Category Archives: Supply Chain

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.

Don’t Overlook the Network (that Corresponds to the Award)

According to a recent Forbes article on Supply Chain Software’s Best Return on Investment, per $1 Billion in company revenues, no supply chain application has a better return on investment (ROI) than network design! And the doctor couldn’t agree more.

Just like strategic sourcing decision optimization is the best bang for the buck in Source to Pay, with documented, average returns of up to 12% year-over-year (by multiple analyst firms) as it can minimize total landed cost, and even total cost of ownership in some cases (including internal inventory costs, waste costs, etc.) and not just bids, while ensuring all business constraints are adhered to, an optimization-backed network design application can help minimize overall organizational supply chain costs. This is because a supply chain network optimization platform can minimize transportation costs, intermediate warehousing costs, tariffs, waste, emergency replenishment in the case of an unexpected stock-out, carbon/GHG, etc.

Plus, as the article notes:

  • network design solutions are absolutely necessary to uncover business value when the production-distribution infrastructure is large (and not just because you just can’t model that infrastructure in a spreadsheet)
  • network design solutions can look at Total Cost to Serve (TCTS) across a wide-range of fixed and marginal costs (and identify unintended circumstances of network design changes that could cause marginal costs to skyrocket)
  • network solutions can allow for multiple scenarios to be defined and multiple models to be run and cross-model and cross-scenario Pareto analysis to be run, trade-offs to be analyzed, and the best decisions to be made

One point that should not be overlooked is that projects will take some time, and it’s not because of the complexity of the network modelling or the time it takes to run the scenarios (as modern computing architectures are super powerful and modern algorithms highly optimized to be efficient and take advantage of massively parallel processing), it’s because you need a lot of good, clean, data. It can take months (and months) just to identify, collect, clean, and enrich the data required for global supply network optimization. But once you do that, the ROI will be beyond the expectations you have for every other supply chain solution.

The article, which describes a project to redesign the spare parts supply chain for a global automotive manufacturer, resulted in a redesign that immediately reduced network costs by 4% and identified transportation cost reduction opportunities through consolidation and re-allocating of routes to a smaller set of 3PLs that will save another 2.5% at contract renewal time. In today’s climate, especially in direct supply chains, a savings of 6%+ across the entire supply chain, and not just one category, is phenomenal!

Plus, as the article notes, in the age of sustainability, reduced transportation mileage and fuller trucks also equate to significant reductions in carbon emissions. WHAT A BONUS!

Will a Circular Economy Work with Leakage?

Sustainability is one of the big buzzwords, and the biggest verbal pushes, in today’s Procurement. (In practicality, most organizations won’t put their money where their mouth is and if the more sustainable solution is more than a point or two more cost-wise, environmentally damaging sweat-shop production, here we come!) We need to get there, because only an idiot would deny global warming (the last 13 years have seen 10 of the hottest year on record), and no one can deny the correlation between carbon emission, atmospheric carbon increase, and global warming. (You can argue just how much is due to carbon emission and how much due to other factors, many of which are indirectly caused by warming, but not that carbon is a problem.) Thus, even though we don’t know how much carbon reduction will help, we know it will, so we need to get there.

One big way to reduce carbon is to reduce production, which can done by reducing waste, which can be done through more refurbishment, repair, re-use, recycling, and reclamation — which are all part of the circular economy. Which is where we really need to get to (because waste is a problem — in addition to overflowing landfills that can pollute nearby water suppliers and make nearby land unfarmable, and even uninhabitable, think of the great pacific garbage patch and the containers of e-waste being sent to India, which has been a problem for well over a decade, see this 2010 article on the Times of India, and you start to get a grip on the magnitude of the problem).

But how efficient does the circular economy have to be to be effective? Theoretically, anything more that we do is one step better than what we are doing today, but, given that most products weren’t designed for recycle and reclamation, technologies for recycling and reclamation are immature and possibly carbon/generating themselves (especially if the answer is extract what we can, bury or burn the rest), and that there are breaks in the chain, is this leading to new waste that could possibly offset (or exceed) the expected (carbon) savings?

It’s a question Karolina Safarzynska, Lorenzo Di Domenico, and Marco Raberto recently tackled in an open-access paper on how the leakage effect may undermine the circular economy efforts available on nature.com. In the paper, the authors examine the impact of the circular economy on global resource extraction by way of an input-output analysis using an agent-based model of the capital sector. Through a detailed analysis they find that an appropriately structured circular economy economy can significantly reduce the extraction of iron, aluminum, and nonferrous metals if
implemented globally but the leakage effect may also cause some metal-intensive industries to relocate outside the EU, offsetting the circular economy efforts because an overlooked requirement for the circular economy is not just a reduction of waste, but a reduction of transport as transportation (air, rail, truck, and ship) contributes a significant amount of global carbon. In fact, if you go to Our World in Data, in the United States, the transportation sector accounts, like the energy (electricity and heat) sector, for approximately 30% of transportation emissions. The statistics right now are similar for the EU (24% for transportation and 28% for energy). So, if all of a sudden products need to be shipped halfway around the world to be recycled and reclaimed and the core materials shipped back, transportation-based emissions would increase significantly and possibly even overtake the extraction and raw material processing emissions!

