaults) so that standard models can be built for analysis quick and easy (and it is also quick and easy to change or override any default as needed).

Explore provides the capability where you build scenarios for what-if? exploration.

Building scenarios is simple. You simply select the scenario requirements, or constraints, from a set of existing, or newly created, scenario items that define the parameters of the scenario. For example, for a network optimization, you might want to explore limiting the number of existing distribution hubs or adding more proposed nodes to see if you can reduce cost, carbon, or distribution time. For transportation, you might want to explore adding in rail to a network that is currently all truck to see if you can decrease cost. For inventory, you might want to reduce the number of locations where safety stock for rarely used components is stored (so you can limit the number of locations with a low turn rate and minimize the warehouse size/footprint you need at those locations) and see what happens and so on. Each scenario is built from a set of specifications that specify the restrictions that you want to enforce, which could even be a reduction in the current number of restrictions. These restrictions can be on any entity, or relationship. One can also create scenarios to explore how the network will change under different circumstances, such as demand change, cost change, or disruption. Selecting is a simple point-and-click or drag and drop exercise.

Once you’ve created the scenario(s) of interest (remembering that you can optimize multiple simultaneously in the online version), you launch them by selecting the type of optimization (the “technology”), the sub-type of optimization (the “problem type”), the horizon (the timeframe you want to analyze), and, optionally, override default parameters (if you don’t want to do a cost optimization but instead want to optimize carbon, service level, fulfillment time, risk, etc.). Then you run the scenario, and once the optimization engine works its math, you can explore the results.

The Model supports:

  • Network Optimization
    • Standard Network Optimization
    • … with Network Decomposition
    • … with Infeasibility Diagnosis
    • Greenfield Analysis
    • Cost-to-Serve Analysis
  • Inventory Optimization
    • Safety Stock
    • Safety Stock & Service Level
    • Safety Stock & Rolling Horizon
    • Safety Stock Infeasibility
    • Service Level
    • Rolling Horizon
    • Rolling Horizon Validation
    • Demand
  • Transportation Optimization
    • Transportation – Standard
    • Transportation – Interleaved
    • Transportation – Hub
    • Transportation – Periodic
    • Transportation – Backhaul
    • Transportation – Backhaul Matching
    • Driver Scheduling

In short, it’s a very extensive network, inventory, and transportation optimization modelling solution out of the box that makes it really easy for supply chain and procurement analysts to build scenarios and solve them against all of the traditional models (and variants) they would want to run. (And if your particular variant isn’t out of the box, the SCP team can code and add the variant into your deployment as the underlying solution was built to allow for as many models as was needed as well as unlimited scenarios on those models.) Note that, by default, the platform will always run the baseline scenario so you have a basis for comparison.

Results, which are output in the form of results tables, can then be analyzed in table form (by selecting the output table), graph form (by accessing the graphs), map mode (by accessing the map), or as a built-in or custom report/dashboards that the analyst can create as needed. For every type of analysis in the system, SCP includes a default set of dashboards for exploring the data set, which adapt to not only the type and subtype of optimization that was run, but the goal (objective function) as well. So if you did a cost optimization scenario, they summarize the costs. If you did a carbon optimization scenario, they summarize the carbon. If you did a service level optimization, they summarize the service level. If you did a carbon optimization relative to a maximum cost increase, they summarize the carbon and cost (and the relationship). In their platform, if you optimize one element or KPI, you can see the impact on all of the other costs and KPIs as all of the associated data is also output for analysis.

There is an output table for all elements which can be analyzed in detail, but most users prefer graph or map view on the relevant data.

Views provide custom, tabular, reports on the relevant fields of one or more tables, which can be exported to csv or pushed to another application for planning purposes. For example, if the model was a network optimization model, you can create a view that outputs the new distribution centres and fulfilment lanes for the revised network and push that to the TMS (Transportation Management System). If it was a transportation optimization model, you can output a table that specifies the carrier and rate for each lane, or, if necessary, each lane product combination and push that into the TMS. If it was a safety stock optimization model, you can output the product, location, minimum stock levels, and reorder points and push that into the Inventory Management or ERP system. And so on. There are default views for cost, carbon, service level, demand, and inventory optimizations, along with drill ins for relevant types of cost (site, production, by transportation type, etc.), but it is quite easy for a user to create a view on any table, or set of tables, with derived fields, with the view editor.

Graphs summarize the data in tables or views graphically, allowing for easy visual comparison. Select the scenario, select the data, select the graph type, and there’s your graph. They are most useful as components in dashboard summaries.

Maps provide a visual representation of the supply chain network — warehouses/distribution centers, customer locations, transportation lanes — overlaid on a real-world map with the ability to filter into particular supply chain network elements. There is a default map for the full network overview, and it can be copied and edited to just display certain elements.

Dashboards group relevant elements, such as a map of the current distribution network, a map of the optimized distribution network, a graphic summary of current distribution costs, a graphic summary of new distribution costs, and tabular (view-based) cost, carbon, and service level comparisons as the result of a supply chain network optimization scenario. These are typically custom built by the analyst to what is relevant to them.

Prescriptions, only in the online version of Supply Chain Modeller, are based on the 22 years of experience the SCP team has in building and analyzing models and uses advanced ML, simulation, and AI to automatically identify potential cost savings, and risk reductions and presents rank-ordered opportunities for you in each category, which you can drill into and explore. This solution automatically generates dozens (upon dozens) of scenarios and performs hundreds (or thousands) of analyses to automatically bring you actionable insights that you can implement TODAY to improve your network.

These savings will be grouped by type for easy exploration. For example, when it comes to cost savings, these will often be obtained by node skipping, mode switching, or volume consolidation — and the prescriptions module will summarize the prescriptions in each category, as well as summarizing the relative total savings of each category. A user can accept or reject each (sub) set of prescriptions, and then export all of the accepted prescriptions into new route definition records that can be imported into the TMS.

Note that the analysis that underlies the prescription analysis is very detailed, and in addition to the prescriptions, the platform will also identify the top network factors that are impacting the transportation costs, such as fleet distance, unique modes, certain carriers, country, etc.

When a user drills in, she sees the complete details of the prescription, including the before and after. In the node skipping example, they will see the current distance, products, quantities, (total) weight and volume, and current rates and then will see these in comparison to the new distance, new rates, and new costs. The old and new routes will be mapped side by side. The old and new lanes will be detailed.

The out of the box network risk summary for revenue at risk is quite impressive. The platform is able to compute the overall network revenue AND network profit at risk based on single sourced site-products, % of flow quantity single sourced, avg. end-to-end service times, and impacted paths. It will then do analyses to identify potential risk mitigation improvements allowing for 5%, 10%, and 15% network change (based on how product flows through the network with the current design) and compute the corresponding change in revenue and profit at risk as a result of those changes as well as the change in network cost. Usually the cost will increase slightly, but not always. For example, it could be that you could reduce the revenue at risk by 5% just through a supplier reallocation and network redesign, and if you were really risk averse, it could be that a 1% increase in network cost could result in an 8% to 10% decrease in revenue, and profit, at risk. And that could be the cheapest supply chain insurance you can buy.

Of course, you can drill into each model, the prescriptions, and the risk reduction with each individual change. It’s an extremely powerful tool.

Another thing that is really powerful in Coupa Supply Chain Solutions is the specific applications they can enable in the online App Studio, including the Cost-to-Serve App (which is just one example of the custom interfaces that can be built) that is one of the most complete dynamic dashboards for network insights that the doctor has ever seen. A summary can’t do it justice, but to whet your appetite to be sure you ask to see it in a demo, it has a full set of meaningful baseline KPIs, a visual network and flow summary, deep details on product costs and profitability, deep details on lanes and transportation costs, and so on. You can also quick-select a scenario to run and compare against the baseline in the app. It’s extremely well thought out.