In all fairness, we should note that the paper is pretty technical and metric heavy, and this is a bit of a simplification, but it’s the core idea we need to be aware of. It’s not an improvement if the carbon you take out of one segment is exceeded by changes in another. Just like we need to home/near-source for anything we can grow/mine/make at/near home, we also need to home/near reduce/reuse/refurbish/remanufacture/recycle whatever we can. It might be that the rare earths can only be mined in certain areas, but that doesn’t mean they have to be reclaimed and re-used there.

Strengthening Supply Chains is Simple …

It just takes proper people, planning, processes, and platforms. But let’s backtrack.

Forbes recently ran an article on how companies can improve supply chain management to strengthen business operations in 2023 which gave some great advice on various ways a business can improve their supply chain management, which included the following suggestions:

  • align partnerships to prepare for supply chain disruptions,
  • prioritize Learning & Development when it comes to automation in quality-focussed procurement, and
  • look ahead

… and these are really great suggestions, but they skip the starting point — and if an organization does not start off right

  • you’ll never be able to align the wrong partnerships,
  • no Learning & Development program will deliver fast enough if your people don’t have the right educational and experiential background, and
  • looking ahead will be impossible without the right platform.

You see, before you can jump into partnerships and learning and development, you have to go back and make sure you get the basics rights.

  1. Define proper procurement processes, including what will be strategically vs. tactically purchased, this will help you
  2. Hire the right people with the right backgrounds for the categories — not necessarily experienced buyers, but possibly experienced engineers with the insights to know what is needed, what makes a supplier who can meet the needs, when the cost models/quotes are accurate, etc. as it’s often easier to teach an engineer proper purchasing than teach a business grad the basics of electrical engineering
  3. Select the right platforms, which will allow you to qualify and select the right suppliers with whom you can build productive partnerships and
  4. Build the right models, which will allow you to do proper predictive analytics for demand, supply, and related planning

When you get the foundations right, it’s easy to build on those with partnerships and advanced training (to make your good buyers even better), but if you don’t have the foundations right, any attempts to polish partnerships and buildup better buyers will be for naught. (For more on foundations, see past articles on this blog, including The 39 Part Series to Help You Figure Out Where to Start with Source-to-Pay.)

To What Extent Can True Supply Chain Value be Created under Private Equity?

the doctor recently encountered a headline that implied that there could be supply chain value creation under private equity ownership, which, even before he made it to the tenth word, caused him to stop and ask just how much supply chain value could be created under private equity as the entire point of private equity is NOT to create supply chain value but to increase investment value in the short term for the fund contributors who are essentially the shareholders of the private equity firm.

And when we are talking short-term investment value creation, usually the biggest value creation levers are:

  • revenue / customer base increase
    (Wall Street Values this the most, so most investors value this the most as it gives them a better exit opportunity)
  • operational cost reduction
    (layoffs of the perceived dead-weight or high-earners, job consolidation, etc.; office space downsizing; cloud/SaaS infrastructure reduction/optimization; etc; as it’s an immediate reduction on the balance sheet which results in an immediate profit increase)

Supply chain is not the top two, and in many cases it’s not even in the top twenty, when you’re talking short-term. Mid-term (5 years), it gets up there (but not high enough for anything significant to be done), and long-term, it’s likely the second top value driver there is (as we must always remember that financiers will always put revenue first) as it can lead to cost reductions and value generation that can exceed any short-term operational cost reduction as the benefits from a supply chain improvement will be realized every year (and not just one time).

When the doctor got past these thoughts and returned to the article, the first thing the article noted is that private equity (PE) and the supply chain have been somewhat at odds with each other … due to what we could call a timeframe imbalance since PE typically aims to secure an exit within 3-5 years while supply chains … tended to operate on longer timespans. (Often much longer timespans.)

Now we must admit that, thanks to the pandemic, PE firms now realize more than ever that, without a functioning supply chain, any traditional business that needs to buy and sell physical goods to function is up Schitt’s Creek without a paddle. As a result, the smarter PE firms have started to give the supply chain some attention, but for the most part their focus and investments are usually limited to qualifying suppliers and carriers, not transforming global supply chains.

Moreover, the execution of this focus on qualifying suppliers and carriers is usually part of a broader strategy to make better decisions, which needs better data, so the focus ends up being a data, analytics, and BI (which is supposed to stand for Business Intelligence, but in some companies just ends up being BullSh!t Interpretation when they buy the wrong tool) strategy and an investment in the right SaaS tools to do that, and not on actual supply chain modelling, (re)design, or transformation. The best companies will procure modern S2P and ERP platforms which support real-time visibility into the location of all product — be they inventory, in transport, and ordered — by way of message and e-Document (EDI, XML, etc.) exchange with supplier platforms, but that’s as far as they’ll go on the “supply chain“.

And when the doctor finally brought himself to finish the article, it mostly admitted all of this, but finished by saying that there has been a surge in PE investment into supply chain technology, which he knows to be true.

In other words, PE firms do invest in supply chain technology and do utilize such to maximize the value in the supply chains of the companies they invest in, but they don’t actually invest in the actual supply chain, which is a much greater source of value (and carbon reduction, FYI) in the long term. And, as the doctor thought, the title was quite misleading. PE firms, if they took a longer term view (even 8 to 10 years would be enough), could totally transform supply chains, but, at least for now, all they do is tighten up what’s there in the hopes of making the company profitable enough to flip it to a bigger PE firm or take it public. So, to be brutally honest, there is no true supply chain value created under Private Equity today. (Hopefully tomorrow is a different story, but we’re not holding our breath.)

Disagree … contribute to the conversation on LinkedIn.