Furthermore, you can build scripts in the App Studio to rebuild and run models on a schedule when you have a network in flux (because of disruptions, supply base changes, network changes as a result of prescriptions, etc.). And, of course, you can share these models and apps and dashboards with other analysts and democratize supply chain planning, easily enabling planners to analyze their own scenarios and make decisions collaboratively in a user-friendly App.

In short, Coupa has fulfilled the supply chain use cases we identified back in 2020 in Procurement, Finance, and Supply Chain Use Cases. It’s a great solution that you should check out, especially if you would like to have procurement and supply chain under one umbrella.

Need to Trade More Confidently? Maybe You Need Trademo to Monitor Your Supply Chain!

As you should be well aware by now (as we recently gave you a 10-part series on supply chain risk), supply chains are fraught with risks — that you need to manage, and that, in many cases you can only manage with visibility. In particular, multi-tier visibility down to the source raw material. You also need insight into key areas of regulatory compliance around H(T)S codes for trade (and ECCN for defense trade), sanctions and denied parties, and (known) forced/slave labour violations by any supplier in your multi-tier supply chain.

One application that can give you multi-tier visibility, detailed insight into key areas of compliance, supplier discovery, and even trade intelligence is Trademo. Centered around a global supply chain knowledge graph on over 5M buyer and supplier entities with over 100M relationships built upon public trade (import/export) data from over 140 countries, Trademo can provide unique multi-tier visibility and insight into your supply chain, and the supply chains of your competitors which can help you find potential suppliers who could also serve you and even identify other supplier locations that could be more relevant for you.

There are three main parts of the Trademo platform.

  1. Global Supply Chain Intelligence
  2. Supply Chain Visibility & Resilience
  3. Global Trade Compliance

We’ll discuss these in reverse order, as that is the typical order in which organizations generally seek out, implement, and use these solutions.

Trademo‘s Global Trade Compliance module supports an organization with

  • HS Tariff Search, Validation and Classification across 140+ countries
  • ECCN Search
  • Sanctions Screening across over 640 global sanctions list
  • (Import/Export) Controls (and Embargo) Search
  • Product Master
  • Landed Cost Calculator

HS (Code) Search is by country, trade direction (import or export), and partial code or product keyword. (HS codes could be classified either by referring to the built-in tariff tree structure or using the AI model to classify the HS Codes.) it brings up all the matching codes based on the product key word (or partial HS code), as well as the computed match relevance. You can then select the code of interest and see the associated tariffs and duties, controls, and any associated rulings.

ECCN search is similar to HS (Code) Search and is by country and ecn/ml number or keyword and brings up the relevant subcategories that you can dive into and get relevant details.

Sanctions screening can be ad-hoc, bulk, or advance. Adhoc allows a sourcing / supply chain professional to enter a person, company, or vessel name and screen against any set of sanction lists of interest (one, some, or all). Bulk allows the same, but against a list of uploaded persons, companies, and/or vessels. Advance screening is similar to adhoc, but allows the user to limit to countries, specific locations, and even set thresholds for partial match retrievals. The user can also setup blacklists, so that any attempt to associate a product in the master with a supplier that is blacklisted fails, any search on it returns its status, and any export includes the blacklist status. The user can also setup watchlists (for daily monitoring) and any time a new sanction, control, etc. is detected for the person, company, or vessel, an alert is created in the tool and sent to the user through e-mail.

Sanctions screening are against rules that define collections of sanction lists that are relevant to the user and the types of screenings they usually do. For example, if the organization only sources from and/or two 20 countries, they may not care about any sanctions or embargoes against the remaining countries for which sanctions and embargoes are encoded in the system. In the Trademo system, rules are sorted into list groups (global sanctions, PEP, OFAC, health & human service, banking & investments, enforcement, and maritime) and then sub-groups by source (country, entity, etc.). The buyer can select what interests them, a threshold for matching, define a rule name, and then easy peasy search just those lists going forward.

When a sanction is found, extremely detailed information is returned and generally includes the entity name, the list, the country, the authority, all known entity (operating) aliases, effective date, expiry date (if a limited embargo, for example), company address / vessel birth and identifiers / personage citizenship or address, etc. A user can also bring up the full citation and download everything in PDF if they desire.

Controls bring up, for an import country or ISO Code and/or export country and ISO Code and/or country of origin and ISO Code and/or a HS Code, all related controls and embargoes along with their type (such as import permit or export permit), the controlling authority, and the scope of the control. As with a sanction or HS code, the user can click into a control of interest and see the complete details and download the source (as a PDF) if they so desire.

The Product Master allows the organization to manage their product database down to a SKU level, along with all countries of import, export, and associated HS codes. This makes it easy for the platform to automatically monitor for relevant changes to HS/ECCN codes, duty rates, controls, embargoes, etc. and notify the user when these changes occur.

The Landed Cost Calculator is very useful for sourcing professionals as it allows them, for a lot, to enter some basic information and source unit and carrier costs and get a complete total landed cost based upon the HS / ECCN code and all import and export tariffs.

The user needs to simply enter:

  1. Country (of import, export, and origin), duties of interest (default, preferential, or both), and HS CODE
  2. Mode of transport, incoterm, currency, value (and, optionally, unit of measurement & total quantity)
  3. Freight, insurance, and any other known (sur)charges

The platform will then calculate the total landed cost that will include all the duties and tariffs on the lot, the known merchandise processing fees, the known vessel fees, the known port fees, and other known fees and give the user a total landed cost (where the user can see a 200K buy become a 250K or 300K or more buy and truly understand the cost of global sourcing). the user can also compare the landed cost across different sourcing markets.

Moving on to Trademo‘s Supply Chain Visibility & Resilience solution, it is essentially a supply chain mapping solution that allows an organization to see all of their 1 to n suppliers (3 by default, but more if they want) and filter into suppliers by tier, country, HS code, and associated trade lanes. They can create product groups by brand or region and just see the associated supply chains for those brands and regions as well. The default view shows them the supplier name, domicile country, HS codes supplied downstream, trade lanes used, tier 1 connection, and total shipment value. From this complete list, the user can select a subset of suppliers by country, HS code, and/or trade lane and see a graphical representation of their supply chain, augmented with trade value. It’s simple, but quickly informative and very useful to discovering just who is in your supply chain, as well as who is in a certain region / on a certain trade lane that was just impacted by a natural disaster or border shutdown and you need to react.

Finally, there is the foundational Global Supply Chain Intelligence intelligence offering (Trademo Intel) that is based on their core supply chain knowledge graph and all of the public trade data it incorporates. The entry point to Trademo Intel is the shipment search screen which allows the user to search across all bills of lading in all categories and retrieve all associated shipments, which can then be filtered by shipper details, consignee details, ports, cargo, and freight details, and see a summary, for the selected timeframe, of total shipments, total weight, and total value. They can then drill into (top) importers, exporters, and more detailed analytics. If the amount of data is overwhelming, they can limit to specific product categories, HS codes, shippers, or consignees before starting the search.

It’s a great tool for exploring your competitors’ supply chains, which, when limited to certain product (categories), allows you to discover potential suppliers you might not have known about otherwise. Furthermore, you can see the volumes they are capable of supplying globally and the trade lanes they are already navigating. While most risk solutions will give you credit, cyber, compliance, and/or sustainability risk, they don’t give you deep insights into products supplied, locations supplied from, lanes the supplier is using (which indicates which global regulations they comply with), and so on. When you click into an entity, you can see all of their trading partners, total shipments to/from each, HS Codes supplied, and associated shipments. They can then drill into any and all shipments of interest and see complete details. The analytics are super helpful in identifying the top HS codes, HS sections, modes of transport, and routes used by the entity.

It also allows an organization to keep tabs on global trade from a certain region and whether it is increasing or decreasing, which could signal tidal shifts that could affect future cargo availability, rates, and risks if there is over saturation or under saturation of a trade region predicted.

If you need global trade support around HS codes, sanctions or embargoes; supply chain visibility; and supplier discovery (and deep trade insight in this discovery), Trademo is a solution that should definitely be in your RFP short list. It’s easy to use, powerful, and already validated by a number of Global 3000 companies. Check it out and TRADE MOre confindently!

Source-to-Pay+ Part 6: (In) Transport Risk

In Part 1 we noted that Risk Management went much beyond Supplier Risk, and the primitive Supplier “Risk” Management application that is bundled in many S2P suites. Then, in Part 2, we noted that there are risks in every supply chain entity; with the people and materials used; and with the locales they operate in. In Part 3 we moved onto an overview of Corporate Risk, in Part 4 we took on Third Party Risk (in Part 4A and Part 4B), and then in Part 5 we laid the foundation for Supply Chain Risk (Generic).

As part of supply chain risk, we highlighted transport mapping and tracking as a key risk that the system should track, but noted that a generic supply chain risk management system would generally not be a full featured transport risk management system because such a system would also monitor and mitigate risks of goods in-transport. (Not just risks at nodes.) Such a system has a number of specific requirements beyond the basics outlined in our last article. In this article, we are going to discuss a number of those specific requirements.

Capability Description
Modal-Specific Support Cargo can travel by land, rail, sea, or air. As a result, an in-transport platform has to recognize each of these modes, the differences between them, the data that needs to be tracked, and the data that can be obtained from carriers providing each mode.

Such a platform should integrate with industry standard data feeds from TMS (Transport Management Systems), data feeds from major carriers, GPS systems, and other systems that provide data on your shipments, where they are, and when they are expected to get to the next location if the current leg of transport does not have a real-time GPS feed.
Cold Chain/Hazardous Not all cargo can travel dry at room temperature. Some has to travel wet, some has to travel refrigerated or frozen, and some has to travel with special precautions for hazardous materials. It’s critical that such a platform be able to tag items with these tags, these transport requirements, and assess the risks associated with the transport based on carrier, route, geolocation, etc.

Such a platform must be able to detect when a risk materializes or escalates, such as the delivery time estimate being pushed forward by a week when the cargo was only expected to have a shelf-life of six (6) days when delivered, extreme weather phenomena suddenly materializing in the region of the transport vehicle, or dangerous (man-made) accidents occurring as a result of a leak, accident, or failure in transport.
Manifests/Bills of Lading The system should be capable of accepting bills of lading and cargo / shipping manifests and ensuring that the bill of lading exactly matches the shipment that is expected from the supplier, the cargo/shipping manifest exactly matches the bill of lading, and the inventory at the dock/yard matches the cargo manifest. This is the only way to minimize the chance of theft and fraud during transport. And by fraud, we don’t just mean your goods disappearing, we mean your containers and your company being used to smuggle goods into one or more countries where the goods are prohibited in those countries.

The system should also be capable of identifying carriers who have had incidents in the past, the carriers who are most at risk due to the regions they operate in, and the carriers who are most at risk due to the products they are carrying, both for you and for others (based on public manifests).
Ports The system will track detailed information on the ports that are used in the supply network. It will maintain information on port capacities / throughput, the carriers that go in and out, the equipment, the security at the dockyards, and so on. It will maintain information on the labour situation (last strike, the date the contract ends, likelihood of a strike/slowdown, etc.) as well as the available workforce.

The system should be capable of tying in weather information, local geopolitical information, economic information, and other disruptions that could affect the port, as well as any other risk-based factors that are relevant.
Canals/Straits A lot of the world’s goods flow through canals (primarily the Panama and Suez) and straits to ports that are off of lakes and seas and not on the Atlantic or Pacific Ocean. While there are the risks of natural disasters just as there are on the high seas, there are also the geopolitical risks associated with all of the countries that border the canal or strait. (Especially if they are unfriendly to the country of origin, destination, or registration of the ship.)

The system must track all of the risks specific to the canals and ports that the organization, and its carriers, use in the ocean-based transport of goods.
Warehouses/Cross-Docks Most goods procured by an organization will live in multiple warehouses in their journey through the supply chain. The suppliers, the shipper’s local cross-dock, the port warehouse, the railroad cross-dock, your primary warehouse, and the regional warehouses that supply your local retail centers or manufacturing plants, as appropriate. These docks all pose a security risk.

The system should support all of the third party risk capabilities that are relevant for the owner/operator of the warehouse, the locale the work force is in, the third parties that provide the workers, and any other risks that can be identified and monitored for.
In-Yard (Rail/Dock) Sometimes the goods are in a warehouse, and sometimes they are just in a yard at the dock or the (rail)yard waiting to be loaded on a truck or a train to be taken to a cross-dock or warehouse. The risk will be a blend of warehouse/cross-dock and port/rail risks, tailored to the relevant locale.

The system should support all of the associated third party risk capabilities that are relevant, and, as with the warehouse/cross-dock, support risks that can be identified and monitored for.
Airports/ Some goods will go by sea, some by rail, some by land, and some by air. Airports have their own class of risks — which can include hijackings, crashes, and way too many carriers and personnel in and out of shared warehouses.

Similar monitoring to in-yard, but expanded to meet the specific need of airports servicing your cargo.
Driver/Conductor/Captain The biggest risks in transport are often not the third party carriers you deal with, but the people — are they appropriately vetted, trained, certified, and monitored? Who are they associated with? Can those associates pose risks? Do they need to be monitored? If so, when and how?

This system should integrate with an employee/contractor certification and monitoring systems to at least make sure all employees/contractors assigned to the organization’s cargo have appropriate licenses, certifications, training, and insurance.

And, of course, an In-Transport Risk Management system will also need a host of generic analytics/planning/monitoring capabilities, but since many of these are common, and since stand alone risk-focussed analytics applications are also part of the plethora of offerings out there, instead of discussing these generic features in this and every other article, as we noted in our coverage of Corporate Risk, we will instead discuss these capabilities in an article dedicated to Risk Analytics and Monitoring.

Logility “Starboard”: The Real-Time What-If Supply Chain Network Modeller that Every Sourcing Professional Should Have

Now, it’s true that this blog is focussed on Source-to-Pay and it’s true that, as a result, we usually focus on Strategic Sourcing Decision Optimization and occasionally on Logistics-focussed Models and Optimization Solutions, as that what’s typically needed for a Sourcing Professional to make the optimum buy, but this time we’re going to make an exception.

Why is network modelling an exception (besides the fact that, as we told you yesterday when we said Don’t Overlook the Network, it has the absolute best return on investment across all supply chain applications)? Well, if you think about classic network modelling, it’s not something a sourcing professional would do because it’s typically up to logistics and supply chain to maintain the network infrastructure that gets the product from the suppliers to the ports and warehouses and then to the distribution centres, retail facilities, and end consumers in drop-ship models. It’s up to logistics to re-evaluate the supporting network infrastructure on a bi/tri-annual basis and determine if warehouses should be added, relocated, or deleted (on lease end); if ports should be changed (to reduce overall costs due to port fees or local carrier costs or rail vs truck options); if new carriers should be considered; and so on.

The reason that this is typically only done on a bi/tri-annual basis is because it has traditionally been an arduous endeavour where you have to

  • build a very detailed model of all
    • the supplier production facilities, ports, warehouses, distribution centers, manufacturing/assembly centers, and retail facilities
    • the lanes used
    • the modes used for each lane
    • the carriers used for each mode / lane combination
    • the LTL and FTL rates for each carrier
    • the drop-ship rates for direct-to-consumer
  • identify all of the products being purchased and
    • associate them with the appropriate suppliers
    • associate them with the appropriate lanes, modes, and carriers
    • associate them with the appropriate warehouses
    • associate them with the appropriate retail locations or drop-ship locations
  • collect all of the current rates, for every supplier-carrier-lane-mode option in use
  • then solve a current-state optimization problem to determine baseline costs, times to serve, carbon emissions, etc.
  • identify all of the potential port and warehouse locations you could (also) use
  • identify all of the new lanes that would create
  • identify all of the additional carriers that could be used
  • collect quotes for every lane-carrier-mode combination from the potential new options that might actually be used
  • then build an extended model that includes all options and feed in all of the data
  • then solve a full-state model to determine baseline costs, times to serve, carbon emissions, etc.
  • then determine the ranges for the number of ports, warehouses, distribution centers, carriers, time to serve, carbon emissions, etc. that are acceptable
  • solve a copy of the restricted full-state model to determine a new baseline cost
  • then make and create copies of the model and run analysis against different objectives until the model is acceptable, and the costs (time to serve, emissions, etc.) reduced significantly enough to do a network transformation exercise

and this endeavour would typically take three to six months due to the fact it would take weeks to build the baseline models, months to collect the data, and weeks to build, solve, and analyze the models and come up with a new state that improved all the measures of interest as well as the implementation plan to make it happen.

But the problem with doing this bi/tri-annually is that you never know the impact of adding a new supplier or, more importantly, replacing a supplier of a significant product line or category where that supplier is in a completely different location, and possibly one that the last network design never took into account. Plus, the removal of a big supplier might cause a certain node (warehouse, distribution center, etc.) to be significantly under-utilized, resulting in unexpected overspend in certain parts of the distribution network.

But this knowledge is critically important to know before making a major sourcing decision that might change the supply base for a highly utilized product line or category — because the costs of the award will not be the expected costs. They will not be the unit or expected transportation costs used in the analysis that the award decision is based on, but will instead be those costs plus the fixed and variable losses incurred from underutilizing a sub-set of the network and/or overutilizing another sub-set of the network.

While this has always been the case, as the belief was that nothing could traditionally be done about it, if there was a tool that could

  • actively maintain the current network model
  • allow for copies to be created on the fly
  • allow for those copies to be easily modified, including
    • the addition or deletion of nodes (suppliers, ports, warehouses, distribution centers, retail locations, etc.)
    • the definition of new lanes
    • the the addition of carriers and/or carrier modes
    • updated costs for every lane
  • solve those copies quickly and accurately

then a sourcing professional could have deep insight into whether their cost models and assumptions are correct and logistics could update the network model, or at least the future state (if leases/contracts need to expire and new leases/contracts need to be signed), upon every award, and the overall sourcing, logistics, and supply chain costs.

And this is what you can do with Logility Network Optimization, formerly Starboard Solutions (acquired in 2022) and exactly why we are making an exception and covering them.

With the Logility Network Optimization Solution (which really should be called Logility Starboard, for reasons that will soon become clear), a Sourcing Professional can:

  • instantly see a graphical view of the current global network
  • bring up reports that summarize all of the key data
  • drill in to node / carrier / supplier / port / warehouse / distribution / product / combination costs
  • create a copy of the current network with all relevant data
  • and then create a what-if baseline scenario where they can
    • add whatever they wish (through simple pop-up interfaces they can add nodes and relationships),
    • remove whatever they wish (by simply clicking on a node or searching for the entity or relationship and deleting it), and, most importantly,
    • change whatever they want through in the network design through a simple drag-and-drop mechanism
  • they can then specify any constraints and goals, run an optimization, and see the new costs, and, most importantly, extract lanes / costs / variables of interest to populate into the TCO (total cost of ownership) calculations in their sourcing events

Logility Network Optimization can do this because it integrates with third party platforms and constantly extracts current market quotes and market rates for all major global lanes and can, when you change a design, automatically bring in those market rates and costs as a baseline for any lane / (generic) carrier / mode / volume combination you don’t already have a quote for. This not only provides a baseline rate (which might get better with a volume promise, negotiation, or current quote), but a statistically accurate one (especially if you just go with a generic carrier rate). (And, if there is no quote for a lane, the platform is smart enough to build one up from lane segments or tear one down using existing quotes and statistically significant costs per distance using statistically significant base rates for just securing the transportation mode.)

Furthermore, because it is a true multi-tenant cloud solution that uses a distributed “serverless” model that can decompose tasks into subtasks that can be run in (a massively) parallel (manner), such as data fetching, sub-model building, and even model solving (as all optimization models can be solved by solving sub-models on convex subspaces of the high-dimensional solution space), it can do it fast. And it’s just as accurate as the traditional, prior generation tools, at a speed that is breakneck in comparison, and that’s even if it uses statistically significant calculated data.

Moreover, it’s very easy to define multiple constraints and weighted objectives. You can guarantee maximum times to serve / times to deliver (subject to minimums that cannot be improved upon) while balancing overall cost and carbon footprint (through a weighted objective). (It’s quite easy to define objectives in the platform which have built in pop-ups to solve for different goals — service time, emissions limit, cost, and best X, where X is a single dimension or derived dimension that weights 2 or more other dimensions.) Or you can guarantee maximum times to serve, a fixed / x% carbon reduction, while minimizing overall cost. Or you can keep ports you know are stable and the warehouses with contracts you can’t break while allowing the delivery network architecture to shift to minimize overall costs.

The browser based interface to Logility’s platform offers a graphically represented virtual twin to an organization’s network with high-level summary data (products, facilities, lanes, suppliers, customers, activities, and costs) with easy scenario selection and easy definition and modification of scenarios. It’s very easy to dive into definition screens and see the suppliers, facilities, lanes, etc. and see/edit all of the data for any individual supplier, facility, lane, etc.; add a new instance, delete one, and see the associated costs, times, emissions, etc. and the underlying calculations associated with a node or relationship in the network graph (which is stored in a graph database that allows for massive scalability).

It’s also very easy to dynamically generate comparison reports between scenarios that compare (activity) costs (across cost types, such as leases, handling, transport costs, rail costs, ocean freight, tariffs, etc.), (average) service times (by supplier, product, lane, etc.), carbon (by carrier, lane, product, supplier, etc.), and other metrics of interest. Furthermore, when a user is happy with a scenario, they can one-click generate and output a complete comparison / summary report deck to PowerPoint for executive reporting (across as many scenarios as they like).

To enhance usability — which is quite obvious out-of-the-box to anyone who understands the basics of modelling, optimization, and decision analysis — Logility has an integrated quick-tour to get started, a full multi-media course on the platform and the modelling that can be done, playbooks for particular problems and challenges, and weekly office hours where users can ask Logility pros questions and get answers in real time. Logility Network Optimization was designed from the bottom up for usability and success.

Logility Network Optimization is the perfect complement to optimization-backed sourcing platforms with bill of material support. Buyers can model potential changes that would result from awarding to a new supplier, not awarding to an existing supplier, changing carriers or lanes, get expected transportation and tariff costs, augment the supplier quotes with this updated data in real-time through a Logility API feed (from an identified scenario), run a total cost of optimization scenario on the full set of bids augmented with accurate total cost of ownership data, make an award, push that award back to Logility Network Optimization which will update the network model in real time, create a new what-if, and see if the network model should be altered when the new supplier is brought fully on board. For the first time, an organization could have closed loop sourcing, logistics, and network optimization in real-time — a reality that was once as far away as the stars themselves (and why the platform takes you Starboard). It’s a powerful concept, and worth branching out beyond traditional Source-to-Pay providers and Strategic Sourcing Decision Optimization to achieve.